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3 Commits

Author SHA1 Message Date
Josh Yan
5dc5a295bf added testcase 2024-06-03 17:28:05 -07:00
Josh Yan
e21e6b2a33 added testcase 2024-06-03 17:27:38 -07:00
Josh Yan
a240ea3367 humanNumbers formats to 3 digits, added trillion case for future 2024-06-03 17:26:02 -07:00
145 changed files with 1897 additions and 5079 deletions

View File

@@ -437,7 +437,6 @@ jobs:
env:
OLLAMA_SKIP_IMAGE_BUILD: '1'
PUSH: '1'
GH_TOKEN: ${{ github.token }}
steps:
- uses: actions/checkout@v4
- name: Set Version
@@ -461,20 +460,15 @@ jobs:
ls -lh dist/
(cd dist; sha256sum * > sha256sum.txt)
cat dist/sha256sum.txt
- name: Create or update Release
run: |
echo "Looking for existing release for ${{ env.RELEASE_VERSION }}"
OLD_TAG=$(gh release ls --json name,tagName | jq -r ".[] | select(.name == \"${{ env.RELEASE_VERSION }}\") | .tagName")
if [ -n "$OLD_TAG" ]; then
echo "Updating release ${{ env.RELEASE_VERSION }} to point to new tag ${GITHUB_REF_NAME}"
gh release edit ${OLD_TAG} --tag ${GITHUB_REF_NAME}
else
echo "Creating new release ${{ env.RELEASE_VERSION }} pointing to tag ${GITHUB_REF_NAME}"
gh release create ${GITHUB_REF_NAME} \
--title ${{ env.RELEASE_VERSION }} \
--draft \
--generate-notes \
--prerelease
fi
echo "Uploading artifacts for tag ${GITHUB_REF_NAME}"
gh release upload ${GITHUB_REF_NAME} dist/* --clobber
- uses: ncipollo/release-action@v1
with:
name: ${{ env.RELEASE_VERSION }}
allowUpdates: true
artifacts: 'dist/*'
draft: true
prerelease: true
omitBodyDuringUpdate: true
generateReleaseNotes: true
omitDraftDuringUpdate: true
omitPrereleaseDuringUpdate: true
replacesArtifacts: true

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@@ -124,7 +124,7 @@ jobs:
strategy:
matrix:
rocm-version:
- '6.1.1'
- '6.0.2'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
@@ -269,9 +269,9 @@ jobs:
mkdir -p llm/build/darwin/$ARCH/stub/bin
touch llm/build/darwin/$ARCH/stub/bin/ollama_llama_server
if: ${{ startsWith(matrix.os, 'macos-') }}
- uses: golangci/golangci-lint-action@v6
- uses: golangci/golangci-lint-action@v4
with:
args: --timeout 8m0s -v ${{ startsWith(matrix.os, 'windows-') && '' || '--disable gofmt --disable goimports' }}
args: --timeout 8m0s -v
test:
strategy:
matrix:

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@@ -9,26 +9,9 @@ linters:
- contextcheck
- exportloopref
- gocheckcompilerdirectives
# conditionally enable this on linux/macos
# FIXME: for some reason this errors on windows
# - gofmt
# - goimports
- intrange
- misspell
- nilerr
- nolintlint
- nosprintfhostport
- testifylint
- unconvert
- unused
- wastedassign
- whitespace
- usestdlibvars
severity:
default-severity: error
rules:
- linters:
- gofmt
- goimports
- intrange
- usestdlibvars
severity: info

View File

@@ -2,7 +2,7 @@ ARG GOLANG_VERSION=1.22.1
ARG CMAKE_VERSION=3.22.1
# this CUDA_VERSION corresponds with the one specified in docs/gpu.md
ARG CUDA_VERSION=11.3.1
ARG ROCM_VERSION=6.1.1
ARG ROCM_VERSION=6.0.2
# Copy the minimal context we need to run the generate scripts
FROM scratch AS llm-code

View File

@@ -6,7 +6,7 @@
[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
Get up and running with large language models.
Get up and running with large language models locally.
### macOS
@@ -53,8 +53,8 @@ Here are some example models that can be downloaded:
| Llama 3 | 70B | 40GB | `ollama run llama3:70b` |
| Phi 3 Mini | 3.8B | 2.3GB | `ollama run phi3` |
| Phi 3 Medium | 14B | 7.9GB | `ollama run phi3:medium` |
| Gemma 2 | 9B | 5.5GB | `ollama run gemma2` |
| Gemma 2 | 27B | 16GB | `ollama run gemma2:27b` |
| Gemma | 2B | 1.4GB | `ollama run gemma:2b` |
| Gemma | 7B | 4.8GB | `ollama run gemma:7b` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| Moondream 2 | 1.4B | 829MB | `ollama run moondream` |
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
@@ -182,12 +182,6 @@ $ ollama run llama3 "Summarize this file: $(cat README.md)"
Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
```
### Show model information
```
ollama show llama3
```
### List models on your computer
```
@@ -291,7 +285,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [macai](https://github.com/Renset/macai) (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
- [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
- [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
- [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
### Terminal
@@ -314,7 +307,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [ShellOracle](https://github.com/djcopley/ShellOracle)
- [tlm](https://github.com/yusufcanb/tlm)
- [podman-ollama](https://github.com/ericcurtin/podman-ollama)
- [gollama](https://github.com/sammcj/gollama)
### Database
@@ -332,13 +324,11 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama) with [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
- [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
- [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
- [LangChainRust](https://github.com/Abraxas-365/langchain-rust) with [example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs)
- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
- [LiteLLM](https://github.com/BerriAI/litellm)
- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
- [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs)
- [Ollama-hpp for C++](https://github.com/jmont-dev/ollama-hpp)
- [Ollama4j for Java](https://github.com/amithkoujalgi/ollama4j)
- [ModelFusion Typescript Library](https://modelfusion.dev/integration/model-provider/ollama)
- [OllamaKit for Swift](https://github.com/kevinhermawan/OllamaKit)
@@ -356,7 +346,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Portkey](https://portkey.ai/docs/welcome/integration-guides/ollama)
- [PromptingTools.jl](https://github.com/svilupp/PromptingTools.jl) with an [example](https://svilupp.github.io/PromptingTools.jl/dev/examples/working_with_ollama)
- [LlamaScript](https://github.com/Project-Llama/llamascript)
### Mobile
- [Enchanted](https://github.com/AugustDev/enchanted)
@@ -389,9 +378,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support)
- [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) (Generalized TypeScript Discord Bot w/ Tuning Documentation)
- [Discord AI chat/moderation bot](https://github.com/rapmd73/Companion) Chat/moderation bot written in python. Uses Ollama to create personalities.
- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depends on ollama server)
### Supported backends
### Supported backends
- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.

View File

@@ -23,9 +23,11 @@ import (
"net"
"net/http"
"net/url"
"os"
"runtime"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/version"
)
@@ -63,7 +65,10 @@ func checkError(resp *http.Response, body []byte) error {
// If the variable is not specified, a default ollama host and port will be
// used.
func ClientFromEnvironment() (*Client, error) {
ollamaHost := envconfig.Host
ollamaHost, err := GetOllamaHost()
if err != nil {
return nil, err
}
return &Client{
base: &url.URL{
@@ -74,6 +79,52 @@ func ClientFromEnvironment() (*Client, error) {
}, nil
}
type OllamaHost struct {
Scheme string
Host string
Port string
}
func GetOllamaHost() (OllamaHost, error) {
defaultPort := "11434"
hostVar := os.Getenv("OLLAMA_HOST")
hostVar = strings.TrimSpace(strings.Trim(strings.TrimSpace(hostVar), "\"'"))
scheme, hostport, ok := strings.Cut(hostVar, "://")
switch {
case !ok:
scheme, hostport = "http", hostVar
case scheme == "http":
defaultPort = "80"
case scheme == "https":
defaultPort = "443"
}
// trim trailing slashes
hostport = strings.TrimRight(hostport, "/")
host, port, err := net.SplitHostPort(hostport)
if err != nil {
host, port = "127.0.0.1", defaultPort
if ip := net.ParseIP(strings.Trim(hostport, "[]")); ip != nil {
host = ip.String()
} else if hostport != "" {
host = hostport
}
}
if portNum, err := strconv.ParseInt(port, 10, 32); err != nil || portNum > 65535 || portNum < 0 {
return OllamaHost{}, ErrInvalidHostPort
}
return OllamaHost{
Scheme: scheme,
Host: host,
Port: port,
}, nil
}
func NewClient(base *url.URL, http *http.Client) *Client {
return &Client{
base: base,
@@ -304,8 +355,8 @@ func (c *Client) List(ctx context.Context) (*ListResponse, error) {
}
// List running models.
func (c *Client) ListRunning(ctx context.Context) (*ProcessResponse, error) {
var lr ProcessResponse
func (c *Client) ListRunning(ctx context.Context) (*ListResponse, error) {
var lr ListResponse
if err := c.do(ctx, http.MethodGet, "/api/ps", nil, &lr); err != nil {
return nil, err
}

View File

@@ -1,9 +1,11 @@
package api
import (
"fmt"
"net"
"testing"
"github.com/ollama/ollama/envconfig"
"github.com/stretchr/testify/assert"
)
func TestClientFromEnvironment(t *testing.T) {
@@ -33,7 +35,6 @@ func TestClientFromEnvironment(t *testing.T) {
for k, v := range testCases {
t.Run(k, func(t *testing.T) {
t.Setenv("OLLAMA_HOST", v.value)
envconfig.LoadConfig()
client, err := ClientFromEnvironment()
if err != v.err {
@@ -45,4 +46,40 @@ func TestClientFromEnvironment(t *testing.T) {
}
})
}
hostTestCases := map[string]*testCase{
"empty": {value: "", expect: "127.0.0.1:11434"},
"only address": {value: "1.2.3.4", expect: "1.2.3.4:11434"},
"only port": {value: ":1234", expect: ":1234"},
"address and port": {value: "1.2.3.4:1234", expect: "1.2.3.4:1234"},
"hostname": {value: "example.com", expect: "example.com:11434"},
"hostname and port": {value: "example.com:1234", expect: "example.com:1234"},
"zero port": {value: ":0", expect: ":0"},
"too large port": {value: ":66000", err: ErrInvalidHostPort},
"too small port": {value: ":-1", err: ErrInvalidHostPort},
"ipv6 localhost": {value: "[::1]", expect: "[::1]:11434"},
"ipv6 world open": {value: "[::]", expect: "[::]:11434"},
"ipv6 no brackets": {value: "::1", expect: "[::1]:11434"},
"ipv6 + port": {value: "[::1]:1337", expect: "[::1]:1337"},
"extra space": {value: " 1.2.3.4 ", expect: "1.2.3.4:11434"},
"extra quotes": {value: "\"1.2.3.4\"", expect: "1.2.3.4:11434"},
"extra space+quotes": {value: " \" 1.2.3.4 \" ", expect: "1.2.3.4:11434"},
"extra single quotes": {value: "'1.2.3.4'", expect: "1.2.3.4:11434"},
}
for k, v := range hostTestCases {
t.Run(k, func(t *testing.T) {
t.Setenv("OLLAMA_HOST", v.value)
oh, err := GetOllamaHost()
if err != v.err {
t.Fatalf("expected %s, got %s", v.err, err)
}
if err == nil {
host := net.JoinHostPort(oh.Host, oh.Port)
assert.Equal(t, v.expect, host, fmt.Sprintf("%s: expected %s, got %s", k, v.expect, host))
}
})
}
}

View File

@@ -2,6 +2,7 @@ package api
import (
"encoding/json"
"errors"
"fmt"
"log/slog"
"math"
@@ -159,49 +160,18 @@ type Options struct {
// Runner options which must be set when the model is loaded into memory
type Runner struct {
UseNUMA bool `json:"numa,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
LowVRAM bool `json:"low_vram,omitempty"`
F16KV bool `json:"f16_kv,omitempty"`
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap TriState `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
type TriState int
const (
TriStateUndefined TriState = -1
TriStateFalse TriState = 0
TriStateTrue TriState = 1
)
func (b *TriState) UnmarshalJSON(data []byte) error {
var v bool
if err := json.Unmarshal(data, &v); err != nil {
return err
}
if v {
*b = TriStateTrue
}
*b = TriStateFalse
return nil
}
func (b *TriState) MarshalJSON() ([]byte, error) {
if *b == TriStateUndefined {
return nil, nil
}
var v bool
if *b == TriStateTrue {
v = true
}
return json.Marshal(v)
UseNUMA bool `json:"numa,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
LowVRAM bool `json:"low_vram,omitempty"`
F16KV bool `json:"f16_kv,omitempty"`
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap bool `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
// EmbeddingRequest is the request passed to [Client.Embeddings].
@@ -253,7 +223,6 @@ type ShowRequest struct {
Model string `json:"model"`
System string `json:"system"`
Template string `json:"template"`
Verbose bool `json:"verbose"`
Options map[string]interface{} `json:"options"`
@@ -263,16 +232,13 @@ type ShowRequest struct {
// ShowResponse is the response returned from [Client.Show].
type ShowResponse struct {
License string `json:"license,omitempty"`
Modelfile string `json:"modelfile,omitempty"`
Parameters string `json:"parameters,omitempty"`
Template string `json:"template,omitempty"`
System string `json:"system,omitempty"`
Details ModelDetails `json:"details,omitempty"`
Messages []Message `json:"messages,omitempty"`
ModelInfo map[string]any `json:"model_info,omitempty"`
ProjectorInfo map[string]any `json:"projector_info,omitempty"`
ModifiedAt time.Time `json:"modified_at,omitempty"`
License string `json:"license,omitempty"`
Modelfile string `json:"modelfile,omitempty"`
Parameters string `json:"parameters,omitempty"`
Template string `json:"template,omitempty"`
System string `json:"system,omitempty"`
Details ModelDetails `json:"details,omitempty"`
Messages []Message `json:"messages,omitempty"`
}
// CopyRequest is the request passed to [Client.Copy].
@@ -316,33 +282,19 @@ type PushRequest struct {
// ListResponse is the response from [Client.List].
type ListResponse struct {
Models []ListModelResponse `json:"models"`
Models []ModelResponse `json:"models"`
}
// ProcessResponse is the response from [Client.Process].
type ProcessResponse struct {
Models []ProcessModelResponse `json:"models"`
}
// ListModelResponse is a single model description in [ListResponse].
type ListModelResponse struct {
// ModelResponse is a single model description in [ListResponse].
type ModelResponse struct {
Name string `json:"name"`
Model string `json:"model"`
ModifiedAt time.Time `json:"modified_at"`
ModifiedAt time.Time `json:"modified_at,omitempty"`
Size int64 `json:"size"`
Digest string `json:"digest"`
Details ModelDetails `json:"details,omitempty"`
}
// ProcessModelResponse is a single model description in [ProcessResponse].
type ProcessModelResponse struct {
Name string `json:"name"`
Model string `json:"model"`
Size int64 `json:"size"`
Digest string `json:"digest"`
Details ModelDetails `json:"details,omitempty"`
ExpiresAt time.Time `json:"expires_at"`
SizeVRAM int64 `json:"size_vram"`
ExpiresAt time.Time `json:"expires_at,omitempty"`
SizeVRAM int64 `json:"size_vram,omitempty"`
}
type TokenResponse struct {
@@ -354,7 +306,7 @@ type GenerateResponse struct {
// Model is the model name that generated the response.
Model string `json:"model"`
// CreatedAt is the timestamp of the response.
//CreatedAt is the timestamp of the response.
CreatedAt time.Time `json:"created_at"`
// Response is the textual response itself.
@@ -411,6 +363,8 @@ func (m *Metrics) Summary() {
}
}
var ErrInvalidHostPort = errors.New("invalid port specified in OLLAMA_HOST")
func (opts *Options) FromMap(m map[string]interface{}) error {
valueOpts := reflect.ValueOf(opts).Elem() // names of the fields in the options struct
typeOpts := reflect.TypeOf(opts).Elem() // types of the fields in the options struct
@@ -437,19 +391,6 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
continue
}
if reflect.PointerTo(field.Type()) == reflect.TypeOf((*TriState)(nil)) {
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
if val {
field.SetInt(int64(TriStateTrue))
} else {
field.SetInt(int64(TriStateFalse))
}
continue
}
switch field.Kind() {
case reflect.Int:
switch t := val.(type) {
@@ -538,7 +479,7 @@ func DefaultOptions() Options {
LowVRAM: false,
F16KV: true,
UseMLock: false,
UseMMap: TriStateUndefined,
UseMMap: true,
UseNUMA: false,
},
}
@@ -608,19 +549,6 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
} else {
field := valueOpts.FieldByName(opt.Name)
if field.IsValid() && field.CanSet() {
if reflect.PointerTo(field.Type()) == reflect.TypeOf((*TriState)(nil)) {
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
return nil, fmt.Errorf("invalid bool value %s", vals)
}
if boolVal {
out[key] = TriStateTrue
} else {
out[key] = TriStateFalse
}
continue
}
switch field.Kind() {
case reflect.Float32:
floatVal, err := strconv.ParseFloat(vals[0], 32)

View File

@@ -2,7 +2,6 @@ package api
import (
"encoding/json"
"fmt"
"math"
"testing"
"time"
@@ -73,13 +72,13 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
},
{
"positive duration",
42 * time.Second,
42 * time.Second,
time.Duration(42 * time.Second),
time.Duration(42 * time.Second),
},
{
"another positive duration",
42 * time.Minute,
42 * time.Minute,
time.Duration(42 * time.Minute),
time.Duration(42 * time.Minute),
},
{
"zero duration",
@@ -106,101 +105,3 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
})
}
}
func TestUseMmapParsingFromJSON(t *testing.T) {
tests := []struct {
name string
req string
exp TriState
}{
{
name: "Undefined",
req: `{ }`,
exp: TriStateUndefined,
},
{
name: "True",
req: `{ "use_mmap": true }`,
exp: TriStateTrue,
},
{
name: "False",
req: `{ "use_mmap": false }`,
exp: TriStateFalse,
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
var oMap map[string]interface{}
err := json.Unmarshal([]byte(test.req), &oMap)
require.NoError(t, err)
opts := DefaultOptions()
err = opts.FromMap(oMap)
require.NoError(t, err)
assert.Equal(t, test.exp, opts.UseMMap)
})
}
}
func TestUseMmapFormatParams(t *testing.T) {
tests := []struct {
name string
req map[string][]string
exp TriState
err error
}{
{
name: "True",
req: map[string][]string{
"use_mmap": []string{"true"},
},
exp: TriStateTrue,
err: nil,
},
{
name: "False",
req: map[string][]string{
"use_mmap": []string{"false"},
},
exp: TriStateFalse,
err: nil,
},
{
name: "Numeric True",
req: map[string][]string{
"use_mmap": []string{"1"},
},
exp: TriStateTrue,
err: nil,
},
{
name: "Numeric False",
req: map[string][]string{
"use_mmap": []string{"0"},
},
exp: TriStateFalse,
err: nil,
},
{
name: "invalid string",
req: map[string][]string{
"use_mmap": []string{"foo"},
},
exp: TriStateUndefined,
err: fmt.Errorf("invalid bool value [foo]"),
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
resp, err := FormatParams(test.req)
require.Equal(t, err, test.err)
respVal, ok := resp["use_mmap"]
if test.exp != TriStateUndefined {
assert.True(t, ok, "resp: %v", resp)
assert.Equal(t, test.exp, respVal)
}
})
}
}

View File

@@ -5,8 +5,6 @@ import (
"log/slog"
"os"
"path/filepath"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
)
@@ -26,7 +24,6 @@ func InitLogging() {
logFile = os.Stderr
// TODO - write one-line to the app.log file saying we're running in console mode to help avoid confusion
} else {
rotateLogs(AppLogFile)
logFile, err = os.OpenFile(AppLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
if err != nil {
slog.Error(fmt.Sprintf("failed to create server log %v", err))
@@ -49,32 +46,3 @@ func InitLogging() {
slog.Info("ollama app started")
}
func rotateLogs(logFile string) {
if _, err := os.Stat(logFile); os.IsNotExist(err) {
return
}
index := strings.LastIndex(logFile, ".")
pre := logFile[:index]
post := "." + logFile[index+1:]
for i := LogRotationCount; i > 0; i-- {
older := pre + "-" + strconv.Itoa(i) + post
newer := pre + "-" + strconv.Itoa(i-1) + post
if i == 1 {
newer = pre + post
}
if _, err := os.Stat(newer); err == nil {
if _, err := os.Stat(older); err == nil {
err := os.Remove(older)
if err != nil {
slog.Warn("Failed to remove older log", "older", older, "error", err)
continue
}
}
err := os.Rename(newer, older)
if err != nil {
slog.Warn("Failed to rotate log", "older", older, "newer", newer, "error", err)
}
}
}
}

View File

@@ -1,44 +0,0 @@
package lifecycle
import (
"os"
"path/filepath"
"strconv"
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestRotateLogs(t *testing.T) {
logDir := t.TempDir()
logFile := filepath.Join(logDir, "testlog.log")
// No log exists
rotateLogs(logFile)
require.NoError(t, os.WriteFile(logFile, []byte("1"), 0644))
assert.FileExists(t, logFile)
// First rotation
rotateLogs(logFile)
assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
assert.NoFileExists(t, logFile)
// Should be a no-op without a new log
rotateLogs(logFile)
assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
assert.NoFileExists(t, logFile)
for i := 2; i <= LogRotationCount+1; i++ {
require.NoError(t, os.WriteFile(logFile, []byte(strconv.Itoa(i)), 0644))
assert.FileExists(t, logFile)
rotateLogs(logFile)
assert.NoFileExists(t, logFile)
for j := 1; j < i; j++ {
assert.FileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(j)+".log"))
}
assert.NoFileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(i+1)+".log"))
}
}

View File

@@ -16,12 +16,11 @@ var (
AppDir = "/opt/Ollama"
AppDataDir = "/opt/Ollama"
// TODO - should there be a distinct log dir?
UpdateStageDir = "/tmp"
AppLogFile = "/tmp/ollama_app.log"
ServerLogFile = "/tmp/ollama.log"
UpgradeLogFile = "/tmp/ollama_update.log"
Installer = "OllamaSetup.exe"
LogRotationCount = 5
UpdateStageDir = "/tmp"
AppLogFile = "/tmp/ollama_app.log"
ServerLogFile = "/tmp/ollama.log"
UpgradeLogFile = "/tmp/ollama_update.log"
Installer = "OllamaSetup.exe"
)
func init() {
@@ -70,6 +69,7 @@ func init() {
slog.Error(fmt.Sprintf("create ollama dir %s: %v", AppDataDir, err))
}
}
} else if runtime.GOOS == "darwin" {
// TODO
AppName += ".app"

View File

@@ -15,7 +15,7 @@ import (
)
func getCLIFullPath(command string) string {
var cmdPath string
cmdPath := ""
appExe, err := os.Executable()
if err == nil {
cmdPath = filepath.Join(filepath.Dir(appExe), command)
@@ -54,7 +54,7 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
return nil, fmt.Errorf("failed to spawn server stderr pipe: %w", err)
}
rotateLogs(ServerLogFile)
// TODO - rotation
logFile, err := os.OpenFile(ServerLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
if err != nil {
return nil, fmt.Errorf("failed to create server log: %w", err)
@@ -65,6 +65,7 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
if err != nil {
if !errors.Is(err, os.ErrNotExist) {
return nil, fmt.Errorf("stat ollama server log dir %s: %v", logDir, err)
}
if err := os.MkdirAll(logDir, 0o755); err != nil {

View File

@@ -24,8 +24,7 @@ func terminate(cmd *exec.Cmd) error {
if err != nil {
return err
}
//nolint:errcheck
defer dll.Release()
defer dll.Release() // nolint: errcheck
pid := cmd.Process.Pid
@@ -74,8 +73,7 @@ func isProcessExited(pid int) (bool, error) {
if err != nil {
return false, fmt.Errorf("failed to open process: %v", err)
}
//nolint:errcheck
defer windows.CloseHandle(hProcess)
defer windows.CloseHandle(hProcess) // nolint: errcheck
var exitCode uint32
err = windows.GetExitCodeProcess(hProcess, &exitCode)

View File

@@ -78,7 +78,7 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
}
defer resp.Body.Close()
if resp.StatusCode == http.StatusNoContent {
if resp.StatusCode == 204 {
slog.Debug("check update response 204 (current version is up to date)")
return false, updateResp
}
@@ -87,7 +87,7 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
slog.Warn(fmt.Sprintf("failed to read body response: %s", err))
}
if resp.StatusCode != http.StatusOK {
if resp.StatusCode != 200 {
slog.Info(fmt.Sprintf("check update error %d - %.96s", resp.StatusCode, string(body)))
return false, updateResp
}
@@ -114,7 +114,7 @@ func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
if err != nil {
return fmt.Errorf("error checking update: %w", err)
}
if resp.StatusCode != http.StatusOK {
if resp.StatusCode != 200 {
return fmt.Errorf("unexpected status attempting to download update %d", resp.StatusCode)
}
resp.Body.Close()

View File

@@ -88,15 +88,10 @@ DialogFontSize=12
[Files]
Source: ".\app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ; Flags: ignoreversion 64bit
Source: "..\ollama.exe"; DestDir: "{app}"; Flags: ignoreversion 64bit
Source: "..\dist\windows-{#ARCH}\*.dll"; DestDir: "{app}"; Flags: ignoreversion 64bit
Source: "..\dist\windows-{#ARCH}\ollama_runners\*"; DestDir: "{app}\ollama_runners"; Flags: ignoreversion 64bit recursesubdirs
Source: "..\dist\ollama_welcome.ps1"; DestDir: "{app}"; Flags: ignoreversion
Source: ".\assets\app.ico"; DestDir: "{app}"; Flags: ignoreversion
#if DirExists("..\dist\windows-amd64\cuda")
Source: "..\dist\windows-amd64\cuda\*"; DestDir: "{app}\cuda\"; Flags: ignoreversion recursesubdirs
#endif
#if DirExists("..\dist\windows-amd64\oneapi")
Source: "..\dist\windows-amd64\oneapi\*"; DestDir: "{app}\oneapi\"; Flags: ignoreversion recursesubdirs
#endif
#if DirExists("..\dist\windows-amd64\rocm")
Source: "..\dist\windows-amd64\rocm\*"; DestDir: "{app}\rocm\"; Flags: ignoreversion recursesubdirs
#endif

View File

@@ -29,6 +29,7 @@ func GetID() string {
initStore()
}
return store.ID
}
func GetFirstTimeRun() bool {

View File

@@ -47,6 +47,7 @@ func nativeLoop() {
default:
pTranslateMessage.Call(uintptr(unsafe.Pointer(m))) //nolint:errcheck
pDispatchMessage.Call(uintptr(unsafe.Pointer(m))) //nolint:errcheck
}
}
}
@@ -159,8 +160,8 @@ func (t *winTray) wndProc(hWnd windows.Handle, message uint32, wParam, lParam ui
lResult, _, _ = pDefWindowProc.Call(
uintptr(hWnd),
uintptr(message),
wParam,
lParam,
uintptr(wParam),
uintptr(lParam),
)
}
return

View File

@@ -186,7 +186,7 @@ func (t *winTray) initInstance() error {
t.muNID.Lock()
defer t.muNID.Unlock()
t.nid = &notifyIconData{
Wnd: t.window,
Wnd: windows.Handle(t.window),
ID: 100,
Flags: NIF_MESSAGE,
CallbackMessage: t.wmSystrayMessage,
@@ -197,6 +197,7 @@ func (t *winTray) initInstance() error {
}
func (t *winTray) createMenu() error {
menuHandle, _, err := pCreatePopupMenu.Call()
if menuHandle == 0 {
return err
@@ -245,7 +246,7 @@ func (t *winTray) addOrUpdateMenuItem(menuItemId uint32, parentId uint32, title
mi := menuItemInfo{
Mask: MIIM_FTYPE | MIIM_STRING | MIIM_ID | MIIM_STATE,
Type: MFT_STRING,
ID: menuItemId,
ID: uint32(menuItemId),
TypeData: titlePtr,
Cch: uint32(len(title)),
}
@@ -301,10 +302,11 @@ func (t *winTray) addOrUpdateMenuItem(menuItemId uint32, parentId uint32, title
}
func (t *winTray) addSeparatorMenuItem(menuItemId, parentId uint32) error {
mi := menuItemInfo{
Mask: MIIM_FTYPE | MIIM_ID | MIIM_STATE,
Type: MFT_SEPARATOR,
ID: menuItemId,
ID: uint32(menuItemId),
}
mi.Size = uint32(unsafe.Sizeof(mi))
@@ -424,6 +426,7 @@ func iconBytesToFilePath(iconBytes []byte) (string, error) {
// Loads an image from file and shows it in tray.
// Shell_NotifyIcon: https://msdn.microsoft.com/en-us/library/windows/desktop/bb762159(v=vs.85).aspx
func (t *winTray) setIcon(src string) error {
h, err := t.loadIconFrom(src)
if err != nil {
return err
@@ -441,6 +444,7 @@ func (t *winTray) setIcon(src string) error {
// Loads an image from file to be shown in tray or menu item.
// LoadImage: https://msdn.microsoft.com/en-us/library/windows/desktop/ms648045(v=vs.85).aspx
func (t *winTray) loadIconFrom(src string) (windows.Handle, error) {
// Save and reuse handles of loaded images
t.muLoadedImages.RLock()
h, ok := t.loadedImages[src]

View File

@@ -20,7 +20,6 @@ import (
"path/filepath"
"regexp"
"runtime"
"slices"
"strings"
"syscall"
"time"
@@ -30,6 +29,7 @@ import (
"github.com/olekukonko/tablewriter"
"github.com/spf13/cobra"
"golang.org/x/crypto/ssh"
"golang.org/x/exp/slices"
"golang.org/x/term"
"github.com/ollama/ollama/api"
@@ -162,6 +162,9 @@ func tempZipFiles(path string) (string, error) {
}
defer tempfile.Close()
zipfile := zip.NewWriter(tempfile)
defer zipfile.Close()
detectContentType := func(path string) (string, error) {
f, err := os.Open(path)
if err != nil {
@@ -230,9 +233,6 @@ func tempZipFiles(path string) (string, error) {
files = append(files, tks...)
}
zipfile := zip.NewWriter(tempfile)
defer zipfile.Close()
for _, file := range files {
f, err := os.Open(file)
if err != nil {
@@ -287,12 +287,38 @@ func createBlob(cmd *cobra.Command, client *api.Client, path string) (string, er
}
func RunHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
name := args[0]
// check if the model exists on the server
show, err := client.Show(cmd.Context(), &api.ShowRequest{Name: name})
var statusError api.StatusError
switch {
case errors.As(err, &statusError) && statusError.StatusCode == http.StatusNotFound:
if err := PullHandler(cmd, []string{name}); err != nil {
return err
}
show, err = client.Show(cmd.Context(), &api.ShowRequest{Name: name})
if err != nil {
return err
}
case err != nil:
return err
}
interactive := true
opts := runOptions{
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
MultiModal: slices.Contains(show.Details.Families, "clip"),
ParentModel: show.Details.ParentModel,
}
format, err := cmd.Flags().GetString("format")
@@ -336,38 +362,11 @@ func RunHandler(cmd *cobra.Command, args []string) error {
}
opts.WordWrap = !nowrap
// Fill out the rest of the options based on information about the
// model.
client, err := api.ClientFromEnvironment()
if err != nil {
return err
if !interactive {
return generate(cmd, opts)
}
name := args[0]
info, err := func() (*api.ShowResponse, error) {
showReq := &api.ShowRequest{Name: name}
info, err := client.Show(cmd.Context(), showReq)
var se api.StatusError
if errors.As(err, &se) && se.StatusCode == http.StatusNotFound {
if err := PullHandler(cmd, []string{name}); err != nil {
return nil, err
}
return client.Show(cmd.Context(), &api.ShowRequest{Name: name})
}
return info, err
}()
if err != nil {
return err
}
opts.MultiModal = slices.Contains(info.Details.Families, "clip")
opts.ParentModel = info.Details.ParentModel
opts.Messages = append(opts.Messages, info.Messages...)
if interactive {
return generateInteractive(cmd, opts)
}
return generate(cmd, opts)
return generateInteractive(cmd, opts)
}
func errFromUnknownKey(unknownKeyErr error) error {
@@ -580,6 +579,10 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return err
}
if len(args) != 1 {
return errors.New("missing model name")
}
license, errLicense := cmd.Flags().GetBool("license")
modelfile, errModelfile := cmd.Flags().GetBool("modelfile")
parameters, errParams := cmd.Flags().GetBool("parameters")
@@ -622,29 +625,8 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
if flagsSet > 1 {
return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
}
if flagsSet == 1 {
req := api.ShowRequest{Name: args[0]}
resp, err := client.Show(cmd.Context(), &req)
if err != nil {
return err
}
switch showType {
case "license":
fmt.Println(resp.License)
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
case "system":
fmt.Println(resp.System)
case "template":
fmt.Println(resp.Template)
}
return nil
} else if flagsSet == 0 {
return errors.New("one of '--license', '--modelfile', '--parameters', '--system', or '--template' must be specified")
}
req := api.ShowRequest{Name: args[0]}
@@ -653,114 +635,22 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return err
}
arch := resp.ModelInfo["general.architecture"].(string)
modelData := [][]string{
{"arch", arch},
{"parameters", resp.Details.ParameterSize},
{"quantization", resp.Details.QuantizationLevel},
{"context length", fmt.Sprintf("%v", resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)].(float64))},
{"embedding length", fmt.Sprintf("%v", resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)].(float64))},
switch showType {
case "license":
fmt.Println(resp.License)
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
case "system":
fmt.Println(resp.System)
case "template":
fmt.Println(resp.Template)
}
mainTableData := [][]string{
{"Model"},
{renderSubTable(modelData, false)},
}
if resp.ProjectorInfo != nil {
projectorData := [][]string{
{"arch", "clip"},
{"parameters", format.HumanNumber(uint64(resp.ProjectorInfo["general.parameter_count"].(float64)))},
{"projector type", resp.ProjectorInfo["clip.projector_type"].(string)},
{"embedding length", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.embedding_length"].(float64))},
{"projection dimensionality", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.projection_dim"].(float64))},
}
mainTableData = append(mainTableData,
[]string{"Projector"},
[]string{renderSubTable(projectorData, false)},
)
}
if resp.Parameters != "" {
mainTableData = append(mainTableData, []string{"Parameters"}, []string{formatParams(resp.Parameters)})
}
if resp.System != "" {
mainTableData = append(mainTableData, []string{"System"}, []string{renderSubTable(twoLines(resp.System), true)})
}
if resp.License != "" {
mainTableData = append(mainTableData, []string{"License"}, []string{renderSubTable(twoLines(resp.License), true)})
}
table := tablewriter.NewWriter(os.Stdout)
table.SetAutoWrapText(false)
table.SetBorder(false)
table.SetAlignment(tablewriter.ALIGN_LEFT)
for _, v := range mainTableData {
table.Append(v)
}
table.Render()
return nil
}
func renderSubTable(data [][]string, file bool) string {
var buf bytes.Buffer
table := tablewriter.NewWriter(&buf)
table.SetAutoWrapText(!file)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding("\t")
table.SetAlignment(tablewriter.ALIGN_LEFT)
for _, v := range data {
table.Append(v)
}
table.Render()
renderedTable := buf.String()
lines := strings.Split(renderedTable, "\n")
for i, line := range lines {
lines[i] = "\t" + line
}
return strings.Join(lines, "\n")
}
func twoLines(s string) [][]string {
lines := strings.Split(s, "\n")
res := [][]string{}
count := 0
for _, line := range lines {
line = strings.TrimSpace(line)
if line != "" {
count++
res = append(res, []string{line})
if count == 2 {
return res
}
}
}
return res
}
func formatParams(s string) string {
lines := strings.Split(s, "\n")
table := [][]string{}
for _, line := range lines {
table = append(table, strings.Fields(line))
}
return renderSubTable(table, false)
}
func CopyHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
@@ -856,6 +746,7 @@ func displayResponse(content string, wordWrap bool, state *displayResponseState)
if wordWrap && termWidth >= 10 {
for _, ch := range content {
if state.lineLength+1 > termWidth-5 {
if runewidth.StringWidth(state.wordBuffer) > termWidth-10 {
fmt.Printf("%s%c", state.wordBuffer, ch)
state.wordBuffer = ""
@@ -1070,11 +961,17 @@ func generate(cmd *cobra.Command, opts runOptions) error {
}
func RunServer(cmd *cobra.Command, _ []string) error {
// retrieve the OLLAMA_HOST environment variable
ollamaHost, err := api.GetOllamaHost()
if err != nil {
return err
}
if err := initializeKeypair(); err != nil {
return err
}
ln, err := net.Listen("tcp", net.JoinHostPort(envconfig.Host.Host, envconfig.Host.Port))
ln, err := net.Listen("tcp", net.JoinHostPort(ollamaHost.Host, ollamaHost.Port))
if err != nil {
return err
}
@@ -1133,6 +1030,24 @@ func initializeKeypair() error {
return nil
}
//nolint:unused
func waitForServer(ctx context.Context, client *api.Client) error {
// wait for the server to start
timeout := time.After(5 * time.Second)
tick := time.Tick(500 * time.Millisecond)
for {
select {
case <-timeout:
return errors.New("timed out waiting for server to start")
case <-tick:
if err := client.Heartbeat(ctx); err == nil {
return nil // server has started
}
}
}
}
func checkServerHeartbeat(cmd *cobra.Command, _ []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {

View File

@@ -8,11 +8,11 @@ import (
"os"
"path/filepath"
"regexp"
"slices"
"sort"
"strings"
"github.com/spf13/cobra"
"golang.org/x/exp/slices"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
@@ -31,40 +31,65 @@ const (
)
func loadModel(cmd *cobra.Command, opts *runOptions) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
p := progress.NewProgress(os.Stderr)
defer p.StopAndClear()
spinner := progress.NewSpinner("")
p.Add("", spinner)
client, err := api.ClientFromEnvironment()
showReq := api.ShowRequest{Name: opts.Model}
showResp, err := client.Show(cmd.Context(), &showReq)
if err != nil {
return err
}
opts.MultiModal = slices.Contains(showResp.Details.Families, "clip")
opts.ParentModel = showResp.Details.ParentModel
chatReq := &api.ChatRequest{
Model: opts.Model,
KeepAlive: opts.KeepAlive,
if len(showResp.Messages) > 0 {
opts.Messages = append(opts.Messages, showResp.Messages...)
}
return client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
chatReq := &api.ChatRequest{
Model: opts.Model,
Messages: []api.Message{},
}
if opts.KeepAlive != nil {
chatReq.KeepAlive = opts.KeepAlive
}
err = client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
p.StopAndClear()
for _, msg := range opts.Messages {
switch msg.Role {
case "user":
fmt.Printf(">>> %s\n", msg.Content)
case "assistant":
state := &displayResponseState{}
displayResponse(msg.Content, opts.WordWrap, state)
fmt.Println()
fmt.Println()
if len(opts.Messages) > 0 {
for _, msg := range opts.Messages {
switch msg.Role {
case "user":
fmt.Printf(">>> %s\n", msg.Content)
case "assistant":
state := &displayResponseState{}
displayResponse(msg.Content, opts.WordWrap, state)
fmt.Println()
fmt.Println()
}
}
}
return nil
})
if err != nil {
return err
}
return nil
}
func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.Messages = make([]api.Message, 0)
err := loadModel(cmd, &opts)
if err != nil {
return err

View File

@@ -6,7 +6,6 @@ import (
"text/template"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
"github.com/ollama/ollama/api"
)
@@ -86,11 +85,11 @@ MESSAGE assistant """Yes it is true, I am half horse, half shark."""
`
tmpl, err := template.New("").Parse(expectedModelfile)
require.NoError(t, err)
assert.Nil(t, err)
var buf bytes.Buffer
err = tmpl.Execute(&buf, opts)
require.NoError(t, err)
assert.Nil(t, err)
assert.Equal(t, buf.String(), mf)
opts.ParentModel = "horseshark"
@@ -108,10 +107,10 @@ MESSAGE assistant """Yes it is true, I am half horse, half shark."""
`
tmpl, err = template.New("").Parse(expectedModelfile)
require.NoError(t, err)
assert.Nil(t, err)
var parentBuf bytes.Buffer
err = tmpl.Execute(&parentBuf, opts)
require.NoError(t, err)
assert.Nil(t, err)
assert.Equal(t, parentBuf.String(), mf)
}

View File

@@ -1,27 +0,0 @@
//go:build darwin || windows
package cmd
import (
"context"
"errors"
"time"
"github.com/ollama/ollama/api"
)
func waitForServer(ctx context.Context, client *api.Client) error {
// wait for the server to start
timeout := time.After(5 * time.Second)
tick := time.Tick(500 * time.Millisecond)
for {
select {
case <-timeout:
return errors.New("timed out waiting for server to start")
case <-tick:
if err := client.Heartbeat(ctx); err == nil {
return nil // server has started
}
}
}
}

View File

@@ -189,7 +189,7 @@ func LoadSentencePieceTokens(dirpath string, params *Params) (*Vocab, error) {
if params.VocabSize > len(v.Tokens) {
missingTokens := params.VocabSize - len(v.Tokens)
slog.Warn(fmt.Sprintf("vocab is missing %d tokens", missingTokens))
for cnt := range missingTokens {
for cnt := 0; cnt < missingTokens; cnt++ {
v.Tokens = append(v.Tokens, fmt.Sprintf("<dummy%05d>", cnt+1))
v.Scores = append(v.Scores, -1)
v.Types = append(v.Types, tokenTypeUserDefined)

View File

@@ -35,6 +35,7 @@ func addOnes(data []float32, vectorSize int) ([]float32, error) {
f32s = append(f32s, t...)
}
return f32s, nil
}

View File

@@ -119,12 +119,11 @@ func llamaRepack(name string, params *Params, data []float32, shape []uint64) ([
}
var heads int
switch {
case strings.HasSuffix(name, "attn_q.weight"):
if strings.HasSuffix(name, "attn_q.weight") {
heads = params.AttentionHeads
case strings.HasSuffix(name, "attn_k.weight"):
} else if strings.HasSuffix(name, "attn_k.weight") {
heads = cmp.Or(params.KeyValHeads, params.AttentionHeads)
default:
} else {
return nil, fmt.Errorf("unknown tensor name: %s", name)
}

View File

@@ -120,7 +120,7 @@ func (m *SafetensorFormat) readTensors(fn string, offset uint64, params *Params)
Name: name,
Kind: kind,
Offset: offset,
Shape: shape,
Shape: shape[:],
}
t.WriterTo = safetensorWriterTo{

View File

@@ -85,8 +85,11 @@ func parseTokens(dirpath string) (pre string, tokens []Token, merges []string, e
sha256sum := sha256.New()
for _, pt := range t.PreTokenizer.PreTokenizers {
if pt.Type == "Split" && pt.Pattern.Regex != "" {
sha256sum.Write([]byte(pt.Pattern.Regex))
switch pt.Type {
case "Split":
if pt.Pattern.Regex != "" {
sha256sum.Write([]byte(pt.Pattern.Regex))
}
}
}

View File

@@ -88,7 +88,7 @@ func (tf *TorchFormat) GetTensors(dirpath string, params *Params) ([]llm.Tensor,
Name: ggufName,
Kind: kind,
Offset: offset, // calculate the offset
Shape: shape,
Shape: shape[:],
}
tensor.WriterTo = torchWriterTo{
@@ -104,6 +104,7 @@ func (tf *TorchFormat) GetTensors(dirpath string, params *Params) ([]llm.Tensor,
}
return tensors, nil
}
func getAltParams(dirpath string) (*Params, error) {

View File

@@ -12,7 +12,6 @@
- [Pull a Model](#pull-a-model)
- [Push a Model](#push-a-model)
- [Generate Embeddings](#generate-embeddings)
- [List Running Models](#list-running-models)
## Conventions
@@ -250,7 +249,7 @@ curl http://localhost:11434/api/generate -d '{
#### Request (Reproducible outputs)
For reproducible outputs, set `seed` to a number:
For reproducible outputs, set `temperature` to 0 and `seed` to a number:
##### Request
@@ -259,7 +258,8 @@ curl http://localhost:11434/api/generate -d '{
"model": "mistral",
"prompt": "Why is the sky blue?",
"options": {
"seed": 123
"seed": 123,
"temperature": 0
}
}'
```
@@ -777,12 +777,11 @@ A single JSON object will be returned.
POST /api/show
```
Show information about a model including details, modelfile, template, parameters, license, system prompt.
Show information about a model including details, modelfile, template, parameters, license, and system prompt.
### Parameters
- `name`: name of the model to show
- `verbose`: (optional) if set to `true`, returns full data for verbose response fields
### Examples
@@ -799,40 +798,14 @@ curl http://localhost:11434/api/show -d '{
```json
{
"modelfile": "# Modelfile generated by \"ollama show\"\n# To build a new Modelfile based on this one, replace the FROM line with:\n# FROM llava:latest\n\nFROM /Users/matt/.ollama/models/blobs/sha256:200765e1283640ffbd013184bf496e261032fa75b99498a9613be4e94d63ad52\nTEMPLATE \"\"\"{{ .System }}\nUSER: {{ .Prompt }}\nASSISTANT: \"\"\"\nPARAMETER num_ctx 4096\nPARAMETER stop \"\u003c/s\u003e\"\nPARAMETER stop \"USER:\"\nPARAMETER stop \"ASSISTANT:\"",
"parameters": "num_keep 24\nstop \"<|start_header_id|>\"\nstop \"<|end_header_id|>\"\nstop \"<|eot_id|>\"",
"template": "{{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|>",
"parameters": "num_ctx 4096\nstop \u003c/s\u003e\nstop USER:\nstop ASSISTANT:",
"template": "{{ .System }}\nUSER: {{ .Prompt }}\nASSISTANT: ",
"details": {
"parent_model": "",
"format": "gguf",
"family": "llama",
"families": [
"llama"
],
"parameter_size": "8.0B",
"families": ["llama", "clip"],
"parameter_size": "7B",
"quantization_level": "Q4_0"
},
"model_info": {
"general.architecture": "llama",
"general.file_type": 2,
"general.parameter_count": 8030261248,
"general.quantization_version": 2,
"llama.attention.head_count": 32,
"llama.attention.head_count_kv": 8,
"llama.attention.layer_norm_rms_epsilon": 0.00001,
"llama.block_count": 32,
"llama.context_length": 8192,
"llama.embedding_length": 4096,
"llama.feed_forward_length": 14336,
"llama.rope.dimension_count": 128,
"llama.rope.freq_base": 500000,
"llama.vocab_size": 128256,
"tokenizer.ggml.bos_token_id": 128000,
"tokenizer.ggml.eos_token_id": 128009,
"tokenizer.ggml.merges": [], // populates if `verbose=true`
"tokenizer.ggml.model": "gpt2",
"tokenizer.ggml.pre": "llama-bpe",
"tokenizer.ggml.token_type": [], // populates if `verbose=true`
"tokenizer.ggml.tokens": [] // populates if `verbose=true`
}
}
```
@@ -1062,47 +1035,3 @@ curl http://localhost:11434/api/embeddings -d '{
]
}
```
## List Running Models
```shell
GET /api/ps
```
List models that are currently loaded into memory.
#### Examples
### Request
```shell
curl http://localhost:11434/api/ps
```
#### Response
A single JSON object will be returned.
```json
{
"models": [
{
"name": "mistral:latest",
"model": "mistral:latest",
"size": 5137025024,
"digest": "2ae6f6dd7a3dd734790bbbf58b8909a606e0e7e97e94b7604e0aa7ae4490e6d8",
"details": {
"parent_model": "",
"format": "gguf",
"family": "llama",
"families": [
"llama"
],
"parameter_size": "7.2B",
"quantization_level": "Q4_0"
},
"expires_at": "2024-06-04T14:38:31.83753-07:00",
"size_vram": 5137025024
}
]
}
```

View File

@@ -114,18 +114,15 @@ If you have Docker available, you can build linux binaries with `./scripts/build
### Windows
Note: The Windows build for Ollama is still under development.
Note: The windows build for Ollama is still under development.
First, install required tools:
Install required tools:
- MSVC toolchain - C/C++ and cmake as minimal requirements
- Go version 1.22 or higher
- MinGW (pick one variant) with GCC.
- [MinGW-w64](https://www.mingw-w64.org/)
- [MSYS2](https://www.msys2.org/)
- The `ThreadJob` Powershell module: `Install-Module -Name ThreadJob -Scope CurrentUser`
Then, build the `ollama` binary:
```powershell
$env:CGO_ENABLED="1"

View File

@@ -8,7 +8,7 @@ Check your compute compatibility to see if your card is supported:
| Compute Capability | Family | Cards |
| ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
| 9.0 | NVIDIA | `H100` |
| 8.9 | GeForce RTX 40xx | `RTX 4090` `RTX 4080 SUPER` `RTX 4080` `RTX 4070 Ti SUPER` `RTX 4070 Ti` `RTX 4070 SUPER` `RTX 4070` `RTX 4060 Ti` `RTX 4060` |
| 8.9 | GeForce RTX 40xx | `RTX 4090` `RTX 4080` `RTX 4070 Ti` `RTX 4060 Ti` |
| | NVIDIA Professional | `L4` `L40` `RTX 6000` |
| 8.6 | GeForce RTX 30xx | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060` |
| | NVIDIA Professional | `A40` `RTX A6000` `RTX A5000` `RTX A4000` `RTX A3000` `RTX A2000` `A10` `A16` `A2` |

View File

@@ -1,88 +1,170 @@
# Import
# Import a model
GGUF models and select Safetensors models can be imported directly into Ollama.
This guide walks through importing a GGUF, PyTorch or Safetensors model.
## Import GGUF
## Importing (GGUF)
A binary GGUF file can be imported directly into Ollama through a Modelfile.
### Step 1: Write a `Modelfile`
```dockerfile
FROM /path/to/file.gguf
Start by creating a `Modelfile`. This file is the blueprint for your model, specifying weights, parameters, prompt templates and more.
```
FROM ./mistral-7b-v0.1.Q4_0.gguf
```
## Import Safetensors
(Optional) many chat models require a prompt template in order to answer correctly. A default prompt template can be specified with the `TEMPLATE` instruction in the `Modelfile`:
If the model being imported is one of these architectures, it can be imported directly into Ollama through a Modelfile:
- LlamaForCausalLM
- MistralForCausalLM
- GemmaForCausalLM
```dockerfile
FROM /path/to/safetensors/directory
```
FROM ./mistral-7b-v0.1.Q4_0.gguf
TEMPLATE "[INST] {{ .Prompt }} [/INST]"
```
For architectures not directly convertable by Ollama, see llama.cpp's [guide](https://github.com/ggerganov/llama.cpp/blob/master/README.md#prepare-and-quantize) on conversion. After conversion, see [Import GGUF](#import-gguf).
### Step 2: Create the Ollama model
## Automatic Quantization
Finally, create a model from your `Modelfile`:
> [!NOTE]
> Automatic quantization requires v0.1.35 or higher.
Ollama is capable of quantizing FP16 or FP32 models to any of the supported quantizations with the `-q/--quantize` flag in `ollama create`.
```dockerfile
FROM /path/to/my/gemma/f16/model
```
ollama create example -f Modelfile
```
### Step 3: Run your model
Next, test the model with `ollama run`:
```
ollama run example "What is your favourite condiment?"
```
## Importing (PyTorch & Safetensors)
> Importing from PyTorch and Safetensors is a longer process than importing from GGUF. Improvements that make it easier are a work in progress.
### Setup
First, clone the `ollama/ollama` repo:
```
git clone git@github.com:ollama/ollama.git ollama
cd ollama
```
and then fetch its `llama.cpp` submodule:
```shell
$ ollama create -q Q4_K_M mymodel
transferring model data
quantizing F16 model to Q4_K_M
creating new layer sha256:735e246cc1abfd06e9cdcf95504d6789a6cd1ad7577108a70d9902fef503c1bd
creating new layer sha256:0853f0ad24e5865173bbf9ffcc7b0f5d56b66fd690ab1009867e45e7d2c4db0f
writing manifest
success
git submodule init
git submodule update llm/llama.cpp
```
### Supported Quantizations
Next, install the Python dependencies:
- `Q4_0`
- `Q4_1`
- `Q5_0`
- `Q5_1`
- `Q8_0`
#### K-means Quantizations
- `Q3_K_S`
- `Q3_K_M`
- `Q3_K_L`
- `Q4_K_S`
- `Q4_K_M`
- `Q5_K_S`
- `Q5_K_M`
- `Q6_K`
## Template Detection
> [!NOTE]
> Template detection requires v0.1.42 or higher.
Ollama uses model metadata, specifically `tokenizer.chat_template`, to automatically create a template appropriate for the model you're importing.
```dockerfile
FROM /path/to/my/gemma/model
```
python3 -m venv llm/llama.cpp/.venv
source llm/llama.cpp/.venv/bin/activate
pip install -r llm/llama.cpp/requirements.txt
```
```shell
$ ollama create mymodel
transferring model data
using autodetected template gemma-instruct
creating new layer sha256:baa2a0edc27d19cc6b7537578a9a7ba1a4e3214dc185ed5ae43692b319af7b84
creating new layer sha256:ba66c3309914dbef07e5149a648fd1877f030d337a4f240d444ea335008943cb
writing manifest
success
Then build the `quantize` tool:
```
make -C llm/llama.cpp quantize
```
Defining a template in the Modelfile will disable this feature which may be useful if you want to use a different template than the autodetected one.
### Clone the HuggingFace repository (optional)
If the model is currently hosted in a HuggingFace repository, first clone that repository to download the raw model.
Install [Git LFS](https://docs.github.com/en/repositories/working-with-files/managing-large-files/installing-git-large-file-storage), verify it's installed, and then clone the model's repository:
```
git lfs install
git clone https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1 model
```
### Convert the model
> Note: some model architectures require using specific convert scripts. For example, Qwen models require running `convert-hf-to-gguf.py` instead of `convert.py`
```
python llm/llama.cpp/convert.py ./model --outtype f16 --outfile converted.bin
```
### Quantize the model
```
llm/llama.cpp/quantize converted.bin quantized.bin q4_0
```
### Step 3: Write a `Modelfile`
Next, create a `Modelfile` for your model:
```
FROM quantized.bin
TEMPLATE "[INST] {{ .Prompt }} [/INST]"
```
### Step 4: Create the Ollama model
Finally, create a model from your `Modelfile`:
```
ollama create example -f Modelfile
```
### Step 5: Run your model
Next, test the model with `ollama run`:
```
ollama run example "What is your favourite condiment?"
```
## Publishing your model (optional early alpha)
Publishing models is in early alpha. If you'd like to publish your model to share with others, follow these steps:
1. Create [an account](https://ollama.com/signup)
2. Copy your Ollama public key:
- macOS: `cat ~/.ollama/id_ed25519.pub | pbcopy`
- Windows: `type %USERPROFILE%\.ollama\id_ed25519.pub`
- Linux: `cat /usr/share/ollama/.ollama/id_ed25519.pub`
3. Add your public key to your [Ollama account](https://ollama.com/settings/keys)
Next, copy your model to your username's namespace:
```
ollama cp example <your username>/example
```
> Note: model names may only contain lowercase letters, digits, and the characters `.`, `-`, and `_`.
Then push the model:
```
ollama push <your username>/example
```
After publishing, your model will be available at `https://ollama.com/<your username>/example`.
## Quantization reference
The quantization options are as follow (from highest highest to lowest levels of quantization). Note: some architectures such as Falcon do not support K quants.
- `q2_K`
- `q3_K`
- `q3_K_S`
- `q3_K_M`
- `q3_K_L`
- `q4_0` (recommended)
- `q4_1`
- `q4_K`
- `q4_K_S`
- `q4_K_M`
- `q5_0`
- `q5_1`
- `q5_K`
- `q5_K_S`
- `q5_K_M`
- `q6_K`
- `q8_0`
- `f16`

View File

@@ -100,16 +100,6 @@ sudo curl -L https://ollama.com/download/ollama-linux-amd64 -o /usr/bin/ollama
sudo chmod +x /usr/bin/ollama
```
## Installing specific versions
Use `OLLAMA_VERSION` environment variable with the install script to install a specific version of Ollama, including pre-releases. You can find the version numbers in the [releases page](https://github.com/ollama/ollama/releases).
For example:
```
curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION=0.1.32 sh
```
## Viewing logs
To view logs of Ollama running as a startup service, run:

View File

@@ -104,6 +104,7 @@ curl http://localhost:11434/v1/chat/completions \
#### Notes
- Setting `seed` will always set `temperature` to `0`
- `finish_reason` will always be `stop`
- `usage.prompt_tokens` will be 0 for completions where prompt evaluation is cached

View File

@@ -22,7 +22,7 @@ docker logs <container-name>
If manually running `ollama serve` in a terminal, the logs will be on that terminal.
When you run Ollama on **Windows**, there are a few different locations. You can view them in the explorer window by hitting `<cmd>+R` and type in:
- `explorer %LOCALAPPDATA%\Ollama` to view logs. The most recent server logs will be in `server.log` and older logs will be in `server-#.log`
- `explorer %LOCALAPPDATA%\Ollama` to view logs
- `explorer %LOCALAPPDATA%\Programs\Ollama` to browse the binaries (The installer adds this to your user PATH)
- `explorer %HOMEPATH%\.ollama` to browse where models and configuration is stored
- `explorer %TEMP%` where temporary executable files are stored in one or more `ollama*` directories

View File

@@ -45,7 +45,7 @@ all_splits = text_splitter.split_documents(data)
```
It's split up, but we have to find the relevant splits and then submit those to the model. We can do this by creating embeddings and storing them in a vector database. We can use Ollama directly to instantiate an embedding model. We will use ChromaDB in this example for a vector database. `pip install chromadb`
We also need to pull embedding model: `ollama pull nomic-embed-text`
```python
from langchain.embeddings import OllamaEmbeddings
from langchain.vectorstores import Chroma
@@ -68,8 +68,7 @@ The next thing is to send the question and the relevant parts of the docs to the
```python
from langchain.chains import RetrievalQA
qachain=RetrievalQA.from_chain_type(ollama, retriever=vectorstore.as_retriever())
res = qachain.invoke({"query": question})
print(res['result'])
qachain.invoke({"query": question})
```
The answer received from this chain was:

View File

@@ -39,8 +39,8 @@ server.
Ollama on Windows stores files in a few different locations. You can view them in
the explorer window by hitting `<cmd>+R` and type in:
- `explorer %LOCALAPPDATA%\Ollama` contains logs, and downloaded updates
- *app.log* contains most resent logs from the GUI application
- *server.log* contains the most recent server logs
- *app.log* contains logs from the GUI application
- *server.log* contains the server logs
- *upgrade.log* contains log output for upgrades
- `explorer %LOCALAPPDATA%\Programs\Ollama` contains the binaries (The installer adds this to your user PATH)
- `explorer %HOMEPATH%\.ollama` contains models and configuration

View File

@@ -1,10 +1,8 @@
package envconfig
import (
"errors"
"fmt"
"log/slog"
"net"
"os"
"path/filepath"
"runtime"
@@ -12,18 +10,6 @@ import (
"strings"
)
type OllamaHost struct {
Scheme string
Host string
Port string
}
func (o OllamaHost) String() string {
return fmt.Sprintf("%s://%s:%s", o.Scheme, o.Host, o.Port)
}
var ErrInvalidHostPort = errors.New("invalid port specified in OLLAMA_HOST")
var (
// Set via OLLAMA_ORIGINS in the environment
AllowOrigins []string
@@ -31,8 +17,6 @@ var (
Debug bool
// Experimental flash attention
FlashAttention bool
// Set via OLLAMA_HOST in the environment
Host *OllamaHost
// Set via OLLAMA_KEEP_ALIVE in the environment
KeepAlive string
// Set via OLLAMA_LLM_LIBRARY in the environment
@@ -41,8 +25,6 @@ var (
MaxRunners int
// Set via OLLAMA_MAX_QUEUE in the environment
MaxQueuedRequests int
// Set via OLLAMA_MODELS in the environment
ModelsDir string
// Set via OLLAMA_MAX_VRAM in the environment
MaxVRAM uint64
// Set via OLLAMA_NOHISTORY in the environment
@@ -53,23 +35,8 @@ var (
NumParallel int
// Set via OLLAMA_RUNNERS_DIR in the environment
RunnersDir string
// Set via OLLAMA_SCHED_SPREAD in the environment
SchedSpread bool
// Set via OLLAMA_TMPDIR in the environment
TmpDir string
// Set via OLLAMA_INTEL_GPU in the environment
IntelGpu bool
// Set via CUDA_VISIBLE_DEVICES in the environment
CudaVisibleDevices string
// Set via HIP_VISIBLE_DEVICES in the environment
HipVisibleDevices string
// Set via ROCR_VISIBLE_DEVICES in the environment
RocrVisibleDevices string
// Set via GPU_DEVICE_ORDINAL in the environment
GpuDeviceOrdinal string
// Set via HSA_OVERRIDE_GFX_VERSION in the environment
HsaOverrideGfxVersion string
)
type EnvVar struct {
@@ -79,33 +46,23 @@ type EnvVar struct {
}
func AsMap() map[string]EnvVar {
ret := map[string]EnvVar{
return map[string]EnvVar{
"OLLAMA_DEBUG": {"OLLAMA_DEBUG", Debug, "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
"OLLAMA_FLASH_ATTENTION": {"OLLAMA_FLASH_ATTENTION", FlashAttention, "Enabled flash attention"},
"OLLAMA_HOST": {"OLLAMA_HOST", Host, "IP Address for the ollama server (default 127.0.0.1:11434)"},
"OLLAMA_HOST": {"OLLAMA_HOST", "", "IP Address for the ollama server (default 127.0.0.1:11434)"},
"OLLAMA_KEEP_ALIVE": {"OLLAMA_KEEP_ALIVE", KeepAlive, "The duration that models stay loaded in memory (default \"5m\")"},
"OLLAMA_LLM_LIBRARY": {"OLLAMA_LLM_LIBRARY", LLMLibrary, "Set LLM library to bypass autodetection"},
"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models (default 1)"},
"OLLAMA_MAX_QUEUE": {"OLLAMA_MAX_QUEUE", MaxQueuedRequests, "Maximum number of queued requests"},
"OLLAMA_MAX_VRAM": {"OLLAMA_MAX_VRAM", MaxVRAM, "Maximum VRAM"},
"OLLAMA_MODELS": {"OLLAMA_MODELS", ModelsDir, "The path to the models directory"},
"OLLAMA_MODELS": {"OLLAMA_MODELS", "", "The path to the models directory"},
"OLLAMA_NOHISTORY": {"OLLAMA_NOHISTORY", NoHistory, "Do not preserve readline history"},
"OLLAMA_NOPRUNE": {"OLLAMA_NOPRUNE", NoPrune, "Do not prune model blobs on startup"},
"OLLAMA_NUM_PARALLEL": {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests (default 1)"},
"OLLAMA_ORIGINS": {"OLLAMA_ORIGINS", AllowOrigins, "A comma separated list of allowed origins"},
"OLLAMA_RUNNERS_DIR": {"OLLAMA_RUNNERS_DIR", RunnersDir, "Location for runners"},
"OLLAMA_SCHED_SPREAD": {"OLLAMA_SCHED_SPREAD", SchedSpread, "Always schedule model across all GPUs"},
"OLLAMA_TMPDIR": {"OLLAMA_TMPDIR", TmpDir, "Location for temporary files"},
}
if runtime.GOOS != "darwin" {
ret["CUDA_VISIBLE_DEVICES"] = EnvVar{"CUDA_VISIBLE_DEVICES", CudaVisibleDevices, "Set which NVIDIA devices are visible"}
ret["HIP_VISIBLE_DEVICES"] = EnvVar{"HIP_VISIBLE_DEVICES", HipVisibleDevices, "Set which AMD devices are visible"}
ret["ROCR_VISIBLE_DEVICES"] = EnvVar{"ROCR_VISIBLE_DEVICES", RocrVisibleDevices, "Set which AMD devices are visible"}
ret["GPU_DEVICE_ORDINAL"] = EnvVar{"GPU_DEVICE_ORDINAL", GpuDeviceOrdinal, "Set which AMD devices are visible"}
ret["HSA_OVERRIDE_GFX_VERSION"] = EnvVar{"HSA_OVERRIDE_GFX_VERSION", HsaOverrideGfxVersion, "Override the gfx used for all detected AMD GPUs"}
ret["OLLAMA_INTEL_GPU"] = EnvVar{"OLLAMA_INTEL_GPU", IntelGpu, "Enable experimental Intel GPU detection"}
}
return ret
}
func Values() map[string]string {
@@ -169,7 +126,7 @@ func LoadConfig() {
var paths []string
for _, root := range []string{filepath.Dir(appExe), cwd} {
paths = append(paths,
root,
filepath.Join(root),
filepath.Join(root, "windows-"+runtime.GOARCH),
filepath.Join(root, "dist", "windows-"+runtime.GOARCH),
)
@@ -216,15 +173,6 @@ func LoadConfig() {
NoHistory = true
}
if spread := clean("OLLAMA_SCHED_SPREAD"); spread != "" {
s, err := strconv.ParseBool(spread)
if err == nil {
SchedSpread = s
} else {
SchedSpread = true
}
}
if noprune := clean("OLLAMA_NOPRUNE"); noprune != "" {
NoPrune = true
}
@@ -236,17 +184,11 @@ func LoadConfig() {
AllowOrigins = append(AllowOrigins,
fmt.Sprintf("http://%s", allowOrigin),
fmt.Sprintf("https://%s", allowOrigin),
fmt.Sprintf("http://%s", net.JoinHostPort(allowOrigin, "*")),
fmt.Sprintf("https://%s", net.JoinHostPort(allowOrigin, "*")),
fmt.Sprintf("http://%s:*", allowOrigin),
fmt.Sprintf("https://%s:*", allowOrigin),
)
}
AllowOrigins = append(AllowOrigins,
"app://*",
"file://*",
"tauri://*",
)
maxRunners := clean("OLLAMA_MAX_LOADED_MODELS")
if maxRunners != "" {
m, err := strconv.Atoi(maxRunners)
@@ -267,80 +209,4 @@ func LoadConfig() {
}
KeepAlive = clean("OLLAMA_KEEP_ALIVE")
var err error
ModelsDir, err = getModelsDir()
if err != nil {
slog.Error("invalid setting", "OLLAMA_MODELS", ModelsDir, "error", err)
}
Host, err = getOllamaHost()
if err != nil {
slog.Error("invalid setting", "OLLAMA_HOST", Host, "error", err, "using default port", Host.Port)
}
if set, err := strconv.ParseBool(clean("OLLAMA_INTEL_GPU")); err == nil {
IntelGpu = set
}
CudaVisibleDevices = clean("CUDA_VISIBLE_DEVICES")
HipVisibleDevices = clean("HIP_VISIBLE_DEVICES")
RocrVisibleDevices = clean("ROCR_VISIBLE_DEVICES")
GpuDeviceOrdinal = clean("GPU_DEVICE_ORDINAL")
HsaOverrideGfxVersion = clean("HSA_OVERRIDE_GFX_VERSION")
}
func getModelsDir() (string, error) {
if models, exists := os.LookupEnv("OLLAMA_MODELS"); exists {
return models, nil
}
home, err := os.UserHomeDir()
if err != nil {
return "", err
}
return filepath.Join(home, ".ollama", "models"), nil
}
func getOllamaHost() (*OllamaHost, error) {
defaultPort := "11434"
hostVar := os.Getenv("OLLAMA_HOST")
hostVar = strings.TrimSpace(strings.Trim(strings.TrimSpace(hostVar), "\"'"))
scheme, hostport, ok := strings.Cut(hostVar, "://")
switch {
case !ok:
scheme, hostport = "http", hostVar
case scheme == "http":
defaultPort = "80"
case scheme == "https":
defaultPort = "443"
}
// trim trailing slashes
hostport = strings.TrimRight(hostport, "/")
host, port, err := net.SplitHostPort(hostport)
if err != nil {
host, port = "127.0.0.1", defaultPort
if ip := net.ParseIP(strings.Trim(hostport, "[]")); ip != nil {
host = ip.String()
} else if hostport != "" {
host = hostport
}
}
if portNum, err := strconv.ParseInt(port, 10, 32); err != nil || portNum > 65535 || portNum < 0 {
return &OllamaHost{
Scheme: scheme,
Host: host,
Port: defaultPort,
}, ErrInvalidHostPort
}
return &OllamaHost{
Scheme: scheme,
Host: host,
Port: port,
}, nil
}

View File

@@ -1,11 +1,8 @@
package envconfig
import (
"fmt"
"net"
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
@@ -24,48 +21,3 @@ func TestConfig(t *testing.T) {
LoadConfig()
require.True(t, FlashAttention)
}
func TestClientFromEnvironment(t *testing.T) {
type testCase struct {
value string
expect string
err error
}
hostTestCases := map[string]*testCase{
"empty": {value: "", expect: "127.0.0.1:11434"},
"only address": {value: "1.2.3.4", expect: "1.2.3.4:11434"},
"only port": {value: ":1234", expect: ":1234"},
"address and port": {value: "1.2.3.4:1234", expect: "1.2.3.4:1234"},
"hostname": {value: "example.com", expect: "example.com:11434"},
"hostname and port": {value: "example.com:1234", expect: "example.com:1234"},
"zero port": {value: ":0", expect: ":0"},
"too large port": {value: ":66000", err: ErrInvalidHostPort},
"too small port": {value: ":-1", err: ErrInvalidHostPort},
"ipv6 localhost": {value: "[::1]", expect: "[::1]:11434"},
"ipv6 world open": {value: "[::]", expect: "[::]:11434"},
"ipv6 no brackets": {value: "::1", expect: "[::1]:11434"},
"ipv6 + port": {value: "[::1]:1337", expect: "[::1]:1337"},
"extra space": {value: " 1.2.3.4 ", expect: "1.2.3.4:11434"},
"extra quotes": {value: "\"1.2.3.4\"", expect: "1.2.3.4:11434"},
"extra space+quotes": {value: " \" 1.2.3.4 \" ", expect: "1.2.3.4:11434"},
"extra single quotes": {value: "'1.2.3.4'", expect: "1.2.3.4:11434"},
}
for k, v := range hostTestCases {
t.Run(k, func(t *testing.T) {
t.Setenv("OLLAMA_HOST", v.value)
LoadConfig()
oh, err := getOllamaHost()
if err != v.err {
t.Fatalf("expected %s, got %s", v.err, err)
}
if err == nil {
host := net.JoinHostPort(oh.Host, oh.Port)
assert.Equal(t, v.expect, host, fmt.Sprintf("%s: expected %s, got %s", k, v.expect, host))
}
})
}
}

View File

@@ -77,21 +77,13 @@ LOADER_MAPPING = {
def load_single_document(file_path: str) -> List[Document]:
if os.path.getsize(file_path) != 0:
filename, ext = os.path.splitext(file_path)
if ext in LOADER_MAPPING:
loader_class, loader_args = LOADER_MAPPING[ext]
try:
loader = loader_class(file_path, **loader_args)
if loader:
return loader.load()
except:
print(f"Corrupted file {file_path}. Ignoring it.")
else:
print(f"Unsupported file {file_path}. Ignoring it.")
else:
print(f"Empty file {file_path}. Ignoring it.")
ext = "." + file_path.rsplit(".", 1)[-1]
if ext in LOADER_MAPPING:
loader_class, loader_args = LOADER_MAPPING[ext]
loader = loader_class(file_path, **loader_args)
return loader.load()
raise ValueError(f"Unsupported file extension '{ext}'")
def load_documents(source_dir: str, ignored_files: List[str] = []) -> List[Document]:
"""
@@ -108,8 +100,7 @@ def load_documents(source_dir: str, ignored_files: List[str] = []) -> List[Docum
results = []
with tqdm(total=len(filtered_files), desc='Loading new documents', ncols=80) as pbar:
for i, docs in enumerate(pool.imap_unordered(load_single_document, filtered_files)):
if docs:
results.extend(docs)
results.extend(docs)
pbar.update()
return results

View File

@@ -11,5 +11,4 @@ tabulate==0.9.0
pandoc==2.3
pypandoc==1.11
tqdm==4.66.1
sentence_transformers==2.2.2
numpy>=1.22.2 # not directly required, pinned by Snyk to avoid a vulnerability
sentence_transformers==2.2.2

View File

@@ -2,32 +2,41 @@ package format
import (
"fmt"
"math"
)
const (
Thousand = 1000
Million = Thousand * 1000
Billion = Million * 1000
Trillion = Billion * 1000
)
func HumanNumber(b uint64) string {
switch {
case b >= Trillion:
number := float64(b) / Trillion
return fmt.Sprintf("%sT", DecimalPlace(number))
case b >= Billion:
number := float64(b) / Billion
if number == math.Floor(number) {
return fmt.Sprintf("%.0fB", number) // no decimals if whole number
}
return fmt.Sprintf("%.1fB", number) // one decimal if not a whole number
return fmt.Sprintf("%sB", DecimalPlace(number))
case b >= Million:
number := float64(b) / Million
if number == math.Floor(number) {
return fmt.Sprintf("%.0fM", number) // no decimals if whole number
}
return fmt.Sprintf("%.2fM", number) // two decimals if not a whole number
return fmt.Sprintf("%sM", DecimalPlace(number))
case b >= Thousand:
return fmt.Sprintf("%.0fK", float64(b)/Thousand)
number := float64(b) / Thousand
return fmt.Sprintf("%sK", DecimalPlace(number))
default:
return fmt.Sprintf("%d", b)
}
}
func DecimalPlace(number float64) string {
switch {
case number >= 100:
return fmt.Sprintf("%.0f", number)
case number >= 10:
return fmt.Sprintf("%.1f", number)
default:
return fmt.Sprintf("%.2f", number)
}
}

View File

@@ -5,6 +5,7 @@ import (
)
func TestHumanNumber(t *testing.T) {
type testCase struct {
input uint64
expected string
@@ -12,14 +13,15 @@ func TestHumanNumber(t *testing.T) {
testCases := []testCase{
{0, "0"},
{1000000, "1M"},
{1000000, "1.00M"},
{125000000, "125M"},
{500500000, "500.50M"},
{500550000, "500.55M"},
{1000000000, "1B"},
{2800000000, "2.8B"},
{2850000000, "2.9B"},
{1000000000000, "1000B"},
{500500000, "500M"},
{500550000, "501M"},
{1000000000, "1.00B"},
{2800000000, "2.80B"},
{2850000000, "2.85B"},
{28550000000, "28.6B"},
{1000000000000, "1.00T"},
}
for _, tc := range testCases {

1
go.mod
View File

@@ -16,7 +16,6 @@ require (
)
require (
github.com/agnivade/levenshtein v1.1.1
github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
github.com/mattn/go-runewidth v0.0.14
github.com/nlpodyssey/gopickle v0.3.0

6
go.sum
View File

@@ -4,14 +4,10 @@ dmitri.shuralyov.com/gpu/mtl v0.0.0-20190408044501-666a987793e9/go.mod h1:H6x//7
gioui.org v0.0.0-20210308172011-57750fc8a0a6/go.mod h1:RSH6KIUZ0p2xy5zHDxgAM4zumjgTw83q2ge/PI+yyw8=
github.com/BurntSushi/toml v0.3.1/go.mod h1:xHWCNGjB5oqiDr8zfno3MHue2Ht5sIBksp03qcyfWMU=
github.com/BurntSushi/xgb v0.0.0-20160522181843-27f122750802/go.mod h1:IVnqGOEym/WlBOVXweHU+Q+/VP0lqqI8lqeDx9IjBqo=
github.com/agnivade/levenshtein v1.1.1 h1:QY8M92nrzkmr798gCo3kmMyqXFzdQVpxLlGPRBij0P8=
github.com/agnivade/levenshtein v1.1.1/go.mod h1:veldBMzWxcCG2ZvUTKD2kJNRdCk5hVbJomOvKkmgYbo=
github.com/ajstarks/svgo v0.0.0-20180226025133-644b8db467af/go.mod h1:K08gAheRH3/J6wwsYMMT4xOr94bZjxIelGM0+d/wbFw=
github.com/antihax/optional v1.0.0/go.mod h1:uupD/76wgC+ih3iEmQUL+0Ugr19nfwCT1kdvxnR2qWY=
github.com/apache/arrow/go/arrow v0.0.0-20211112161151-bc219186db40 h1:q4dksr6ICHXqG5hm0ZW5IHyeEJXoIJSOZeBLmWPNeIQ=
github.com/apache/arrow/go/arrow v0.0.0-20211112161151-bc219186db40/go.mod h1:Q7yQnSMnLvcXlZ8RV+jwz/6y1rQTqbX6C82SndT52Zs=
github.com/arbovm/levenshtein v0.0.0-20160628152529-48b4e1c0c4d0 h1:jfIu9sQUG6Ig+0+Ap1h4unLjW6YQJpKZVmUzxsD4E/Q=
github.com/arbovm/levenshtein v0.0.0-20160628152529-48b4e1c0c4d0/go.mod h1:t2tdKJDJF9BV14lnkjHmOQgcvEKgtqs5a1N3LNdJhGE=
github.com/boombuler/barcode v1.0.0/go.mod h1:paBWMcWSl3LHKBqUq+rly7CNSldXjb2rDl3JlRe0mD8=
github.com/bytedance/sonic v1.11.6 h1:oUp34TzMlL+OY1OUWxHqsdkgC/Zfc85zGqw9siXjrc0=
github.com/bytedance/sonic v1.11.6/go.mod h1:LysEHSvpvDySVdC2f87zGWf6CIKJcAvqab1ZaiQtds4=
@@ -40,8 +36,6 @@ github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1/go.mod h1:uw2gLc
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dgryski/trifles v0.0.0-20200323201526-dd97f9abfb48 h1:fRzb/w+pyskVMQ+UbP35JkH8yB7MYb4q/qhBarqZE6g=
github.com/dgryski/trifles v0.0.0-20200323201526-dd97f9abfb48/go.mod h1:if7Fbed8SFyPtHLHbg49SI7NAdJiC5WIA09pe59rfAA=
github.com/emirpasic/gods v1.18.1 h1:FXtiHYKDGKCW2KzwZKx0iC0PQmdlorYgdFG9jPXJ1Bc=
github.com/emirpasic/gods v1.18.1/go.mod h1:8tpGGwCnJ5H4r6BWwaV6OrWmMoPhUl5jm/FMNAnJvWQ=
github.com/envoyproxy/go-control-plane v0.9.0/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=

View File

@@ -13,7 +13,6 @@ import (
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
)
@@ -26,16 +25,7 @@ const (
// Prefix with the node dir
GPUTotalMemoryFileGlob = "mem_banks/*/properties" // size_in_bytes line
// Direct Rendering Manager sysfs location
DRMDeviceDirGlob = "/sys/class/drm/card*/device"
DRMTotalMemoryFile = "mem_info_vram_total"
DRMUsedMemoryFile = "mem_info_vram_used"
// In hex; properties file is in decimal
DRMUniqueIDFile = "unique_id"
DRMVendorFile = "vendor"
DRMDeviceFile = "device"
GPUUsedMemoryFileGlob = "mem_banks/*/used_memory"
)
var (
@@ -45,8 +35,8 @@ var (
)
// Gather GPU information from the amdgpu driver if any supported GPUs are detected
func AMDGetGPUInfo() []RocmGPUInfo {
resp := []RocmGPUInfo{}
func AMDGetGPUInfo() []GpuInfo {
resp := []GpuInfo{}
if !AMDDetected() {
return resp
}
@@ -60,9 +50,9 @@ func AMDGetGPUInfo() []RocmGPUInfo {
// Determine if the user has already pre-selected which GPUs to look at, then ignore the others
var visibleDevices []string
hipVD := envconfig.HipVisibleDevices // zero based index only
rocrVD := envconfig.RocrVisibleDevices // zero based index or UUID, but consumer cards seem to not support UUID
gpuDO := envconfig.GpuDeviceOrdinal // zero based index
hipVD := os.Getenv("HIP_VISIBLE_DEVICES") // zero based index only
rocrVD := os.Getenv("ROCR_VISIBLE_DEVICES") // zero based index or UUID, but consumer cards seem to not support UUID
gpuDO := os.Getenv("GPU_DEVICE_ORDINAL") // zero based index
switch {
// TODO is this priorty order right?
case hipVD != "":
@@ -75,7 +65,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
visibleDevices = strings.Split(gpuDO, ",")
}
gfxOverride := envconfig.HsaOverrideGfxVersion
gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
var supported []string
libDir := ""
@@ -100,7 +90,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
scanner := bufio.NewScanner(fp)
isCPU := false
var major, minor, patch uint64
var vendor, device, uniqueID uint64
var vendor, device uint64
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
// Note: we could also use "cpu_cores_count X" where X is greater than zero to detect CPUs
@@ -131,43 +121,30 @@ func AMDGetGPUInfo() []RocmGPUInfo {
} else if strings.HasPrefix(line, "vendor_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "vendor_id", line)
slog.Debug("malformed vendor_id", "vendor_id", line)
continue
}
vendor, err = strconv.ParseUint(ver[1], 10, 64)
vendor, err = strconv.ParseUint(ver[1], 10, 32)
if err != nil {
slog.Debug("malformed", "vendor_id", line, "error", err)
slog.Debug("malformed vendor_id" + line)
}
} else if strings.HasPrefix(line, "device_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "device_id", line)
slog.Debug("malformed device_id", "device_id", line)
continue
}
device, err = strconv.ParseUint(ver[1], 10, 64)
device, err = strconv.ParseUint(ver[1], 10, 32)
if err != nil {
slog.Debug("malformed", "device_id", line, "error", err)
}
} else if strings.HasPrefix(line, "unique_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "unique_id", line)
continue
}
uniqueID, err = strconv.ParseUint(ver[1], 10, 64)
if err != nil {
slog.Debug("malformed", "unique_id", line, "error", err)
slog.Debug("malformed device_id" + line)
}
}
// TODO - any other properties we want to extract and record?
// vendor_id + device_id -> pci lookup for "Name"
// Other metrics that may help us understand relative performance between multiple GPUs
}
// Note: while ./mem_banks/*/used_memory exists, it doesn't appear to take other VRAM consumers
// into consideration, so we instead map the device over to the DRM driver sysfs nodes which
// do reliably report VRAM usage.
if isCPU {
cpuCount++
continue
@@ -179,7 +156,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
// Shouldn't happen, but just in case...
if gpuID < 0 {
slog.Error("unexpected amdgpu sysfs data resulted in negative GPU ID, please set OLLAMA_DEBUG=1 and report an issue")
return nil
return []GpuInfo{}
}
if int(major) < RocmComputeMin {
@@ -190,68 +167,65 @@ func AMDGetGPUInfo() []RocmGPUInfo {
// Look up the memory for the current node
totalMemory := uint64(0)
usedMemory := uint64(0)
var usedFile string
mapping := []struct {
id uint64
filename string
}{
{vendor, DRMVendorFile},
{device, DRMDeviceFile},
{uniqueID, DRMUniqueIDFile}, // Not all devices will report this
propGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUTotalMemoryFileGlob)
propFiles, err := filepath.Glob(propGlob)
if err != nil {
slog.Warn("error looking up total GPU memory", "glob", propGlob, "error", err)
}
slog.Debug("mapping amdgpu to drm sysfs nodes", "amdgpu", match, "vendor", vendor, "device", device, "unique_id", uniqueID)
// Map over to DRM location to find the total/free memory
drmMatches, _ := filepath.Glob(DRMDeviceDirGlob)
for _, devDir := range drmMatches {
matched := true
for _, m := range mapping {
if m.id == 0 {
// Null ID means it didn't populate, so we can't use it to match
continue
}
filename := filepath.Join(devDir, m.filename)
buf, err := os.ReadFile(filename)
if err != nil {
slog.Debug("failed to read sysfs node", "file", filename, "error", err)
matched = false
break
}
// values here are in hex, strip off the lead 0x and parse so we can compare the numeric (decimal) values in amdgpu
cmp, err := strconv.ParseUint(strings.TrimPrefix(strings.TrimSpace(string(buf)), "0x"), 16, 64)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", filename, "error", err)
matched = false
break
}
if cmp != m.id {
matched = false
break
}
}
if !matched {
// 1 or more memory banks - sum the values of all of them
for _, propFile := range propFiles {
fp, err := os.Open(propFile)
if err != nil {
slog.Warn("failed to open sysfs node", "file", propFile, "erroir", err)
continue
}
// Found the matching DRM directory
slog.Debug("matched", "amdgpu", match, "drm", devDir)
totalFile := filepath.Join(devDir, DRMTotalMemoryFile)
buf, err := os.ReadFile(totalFile)
if err != nil {
slog.Debug("failed to read sysfs node", "file", totalFile, "error", err)
break
defer fp.Close()
scanner := bufio.NewScanner(fp)
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
if strings.HasPrefix(line, "size_in_bytes") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Warn("malformed " + line)
continue
}
bankSizeInBytes, err := strconv.ParseUint(ver[1], 10, 64)
if err != nil {
slog.Warn("malformed int " + line)
continue
}
totalMemory += bankSizeInBytes
}
}
totalMemory, err = strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
}
if totalMemory == 0 {
slog.Warn("amdgpu reports zero total memory", "gpu", gpuID)
continue
}
usedGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUUsedMemoryFileGlob)
usedFiles, err := filepath.Glob(usedGlob)
if err != nil {
slog.Warn("error looking up used GPU memory", "glob", usedGlob, "error", err)
continue
}
for _, usedFile := range usedFiles {
fp, err := os.Open(usedFile)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", totalFile, "error", err)
break
slog.Warn("failed to open sysfs node", "file", usedFile, "error", err)
continue
}
usedFile = filepath.Join(devDir, DRMUsedMemoryFile)
usedMemory, err = getFreeMemory(usedFile)
defer fp.Close()
data, err := io.ReadAll(fp)
if err != nil {
slog.Debug("failed to update used memory", "error", err)
slog.Warn("failed to read sysfs node", "file", usedFile, "error", err)
continue
}
break
used, err := strconv.ParseUint(strings.TrimSpace(string(data)), 10, 64)
if err != nil {
slog.Warn("malformed used memory", "data", string(data), "error", err)
continue
}
usedMemory += used
}
// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
@@ -267,21 +241,18 @@ func AMDGetGPUInfo() []RocmGPUInfo {
slog.Debug("amdgpu memory", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
slog.Debug("amdgpu memory", "gpu", gpuID, "available", format.HumanBytes2(totalMemory-usedMemory))
gpuInfo := RocmGPUInfo{
GpuInfo: GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: (totalMemory - usedMemory),
},
ID: strconv.Itoa(gpuID),
Name: name,
Compute: fmt.Sprintf("gfx%d%x%x", major, minor, patch),
MinimumMemory: rocmMinimumMemory,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
gpuInfo := GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: (totalMemory - usedMemory),
},
usedFilepath: usedFile,
ID: fmt.Sprintf("%d", gpuID),
Name: name,
Compute: fmt.Sprintf("gfx%d%x%x", major, minor, patch),
MinimumMemory: rocmMinimumMemory,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
}
// If the user wants to filter to a subset of devices, filter out if we aren't a match
@@ -305,7 +276,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
libDir, err = AMDValidateLibDir()
if err != nil {
slog.Warn("unable to verify rocm library, will use cpu", "error", err)
return nil
return []GpuInfo{}
}
}
gpuInfo.DependencyPath = libDir
@@ -316,7 +287,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
supported, err = GetSupportedGFX(libDir)
if err != nil {
slog.Warn("failed to lookup supported GFX types, falling back to CPU mode", "error", err)
return nil
return []GpuInfo{}
}
slog.Debug("rocm supported GPUs", "types", supported)
}
@@ -333,11 +304,6 @@ func AMDGetGPUInfo() []RocmGPUInfo {
slog.Info("skipping rocm gfx compatibility check", "HSA_OVERRIDE_GFX_VERSION", gfxOverride)
}
// Check for env var workarounds
if name == "1002:687f" { // Vega RX 56
gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, [2]string{"HSA_ENABLE_SDMA", "0"})
}
// The GPU has passed all the verification steps and is supported
resp = append(resp, gpuInfo)
}
@@ -412,31 +378,3 @@ func AMDDriverVersion() (driverMajor, driverMinor int, err error) {
}
return driverMajor, driverMinor, nil
}
func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
if len(gpus) == 0 {
return nil
}
for i := range gpus {
usedMemory, err := getFreeMemory(gpus[i].usedFilepath)
if err != nil {
return err
}
slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(gpus[i].TotalMemory-usedMemory))
gpus[i].FreeMemory = gpus[i].TotalMemory - usedMemory
}
return nil
}
func getFreeMemory(usedFile string) (uint64, error) {
buf, err := os.ReadFile(usedFile)
if err != nil {
return 0, fmt.Errorf("failed to read sysfs node %s %w", usedFile, err)
}
usedMemory, err := strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", usedFile, "error", err)
return 0, fmt.Errorf("failed to parse sysfs node %s %w", usedFile, err)
}
return usedMemory, nil
}

View File

@@ -7,10 +7,8 @@ import (
"os"
"path/filepath"
"slices"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
)
@@ -26,8 +24,8 @@ var (
RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\5.7\\bin"} // TODO glob?
)
func AMDGetGPUInfo() []RocmGPUInfo {
resp := []RocmGPUInfo{}
func AMDGetGPUInfo() []GpuInfo {
resp := []GpuInfo{}
hl, err := NewHipLib()
if err != nil {
slog.Debug(err.Error())
@@ -54,7 +52,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
}
var supported []string
gfxOverride := envconfig.HsaOverrideGfxVersion
gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
if gfxOverride == "" {
supported, err = GetSupportedGFX(libDir)
if err != nil {
@@ -67,7 +65,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
slog.Debug("detected hip devices", "count", count)
// TODO how to determine the underlying device ID when visible devices is causing this to subset?
for i := range count {
for i := 0; i < count; i++ {
err = hl.HipSetDevice(i)
if err != nil {
slog.Warn("set device", "id", i, "error", err)
@@ -119,24 +117,21 @@ func AMDGetGPUInfo() []RocmGPUInfo {
// v5.7 only reports VRAM used by this process, so it's completely wrong and unusable
slog.Debug("amdgpu memory", "gpu", i, "total", format.HumanBytes2(totalMemory))
slog.Debug("amdgpu memory", "gpu", i, "available", format.HumanBytes2(freeMemory))
gpuInfo := RocmGPUInfo{
GpuInfo: GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: freeMemory,
},
ID: strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
DependencyPath: libDir,
MinimumMemory: rocmMinimumMemory,
Name: name,
Compute: gfx,
// TODO - this information isn't accurate on windows, so don't report it until we find the right way to retrieve
// DriverMajor: driverMajor,
// DriverMinor: driverMinor,
gpuInfo := GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: freeMemory,
},
index: i,
ID: fmt.Sprintf("%d", i), // TODO this is probably wrong if we specify visible devices
DependencyPath: libDir,
MinimumMemory: rocmMinimumMemory,
Name: name,
Compute: gfx,
// TODO - this information isn't accurate on windows, so don't report it until we find the right way to retrieve
// DriverMajor: driverMajor,
// DriverMinor: driverMinor,
}
resp = append(resp, gpuInfo)
@@ -164,30 +159,3 @@ func AMDValidateLibDir() (string, error) {
slog.Warn("amdgpu detected, but no compatible rocm library found. Please install ROCm")
return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
}
func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
if len(gpus) == 0 {
return nil
}
hl, err := NewHipLib()
if err != nil {
slog.Debug(err.Error())
return nil
}
defer hl.Release()
for i := range gpus {
err := hl.HipSetDevice(gpus[i].index)
if err != nil {
return err
}
freeMemory, _, err := hl.HipMemGetInfo()
if err != nil {
slog.Warn("get mem info", "id", i, "error", err)
continue
}
slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(freeMemory))
gpus[i].FreeMemory = freeMemory
}
return nil
}

View File

@@ -77,27 +77,20 @@ func cleanupTmpDirs() {
continue
}
raw, err := os.ReadFile(filepath.Join(d, "ollama.pid"))
if err == nil {
pid, err := strconv.Atoi(string(raw))
if err == nil {
if proc, err := os.FindProcess(int(pid)); err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
// Another running ollama, ignore this tmpdir
continue
}
}
} else {
slog.Debug("failed to open ollama.pid", "path", d, "error", err)
}
err = os.RemoveAll(d)
if err != nil {
slog.Warn("failed to read ollama.pid", "path", d, "error", err)
// No pid, ignore this tmpdir
continue
}
pid, err := strconv.Atoi(string(raw))
if err != nil {
slog.Warn("failed to parse pid", "path", d, "error", err)
continue
}
proc, err := os.FindProcess(pid)
if err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
slog.Warn("found running ollama", "pid", pid, "path", d)
// Another running ollama, ignore this tmpdir
continue
}
if err := os.Remove(d); err != nil {
slog.Warn("unable to cleanup stale tmpdir", "path", d, "error", err)
slog.Debug("unable to cleanup stale tmpdir", "path", d, "error", err)
}
}
}

View File

@@ -1,16 +1,21 @@
package gpu
import (
"log/slog"
"golang.org/x/sys/cpu"
)
func GetCPUCapability() CPUCapability {
func GetCPUVariant() string {
if cpu.X86.HasAVX2 {
return CPUCapabilityAVX2
slog.Debug("CPU has AVX2")
return "avx2"
}
if cpu.X86.HasAVX {
return CPUCapabilityAVX
slog.Debug("CPU has AVX")
return "avx"
}
slog.Debug("CPU does not have vector extensions")
// else LCD
return CPUCapabilityNone
return ""
}

View File

@@ -18,4 +18,5 @@ func cudaGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
ids = append(ids, info.ID)
}
return "CUDA_VISIBLE_DEVICES", strings.Join(ids, ",")
}

View File

@@ -24,37 +24,19 @@ import (
"github.com/ollama/ollama/format"
)
type cudaHandles struct {
type handles struct {
deviceCount int
cudart *C.cudart_handle_t
nvcuda *C.nvcuda_handle_t
nvml *C.nvml_handle_t
}
type oneapiHandles struct {
oneapi *C.oneapi_handle_t
deviceCount int
}
const (
cudaMinimumMemory = 457 * format.MebiByte
rocmMinimumMemory = 457 * format.MebiByte
// TODO OneAPI minimum memory
)
var (
gpuMutex sync.Mutex
bootstrapped bool
cpuCapability CPUCapability
cpus []CPUInfo
cudaGPUs []CudaGPUInfo
nvcudaLibPath string
cudartLibPath string
oneapiLibPath string
nvmlLibPath string
rocmGPUs []RocmGPUInfo
oneapiGPUs []OneapiGPUInfo
)
var gpuMutex sync.Mutex
// With our current CUDA compile flags, older than 5.0 will not work properly
var CudaComputeMin = [2]C.int{5, 0}
@@ -64,113 +46,113 @@ var RocmComputeMin = 9
// TODO find a better way to detect iGPU instead of minimum memory
const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU
var CudartLinuxGlobs = []string{
"/usr/local/cuda/lib64/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/libcudart.so*",
"/usr/lib/wsl/lib/libcudart.so*",
"/usr/lib/wsl/drivers/*/libcudart.so*",
"/opt/cuda/lib64/libcudart.so*",
"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/libcudart.so*",
"/usr/local/cuda/lib*/libcudart.so*",
"/usr/lib*/libcudart.so*",
"/usr/local/lib*/libcudart.so*",
}
var CudartWindowsGlobs = []string{
"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
}
var NvcudaLinuxGlobs = []string{
"/usr/local/cuda*/targets/*/lib/libcuda.so*",
"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
"/usr/lib/*-linux-gnu/libcuda.so*",
"/usr/lib/wsl/lib/libcuda.so*",
"/usr/lib/wsl/drivers/*/libcuda.so*",
"/opt/cuda/lib*/libcuda.so*",
"/usr/local/cuda/lib*/libcuda.so*",
"/usr/lib*/libcuda.so*",
"/usr/local/lib*/libcuda.so*",
}
var NvcudaWindowsGlobs = []string{
"c:\\windows\\system*\\nvcuda.dll",
}
var OneapiWindowsGlobs = []string{
"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
}
var OneapiLinuxGlobs = []string{
"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
"/usr/lib*/libze_intel_gpu.so*",
}
// Jetson devices have JETSON_JETPACK="x.y.z" factory set to the Jetpack version installed.
// Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
var CudaTegra string = os.Getenv("JETSON_JETPACK")
// Note: gpuMutex must already be held
func initCudaHandles() *cudaHandles {
func initGPUHandles() *handles {
// TODO - if the ollama build is CPU only, don't do these checks as they're irrelevant and confusing
cHandles := &cudaHandles{}
// Short Circuit if we already know which library to use
if nvmlLibPath != "" {
cHandles.nvml, _ = LoadNVMLMgmt([]string{nvmlLibPath})
return cHandles
}
if nvcudaLibPath != "" {
cHandles.deviceCount, cHandles.nvcuda, _ = LoadNVCUDAMgmt([]string{nvcudaLibPath})
return cHandles
}
if cudartLibPath != "" {
cHandles.deviceCount, cHandles.cudart, _ = LoadCUDARTMgmt([]string{cudartLibPath})
return cHandles
}
slog.Debug("searching for GPU discovery libraries for NVIDIA")
gpuHandles := &handles{}
var cudartMgmtName string
var cudartMgmtPatterns []string
var nvcudaMgmtName string
var nvcudaMgmtPatterns []string
// Aligned with driver, we can't carry as payloads
nvcudaMgmtPatterns := NvcudaGlobs
if runtime.GOOS == "windows" {
localAppData := os.Getenv("LOCALAPPDATA")
cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", CudartMgmtName)}
}
tmpDir, _ := PayloadsDir()
if tmpDir != "" {
// TODO - add "payloads" for subprocess
cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", CudartMgmtName)}
}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartGlobs...)
if len(NvmlGlobs) > 0 {
nvmlLibPaths := FindGPULibs(NvmlMgmtName, NvmlGlobs)
if len(nvmlLibPaths) > 0 {
nvml, libPath := LoadNVMLMgmt(nvmlLibPaths)
if nvml != nil {
slog.Debug("nvidia-ml loaded", "library", libPath)
cHandles.nvml = nvml
nvmlLibPath = libPath
}
switch runtime.GOOS {
case "windows":
cudartMgmtName = "cudart64_*.dll"
localAppData := os.Getenv("LOCALAPPDATA")
cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", cudartMgmtName)}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartWindowsGlobs...)
// Aligned with driver, we can't carry as payloads
nvcudaMgmtName = "nvcuda.dll"
nvcudaMgmtPatterns = NvcudaWindowsGlobs
case "linux":
cudartMgmtName = "libcudart.so*"
if tmpDir != "" {
// TODO - add "payloads" for subprocess
cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", cudartMgmtName)}
}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartLinuxGlobs...)
// Aligned with driver, we can't carry as payloads
nvcudaMgmtName = "libcuda.so*"
nvcudaMgmtPatterns = NvcudaLinuxGlobs
default:
return gpuHandles
}
nvcudaLibPaths := FindGPULibs(NvcudaMgmtName, nvcudaMgmtPatterns)
slog.Debug("Detecting GPUs")
nvcudaLibPaths := FindGPULibs(nvcudaMgmtName, nvcudaMgmtPatterns)
if len(nvcudaLibPaths) > 0 {
deviceCount, nvcuda, libPath := LoadNVCUDAMgmt(nvcudaLibPaths)
if nvcuda != nil {
slog.Debug("detected GPUs", "count", deviceCount, "library", libPath)
cHandles.nvcuda = nvcuda
cHandles.deviceCount = deviceCount
nvcudaLibPath = libPath
return cHandles
gpuHandles.nvcuda = nvcuda
gpuHandles.deviceCount = deviceCount
return gpuHandles
}
}
cudartLibPaths := FindGPULibs(CudartMgmtName, cudartMgmtPatterns)
cudartLibPaths := FindGPULibs(cudartMgmtName, cudartMgmtPatterns)
if len(cudartLibPaths) > 0 {
deviceCount, cudart, libPath := LoadCUDARTMgmt(cudartLibPaths)
if cudart != nil {
slog.Debug("detected GPUs", "library", libPath, "count", deviceCount)
cHandles.cudart = cudart
cHandles.deviceCount = deviceCount
cudartLibPath = libPath
return cHandles
gpuHandles.cudart = cudart
gpuHandles.deviceCount = deviceCount
return gpuHandles
}
}
return cHandles
}
// Note: gpuMutex must already be held
func initOneAPIHandles() *oneapiHandles {
oHandles := &oneapiHandles{}
// Short Circuit if we already know which library to use
if oneapiLibPath != "" {
oHandles.deviceCount, oHandles.oneapi, _ = LoadOneapiMgmt([]string{oneapiLibPath})
return oHandles
}
oneapiLibPaths := FindGPULibs(OneapiMgmtName, OneapiGlobs)
if len(oneapiLibPaths) > 0 {
oHandles.deviceCount, oHandles.oneapi, oneapiLibPath = LoadOneapiMgmt(oneapiLibPaths)
}
return oHandles
}
func GetCPUInfo() GpuInfoList {
gpuMutex.Lock()
if !bootstrapped {
gpuMutex.Unlock()
GetGPUInfo()
} else {
gpuMutex.Unlock()
}
return GpuInfoList{cpus[0].GpuInfo}
return gpuHandles
}
func GetGPUInfo() GpuInfoList {
@@ -178,255 +160,112 @@ func GetGPUInfo() GpuInfoList {
// GPUs so we can report warnings if we see Nvidia/AMD but fail to load the libraries
gpuMutex.Lock()
defer gpuMutex.Unlock()
needRefresh := true
var cHandles *cudaHandles
var oHandles *oneapiHandles
gpuHandles := initGPUHandles()
defer func() {
if cHandles != nil {
if cHandles.cudart != nil {
C.cudart_release(*cHandles.cudart)
}
if cHandles.nvcuda != nil {
C.nvcuda_release(*cHandles.nvcuda)
}
if cHandles.nvml != nil {
C.nvml_release(*cHandles.nvml)
}
if gpuHandles.cudart != nil {
C.cudart_release(*gpuHandles.cudart)
}
if oHandles != nil {
if oHandles.oneapi != nil {
// TODO - is this needed?
C.oneapi_release(*oHandles.oneapi)
}
if gpuHandles.nvcuda != nil {
C.nvcuda_release(*gpuHandles.nvcuda)
}
}()
if !bootstrapped {
slog.Debug("Detecting GPUs")
needRefresh = false
cpuCapability = GetCPUCapability()
var memInfo C.mem_info_t
mem, err := GetCPUMem()
if err != nil {
slog.Warn("error looking up system memory", "error", err)
}
cpus = []CPUInfo{CPUInfo{
GpuInfo: GpuInfo{
memInfo: mem,
Library: "cpu",
Variant: cpuCapability,
ID: "0",
},
}}
// Fallback to CPU mode if we're lacking required vector extensions on x86
if cpuCapability < GPURunnerCPUCapability && runtime.GOARCH == "amd64" {
slog.Warn("CPU does not have minimum vector extensions, GPU inference disabled", "required", GPURunnerCPUCapability, "detected", cpuCapability)
bootstrapped = true
// No need to do any GPU discovery, since we can't run on them
return GpuInfoList{cpus[0].GpuInfo}
}
// On windows we bundle the nvidia library one level above the runner dir
depPath := ""
if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
depPath = filepath.Join(filepath.Dir(envconfig.RunnersDir), "cuda")
}
// Load ALL libraries
cHandles = initCudaHandles()
// NVIDIA
for i := range cHandles.deviceCount {
if cHandles.cudart != nil || cHandles.nvcuda != nil {
gpuInfo := CudaGPUInfo{
GpuInfo: GpuInfo{
Library: "cuda",
},
index: i,
}
var driverMajor int
var driverMinor int
if cHandles.cudart != nil {
C.cudart_bootstrap(*cHandles.cudart, C.int(i), &memInfo)
} else {
C.nvcuda_bootstrap(*cHandles.nvcuda, C.int(i), &memInfo)
driverMajor = int(cHandles.nvcuda.driver_major)
driverMinor = int(cHandles.nvcuda.driver_minor)
}
if memInfo.err != nil {
slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
continue
}
if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
continue
}
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
gpuInfo.MinimumMemory = cudaMinimumMemory
gpuInfo.DependencyPath = depPath
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.DriverMajor = driverMajor
gpuInfo.DriverMinor = driverMinor
// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
cudaGPUs = append(cudaGPUs, gpuInfo)
}
}
// Intel
if envconfig.IntelGpu {
oHandles = initOneAPIHandles()
// On windows we bundle the oneapi library one level above the runner dir
depPath = ""
if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
depPath = filepath.Join(filepath.Dir(envconfig.RunnersDir), "oneapi")
}
for d := range oHandles.oneapi.num_drivers {
if oHandles.oneapi == nil {
// shouldn't happen
slog.Warn("nil oneapi handle with driver count", "count", int(oHandles.oneapi.num_drivers))
continue
}
devCount := C.oneapi_get_device_count(*oHandles.oneapi, C.int(d))
for i := range devCount {
gpuInfo := OneapiGPUInfo{
GpuInfo: GpuInfo{
Library: "oneapi",
},
driverIndex: int(d),
gpuIndex: int(i),
}
// TODO - split bootstrapping from updating free memory
C.oneapi_check_vram(*oHandles.oneapi, C.int(d), i, &memInfo)
// TODO - convert this to MinimumMemory based on testing...
var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
memInfo.free = C.uint64_t(totalFreeMem)
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.DependencyPath = depPath
oneapiGPUs = append(oneapiGPUs, gpuInfo)
}
}
}
rocmGPUs = AMDGetGPUInfo()
bootstrapped = true
// All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX
cpuVariant := GetCPUVariant()
if cpuVariant == "" && runtime.GOARCH == "amd64" {
slog.Warn("CPU does not have AVX or AVX2, disabling GPU support.")
}
// For detected GPUs, load library if not loaded
// On windows we bundle the nvidia library one level above the runner dir
depPath := ""
if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
depPath = filepath.Dir(envconfig.RunnersDir)
}
// Refresh free memory usage
if needRefresh {
mem, err := GetCPUMem()
if err != nil {
slog.Warn("error looking up system memory", "error", err)
} else {
slog.Debug("updating system memory data",
slog.Group(
"before",
"total", format.HumanBytes2(cpus[0].TotalMemory),
"free", format.HumanBytes2(cpus[0].FreeMemory),
),
slog.Group(
"now",
"total", format.HumanBytes2(mem.TotalMemory),
"free", format.HumanBytes2(mem.FreeMemory),
),
)
cpus[0].FreeMemory = mem.FreeMemory
}
var memInfo C.mem_info_t
resp := []GpuInfo{}
var memInfo C.mem_info_t
if cHandles == nil && len(cudaGPUs) > 0 {
cHandles = initCudaHandles()
// NVIDIA first
for i := 0; i < gpuHandles.deviceCount; i++ {
// TODO once we support CPU compilation variants of GPU libraries refine this...
if cpuVariant == "" && runtime.GOARCH == "amd64" {
continue
}
for i, gpu := range cudaGPUs {
if cHandles.nvml != nil {
C.nvml_get_free(*cHandles.nvml, C.int(gpu.index), &memInfo.free, &memInfo.total, &memInfo.used)
} else if cHandles.cudart != nil {
C.cudart_bootstrap(*cHandles.cudart, C.int(gpu.index), &memInfo)
} else if cHandles.nvcuda != nil {
C.nvcuda_get_free(*cHandles.nvcuda, C.int(gpu.index), &memInfo.free, &memInfo.total)
memInfo.used = memInfo.total - memInfo.free
if gpuHandles.cudart != nil || gpuHandles.nvcuda != nil {
gpuInfo := GpuInfo{
Library: "cuda",
}
var driverMajor int
var driverMinor int
if gpuHandles.cudart != nil {
C.cudart_check_vram(*gpuHandles.cudart, C.int(i), &memInfo)
} else {
// shouldn't happen
slog.Warn("no valid cuda library loaded to refresh vram usage")
break
C.nvcuda_check_vram(*gpuHandles.nvcuda, C.int(i), &memInfo)
driverMajor = int(gpuHandles.nvcuda.driver_major)
driverMinor = int(gpuHandles.nvcuda.driver_minor)
}
if memInfo.err != nil {
slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
continue
}
if memInfo.free == 0 {
slog.Warn("error looking up nvidia GPU memory")
if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
continue
}
slog.Debug("updating cuda memory data",
"gpu", gpu.ID,
"name", gpu.Name,
slog.Group(
"before",
"total", format.HumanBytes2(gpu.TotalMemory),
"free", format.HumanBytes2(gpu.FreeMemory),
),
slog.Group(
"now",
"total", format.HumanBytes2(uint64(memInfo.total)),
"free", format.HumanBytes2(uint64(memInfo.free)),
"used", format.HumanBytes2(uint64(memInfo.used)),
),
)
cudaGPUs[i].FreeMemory = uint64(memInfo.free)
}
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
gpuInfo.MinimumMemory = cudaMinimumMemory
gpuInfo.DependencyPath = depPath
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.DriverMajor = int(driverMajor)
gpuInfo.DriverMinor = int(driverMinor)
if oHandles == nil && len(oneapiGPUs) > 0 {
oHandles = initOneAPIHandles()
}
for i, gpu := range oneapiGPUs {
if oHandles.oneapi == nil {
// shouldn't happen
slog.Warn("nil oneapi handle with device count", "count", oHandles.deviceCount)
continue
}
C.oneapi_check_vram(*oHandles.oneapi, C.int(gpu.driverIndex), C.int(gpu.gpuIndex), &memInfo)
// TODO - convert this to MinimumMemory based on testing...
var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
memInfo.free = C.uint64_t(totalFreeMem)
oneapiGPUs[i].FreeMemory = uint64(memInfo.free)
}
err = RocmGPUInfoList(rocmGPUs).RefreshFreeMemory()
if err != nil {
slog.Debug("problem refreshing ROCm free memory", "error", err)
// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
resp = append(resp, gpuInfo)
}
}
resp := []GpuInfo{}
for _, gpu := range cudaGPUs {
resp = append(resp, gpu.GpuInfo)
}
for _, gpu := range rocmGPUs {
resp = append(resp, gpu.GpuInfo)
}
for _, gpu := range oneapiGPUs {
resp = append(resp, gpu.GpuInfo)
}
// Then AMD
resp = append(resp, AMDGetGPUInfo()...)
if len(resp) == 0 {
resp = append(resp, cpus[0].GpuInfo)
C.cpu_check_ram(&memInfo)
if memInfo.err != nil {
slog.Info("error looking up CPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
return resp
}
gpuInfo := GpuInfo{
Library: "cpu",
Variant: cpuVariant,
}
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
resp = append(resp, gpuInfo)
}
return resp
}
func GetCPUMem() (memInfo, error) {
var ret memInfo
var info C.mem_info_t
C.cpu_check_ram(&info)
if info.err != nil {
defer C.free(unsafe.Pointer(info.err))
return ret, fmt.Errorf(C.GoString(info.err))
}
ret.FreeMemory = uint64(info.free)
ret.TotalMemory = uint64(info.total)
return ret, nil
}
func FindGPULibs(baseLibName string, defaultPatterns []string) []string {
// Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them
var ldPaths []string
@@ -457,7 +296,6 @@ func FindGPULibs(baseLibName string, defaultPatterns []string) []string {
// Nvidia PhysX known to return bogus results
if strings.Contains(pattern, "PhysX") {
slog.Debug("skipping PhysX cuda library path", "path", pattern)
continue
}
// Ignore glob discovery errors
matches, _ := filepath.Glob(pattern)
@@ -523,26 +361,8 @@ func LoadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string) {
return 0, nil, ""
}
func LoadNVMLMgmt(nvmlLibPaths []string) (*C.nvml_handle_t, string) {
var resp C.nvml_init_resp_t
resp.ch.verbose = getVerboseState()
for _, libPath := range nvmlLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.nvml_init(lib, &resp)
if resp.err != nil {
slog.Info(fmt.Sprintf("Unable to load NVML management library %s: %s", libPath, C.GoString(resp.err)))
C.free(unsafe.Pointer(resp.err))
} else {
return &resp.ch, libPath
}
}
return nil, ""
}
func LoadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string) {
var resp C.oneapi_init_resp_t
num_devices := 0
resp.oh.verbose = getVerboseState()
for _, libPath := range oneapiLibPaths {
lib := C.CString(libPath)
@@ -552,10 +372,7 @@ func LoadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string) {
slog.Debug("Unable to load oneAPI management library", "library", libPath, "error", C.GoString(resp.err))
C.free(unsafe.Pointer(resp.err))
} else {
for i := range resp.oh.num_drivers {
num_devices += int(C.oneapi_get_device_count(resp.oh, C.int(i)))
}
return num_devices, &resp.oh, libPath
return int(resp.num_devices), &resp.oh, libPath
}
}
return 0, nil, ""

View File

@@ -24,7 +24,7 @@ func GetGPUInfo() GpuInfoList {
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability(),
Variant: GetCPUVariant(),
memInfo: mem,
},
}
@@ -42,17 +42,6 @@ func GetGPUInfo() GpuInfoList {
return []GpuInfo{info}
}
func GetCPUInfo() GpuInfoList {
mem, _ := GetCPUMem()
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability(),
memInfo: mem,
},
}
}
func GetCPUMem() (memInfo, error) {
return memInfo{
TotalMemory: uint64(C.getPhysicalMemory()),

View File

@@ -47,7 +47,6 @@ typedef struct mem_info {
char gpu_name[GPU_NAME_LEN];
uint64_t total;
uint64_t free;
uint64_t used;
// Compute Capability
int major;
@@ -63,7 +62,6 @@ void cpu_check_ram(mem_info_t *resp);
#include "gpu_info_cudart.h"
#include "gpu_info_nvcuda.h"
#include "gpu_info_nvml.h"
#include "gpu_info_oneapi.h"
#endif // __GPU_INFO_H__

45
gpu/gpu_info_cpu.c Normal file
View File

@@ -0,0 +1,45 @@
#include "gpu_info.h"
// Fallbacks for CPU mode
#ifdef _WIN32
#include <sysinfoapi.h>
void cpu_check_ram(mem_info_t *resp) {
resp->err = NULL;
MEMORYSTATUSEX info;
info.dwLength = sizeof(info);
if (GlobalMemoryStatusEx(&info) != 0) {
resp->total = info.ullTotalPhys;
resp->free = info.ullAvailPhys;
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
} else {
resp->err = LOAD_ERR();
}
return;
}
#elif __linux__
#include <errno.h>
#include <string.h>
#include <sys/sysinfo.h>
void cpu_check_ram(mem_info_t *resp) {
struct sysinfo info;
resp->err = NULL;
if (sysinfo(&info) != 0) {
resp->err = strdup(strerror(errno));
} else {
resp->total = info.totalram * info.mem_unit;
resp->free = info.freeram * info.mem_unit;
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
}
return;
}
#elif __APPLE__
// TODO consider an Apple implementation that does something useful
// mem_info_t cpu_check_ram() {
// mem_info_t resp = {0, 0, NULL};
// return resp;
// }
#else
#error "Unsupported platform"
#endif

View File

@@ -40,7 +40,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
for (i = 0; l[i].s != NULL; i++) {
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
if (!l[i].p) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
@@ -94,7 +94,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
}
void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
void cudart_check_vram(cudart_handle_t h, int i, mem_info_t *resp) {
resp->err = NULL;
cudartMemory_t memInfo = {0,0,0};
cudartReturn_t ret;
@@ -166,11 +166,9 @@ void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
resp->total = memInfo.total;
resp->free = memInfo.free;
resp->used = memInfo.used;
LOG(h.verbose, "[%s] CUDA totalMem %lu\n", resp->gpu_id, resp->total);
LOG(h.verbose, "[%s] CUDA freeMem %lu\n", resp->gpu_id, resp->free);
LOG(h.verbose, "[%s] CUDA usedMem %lu\n", resp->gpu_id, resp->used);
LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
}

View File

@@ -140,8 +140,7 @@ typedef struct cudart_init_resp {
} cudart_init_resp_t;
void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp);
void cudart_bootstrap(cudart_handle_t ch, int device_id, mem_info_t *resp);
// TODO - if we keep this library longer term, add cudart_get_free
void cudart_check_vram(cudart_handle_t ch, int device_id, mem_info_t *resp);
void cudart_release(cudart_handle_t ch);
#endif // __GPU_INFO_CUDART_H__

View File

@@ -43,7 +43,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
for (i = 0; l[i].s != NULL; i++) {
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
if (!*l[i].p) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
@@ -96,7 +96,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
}
const int buflen = 256;
void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
void nvcuda_check_vram(nvcuda_handle_t h, int i, mem_info_t *resp) {
resp->err = NULL;
nvcudaMemory_t memInfo = {0,0};
CUresult ret;
@@ -168,7 +168,7 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "nvcuda failed to get device context %d", ret);
snprintf(buf, buflen, "nvcuda failed to get primary device context %d", ret);
resp->err = strdup(buf);
return;
}
@@ -193,42 +193,7 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to release device context %d", ret);
}
}
void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total) {
CUresult ret;
CUcontext ctx = NULL;
CUdevice device = -1;
*free = 0;
*total = 0;
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda device failed to initialize");
return;
}
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to get device context %d", ret);
return;
}
ret = (*h.cuMemGetInfo_v2)(free, total);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda device memory info lookup failure %d", ret);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
return;
}
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to release device context %d", ret);
LOG(1, "nvcuda failed to release primary device context %d", ret);
}
}

View File

@@ -67,8 +67,7 @@ typedef struct nvcuda_init_resp {
} nvcuda_init_resp_t;
void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp);
void nvcuda_bootstrap(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
void nvcuda_get_free(nvcuda_handle_t ch, int device_id, uint64_t *free, uint64_t *total);
void nvcuda_check_vram(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
void nvcuda_release(nvcuda_handle_t ch);
#endif // __GPU_INFO_NVCUDA_H__

View File

@@ -1,104 +0,0 @@
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include <string.h>
#include "gpu_info_nvml.h"
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
nvmlReturn_t ret;
resp->err = NULL;
const int buflen = 256;
char buf[buflen + 1];
int i;
struct lookup {
char *s;
void **p;
} l[] = {
{"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
{"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
{"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.nvmlDeviceGetHandleByIndex},
{"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(nvml_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", nvml_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
nvml_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", nvml_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
resp->ch.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
ret = (*resp->ch.nvmlInit_v2)();
if (ret != NVML_SUCCESS) {
LOG(resp->ch.verbose, "nvmlInit_v2 err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "nvml vram init failure: %d", ret);
resp->err = strdup(buf);
return;
}
}
void nvml_get_free(nvml_handle_t h, int device_id, uint64_t *free, uint64_t *total, uint64_t *used) {
nvmlDevice_t device;
nvmlMemory_t memInfo = {0};
nvmlReturn_t ret;
ret = (*h.nvmlDeviceGetHandleByIndex)(device_id, &device);
if (ret != NVML_SUCCESS) {
LOG(1, "unable to get device handle %d: %d", device_id, ret);
*free = 0;
return;
}
ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
if (ret != NVML_SUCCESS) {
LOG(1, "device memory info lookup failure %d: %d", device_id, ret);
*free = 0;
return;
}
*free = memInfo.free;
*total = memInfo.total;
*used = memInfo.used;
}
void nvml_release(nvml_handle_t h) {
LOG(h.verbose, "releasing nvml library\n");
nvmlReturn_t ret;
ret = (*h.nvmlShutdown)();
if (ret != NVML_SUCCESS) {
LOG(1, "error during nvmlShutdown %d", ret);
}
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
#endif // __APPLE__

View File

@@ -1,48 +0,0 @@
#ifndef __APPLE__
#ifndef __GPU_INFO_NVML_H__
#define __GPU_INFO_NVML_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum nvmlReturn_enum {
NVML_SUCCESS = 0,
// Other values omitted for now...
} nvmlReturn_t;
typedef void *nvmlDevice_t; // Opaque is sufficient
typedef struct nvmlMemory_st {
unsigned long long total;
unsigned long long free;
unsigned long long used;
} nvmlMemory_t;
typedef enum nvmlBrandType_enum
{
NVML_BRAND_UNKNOWN = 0,
} nvmlBrandType_t;
typedef struct nvml_handle {
void *handle;
uint16_t verbose;
nvmlReturn_t (*nvmlInit_v2)(void);
nvmlReturn_t (*nvmlShutdown)(void);
nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t *);
nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
} nvml_handle_t;
typedef struct nvml_init_resp {
char *err; // If err is non-null handle is invalid
nvml_handle_t ch;
} nvml_init_resp_t;
typedef struct nvml_compute_capability {
char *err;
int major;
int minor;
} nvml_compute_capability_t;
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp);
void nvml_get_free(nvml_handle_t ch, int device_id, uint64_t *free, uint64_t *total, uint64_t *used);
void nvml_release(nvml_handle_t ch);
#endif // __GPU_INFO_NVML_H__
#endif // __APPLE__

View File

@@ -4,17 +4,15 @@
#include <string.h>
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp)
{
ze_result_t ret;
resp->err = NULL;
resp->oh.devices = NULL;
resp->oh.num_devices = NULL;
resp->oh.drivers = NULL;
resp->oh.num_drivers = 0;
const int buflen = 256;
char buf[buflen + 1];
int i, d;
struct lookup {
int i;
struct lookup
{
char *s;
void **p;
} l[] = {
@@ -30,7 +28,8 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
};
resp->oh.handle = LOAD_LIBRARY(oneapi_lib_path, RTLD_LAZY);
if (!resp->oh.handle) {
if (!resp->oh.handle)
{
char *msg = LOAD_ERR();
snprintf(buf, buflen,
"Unable to load %s library to query for Intel GPUs: %s\n",
@@ -45,12 +44,14 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
"wiring Level-Zero management library functions in %s\n",
oneapi_lib_path);
for (i = 0; l[i].s != NULL; i++) {
for (i = 0; l[i].s != NULL; i++)
{
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->oh.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->oh.handle, l[i].s);
if (!*(l[i].p)) {
if (!l[i].p)
{
resp->oh.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->oh.verbose, "dlerr: %s\n", msg);
@@ -62,70 +63,23 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
}
}
LOG(resp->oh.verbose, "calling zesInit\n");
ret = (*resp->oh.zesInit)(0);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesInit err: %x\n", ret);
snprintf(buf, buflen, "oneapi vram init failure: %x", ret);
if (ret != ZE_RESULT_SUCCESS)
{
LOG(resp->oh.verbose, "zesInit err: %d\n", ret);
UNLOAD_LIBRARY(resp->oh.handle);
resp->oh.handle = NULL;
snprintf(buf, buflen, "oneapi vram init failure: %d", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "calling zesDriverGet\n");
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "oneapi driver count: %d\n", resp->oh.num_drivers);
resp->oh.drivers = malloc(resp->oh.num_drivers * sizeof(zes_driver_handle_t));
resp->oh.num_devices = malloc(resp->oh.num_drivers * sizeof(uint32_t));
memset(&resp->oh.num_devices[0], 0, resp->oh.num_drivers * sizeof(uint32_t));
resp->oh.devices =
malloc(resp->oh.num_drivers * sizeof(zes_device_handle_t *));
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, &resp->oh.drivers[0]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
for (d = 0; d < resp->oh.num_drivers; d++) {
LOG(resp->oh.verbose, "calling zesDeviceGet count %d: %p\n", d, resp->oh.drivers[d]);
ret = (*resp->oh.zesDeviceGet)(resp->oh.drivers[d],
&resp->oh.num_devices[d], NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
resp->oh.devices[d] =
malloc(resp->oh.num_devices[d] * sizeof(zes_device_handle_t));
ret = (*resp->oh.zesDeviceGet)(
resp->oh.drivers[d], &resp->oh.num_devices[d], resp->oh.devices[d]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
}
(*resp->oh.zesDriverGet)(&resp->num_devices, NULL);
return;
}
void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
mem_info_t *resp) {
void oneapi_check_vram(oneapi_handle_t h, mem_info_t *resp)
{
ze_result_t ret;
resp->err = NULL;
uint64_t totalMem = 0;
@@ -134,126 +88,127 @@ void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
char buf[buflen + 1];
int i, d, m;
if (h.handle == NULL) {
if (h.handle == NULL)
{
resp->err = strdup("Level-Zero handle not initialized");
return;
}
if (driver > h.num_drivers || device > h.num_devices[driver]) {
resp->err = strdup("driver of device index out of bounds");
uint32_t driversCount = 0;
ret = (*h.zesDriverGet)(&driversCount, NULL);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get driver count: %d", ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "discovered %d Level-Zero drivers\n", driversCount);
zes_driver_handle_t *allDrivers =
malloc(driversCount * sizeof(zes_driver_handle_t));
(*h.zesDriverGet)(&driversCount, allDrivers);
resp->total = 0;
resp->free = 0;
zes_device_ext_properties_t ext_props;
ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
ext_props.pNext = NULL;
zes_device_properties_t props;
props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
props.pNext = &ext_props;
ret = (*h.zesDeviceGetProperties)(h.devices[driver][device], &props);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get device properties: %d", ret);
resp->err = strdup(buf);
return;
}
snprintf(&resp->gpu_name[0], GPU_NAME_LEN, "%s", props.modelName);
// TODO this needs to map to ONEAPI_DEVICE_SELECTOR syntax
// (this is probably wrong...)
// TODO - the driver isn't included - what if there are multiple drivers?
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", device);
if (h.verbose) {
// When in verbose mode, report more information about
// the card we discover.
LOG(h.verbose, "[%d:%d] oneAPI device name: %s\n", driver, device,
props.modelName);
LOG(h.verbose, "[%d:%d] oneAPI brand: %s\n", driver, device,
props.brandName);
LOG(h.verbose, "[%d:%d] oneAPI vendor: %s\n", driver, device,
props.vendorName);
LOG(h.verbose, "[%d:%d] oneAPI S/N: %s\n", driver, device,
props.serialNumber);
LOG(h.verbose, "[%d:%d] oneAPI board number: %s\n", driver, device,
props.boardNumber);
}
// TODO
// Compute Capability equivalent in resp->major, resp->minor, resp->patch
uint32_t memCount = 0;
ret = (*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount,
NULL);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to enumerate Level-Zero memory modules: %x",
ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
(*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount, mems);
for (m = 0; m < memCount; m++) {
zes_mem_state_t state;
state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
state.pNext = NULL;
ret = (*h.zesMemoryGetState)(mems[m], &state);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get memory state: %x", ret);
for (d = 0; d < driversCount; d++)
{
uint32_t deviceCount = 0;
ret = (*h.zesDeviceGet)(allDrivers[d], &deviceCount, NULL);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
free(mems);
free(allDrivers);
return;
}
resp->total += state.size;
resp->free += state.free;
}
LOG(h.verbose, "discovered %d Level-Zero devices\n", deviceCount);
free(mems);
}
zes_device_handle_t *devices =
malloc(deviceCount * sizeof(zes_device_handle_t));
(*h.zesDeviceGet)(allDrivers[d], &deviceCount, devices);
void oneapi_release(oneapi_handle_t h) {
int d;
LOG(h.verbose, "releasing oneapi library\n");
for (d = 0; d < h.num_drivers; d++) {
if (h.devices != NULL && h.devices[d] != NULL) {
free(h.devices[d]);
for (i = 0; i < deviceCount; i++)
{
zes_device_ext_properties_t ext_props;
ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
ext_props.pNext = NULL;
zes_device_properties_t props;
props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
props.pNext = &ext_props;
ret = (*h.zesDeviceGetProperties)(devices[i], &props);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get device properties: %d", ret);
resp->err = strdup(buf);
free(allDrivers);
free(devices);
return;
}
if (h.verbose)
{
// When in verbose mode, report more information about
// the card we discover.
LOG(h.verbose, "[%d] oneAPI device name: %s\n", i,
props.modelName);
LOG(h.verbose, "[%d] oneAPI brand: %s\n", i,
props.brandName);
LOG(h.verbose, "[%d] oneAPI vendor: %s\n", i,
props.vendorName);
LOG(h.verbose, "[%d] oneAPI S/N: %s\n", i,
props.serialNumber);
LOG(h.verbose, "[%d] oneAPI board number: %s\n", i,
props.boardNumber);
}
uint32_t memCount = 0;
ret = (*h.zesDeviceEnumMemoryModules)(devices[i], &memCount, NULL);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen,
"unable to enumerate Level-Zero memory modules: %d", ret);
resp->err = strdup(buf);
free(allDrivers);
free(devices);
return;
}
LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
(*h.zesDeviceEnumMemoryModules)(devices[i], &memCount, mems);
for (m = 0; m < memCount; m++)
{
zes_mem_state_t state;
state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
state.pNext = NULL;
ret = (*h.zesMemoryGetState)(mems[m], &state);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get memory state: %d", ret);
resp->err = strdup(buf);
free(allDrivers);
free(devices);
free(mems);
return;
}
resp->total += state.size;
resp->free += state.free;
}
free(mems);
}
}
if (h.devices != NULL) {
free(h.devices);
h.devices = NULL;
}
if (h.num_devices != NULL) {
free(h.num_devices);
h.num_devices = NULL;
}
if (h.drivers != NULL) {
free(h.drivers);
h.drivers = NULL;
}
h.num_drivers = 0;
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
int oneapi_get_device_count(oneapi_handle_t h, int driver) {
if (h.handle == NULL || h.num_devices == NULL) {
return 0;
free(devices);
}
if (driver > h.num_drivers) {
return 0;
}
return (int)h.num_devices[driver];
free(allDrivers);
}
#endif // __APPLE__

View File

@@ -9,7 +9,8 @@
#define ZE_BIT(_i) (1 << _i)
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum ze_result_t {
typedef enum ze_result_t
{
ZE_RESULT_SUCCESS = 0,
// Other values omitted for now...
} ze_result_t;
@@ -19,11 +20,13 @@ typedef struct _zes_driver_handle_t *zes_driver_handle_t;
typedef struct _zes_device_handle_t *zes_device_handle_t;
typedef struct _zes_mem_handle_t *zes_mem_handle_t;
typedef enum _ze_structure_type_t {
typedef enum _ze_structure_type_t
{
ZE_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
} ze_structure_type_t;
typedef enum _zes_structure_type_t {
typedef enum _zes_structure_type_t
{
ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES = 0x1,
ZES_STRUCTURE_TYPE_MEM_PROPERTIES = 0xb,
ZES_STRUCTURE_TYPE_MEM_STATE = 0x1e,
@@ -31,29 +34,35 @@ typedef enum _zes_structure_type_t {
ZES_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
} zes_structure_type_t;
typedef enum _zes_mem_type_t {
typedef enum _zes_mem_type_t
{
ZES_MEM_TYPE_FORCE_UINT32 = 0x7fffffff
} zes_mem_type_t;
typedef enum _zes_mem_loc_t {
typedef enum _zes_mem_loc_t
{
ZES_MEM_LOC_SYSTEM = 0,
ZES_MEM_LOC_DEVICE = 1,
ZES_MEM_LOC_FORCE_UINT32 = 0x7fffffff
} zes_mem_loc_t;
typedef enum _zes_mem_health_t {
typedef enum _zes_mem_health_t
{
ZES_MEM_HEALTH_FORCE_UINT32 = 0x7fffffff
} zes_mem_health_t;
typedef struct _ze_device_uuid_t {
typedef struct _ze_device_uuid_t
{
uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
} ze_device_uuid_t;
typedef struct _zes_uuid_t {
typedef struct _zes_uuid_t
{
uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
} zes_uuid_t;
typedef enum _ze_device_type_t {
typedef enum _ze_device_type_t
{
ZE_DEVICE_TYPE_GPU = 1,
ZE_DEVICE_TYPE_CPU = 2,
ZE_DEVICE_TYPE_FPGA = 3,
@@ -62,7 +71,8 @@ typedef enum _ze_device_type_t {
ZE_DEVICE_TYPE_FORCE_UINT32 = 0x7fffffff
} ze_device_type_t;
typedef enum _zes_device_type_t {
typedef enum _zes_device_type_t
{
ZES_DEVICE_TYPE_GPU = 1,
ZES_DEVICE_TYPE_CPU = 2,
ZES_DEVICE_TYPE_FPGA = 3,
@@ -72,7 +82,8 @@ typedef enum _zes_device_type_t {
} zes_device_type_t;
typedef uint32_t ze_device_property_flags_t;
typedef enum _ze_device_property_flag_t {
typedef enum _ze_device_property_flag_t
{
ZE_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
ZE_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
ZE_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
@@ -81,7 +92,8 @@ typedef enum _ze_device_property_flag_t {
} ze_device_property_flag_t;
typedef uint32_t zes_device_property_flags_t;
typedef enum _zes_device_property_flag_t {
typedef enum _zes_device_property_flag_t
{
ZES_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
ZES_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
ZES_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
@@ -89,7 +101,8 @@ typedef enum _zes_device_property_flag_t {
ZES_DEVICE_PROPERTY_FLAG_FORCE_UINT32 = 0x7fffffff
} zes_device_property_flag_t;
typedef struct _ze_device_properties_t {
typedef struct _ze_device_properties_t
{
ze_structure_type_t stype;
void *pNext;
ze_device_type_t type;
@@ -113,7 +126,8 @@ typedef struct _ze_device_properties_t {
char name[ZE_MAX_DEVICE_NAME];
} ze_device_properties_t;
typedef struct _zes_device_properties_t {
typedef struct _zes_device_properties_t
{
zes_structure_type_t stype;
void *pNext;
ze_device_properties_t core;
@@ -126,7 +140,8 @@ typedef struct _zes_device_properties_t {
char driverVersion[ZES_STRING_PROPERTY_SIZE];
} zes_device_properties_t;
typedef struct _zes_device_ext_properties_t {
typedef struct _zes_device_ext_properties_t
{
zes_structure_type_t stype;
void *pNext;
zes_uuid_t uuid;
@@ -134,7 +149,8 @@ typedef struct _zes_device_ext_properties_t {
zes_device_property_flags_t flags;
} zes_device_ext_properties_t;
typedef struct _zes_mem_properties_t {
typedef struct _zes_mem_properties_t
{
zes_structure_type_t stype;
void *pNext;
zes_mem_type_t type;
@@ -146,7 +162,8 @@ typedef struct _zes_mem_properties_t {
int32_t numChannels;
} zes_mem_properties_t;
typedef struct _zes_mem_state_t {
typedef struct _zes_mem_state_t
{
zes_structure_type_t stype;
const void *pNext;
zes_mem_health_t health;
@@ -154,19 +171,10 @@ typedef struct _zes_mem_state_t {
uint64_t size;
} zes_mem_state_t;
typedef struct oneapi_handle {
typedef struct oneapi_handle
{
void *handle;
uint16_t verbose;
uint32_t num_drivers;
zes_driver_handle_t *drivers;
uint32_t *num_devices;
zes_device_handle_t **devices;
// TODO Driver major, minor information
// int driver_major;
// int driver_minor;
ze_result_t (*zesInit)(int);
ze_result_t (*zesDriverGet)(uint32_t *pCount, zes_driver_handle_t *phDrivers);
ze_result_t (*zesDeviceGet)(zes_driver_handle_t hDriver, uint32_t *pCount,
@@ -183,21 +191,21 @@ typedef struct oneapi_handle {
} oneapi_handle_t;
typedef struct oneapi_init_resp {
typedef struct oneapi_init_resp
{
char *err; // If err is non-null handle is invalid
int num_devices;
oneapi_handle_t oh;
} oneapi_init_resp_t;
typedef struct oneapi_version_resp {
typedef struct oneapi_version_resp
{
ze_result_t status;
char *str; // Contains version or error string if status != 0
} oneapi_version_resp_t;
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp);
void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
mem_info_t *resp);
void oneapi_release(oneapi_handle_t h);
int oneapi_get_device_count(oneapi_handle_t h, int driver);
void oneapi_check_vram(oneapi_handle_t rh, mem_info_t *resp);
#endif // __GPU_INFO_INTEL_H__
#endif // __APPLE__

View File

@@ -1,89 +0,0 @@
package gpu
import (
"bufio"
"fmt"
"os"
"strings"
"github.com/ollama/ollama/format"
)
var CudartGlobs = []string{
"/usr/local/cuda/lib64/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/libcudart.so*",
"/usr/lib/wsl/lib/libcudart.so*",
"/usr/lib/wsl/drivers/*/libcudart.so*",
"/opt/cuda/lib64/libcudart.so*",
"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/libcudart.so*",
"/usr/local/cuda/lib*/libcudart.so*",
"/usr/lib*/libcudart.so*",
"/usr/local/lib*/libcudart.so*",
}
var NvmlGlobs = []string{}
var NvcudaGlobs = []string{
"/usr/local/cuda*/targets/*/lib/libcuda.so*",
"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
"/usr/lib/*-linux-gnu/libcuda.so*",
"/usr/lib/wsl/lib/libcuda.so*",
"/usr/lib/wsl/drivers/*/libcuda.so*",
"/opt/cuda/lib*/libcuda.so*",
"/usr/local/cuda/lib*/libcuda.so*",
"/usr/lib*/libcuda.so*",
"/usr/local/lib*/libcuda.so*",
}
var OneapiGlobs = []string{
"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
"/usr/lib*/libze_intel_gpu.so*",
}
var CudartMgmtName = "libcudart.so*"
var NvcudaMgmtName = "libcuda.so*"
var NvmlMgmtName = "" // not currently wired on linux
var OneapiMgmtName = "libze_intel_gpu.so"
func GetCPUMem() (memInfo, error) {
var mem memInfo
var total, available, free, buffers, cached uint64
f, err := os.Open("/proc/meminfo")
if err != nil {
return mem, err
}
defer f.Close()
s := bufio.NewScanner(f)
for s.Scan() {
line := s.Text()
switch {
case strings.HasPrefix(line, "MemTotal:"):
_, err = fmt.Sscanf(line, "MemTotal:%d", &total)
case strings.HasPrefix(line, "MemAvailable:"):
_, err = fmt.Sscanf(line, "MemAvailable:%d", &available)
case strings.HasPrefix(line, "MemFree:"):
_, err = fmt.Sscanf(line, "MemFree:%d", &free)
case strings.HasPrefix(line, "Buffers:"):
_, err = fmt.Sscanf(line, "Buffers:%d", &buffers)
case strings.HasPrefix(line, "Cached:"):
_, err = fmt.Sscanf(line, "Cached:%d", &cached)
default:
continue
}
if err != nil {
return mem, err
}
if total > 0 && available > 0 {
mem.TotalMemory = total * format.KibiByte
mem.FreeMemory = available * format.KibiByte
return mem, nil
}
}
mem.TotalMemory = total * format.KibiByte
mem.FreeMemory = (free + buffers + cached) * format.KibiByte
return mem, nil
}

View File

@@ -5,12 +5,11 @@ import (
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestBasicGetGPUInfo(t *testing.T) {
info := GetGPUInfo()
assert.NotEmpty(t, len(info))
assert.Greater(t, len(info), 0)
assert.Contains(t, "cuda rocm cpu metal", info[0].Library)
if info[0].Library != "cpu" {
assert.Greater(t, info[0].TotalMemory, uint64(0))
@@ -20,7 +19,7 @@ func TestBasicGetGPUInfo(t *testing.T) {
func TestCPUMemInfo(t *testing.T) {
info, err := GetCPUMem()
require.NoError(t, err)
assert.NoError(t, err)
switch runtime.GOOS {
case "darwin":
t.Skip("CPU memory not populated on darwin")

View File

@@ -1,55 +0,0 @@
package gpu
import (
"fmt"
"syscall"
"unsafe"
)
type MEMORYSTATUSEX struct {
length uint32
MemoryLoad uint32
TotalPhys uint64
AvailPhys uint64
TotalPageFile uint64
AvailPageFile uint64
TotalVirtual uint64
AvailVirtual uint64
AvailExtendedVirtual uint64
}
var (
k32 = syscall.NewLazyDLL("kernel32.dll")
globalMemoryStatusExProc = k32.NewProc("GlobalMemoryStatusEx")
sizeofMemoryStatusEx = uint32(unsafe.Sizeof(MEMORYSTATUSEX{}))
)
var CudartGlobs = []string{
"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
}
var NvmlGlobs = []string{
"c:\\Windows\\System32\\nvml.dll",
}
var NvcudaGlobs = []string{
"c:\\windows\\system*\\nvcuda.dll",
}
var OneapiGlobs = []string{
"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
}
var CudartMgmtName = "cudart64_*.dll"
var NvcudaMgmtName = "nvcuda.dll"
var NvmlMgmtName = "nvml.dll"
var OneapiMgmtName = "ze_intel_gpu64.dll"
func GetCPUMem() (memInfo, error) {
memStatus := MEMORYSTATUSEX{length: sizeofMemoryStatusEx}
r1, _, err := globalMemoryStatusExProc.Call(uintptr(unsafe.Pointer(&memStatus)))
if r1 == 0 {
return memInfo{}, fmt.Errorf("GlobalMemoryStatusEx failed: %w", err)
}
return memInfo{TotalMemory: memStatus.TotalPhys, FreeMemory: memStatus.AvailPhys}, nil
}

View File

@@ -18,7 +18,7 @@ type GpuInfo struct {
Library string `json:"library,omitempty"`
// Optional variant to select (e.g. versions, cpu feature flags)
Variant CPUCapability `json:"variant"`
Variant string `json:"variant,omitempty"`
// MinimumMemory represents the minimum memory required to use the GPU
MinimumMemory uint64 `json:"-"`
@@ -26,9 +26,6 @@ type GpuInfo struct {
// Any extra PATH/LD_LIBRARY_PATH dependencies required for the Library to operate properly
DependencyPath string `json:"lib_path,omitempty"`
// Extra environment variables specific to the GPU as list of [key,value]
EnvWorkarounds [][2]string `json:"envs,omitempty"`
// GPU information
ID string `json:"gpu_id"` // string to use for selection of this specific GPU
Name string `json:"name"` // user friendly name if available
@@ -41,30 +38,6 @@ type GpuInfo struct {
// TODO other performance capability info to help in scheduling decisions
}
type CPUInfo struct {
GpuInfo
}
type CudaGPUInfo struct {
GpuInfo
index int //nolint:unused,nolintlint
}
type CudaGPUInfoList []CudaGPUInfo
type RocmGPUInfo struct {
GpuInfo
usedFilepath string //nolint:unused,nolintlint
index int //nolint:unused,nolintlint
}
type RocmGPUInfoList []RocmGPUInfo
type OneapiGPUInfo struct {
GpuInfo
driverIndex int //nolint:unused,nolintlint
gpuIndex int //nolint:unused,nolintlint
}
type OneapiGPUInfoList []OneapiGPUInfo
type GpuInfoList []GpuInfo
// Split up the set of gpu info's by Library and variant
@@ -74,8 +47,8 @@ func (l GpuInfoList) ByLibrary() []GpuInfoList {
for _, info := range l {
found := false
requested := info.Library
if info.Variant != CPUCapabilityNone {
requested += "_" + info.Variant.String()
if info.Variant != "" {
requested += "_" + info.Variant
}
for i, lib := range libs {
if lib == requested {
@@ -113,26 +86,3 @@ type ByFreeMemory []GpuInfo
func (a ByFreeMemory) Len() int { return len(a) }
func (a ByFreeMemory) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a ByFreeMemory) Less(i, j int) bool { return a[i].FreeMemory < a[j].FreeMemory }
type CPUCapability uint32
// Override at build time when building base GPU runners
var GPURunnerCPUCapability = CPUCapabilityAVX
const (
CPUCapabilityNone CPUCapability = iota
CPUCapabilityAVX
CPUCapabilityAVX2
// TODO AVX512
)
func (c CPUCapability) String() string {
switch c {
case CPUCapabilityAVX:
return "avx"
case CPUCapabilityAVX2:
return "avx2"
default:
return "no vector extensions"
}
}

View File

@@ -19,19 +19,17 @@ func TestMultiModelConcurrency(t *testing.T) {
var (
req = [2]api.GenerateRequest{
{
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "tinydolphin",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "tinydolphin",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
@@ -40,64 +38,42 @@ func TestMultiModelConcurrency(t *testing.T) {
}
resp = [2][]string{
[]string{"sunlight"},
[]string{"england", "english", "massachusetts", "pilgrims", "british"},
[]string{"england", "english", "massachusetts", "pilgrims"},
}
)
var wg sync.WaitGroup
wg.Add(len(req))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*240)
ctx, cancel := context.WithTimeout(context.Background(), time.Second*120)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
for i := 0; i < len(req); i++ {
require.NoError(t, PullIfMissing(ctx, client, req[i].Model))
}
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
DoGenerate(ctx, t, client, req[i], resp[i], 60*time.Second, 10*time.Second)
GenerateTestHelper(ctx, t, req[i], resp[i])
}(i)
}
wg.Wait()
}
func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
req, resp := GenerateRequests()
reqLimit := len(req)
iterLimit := 5
vram := os.Getenv("OLLAMA_MAX_VRAM")
if vram != "" {
max, err := strconv.ParseUint(vram, 10, 64)
require.NoError(t, err)
// Don't hammer on small VRAM cards...
if max < 4*1024*1024*1024 {
reqLimit = min(reqLimit, 2)
iterLimit = 2
}
}
ctx, cancel := context.WithTimeout(context.Background(), 9*time.Minute)
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Minute) // GTX 750 2G card takes ~9 minutes
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
req, resp := GenerateRequests()
// Get the server running (if applicable) warm the model up with a single initial request
DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 10*time.Second)
DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 5*time.Second)
var wg sync.WaitGroup
wg.Add(reqLimit)
for i := 0; i < reqLimit; i++ {
wg.Add(len(req))
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
for j := 0; j < iterLimit; j++ {
for j := 0; j < 5; j++ {
slog.Info("Starting", "req", i, "iter", j)
// On slower GPUs it can take a while to process the concurrent requests
// On slower GPUs it can take a while to process the 4 concurrent requests
// so we allow a much longer initial timeout
DoGenerate(ctx, t, client, req[i], resp[i], 120*time.Second, 20*time.Second)
DoGenerate(ctx, t, client, req[i], resp[i], 90*time.Second, 5*time.Second)
}
}(i)
}
@@ -245,23 +221,5 @@ func TestMultiModelStress(t *testing.T) {
}
}(i)
}
go func() {
for {
time.Sleep(2 * time.Second)
select {
case <-ctx.Done():
return
default:
models, err := client.ListRunning(ctx)
if err != nil {
slog.Warn("failed to list running models", "error", err)
continue
}
for _, m := range models.Models {
slog.Info("loaded model snapshot", "model", m)
}
}
}
}()
wg.Wait()
}

View File

@@ -11,8 +11,7 @@ import (
)
func TestContextExhaustion(t *testing.T) {
// Longer needed for small footprint GPUs
ctx, cancel := context.WithTimeout(context.Background(), 6*time.Minute)
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute) // TODO maybe shorter?
defer cancel()
// Set up the test data
req := api.GenerateRequest{

View File

@@ -32,11 +32,7 @@ func TestIntegrationMultimodal(t *testing.T) {
resp := "the ollam"
ctx, cancel := context.WithTimeout(context.Background(), 3*time.Minute)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
require.NoError(t, PullIfMissing(ctx, client, req.Model))
// llava models on CPU can be quite slow to start,
DoGenerate(ctx, t, client, req, []string{resp}, 120*time.Second, 30*time.Second)
GenerateTestHelper(ctx, t, req, []string{resp})
}
const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb

View File

@@ -140,7 +140,7 @@ func PullIfMissing(ctx context.Context, client *api.Client, modelName string) er
showCtx, cancel := context.WithDeadlineCause(
ctx,
time.Now().Add(10*time.Second),
time.Now().Add(5*time.Second),
fmt.Errorf("show for existing model %s took too long", modelName),
)
defer cancel()
@@ -287,46 +287,41 @@ func DoGenerate(ctx context.Context, t *testing.T, client *api.Client, genReq ap
func GenerateRequests() ([]api.GenerateRequest, [][]string) {
return []api.GenerateRequest{
{
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "why is the color of dirt brown?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "why is the color of dirt brown?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "what is the origin of independence day?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "what is the origin of independence day?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "what is the composition of air?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "what is the composition of air?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
@@ -336,7 +331,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
[][]string{
[]string{"sunlight"},
[]string{"soil", "organic", "earth", "black", "tan"},
[]string{"england", "english", "massachusetts", "pilgrims", "british"},
[]string{"england", "english", "massachusetts", "pilgrims"},
[]string{"fourth", "july", "declaration", "independence"},
[]string{"nitrogen", "oxygen", "carbon", "dioxide"},
}

View File

@@ -56,6 +56,7 @@ struct server_params {
std::string hostname = "127.0.0.1";
std::vector<std::string> api_keys;
std::string public_path = "examples/server/public";
std::string chat_template = "";
int32_t port = 8080;
int32_t read_timeout = 600;
int32_t write_timeout = 600;
@@ -358,6 +359,7 @@ struct llama_server_context
// slots / clients
std::vector<server_slot> slots;
json default_generation_settings_for_props;
llama_server_queue queue_tasks;
llama_server_response queue_results;
@@ -426,6 +428,16 @@ struct llama_server_context
return true;
}
void validate_model_chat_template(server_params & sparams) {
llama_chat_message chat[] = {{"user", "test"}};
std::vector<char> buf(1);
int res = llama_chat_apply_template(model, nullptr, chat, 1, true, buf.data(), buf.size());
if (res < 0) {
LOG_ERROR("The chat template comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", {});
sparams.chat_template = "chatml";
}
}
void initialize() {
// create slots
all_slots_are_idle = true;
@@ -471,6 +483,9 @@ struct llama_server_context
slots.push_back(slot);
}
default_generation_settings_for_props = get_formated_generation(slots.front());
default_generation_settings_for_props["seed"] = -1;
batch = llama_batch_init(n_ctx, 0, params.n_parallel);
}
@@ -569,7 +584,7 @@ struct llama_server_context
slot->sparams.mirostat_eta = json_value(data, "mirostat_eta", default_sparams.mirostat_eta);
slot->sparams.penalize_nl = json_value(data, "penalize_nl", default_sparams.penalize_nl);
slot->params.n_keep = json_value(data, "n_keep", slot->params.n_keep);
slot->sparams.seed = json_value(data, "seed", default_params.seed);
slot->params.seed = json_value(data, "seed", default_params.seed);
slot->sparams.grammar = json_value(data, "grammar", default_sparams.grammar);
slot->sparams.n_probs = json_value(data, "n_probs", default_sparams.n_probs);
slot->sparams.min_keep = json_value(data, "min_keep", default_sparams.min_keep);
@@ -796,6 +811,7 @@ struct llama_server_context
llama_sampling_free(slot->ctx_sampling);
}
slot->ctx_sampling = llama_sampling_init(slot->sparams);
llama_set_rng_seed(ctx, slot->params.seed);
slot->command = LOAD_PROMPT;
all_slots_are_idle = false;
@@ -819,7 +835,7 @@ struct llama_server_context
system_tokens.clear();
if (!system_prompt.empty()) {
system_tokens = ::llama_tokenize(ctx, system_prompt, true);
system_tokens = ::llama_tokenize(ctx, system_prompt, add_bos_token);
llama_batch_clear(batch);
@@ -1640,7 +1656,7 @@ struct llama_server_context
slot.t_start_process_prompt = ggml_time_us();
slot.t_start_genereration = 0;
prompt_tokens = tokenize(slot.prompt, system_prompt.empty()); // add BOS if there isn't system prompt
prompt_tokens = tokenize(slot.prompt, system_prompt.empty() && add_bos_token); // add BOS if there isn't system prompt
slot.n_prompt_tokens = prompt_tokens.size();
@@ -2324,9 +2340,9 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
#ifndef GGML_USE_CUDA
fprintf(stderr, "warning: llama.cpp was compiled without CUDA. Setting the split mode has no effect.\n");
#endif // GGML_USE_CUDA
#ifndef GGML_USE_CUBLAS
fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. Setting the split mode has no effect.\n");
#endif // GGML_USE_CUBLAS
}
else if (arg == "--tensor-split" || arg == "-ts")
{
@@ -2335,7 +2351,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
#if defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)
#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)
std::string arg_next = argv[i];
// split string by , and /
@@ -2356,8 +2372,8 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
}
}
#else
LOG_WARNING("llama.cpp was compiled without CUDA. It is not possible to set a tensor split.\n", {});
#endif // GGML_USE_CUDA
LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n", {});
#endif // GGML_USE_CUBLAS
}
else if (arg == "--main-gpu" || arg == "-mg")
{
@@ -2366,7 +2382,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
#if defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)
#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)
params.main_gpu = std::stoi(argv[i]);
#else
LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a main GPU.", {});
@@ -2524,6 +2540,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
sparams.chat_template = argv[i];
}
else if (arg == "--override-kv")
{
@@ -2996,6 +3013,11 @@ int main(int argc, char **argv) {
}
const auto model_meta = llama.model_meta();
if (sparams.chat_template.empty()) { // custom chat template is not supplied
// check if the template comes with the model is supported by us
llama.validate_model_chat_template(sparams);
}
// Middleware for API key validation
auto validate_api_key = [&sparams](const httplib::Request &req, httplib::Response &res) -> bool {
// If API key is not set, skip validation

View File

@@ -18,7 +18,7 @@ sign() {
fi
}
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DLLAMA_METAL_EMBED_LIBRARY=on -DLLAMA_OPENMP=off"
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DLLAMA_METAL_EMBED_LIBRARY=on"
case "${GOARCH}" in
"amd64")
@@ -27,7 +27,7 @@ case "${GOARCH}" in
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_BLAS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
@@ -37,7 +37,7 @@ case "${GOARCH}" in
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_BLAS=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu"
echo "Building LCD CPU"
build
@@ -49,7 +49,7 @@ case "${GOARCH}" in
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_BLAS=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
@@ -61,7 +61,7 @@ case "${GOARCH}" in
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_BLAS=off -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation"
@@ -75,7 +75,7 @@ case "${GOARCH}" in
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_BLAS=off -DCMAKE_SYSTEM_NAME=Darwin -DBUILD_SHARED_LIBS=off -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DBUILD_SHARED_LIBS=off -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build

View File

@@ -51,7 +51,7 @@ if [ -z "${CUDACXX}" ]; then
export CUDACXX=$(command -v nvcc)
fi
fi
COMMON_CMAKE_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_OPENMP=off"
COMMON_CMAKE_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off"
source $(dirname $0)/gen_common.sh
init_vars
git_module_setup
@@ -64,7 +64,7 @@ if [ -z "${OLLAMA_SKIP_STATIC_GENERATE}" -o "${OLLAMA_CPU_TARGET}" = "static" ];
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_OPENMP=off ${CMAKE_DEFS}"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}_static"
echo "Building static library"
build
@@ -93,7 +93,7 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
# -DLLAMA_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DLLAMA_AVX512_VNNI -- 2021 Intel Alder Lake
COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_OPENMP=off"
COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off"
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu" ]; then
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
@@ -178,7 +178,7 @@ if [ -z "${OLLAMA_SKIP_CUDA_GENERATE}" -a -d "${CUDA_LIB_DIR}" ]; then
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
echo "Building custom CUDA GPU"
else
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
fi
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS} ${CMAKE_CUDA_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cuda${CUDA_VARIANT}"
@@ -211,7 +211,7 @@ if [ -z "${ONEAPI_ROOT}" ]; then
ONEAPI_ROOT=/opt/intel/oneapi
fi
if [ -z "${OLLAMA_SKIP_ONEAPI_GENERATE}" -a -d "${ONEAPI_ROOT}" ]; then
if [ -d "${ONEAPI_ROOT}" ]; then
echo "OneAPI libraries detected - building dynamic OneAPI library"
init_vars
source ${ONEAPI_ROOT}/setvars.sh --force # set up environment variables for oneAPI

View File

@@ -39,8 +39,7 @@ function init_vars {
}
$script:cmakeDefs = @(
"-DBUILD_SHARED_LIBS=on",
"-DLLAMA_NATIVE=off",
"-DLLAMA_OPENMP=off"
"-DLLAMA_NATIVE=off"
)
$script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
$script:ARCH = $Env:PROCESSOR_ARCHITECTURE.ToLower()
@@ -123,13 +122,8 @@ function build {
& cmake --version
& cmake -S "${script:llamacppDir}" -B $script:buildDir $script:cmakeDefs
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
if ($cmakeDefs -contains "-G") {
$extra=@("-j8")
} else {
$extra= @("--", "/p:CL_MPcount=8")
}
write-host "building with: cmake --build $script:buildDir --config $script:config $($script:cmakeTargets | ForEach-Object { `"--target`", $_ }) $extra"
& cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ }) $extra
write-host "building with: cmake --build $script:buildDir --config $script:config $($script:cmakeTargets | ForEach-Object { `"--target`", $_ })"
& cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ })
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
# Rearrange output to be consistent between different generators
if ($null -ne ${script:config} -And (test-path -path "${script:buildDir}/bin/${script:config}" ) ) {
@@ -209,8 +203,7 @@ function build_static() {
"-DLLAMA_AVX2=off",
"-DLLAMA_AVX512=off",
"-DLLAMA_F16C=off",
"-DLLAMA_FMA=off",
"-DLLAMA_OPENMP=off")
"-DLLAMA_FMA=off")
$script:buildDir="../build/windows/${script:ARCH}_static"
write-host "Building static library"
build
@@ -277,15 +270,7 @@ function build_cuda() {
init_vars
$script:buildDir="../build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
$script:distDir="$script:DIST_BASE\cuda$script:CUDA_VARIANT"
$script:cmakeDefs += @(
"-A", "x64",
"-DLLAMA_CUDA=ON",
"-DLLAMA_AVX=on",
"-DLLAMA_AVX2=off",
"-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR",
"-DCMAKE_CUDA_FLAGS=-t8",
"-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}"
)
$script:cmakeDefs += @("-A", "x64", "-DLLAMA_CUDA=ON", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR", "-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}")
if ($null -ne $env:OLLAMA_CUSTOM_CUDA_DEFS) {
write-host "OLLAMA_CUSTOM_CUDA_DEFS=`"${env:OLLAMA_CUSTOM_CUDA_DEFS}`""
$script:cmakeDefs +=@("${env:OLLAMA_CUSTOM_CUDA_DEFS}")
@@ -295,19 +280,17 @@ function build_cuda() {
sign
install
rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
md "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\" -ea 0 > $null
write-host "copying CUDA dependencies to ${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
cp "${script:CUDA_LIB_DIR}\cudart64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
cp "${script:CUDA_LIB_DIR}\cublas64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
cp "${script:CUDA_LIB_DIR}\cublasLt64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
write-host "copying CUDA dependencies to ${script:SRC_DIR}\dist\windows-${script:ARCH}\"
cp "${script:CUDA_LIB_DIR}\cudart64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
cp "${script:CUDA_LIB_DIR}\cublas64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
cp "${script:CUDA_LIB_DIR}\cublasLt64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
} else {
write-host "Skipping CUDA generation step"
}
}
function build_oneapi() {
if ((-not "${env:OLLAMA_SKIP_ONEAPI_GENERATE}") -and ("${env:ONEAPI_ROOT}")) {
if ((-not "${env:OLLAMA_SKIP_CUDA_GENERATE}") -and ("${env:ONEAPI_ROOT}")) {
# Get oneAPI version
$script:ONEAPI_VERSION = icpx --version
$script:ONEAPI_VERSION = [regex]::Match($script:ONEAPI_VERSION, '(?<=oneAPI DPC\+\+/C\+\+ Compiler )(?<version>\d+\.\d+\.\d+)').Value
@@ -334,18 +317,16 @@ function build_oneapi() {
sign
install
rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
md "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\" -ea 0 > $null
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libirngmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libmmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_level_zero.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_unified_runtime.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_win_proxy_loader.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\svml_dispmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\sycl7.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_core.2.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_sycl_blas.4.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_tbb_thread.2.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libirngmd.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libmmd.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_level_zero.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_unified_runtime.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_win_proxy_loader.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\svml_dispmd.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\sycl7.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_core.2.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_sycl_blas.4.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_tbb_thread.2.dll" "${script:distDir}"
} else {
Write-Host "Skipping oneAPI generation step"
}

View File

@@ -53,7 +53,7 @@ func (llm *ggla) Tensors() Tensors {
return llm.tensors
}
func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
func (llm *ggla) decode(rs io.ReadSeeker) error {
var r uint32
if err := binary.Read(rs, binary.LittleEndian, &r); err != nil {
return err
@@ -69,18 +69,9 @@ func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
for {
var dims uint32
if err := binary.Read(rs, binary.LittleEndian, &dims); err != nil {
if errors.Is(err, io.EOF) {
return nil
}
return err
}
defer func() {
if errors.Is(retErr, io.EOF) {
retErr = io.ErrUnexpectedEOF
}
}()
var namesize uint32
if err := binary.Read(rs, binary.LittleEndian, &namesize); err != nil {
return err
@@ -117,7 +108,7 @@ func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
return err
}
if _, err := rs.Seek((offset+31)&-32-offset, io.SeekCurrent); err != nil {
if _, err := rs.Seek((offset+31)&-32, io.SeekStart); err != nil {
return err
}

View File

@@ -6,8 +6,6 @@ import (
"fmt"
"io"
"strings"
"github.com/ollama/ollama/util/bufioutil"
)
type GGML struct {
@@ -71,30 +69,6 @@ func (kv KV) HeadCountKV() uint64 {
return 1
}
func (kv KV) EmbeddingHeadCount() uint64 {
if heads := kv.HeadCount(); heads > 0 {
return kv.EmbeddingLength() / kv.HeadCount()
}
return 0
}
func (kv KV) EmbeddingHeadCountK() uint64 {
if k := kv.u64(fmt.Sprintf("%s.attention.key_length", kv.Architecture())); k > 0 {
return k
}
return kv.EmbeddingHeadCount()
}
func (kv KV) EmbeddingHeadCountV() uint64 {
if v := kv.u64(fmt.Sprintf("%s.attention.value_length", kv.Architecture())); v > 0 {
return v
}
return kv.EmbeddingHeadCount()
}
func (kv KV) GQA() uint64 {
return kv.HeadCount() / kv.HeadCountKV()
}
@@ -107,11 +81,6 @@ func (kv KV) ContextLength() uint64 {
return kv.u64(fmt.Sprintf("%s.context_length", kv.Architecture()))
}
func (kv KV) ChatTemplate() string {
s, _ := kv["tokenizer.chat_template"].(string)
return s
}
type Tensors []*Tensor
func (ts Tensors) Layers() map[string]Layer {
@@ -280,18 +249,7 @@ func DetectGGMLType(b []byte) string {
}
}
// DecodeGGML decodes a GGML model from the given reader.
//
// It collects array values for arrays with a size less than or equal to
// maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
// the maxArraySize is negative, all arrays are collected.
func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
if maxArraySize == 0 {
maxArraySize = 1024
}
rs = bufioutil.NewBufferedSeeker(rs, 32<<10)
func DecodeGGML(rs io.ReadSeeker) (*GGML, int64, error) {
var magic uint32
if err := binary.Read(rs, binary.LittleEndian, &magic); err != nil {
return nil, 0, err
@@ -304,15 +262,17 @@ func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
case FILE_MAGIC_GGLA:
c = &containerGGLA{}
case FILE_MAGIC_GGUF_LE:
c = &containerGGUF{ByteOrder: binary.LittleEndian, maxArraySize: maxArraySize}
c = &containerGGUF{ByteOrder: binary.LittleEndian}
case FILE_MAGIC_GGUF_BE:
c = &containerGGUF{ByteOrder: binary.BigEndian, maxArraySize: maxArraySize}
c = &containerGGUF{ByteOrder: binary.BigEndian}
default:
return nil, 0, errors.New("invalid file magic")
}
model, err := c.Decode(rs)
if err != nil {
if errors.Is(err, io.EOF) {
// noop
} else if err != nil {
return nil, 0, err
}
@@ -332,10 +292,7 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
embedding := llm.KV().EmbeddingLength()
heads := llm.KV().HeadCount()
headsKV := llm.KV().HeadCountKV()
vocab := uint64(llm.KV()["tokenizer.ggml.tokens"].(*array).size)
embeddingHeads := llm.KV().EmbeddingHeadCount()
embeddingHeadsK := llm.KV().EmbeddingHeadCountK()
vocab := uint64(len(llm.KV()["tokenizer.ggml.tokens"].([]any)))
layers := llm.Tensors().Layers()
@@ -345,8 +302,7 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
partialOffload = 4 * batch * embedding
partialOffload += max(
// 4*batch*(4+6*embedding+context*(2*heads)+llm.KV().GQA()),
4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*heads+embeddingHeads*headsKV),
4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*heads+embedding/heads*headsKV),
4*batch*(embedding+vocab)+embedding*vocab*105/128,
)
@@ -354,15 +310,15 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
// mixtral 8x22b
ff := uint64(llm.KV()["llama.feed_forward_length"].(uint32))
partialOffload = max(
3*ffnGateExpsWeight.Size()+4*batch*(2*ff+headsKV+embedding+context+embeddingHeads*headsKV),
4*(context*batch*heads+context*embeddingHeads*headsKV+batch*1024+embeddingHeads*headsKV*batch),
3*ffnGateExpsWeight.Size()+4*batch*(2*ff+headsKV+embedding+context+embedding/heads*headsKV),
4*(context*batch*heads+context*embedding/heads*headsKV+batch*1024+embedding/heads*headsKV*batch),
)
} else if ffnGateWeight, ok := layers["blk.0"]["ffn_gate.0.weight"]; ok {
// mixtral 8x7b
ffnGateWeight1 := ffnGateWeight.Shape[1]
fullOffload = 4 * batch * (2 + 3*embedding + context*(1+heads) + 2*headsKV + ffnGateWeight1)
partialOffload = max(
4*batch*(3+embeddingHeads*headsKV+embedding+context*(1+heads)+ffnGateWeight1)+(embedding*embedding+3*embedding*headsKV*ffnGateWeight1)*9/16,
4*batch*(3+embedding/heads*headsKV+embedding+context*(1+heads)+ffnGateWeight1)+(embedding*embedding+3*embedding*headsKV*ffnGateWeight1)*9/16,
4*batch*(1+2*embedding+context*(1+heads))+embedding*(6*context*headsKV/heads+embedding*9/16),
)
}
@@ -405,16 +361,6 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
4*batch*(vocab+2*embedding),
fullOffload,
)
case "deepseek2":
fullOffload = max(
4*batch*(3*embedding+vocab),
4*batch*(3*embedding+2+context*(1+headsKV)+2*embeddingHeadsK*headsKV),
)
partialOffload = max(
4*batch*(3*embedding+vocab)+embedding*vocab*105/128,
4*batch*(2*embedding+1+2*embeddingHeadsK*headsKV+context+context*headsKV)+4*embeddingHeadsK*context*headsKV+embedding*embeddingHeadsK*headsKV*9/16,
)
}
return

View File

@@ -1 +0,0 @@
package llm

View File

@@ -3,10 +3,11 @@ package llm
import (
"bytes"
"encoding/binary"
"encoding/json"
"fmt"
"io"
"strings"
"log/slog"
)
type containerGGUF struct {
@@ -28,12 +29,6 @@ type containerGGUF struct {
NumTensor uint64
NumKV uint64
}
maxArraySize int
}
func (c *containerGGUF) canCollectArray(size int) bool {
return c.maxArraySize < 0 || size <= c.maxArraySize
}
func (c *containerGGUF) Name() string {
@@ -59,6 +54,7 @@ func (c *containerGGUF) Decode(rs io.ReadSeeker) (model, error) {
}
model := newGGUF(c)
slog.Debug(fmt.Sprintf("model = %#v", model))
if err := model.Decode(rs); err != nil {
return nil, err
}
@@ -89,8 +85,6 @@ type gguf struct {
tensors []*Tensor
parameters uint64
scratch [16 << 10]byte
}
func newGGUF(container *containerGGUF) *gguf {
@@ -187,34 +181,34 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
}
// decode tensors
for range llm.numTensor() {
for i := 0; uint64(i) < llm.numTensor(); i++ {
name, err := readGGUFString(llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor name: %w", err)
return err
}
// dims is the number of dimensions in the tensor
dims, err := readGGUF[uint32](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor dimensions: %w", err)
return err
}
shape := [4]uint64{1, 1, 1, 1}
for i := 0; uint32(i) < dims; i++ {
shape[i], err = readGGUF[uint64](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor shape: %w", err)
return err
}
}
kind, err := readGGUF[uint32](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor kind: %w", err)
return err
}
offset, err := readGGUF[uint64](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor offset: %w", err)
return err
}
tensor := Tensor{
@@ -236,19 +230,24 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
alignment = 32
}
offset, err := rs.Seek(0, io.SeekCurrent)
if err != nil {
return err
}
padding := llm.padding(offset, int64(alignment))
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
return err
}
for _, tensor := range llm.tensors {
offset, err := rs.Seek(0, io.SeekCurrent)
if err != nil {
return fmt.Errorf("failed to get current offset: %w", err)
}
padding := llm.padding(offset, int64(alignment))
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
return fmt.Errorf("failed to seek to init padding: %w", err)
}
if _, err := rs.Seek(int64(tensor.Size()), io.SeekCurrent); err != nil {
return fmt.Errorf("failed to seek to tensor: %w", err)
return err
}
padding := llm.padding(int64(tensor.Size()), int64(alignment))
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
return err
}
}
@@ -286,48 +285,22 @@ func readGGUFV1String(llm *gguf, r io.Reader) (string, error) {
return b.String(), nil
}
func discardGGUFString(llm *gguf, r io.Reader) error {
buf := llm.scratch[:8]
_, err := io.ReadFull(r, buf)
if err != nil {
return err
}
size := int(llm.ByteOrder.Uint64(buf))
for size > 0 {
n, err := r.Read(llm.scratch[:min(size, cap(llm.scratch))])
if err != nil {
return err
}
size -= n
}
return nil
}
func readGGUFString(llm *gguf, r io.Reader) (string, error) {
if llm.Version == 1 {
return readGGUFV1String(llm, r)
}
buf := llm.scratch[:8]
_, err := io.ReadFull(r, buf)
if err != nil {
var length uint64
if err := binary.Read(r, llm.ByteOrder, &length); err != nil {
return "", err
}
length := int(llm.ByteOrder.Uint64(buf))
if length > len(llm.scratch) {
buf = make([]byte, length)
} else {
buf = llm.scratch[:length]
}
clear(buf)
_, err = io.ReadFull(r, buf)
if err != nil {
var b bytes.Buffer
if _, err := io.CopyN(&b, r, int64(length)); err != nil {
return "", err
}
return string(buf), nil
return b.String(), nil
}
func writeGGUFString(llm *gguf, w io.Writer, s string) error {
@@ -343,16 +316,7 @@ func writeGGUFString(llm *gguf, w io.Writer, s string) error {
return err
}
type array struct {
size int
values []any
}
func (a *array) MarshalJSON() ([]byte, error) {
return json.Marshal(a.values)
}
func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
func readGGUFV1Array(llm *gguf, r io.Reader) (a []any, err error) {
t, err := readGGUF[uint32](llm, r)
if err != nil {
return nil, err
@@ -363,12 +327,7 @@ func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
a := &array{size: int(n)}
if llm.canCollectArray(int(n)) {
a.values = make([]any, 0, int(n))
}
for i := range n {
for i := 0; uint32(i) < n; i++ {
var e any
switch t {
case ggufTypeUint8:
@@ -402,15 +361,13 @@ func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
if a.values != nil {
a.values[i] = e
}
a = append(a, e)
}
return a, nil
return
}
func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
func readGGUFArray(llm *gguf, r io.Reader) (a []any, err error) {
if llm.Version == 1 {
return readGGUFV1Array(llm, r)
}
@@ -425,12 +382,7 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
a := &array{size: int(n)}
if llm.canCollectArray(int(n)) {
a.values = make([]any, int(n))
}
for i := range n {
for i := 0; uint64(i) < n; i++ {
var e any
switch t {
case ggufTypeUint8:
@@ -456,11 +408,7 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
case ggufTypeBool:
e, err = readGGUF[bool](llm, r)
case ggufTypeString:
if a.values != nil {
e, err = readGGUFString(llm, r)
} else {
err = discardGGUFString(llm, r)
}
e, err = readGGUFString(llm, r)
default:
return nil, fmt.Errorf("invalid array type: %d", t)
}
@@ -468,12 +416,10 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
if a.values != nil {
a.values[i] = e
}
a = append(a, e)
}
return a, nil
return
}
func writeGGUFArray[S ~[]E, E any](llm *gguf, w io.Writer, t uint32, s S) error {
@@ -646,8 +592,8 @@ func (llm *gguf) Encode(ws io.WriteSeeker, kv KV, tensors []Tensor) error {
return err
}
var dims int
for cnt := range len(tensor.Shape) {
dims := 0
for cnt := 0; cnt < len(tensor.Shape); cnt++ {
if tensor.Shape[cnt] > 0 {
dims++
}
@@ -657,8 +603,8 @@ func (llm *gguf) Encode(ws io.WriteSeeker, kv KV, tensors []Tensor) error {
return err
}
for i := range dims {
if err := binary.Write(ws, llm.ByteOrder, tensor.Shape[dims-1-i]); err != nil {
for i := 0; i < dims; i++ {
if err := binary.Write(ws, llm.ByteOrder, uint64(tensor.Shape[dims-1-i])); err != nil {
return err
}
}
@@ -672,8 +618,22 @@ func (llm *gguf) Encode(ws io.WriteSeeker, kv KV, tensors []Tensor) error {
}
}
offset, err := ws.Seek(0, io.SeekCurrent)
if err != nil {
return err
}
var alignment int64 = 32
padding := llm.padding(offset, alignment)
if err := binary.Write(ws, llm.ByteOrder, bytes.Repeat([]byte{0}, int(padding))); err != nil {
return err
}
for _, tensor := range tensors {
if _, err := tensor.WriteTo(ws); err != nil {
return err
}
offset, err := ws.Seek(0, io.SeekCurrent)
if err != nil {
return err
@@ -683,10 +643,6 @@ func (llm *gguf) Encode(ws io.WriteSeeker, kv KV, tensors []Tensor) error {
if err := binary.Write(ws, llm.ByteOrder, bytes.Repeat([]byte{0}, int(padding))); err != nil {
return err
}
if _, err := tensor.WriteTo(ws); err != nil {
return err
}
}
return nil

View File

@@ -3,12 +3,11 @@ package llm
import (
"fmt"
"log/slog"
"strconv"
"strings"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/gpu"
"github.com/ollama/ollama/envconfig"
)
// This algorithm looks for a complete fit to determine if we need to unload other models
@@ -17,8 +16,7 @@ func PredictServerFit(allGpus gpu.GpuInfoList, ggml *GGML, adapters, projectors
var estimatedVRAM uint64
for _, gpus := range allGpus.ByLibrary() {
var layerCount int
estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
layerCount, estimatedVRAM = estimate.Layers, estimate.VRAMSize
layerCount, estimatedVRAM, _ = EstimateGPULayers(gpus, ggml, projectors, opts)
if opts.NumGPU < 0 {
if layerCount > 0 && layerCount >= int(ggml.KV().BlockCount()+1) {
return true, estimatedVRAM
@@ -32,76 +30,24 @@ func PredictServerFit(allGpus gpu.GpuInfoList, ggml *GGML, adapters, projectors
return false, estimatedVRAM
}
type MemoryEstimate struct {
// How many layers we predict we can load
Layers int
// The size of the graph which occupies the main GPU
Graph uint64
// How much VRAM will be allocated given the number of layers we predict
VRAMSize uint64
// The total size of the model if loaded into VRAM. If all layers are loaded, VRAMSize == TotalSize
TotalSize uint64
// For multi-GPU scenarios, this provides the tensor split parameter
TensorSplit string
// For multi-GPU scenarios, this is the size in bytes per GPU
GPUSizes []uint64
// internal fields for logging purposes
inferenceLibrary string
layersRequested int
layersModel int
availableList []string
kv uint64
allocationsList []string
memoryWeights uint64
memoryLayerOutput uint64
graphFullOffload uint64
graphPartialOffload uint64
}
// Given a model and one or more GPU targets, predict how many layers and bytes we can load, and the total size
// The GPUs provided must all be the same Library
func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts api.Options) MemoryEstimate {
// Graph size for a partial offload, applies to all GPUs
var graphPartialOffload uint64
// Graph size when all layers are offloaded, applies to all GPUs
var graphFullOffload uint64
// Final graph offload once we know full or partial
var graphOffload uint64
// Projectors loaded into GPU0 only
var projectorSize uint64
// Conditional output size on GPU 0
var memoryLayerOutput uint64
// The sizes of a layer
var layerSize uint64
// The sum of all the layer sizes (just for logging)
var memoryWeights uint64
// True if all the layers are loaded
var fullyLoaded bool
// Overflow that didn't fit into the GPU
var overflow uint64
availableList := make([]string, len(gpus))
for i, gpu := range gpus {
availableList[i] = format.HumanBytes2(gpu.FreeMemory)
func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts api.Options) (int, uint64, uint64) {
var memoryAvailable uint64
for _, info := range gpus {
memoryAvailable += info.FreeMemory
}
slog.Debug("evaluating", "library", gpus[0].Library, "gpu_count", len(gpus), "available", availableList)
if envconfig.MaxVRAM > 0 {
memoryAvailable = envconfig.MaxVRAM
}
slog.Debug("evaluating", "library", gpus[0].Library, "gpu_count", len(gpus), "available", format.HumanBytes2(memoryAvailable))
// TODO - this is probably wrong, first GPU vs secondaries will have different overheads
memoryMinimum := gpus[0].MinimumMemory
for _, projector := range projectors {
projectorSize += projectorMemoryRequirements(projector)
memoryMinimum += projectorMemoryRequirements(projector)
// multimodal models require at least 2048 context
opts.NumCtx = max(opts.NumCtx, 2048)
@@ -110,246 +56,127 @@ func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts
layers := ggml.Tensors().Layers()
// add one layer worth of memory as a buffer
if blk0, ok := layers["blk.0"]; ok {
layerSize = blk0.size()
} else {
slog.Warn("model missing blk.0 layer size")
memoryMinimum += blk0.size()
}
// fp16 k,v = sizeof(float16) * n_ctx * n_layer * (n_embd_head_k + n_embd_head_v) * n_head_kv
var kv uint64 = 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * (ggml.KV().EmbeddingHeadCountK() + ggml.KV().EmbeddingHeadCountV()) * ggml.KV().HeadCountKV()
// fp16 k,v = (1 (k) + 1 (v)) * sizeof(float16) * n_ctx * n_layer * n_embd / n_head * n_head_kv
var kv uint64 = 2 * 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * ggml.KV().EmbeddingLength() / ggml.KV().HeadCount() * ggml.KV().HeadCountKV()
// KV is proportional to the number of layers
layerSize += kv / ggml.KV().BlockCount()
graphPartialOffload, graphFullOffload = ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)))
graphPartialOffload, graphFullOffload := ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)))
if graphPartialOffload == 0 {
graphPartialOffload = ggml.KV().GQA() * kv / 6
}
if graphFullOffload == 0 {
graphFullOffload = graphPartialOffload
}
graphFullOffload *= uint64(len(gpus))
graphPartialOffload *= uint64(len(gpus))
// on metal there's no partial offload overhead
if gpus[0].Library == "metal" {
graphPartialOffload = graphFullOffload
} else if len(gpus) > 1 {
// multigpu should always use the partial graph size
graphFullOffload = graphPartialOffload
}
// memoryRequiredTotal represents the memory required for full GPU offloading (all layers)
memoryRequiredTotal := memoryMinimum + graphFullOffload
// memoryRequiredPartial represents the memory required for partial GPU offloading (n > 0, n < layers)
memoryRequiredPartial := memoryMinimum + graphPartialOffload
var memoryLayerOutput uint64
if layer, ok := layers["output_norm"]; ok {
memoryLayerOutput += layer.size()
}
if layer, ok := layers["output"]; ok {
memoryLayerOutput += layer.size()
} else if layer, ok := layers["token_embd"]; ok {
memoryLayerOutput += layer.size()
}
// Output layer handled at the end if we have space
gpuZeroOverhead := projectorSize
if gpus[0].Library == "metal" && opts.UseMMap {
// memory is preallocated for output tensors
memoryRequiredTotal += memoryLayerOutput
memoryRequiredPartial += memoryLayerOutput
}
// Reduce set of GPUs to only those that have sufficient space to fit overhead and at least one layer
var layerCount int
layerCounts := make([]int, len(gpus))
gpuAllocations := make([]uint64, len(gpus))
type gs struct {
i int
g *gpu.GpuInfo
}
gpusWithSpace := []gs{}
for i := range gpus {
var gzo uint64
if len(gpusWithSpace) == 0 {
gzo = gpuZeroOverhead
}
// Only include GPUs that can fit the graph, gpu minimum, the layer buffer and at least more layer
if gpus[i].FreeMemory < gzo+max(graphPartialOffload, graphFullOffload)+gpus[i].MinimumMemory+2*layerSize {
slog.Debug("gpu has too little memory to allocate any layers", "gpu", gpus[i])
continue
}
gpusWithSpace = append(gpusWithSpace, gs{i, &gpus[i]})
gpuAllocations[i] += gpus[i].MinimumMemory + layerSize // We hold off on graph until we know partial vs. full
}
var gpuZeroID int
if len(gpusWithSpace) > 0 {
gpuZeroID = gpusWithSpace[0].i
gpuAllocations[gpuZeroID] += gpuZeroOverhead
}
// For all the layers, find where they can fit on the GPU(s)
for i := range int(ggml.KV().BlockCount()) {
// Some models have inconsistent layer sizes
for i := 0; i < int(ggml.KV().BlockCount()); i++ {
if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
layerSize = blk.size()
layerSize += kv / ggml.KV().BlockCount()
}
memoryWeights += layerSize
memoryLayer := blk.size()
if opts.NumGPU >= 0 && layerCount >= opts.NumGPU {
// Stop allocating on GPU(s) once we hit the users target NumGPU
continue
}
// KV is proportional to the number of layers
memoryLayer += kv / ggml.KV().BlockCount()
// distribute the layers across the GPU(s) that have space
for j := len(gpusWithSpace); j > 0; j-- {
g := gpusWithSpace[i%j]
used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
if g.g.FreeMemory > used+layerSize {
gpuAllocations[g.i] += layerSize
layerCounts[g.i]++
memoryRequiredTotal += memoryLayer
if (opts.NumGPU >= 0 && layerCount+1 <= opts.NumGPU) || (opts.NumGPU < 0 && memoryAvailable > memoryRequiredPartial+memoryLayer) {
memoryRequiredPartial += memoryLayer
layerCount++
break
} else {
gpusWithSpace = append(gpusWithSpace[:i%j], gpusWithSpace[i%j+1:]...)
}
}
}
if layerCount >= int(ggml.KV().BlockCount()) {
fullyLoaded = true
} else {
for i := layerCount; i < int(ggml.KV().BlockCount()); i++ {
overflow += layerSize
}
if gpus[0].Library != "metal" || !opts.UseMMap {
// memory was not preallocated for output tensors
memoryRequiredTotal += memoryLayerOutput
}
// Determine if we need to consider output then find where it fits
if memoryLayerOutput > 0 && (opts.NumGPU < 0 || layerCount < opts.NumGPU) {
for j := len(gpusWithSpace); j > 0; j-- {
g := gpusWithSpace[layerCount%j]
used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
if g.g.FreeMemory > used+memoryLayerOutput {
gpuAllocations[g.i] += memoryLayerOutput
layerCounts[g.i]++
layerCount++
break
}
}
if layerCount < int(ggml.KV().BlockCount())+1 {
fullyLoaded = false
overflow += memoryLayerOutput
}
if (opts.NumGPU >= 0 && layerCount+1 <= opts.NumGPU) || (opts.NumGPU < 0 && memoryAvailable > memoryRequiredTotal) {
layerCount = int(ggml.KV().BlockCount()) + 1
memoryRequiredPartial = memoryRequiredTotal
}
// Add the applicable (full or partial) graph allocations
for i := range gpus {
if layerCounts[i] <= 0 {
continue
}
if fullyLoaded {
gpuAllocations[i] += graphFullOffload
} else {
gpuAllocations[i] += graphPartialOffload
}
}
if fullyLoaded {
graphOffload = graphFullOffload
} else {
graphOffload = graphPartialOffload
}
memoryWeights := memoryRequiredTotal - memoryMinimum - graphFullOffload - kv
// Summaries for the log
var memoryRequiredPartial, memoryRequiredTotal uint64
for i := range gpuAllocations {
memoryRequiredPartial += gpuAllocations[i]
}
memoryRequiredTotal = memoryRequiredPartial + overflow
tensorSplit := ""
if len(gpus) > 1 {
splits := make([]string, len(gpus))
for i, count := range layerCounts {
splits[i] = strconv.Itoa(count)
}
tensorSplit = strings.Join(splits, ",")
}
allocationsList := []string{}
for _, a := range gpuAllocations {
allocationsList = append(allocationsList, format.HumanBytes2(a))
}
estimate := MemoryEstimate{
TotalSize: memoryRequiredTotal,
Layers: 0,
Graph: 0,
VRAMSize: 0,
GPUSizes: []uint64{},
inferenceLibrary: gpus[0].Library,
layersRequested: opts.NumGPU,
layersModel: int(ggml.KV().BlockCount()) + 1,
availableList: availableList,
kv: kv,
allocationsList: allocationsList,
memoryWeights: memoryWeights,
memoryLayerOutput: memoryLayerOutput,
graphFullOffload: graphFullOffload,
graphPartialOffload: graphPartialOffload,
}
if gpus[0].Library == "cpu" {
return estimate
}
if layerCount == 0 {
slog.Debug("insufficient VRAM to load any model layers")
return estimate
}
estimate.Layers = layerCount
estimate.Graph = graphOffload
estimate.VRAMSize = memoryRequiredPartial
estimate.TotalSize = memoryRequiredTotal
estimate.TensorSplit = tensorSplit
estimate.GPUSizes = gpuAllocations
return estimate
}
func (m MemoryEstimate) log() {
slog.Info(
"offload to "+m.inferenceLibrary,
"offload to gpu",
slog.Group(
"layers",
// requested number of layers to offload
"requested", m.layersRequested,
// The number of layers the model has (including output)
"model", m.layersModel,
"requested", opts.NumGPU,
// estimated number of layers that can be offloaded
"offload", m.Layers,
// multi-gpu split for tensors
"split", m.TensorSplit,
"real", layerCount,
),
slog.Group(
"memory",
// memory available by GPU for offloading
"available", m.availableList,
// memory available for offloading
"available", format.HumanBytes2(memoryAvailable),
slog.Group(
"required",
// memory required for full offloading
"full", format.HumanBytes2(m.TotalSize),
"full", format.HumanBytes2(memoryRequiredTotal),
// memory required to offload layers.estimate layers
"partial", format.HumanBytes2(m.VRAMSize),
"partial", format.HumanBytes2(memoryRequiredPartial),
// memory of KV cache
"kv", format.HumanBytes2(m.kv),
// Allocations across the GPUs
"allocations", m.allocationsList,
"kv", format.HumanBytes2(kv),
),
slog.Group(
"weights",
// memory of the weights
"total", format.HumanBytes2(m.memoryWeights),
"total", format.HumanBytes2(memoryWeights),
// memory of repeating layers
"repeating", format.HumanBytes2(m.memoryWeights-m.memoryLayerOutput),
"repeating", format.HumanBytes2(memoryWeights-memoryLayerOutput),
// memory of non-repeating layers
"nonrepeating", format.HumanBytes2(m.memoryLayerOutput),
"nonrepeating", format.HumanBytes2(memoryLayerOutput),
),
slog.Group(
"graph",
// memory of graph when fully offloaded
"full", format.HumanBytes2(m.graphFullOffload),
"full", format.HumanBytes2(graphFullOffload),
// memory of graph when not fully offloaded
"partial", format.HumanBytes2(m.graphPartialOffload),
"partial", format.HumanBytes2(graphPartialOffload),
),
),
)
if gpus[0].Library == "cpu" {
return 0, 0, memoryRequiredTotal
}
if memoryRequiredPartial > memoryAvailable {
slog.Debug("insufficient VRAM to load any model layers")
return 0, 0, memoryRequiredTotal
}
return layerCount, memoryRequiredPartial, memoryRequiredTotal
}

View File

@@ -1,130 +0,0 @@
package llm
import (
"bytes"
"encoding/binary"
"fmt"
"os"
"testing"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/gpu"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestEstimateGPULayers(t *testing.T) {
envconfig.Debug = true
modelName := "dummy"
f, err := os.CreateTemp(t.TempDir(), modelName)
require.NoError(t, err)
defer f.Close()
gguf := NewGGUFV3(binary.LittleEndian)
inputLayerCount := 5
tensors := []Tensor{
{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.1.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.2.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.3.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.4.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
}
assert.Len(t, tensors, inputLayerCount+1)
err = gguf.Encode(f, KV{
"general.architecture": "llama",
"general.name": "name",
"llama.context_length": uint32(32),
"llama.embedding_length": uint32(4096),
"llama.block_count": uint32(inputLayerCount),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(32),
"tokenizer.ggml.tokens": []string{" "},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, tensors)
require.NoError(t, err)
ggml, err := LoadModel(f.Name(), 0)
if err != nil {
t.Fatal(err)
}
// Simple CPU scenario
gpus := []gpu.GpuInfo{
{
Library: "cpu",
},
}
projectors := []string{}
opts := api.DefaultOptions()
t.Run("cpu", func(t *testing.T) {
estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
assert.Equal(t, 0, estimate.Layers)
assert.Equal(t, uint64(0), estimate.Graph)
})
// derived from the dummy ggml file above
graphPartialOffload := uint64(202377216)
graphFullOffload := uint64(171968512)
layerSize := uint64(33554436)
projectorSize := uint64(0)
memoryLayerOutput := uint64(4)
// Dual CUDA scenario with assymetry
gpuMinimumMemory := uint64(2048)
gpus = []gpu.GpuInfo{
{
Library: "cuda",
MinimumMemory: gpuMinimumMemory,
},
{
Library: "cuda",
MinimumMemory: gpuMinimumMemory,
},
}
// Nested array: GPU0 layer space, GPU1 layer space, expected gpu0, expected gpu1
for i, s := range []struct {
layer0, layer1 uint64
expect0, expect1 uint64
}{
{1, 1, 1, 1},
{2, 1, 2, 1},
{2, 2, 2, 2},
{1, 2, 1, 2},
{3, 3, 3, 3},
{4, 4, 3, 3},
{6, 6, 3, 3},
{0, 3, 0, 3},
} {
t.Run(fmt.Sprintf("%v", s), func(t *testing.T) {
gpus[0].FreeMemory = 0
gpus[1].FreeMemory = 0
gpus[0].FreeMemory += projectorSize
if s.layer0 > 0 {
gpus[0].FreeMemory += memoryLayerOutput
} else {
gpus[1].FreeMemory += memoryLayerOutput
}
gpus[0].FreeMemory += gpuMinimumMemory + layerSize + s.layer0*layerSize + 1
gpus[1].FreeMemory += gpuMinimumMemory + layerSize + s.layer1*layerSize + 1
gpus[0].FreeMemory += max(graphFullOffload, graphPartialOffload)
gpus[1].FreeMemory += max(graphFullOffload, graphPartialOffload)
estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
assert.Equal(t, int(s.expect0+s.expect1), estimate.Layers, "scenario %d: %v", i, s)
assert.Equal(t, fmt.Sprintf("%d,%d", s.expect0, s.expect1), estimate.TensorSplit, "scenario %d: %v", i, s)
var layerSums uint64
for _, b := range estimate.GPUSizes {
layerSums += b
}
if estimate.Layers < inputLayerCount+1 {
assert.Less(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
assert.Equal(t, estimate.VRAMSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
} else {
assert.Equal(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
assert.Equal(t, estimate.TotalSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
}
})
}
}

View File

@@ -1,8 +1,8 @@
diff --git a/common/common.cpp b/common/common.cpp
index 73ff0e85..6adb1a92 100644
index ba1ecf0e..cead57cc 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2447,6 +2447,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
@@ -1836,6 +1836,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
mparams.use_mmap = params.use_mmap;
mparams.use_mlock = params.use_mlock;
mparams.check_tensors = params.check_tensors;
@@ -12,20 +12,20 @@ index 73ff0e85..6adb1a92 100644
mparams.kv_overrides = NULL;
} else {
diff --git a/common/common.h b/common/common.h
index 58ed72f4..0bb2605e 100644
index d80344f2..71e84834 100644
--- a/common/common.h
+++ b/common/common.h
@@ -180,6 +180,13 @@ struct gpt_params {
@@ -174,6 +174,13 @@ struct gpt_params {
// multimodal models (see examples/llava)
std::string mmproj = ""; // path to multimodal projector
std::vector<std::string> image; // path to image file(s)
+
+ // Called with a progress value between 0.0 and 1.0. Pass NULL to disable.
+ // If the provided progress_callback returns true, model loading continues.
+ // If it returns false, model loading is immediately aborted.
+ llama_progress_callback progress_callback = NULL;
+ // context pointer passed to the progress callback
+ void * progress_callback_user_data;
+
// server params
int32_t port = 8080; // server listens on this network port
int32_t timeout_read = 600; // http read timeout in seconds
};
void gpt_params_handle_model_default(gpt_params & params);

View File

@@ -1,8 +1,8 @@
diff --git a/llama.cpp b/llama.cpp
index 61948751..4b72a293 100644
index 40d2ec2c..74f3ee9c 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -4824,16 +4824,7 @@ static void llm_load_vocab(
@@ -4642,16 +4642,7 @@ static void llm_load_vocab(
// for now, only BPE models have pre-tokenizers
if (vocab.type == LLAMA_VOCAB_TYPE_BPE) {
@@ -15,14 +15,14 @@ index 61948751..4b72a293 100644
- LLAMA_LOG_WARN("%s: ************************************ \n", __func__);
- LLAMA_LOG_WARN("%s: \n", __func__);
- vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
- } else if (tokenizer_pre == "default") {
+ if (tokenizer_pre == "default") {
- } else if (
+ if (
tokenizer_pre == "default") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
} else if (
tokenizer_pre == "llama3" ||
@@ -4888,7 +4879,8 @@ static void llm_load_vocab(
tokenizer_pre == "poro-chat") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_PORO;
@@ -4703,7 +4694,8 @@ static void llm_load_vocab(
tokenizer_pre == "smaug-bpe") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_SMAUG;
} else {
- throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
+ LLAMA_LOG_WARN("%s: missing or unrecognized pre-tokenizer type, using: 'default'\n", __func__);

View File

@@ -1,13 +0,0 @@
diff --git a/llama.cpp b/llama.cpp
index 40d2ec2c..f34eb79a 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -6943,7 +6943,7 @@ static struct ggml_tensor * llm_build_kqv(
struct ggml_tensor * kq = ggml_mul_mat(ctx, k, q);
cb(kq, "kq", il);
- if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX) {
+ if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX || model.arch == LLM_ARCH_QWEN2) {
// for this arch, we need to perform the KQ multiplication with F32 precision, otherwise we get NaNs
// ref: https://github.com/ggerganov/llama.cpp/pull/4490#issuecomment-1859055847
ggml_mul_mat_set_prec(kq, GGML_PREC_F32);

View File

@@ -1,305 +0,0 @@
From 5cadb45f39d001ffbad95b690d6cf0abcb4a6d96 Mon Sep 17 00:00:00 2001
From: Ollama maintainers <hello@ollama.com>
Date: Wed, 26 Jun 2024 16:18:09 -0700
Subject: [PATCH] Architecture support
---
llama.cpp | 194 +++++++++++++++++++++++++++++++++++++++++++++++++++++-
1 file changed, 193 insertions(+), 1 deletion(-)
diff --git a/llama.cpp b/llama.cpp
index 61948751..3b4196f5 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -217,6 +217,7 @@ enum llm_arch {
LLM_ARCH_INTERNLM2,
LLM_ARCH_MINICPM,
LLM_ARCH_GEMMA,
+ LLM_ARCH_GEMMA2,
LLM_ARCH_STARCODER2,
LLM_ARCH_MAMBA,
LLM_ARCH_XVERSE,
@@ -255,6 +256,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
{ LLM_ARCH_INTERNLM2, "internlm2" },
{ LLM_ARCH_MINICPM, "minicpm" },
{ LLM_ARCH_GEMMA, "gemma" },
+ { LLM_ARCH_GEMMA2, "gemma2" },
{ LLM_ARCH_STARCODER2, "starcoder2" },
{ LLM_ARCH_MAMBA, "mamba" },
{ LLM_ARCH_XVERSE, "xverse" },
@@ -464,10 +466,12 @@ enum llm_tensor {
LLM_TENSOR_ATTN_NORM,
LLM_TENSOR_ATTN_NORM_2,
LLM_TENSOR_ATTN_OUT_NORM,
+ LLM_TENSOR_ATTN_POST_NORM,
LLM_TENSOR_ATTN_ROT_EMBD,
LLM_TENSOR_FFN_GATE_INP,
LLM_TENSOR_FFN_GATE_INP_SHEXP,
LLM_TENSOR_FFN_NORM,
+ LLM_TENSOR_FFN_POST_NORM,
LLM_TENSOR_FFN_GATE,
LLM_TENSOR_FFN_DOWN,
LLM_TENSOR_FFN_UP,
@@ -960,6 +964,24 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
},
},
+ {
+ LLM_ARCH_GEMMA2,
+ {
+ { LLM_TENSOR_TOKEN_EMBD, "token_embd" },
+ { LLM_TENSOR_OUTPUT_NORM, "output_norm" },
+ { LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },
+ { LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },
+ { LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },
+ { LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },
+ { LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },
+ { LLM_TENSOR_ATTN_POST_NORM, "blk.%d.post_attention_norm" },
+ { LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },
+ { LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },
+ { LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },
+ { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
+ { LLM_TENSOR_FFN_POST_NORM, "blk.%d.post_ffw_norm" },
+ },
+ },
{
LLM_ARCH_STARCODER2,
{
@@ -1941,6 +1963,8 @@ enum e_model {
MODEL_8x22B,
MODEL_16x12B,
MODEL_10B_128x3_66B,
+ MODEL_9B,
+ MODEL_27B,
};
static const size_t kiB = 1024;
@@ -2114,6 +2138,7 @@ struct llama_layer {
struct ggml_tensor * attn_out_norm_b;
struct ggml_tensor * attn_q_a_norm;
struct ggml_tensor * attn_kv_a_norm;
+ struct ggml_tensor * attn_post_norm;
// attention
struct ggml_tensor * wq;
@@ -2136,6 +2161,7 @@ struct llama_layer {
// normalization
struct ggml_tensor * ffn_norm;
struct ggml_tensor * ffn_norm_b;
+ struct ggml_tensor * ffn_post_norm;
struct ggml_tensor * layer_out_norm;
struct ggml_tensor * layer_out_norm_b;
struct ggml_tensor * ffn_norm_exps;
@@ -4529,6 +4555,16 @@ static void llm_load_hparams(
}
} break;
case LLM_ARCH_GEMMA:
+ {
+ ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+
+ switch (hparams.n_layer) {
+ case 18: model.type = e_model::MODEL_9B; break;
+ case 28: model.type = e_model::MODEL_27B; break;
+ default: model.type = e_model::MODEL_UNKNOWN;
+ }
+ } break;
+ case LLM_ARCH_GEMMA2:
{
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
@@ -6305,6 +6341,40 @@ static bool llm_load_tensors(
layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd});
}
} break;
+ case LLM_ARCH_GEMMA2:
+ {
+ model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+ // output
+ model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+ model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
+
+ const int64_t n_ff = hparams.n_ff;
+ const int64_t n_embd_head_k = hparams.n_embd_head_k;
+ const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa();
+ const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa();
+
+ for (uint32_t i = 0; i < n_layer; ++i) {
+ ggml_context * ctx_layer = ctx_for_layer(i);
+ ggml_context * ctx_split = ctx_for_layer_split(i);
+
+ auto & layer = model.layers[i];
+
+ layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
+ layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd_head_k * hparams.n_head});
+ layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_k_gqa});
+ layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_v_gqa});
+ layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head, n_embd});
+ layer.attn_post_norm = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_POST_NORM, "weight", i), {n_embd});
+
+ layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+ layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
+ layer.ffn_up = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff});
+ layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd});
+ layer.ffn_post_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd});
+ }
+ } break;
case LLM_ARCH_STARCODER2:
{
model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
@@ -10614,6 +10684,123 @@ struct llm_build_context {
return gf;
}
+ struct ggml_cgraph * build_gemma2() {
+ struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+ const int64_t n_embd_head_k = hparams.n_embd_head_k;
+
+ struct ggml_tensor * cur;
+ struct ggml_tensor * inpL;
+
+ inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+ inpL = ggml_scale(ctx0, inpL, sqrtf(n_embd));
+ cb(inpL, "inp_scaled", -1);
+
+ // inp_pos - contains the positions
+ struct ggml_tensor * inp_pos = build_inp_pos();
+
+ // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+ struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+ for (int il = 0; il < n_layer; ++il) {
+ // norm
+ cur = llm_build_norm(ctx0, inpL, hparams,
+ model.layers[il].attn_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "attn_norm", il);
+
+ // self-attention
+ {
+ // compute Q and K and RoPE them
+ struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+ cb(Qcur, "Qcur", il);
+
+ struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+ cb(Kcur, "Kcur", il);
+
+ struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+ cb(Vcur, "Vcur", il);
+
+ Qcur = ggml_rope_ext(
+ ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head, n_tokens), inp_pos, nullptr,
+ n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+ ext_factor, attn_factor, beta_fast, beta_slow);
+ cb(Qcur, "Qcur", il);
+
+ Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head_k)));
+ cb(Qcur, "Qcur_scaled", il);
+
+ Kcur = ggml_rope_ext(
+ ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos, nullptr,
+ n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+ ext_factor, attn_factor, beta_fast, beta_slow);
+ cb(Kcur, "Kcur", il);
+
+ cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+ model.layers[il].wo, NULL,
+ Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
+ }
+
+ if (il == n_layer - 1) {
+ // skip computing output for unused tokens
+ struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+ cur = ggml_get_rows(ctx0, cur, inp_out_ids);
+ inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);
+ }
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.layers[il].attn_post_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "attn_post_norm", il);
+
+ struct ggml_tensor * sa_out = ggml_add(ctx0, cur, inpL);
+ cb(sa_out, "sa_out", il);
+
+ cur = llm_build_norm(ctx0, sa_out, hparams,
+ model.layers[il].ffn_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "ffn_norm", il);
+
+ // feed-forward network
+ {
+ cur = llm_build_ffn(ctx0, cur,
+ model.layers[il].ffn_up, NULL,
+ model.layers[il].ffn_gate, NULL,
+ model.layers[il].ffn_down, NULL,
+ NULL,
+ LLM_FFN_GELU, LLM_FFN_PAR, cb, il);
+ cb(cur, "ffn_out", il);
+ }
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.layers[il].ffn_post_norm, NULL,
+ LLM_NORM_RMS, cb, -1);
+ cb(cur, "ffn_post_norm", -1);
+
+ cur = ggml_add(ctx0, cur, sa_out);
+ cb(cur, "l_out", il);
+
+ // input for next layer
+ inpL = cur;
+ }
+
+ cur = inpL;
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.output_norm, NULL,
+ LLM_NORM_RMS, cb, -1);
+ cb(cur, "result_norm", -1);
+
+ // lm_head
+ cur = ggml_mul_mat(ctx0, model.output, cur);
+ cb(cur, "result_output", -1);
+
+ ggml_build_forward_expand(gf, cur);
+
+ return gf;
+ }
+
struct ggml_cgraph * build_starcoder2() {
struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
@@ -11847,6 +12034,10 @@ static struct ggml_cgraph * llama_build_graph(
{
result = llm.build_gemma();
} break;
+ case LLM_ARCH_GEMMA2:
+ {
+ result = llm.build_gemma2();
+ } break;
case LLM_ARCH_STARCODER2:
{
result = llm.build_starcoder2();
@@ -16671,6 +16862,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
case LLM_ARCH_PHI2:
case LLM_ARCH_PHI3:
case LLM_ARCH_GEMMA:
+ case LLM_ARCH_GEMMA2:
case LLM_ARCH_STARCODER2:
case LLM_ARCH_GPTNEOX:
return LLAMA_ROPE_TYPE_NEOX;
@@ -18551,7 +18743,7 @@ static int32_t llama_chat_apply_template_internal(
if (add_ass) {
ss << "<s>assistant\n";
}
- } else if (tmpl == "gemma" || tmpl.find("<start_of_turn>") != std::string::npos) {
+ } else if (tmpl == "gemma" || tmpl == "gemma2" || tmpl.find("<start_of_turn>") != std::string::npos) {
// google/gemma-7b-it
std::string system_prompt = "";
for (auto message : chat) {
--
2.45.2

View File

@@ -10,9 +10,9 @@ import (
"os"
"path/filepath"
"runtime"
"slices"
"strings"
"golang.org/x/exp/slices"
"golang.org/x/sync/errgroup"
"github.com/ollama/ollama/gpu"
@@ -58,7 +58,7 @@ func availableServers() map[string]string {
}
// glob payloadsDir for files that start with ollama_
pattern := filepath.Join(payloadsDir, "*", "ollama_*")
pattern := filepath.Join(payloadsDir, "*")
files, err := filepath.Glob(pattern)
if err != nil {
@@ -69,7 +69,7 @@ func availableServers() map[string]string {
servers := make(map[string]string)
for _, file := range files {
slog.Debug("availableServers : found", "file", file)
servers[filepath.Base(filepath.Dir(file))] = filepath.Dir(file)
servers[filepath.Base(file)] = file
}
return servers
@@ -82,8 +82,8 @@ func serversForGpu(info gpu.GpuInfo) []string {
// glob workDir for files that start with ollama_
availableServers := availableServers()
requested := info.Library
if info.Variant != gpu.CPUCapabilityNone {
requested += "_" + info.Variant.String()
if info.Variant != "" {
requested += "_" + info.Variant
}
servers := []string{}
@@ -117,14 +117,14 @@ func serversForGpu(info gpu.GpuInfo) []string {
// Load up the best CPU variant if not primary requested
if info.Library != "cpu" {
variant := gpu.GetCPUCapability()
variant := gpu.GetCPUVariant()
// If no variant, then we fall back to default
// If we have a variant, try that if we find an exact match
// Attempting to run the wrong CPU instructions will panic the
// process
if variant != gpu.CPUCapabilityNone {
if variant != "" {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {
if cmp == "cpu_"+variant {
servers = append(servers, cmp)
break
}
@@ -146,11 +146,11 @@ func serverForCpu() string {
if runtime.GOOS == "darwin" && runtime.GOARCH == "arm64" {
return "metal"
}
variant := gpu.GetCPUCapability()
variant := gpu.GetCPUVariant()
availableServers := availableServers()
if variant != gpu.CPUCapabilityNone {
if variant != "" {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {
if cmp == "cpu_"+variant {
return cmp
}
}

View File

@@ -37,9 +37,8 @@ type LlamaServer interface {
Tokenize(ctx context.Context, content string) ([]int, error)
Detokenize(ctx context.Context, tokens []int) (string, error)
Close() error
EstimatedVRAM() uint64 // Total VRAM across all GPUs
EstimatedVRAM() uint64
EstimatedTotal() uint64
EstimatedVRAMByGPU(gpuID string) uint64
}
// llmServer is an instance of the llama.cpp server
@@ -50,22 +49,18 @@ type llmServer struct {
status *StatusWriter
options api.Options
estimate MemoryEstimate
totalLayers uint64
// gpuCount int
gpus gpu.GpuInfoList // Recorded just before the model loaded, free space will be incorrect
loadDuration time.Duration // Record how long it took the model to load
loadProgress float32
// TODO - this should be broken down by GPU
estimatedVRAM uint64 // Estimated usage of VRAM by the loaded model
estimatedTotal uint64 // Total size of model
totalLayers uint64
gpuCount int
loadDuration time.Duration // Record how long it took the model to load
loadProgress float32
sem *semaphore.Weighted
}
// LoadModel will load a model from disk. The model must be in the GGML format.
//
// It collects array values for arrays with a size less than or equal to
// maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
// the maxArraySize is negative, all arrays are collected.
func LoadModel(model string, maxArraySize int) (*GGML, error) {
func LoadModel(model string) (*GGML, error) {
if _, err := os.Stat(model); err != nil {
return nil, err
}
@@ -76,7 +71,7 @@ func LoadModel(model string, maxArraySize int) (*GGML, error) {
}
defer f.Close()
ggml, _, err := DecodeGGML(f, maxArraySize)
ggml, _, err := DecodeGGML(f)
return ggml, err
}
@@ -85,47 +80,45 @@ func LoadModel(model string, maxArraySize int) (*GGML, error) {
func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, projectors []string, opts api.Options) (LlamaServer, error) {
var err error
var cpuRunner string
var estimate MemoryEstimate
var systemTotalMemory uint64
var systemFreeMemory uint64
var estimatedVRAM uint64
var estimatedTotal uint64
var systemMemory uint64
gpuCount := len(gpus)
if (len(gpus) == 1 && gpus[0].Library == "cpu") || opts.NumGPU == 0 {
systemMemInfo, err := gpu.GetCPUMem()
if err != nil {
slog.Error("failed to lookup system memory", "error", err)
} else {
systemTotalMemory = systemMemInfo.TotalMemory
systemFreeMemory = systemMemInfo.FreeMemory
slog.Debug("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", systemFreeMemory)
}
// TODO evaluate system memory to see if we should block the load, or force an unload of another CPU runner
// If the user wants zero GPU layers, reset the gpu list to be CPU/system ram info
if opts.NumGPU == 0 {
gpus = gpu.GetCPUInfo()
}
if len(gpus) == 1 && gpus[0].Library == "cpu" {
cpuRunner = serverForCpu()
estimate = EstimateGPULayers(gpus, ggml, projectors, opts)
gpuCount = 0
_, _, estimatedTotal = EstimateGPULayers(gpus, ggml, projectors, opts)
} else {
estimate = EstimateGPULayers(gpus, ggml, projectors, opts)
if gpus[0].Library == "metal" {
memInfo, err := gpu.GetCPUMem()
if err != nil {
slog.Error("failed to lookup system memory", "error", err)
} else {
systemMemory = memInfo.TotalMemory
slog.Debug("system memory", "total", format.HumanBytes2(systemMemory))
}
}
var layers int
layers, estimatedVRAM, estimatedTotal = EstimateGPULayers(gpus, ggml, projectors, opts)
switch {
case gpus[0].Library == "metal" && estimate.VRAMSize > systemTotalMemory:
if gpus[0].Library == "metal" && estimatedVRAM > systemMemory {
// disable partial offloading when model is greater than total system memory as this
// can lead to locking up the system
opts.NumGPU = 0
case gpus[0].Library != "metal" && estimate.Layers == 0:
} else if gpus[0].Library != "metal" && layers == 0 {
// Don't bother loading into the GPU if no layers can fit
cpuRunner = serverForCpu()
gpus = gpu.GetCPUInfo()
case opts.NumGPU < 0 && estimate.Layers > 0 && gpus[0].Library != "cpu":
opts.NumGPU = estimate.Layers
gpuCount = 0
} else if opts.NumGPU < 0 && layers > 0 && gpus[0].Library != "cpu" {
opts.NumGPU = layers
}
}
estimate.log()
// Loop through potential servers
finalErr := errors.New("no suitable llama servers found")
finalErr := fmt.Errorf("no suitable llama servers found")
if len(adapters) > 1 {
return nil, errors.New("ollama supports only one lora adapter, but multiple were provided")
@@ -166,8 +159,6 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
params = append(params, "--log-disable")
params = append(params, "--timeout", fmt.Sprintf("%d", 600))
if opts.NumGPU >= 0 {
params = append(params, "--n-gpu-layers", fmt.Sprintf("%d", opts.NumGPU))
}
@@ -210,7 +201,7 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
if g.Library == "metal" &&
uint64(opts.NumGPU) > 0 &&
uint64(opts.NumGPU) < ggml.KV().BlockCount()+1 {
opts.UseMMap = api.TriStateFalse
opts.UseMMap = false
}
}
@@ -218,11 +209,7 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
params = append(params, "--flash-attn")
}
// Windows CUDA should not use mmap for best performance
// Linux with a model larger than free space, mmap leads to thrashing
if (runtime.GOOS == "windows" && gpus[0].Library == "cuda" && opts.UseMMap == api.TriStateUndefined) ||
(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == api.TriStateUndefined) ||
opts.UseMMap == api.TriStateFalse {
if !opts.UseMMap {
params = append(params, "--no-mmap")
}
@@ -245,15 +232,7 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
params = append(params, "--parallel", fmt.Sprintf("%d", numParallel))
if estimate.TensorSplit != "" {
params = append(params, "--tensor-split", estimate.TensorSplit)
}
if estimate.TensorSplit != "" {
params = append(params, "--tensor-split", estimate.TensorSplit)
}
for i := range len(servers) {
for i := 0; i < len(servers); i++ {
dir := availableServers[servers[i]]
if dir == "" {
// Shouldn't happen
@@ -263,7 +242,8 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
}
if strings.HasPrefix(servers[i], "cpu") {
gpus = gpu.GetCPUInfo()
// TODO if we tried a gpu runner first, and it failed, record the error and bubble that back up
gpuCount = 0
}
// Find an availableServers port, retry on each iteration in case the failure was a port conflict race
@@ -285,8 +265,8 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
if runtime.GOOS == "windows" {
pathEnv = "PATH"
}
// prepend the server directory to LD_LIBRARY_PATH/PATH and the parent dir for common dependencies
libraryPaths := []string{dir, filepath.Dir(dir)}
// prepend the server directory to LD_LIBRARY_PATH/PATH
libraryPaths := []string{dir}
if libraryPath, ok := os.LookupEnv(pathEnv); ok {
// Append our runner directory to the path
@@ -304,7 +284,7 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
server := filepath.Join(dir, "ollama_llama_server")
if runtime.GOOS == "windows" {
server += ".exe"
server = server + ".exe"
}
// Detect tmp cleaners wiping out the file
@@ -319,26 +299,23 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
}
s := &llmServer{
port: port,
cmd: exec.Command(server, finalParams...),
status: NewStatusWriter(os.Stderr),
options: opts,
estimate: estimate,
sem: semaphore.NewWeighted(int64(numParallel)),
totalLayers: ggml.KV().BlockCount() + 1,
gpus: gpus,
done: make(chan error, 1),
port: port,
cmd: exec.Command(server, finalParams...),
status: NewStatusWriter(os.Stderr),
options: opts,
estimatedVRAM: estimatedVRAM,
estimatedTotal: estimatedTotal,
sem: semaphore.NewWeighted(int64(numParallel)),
totalLayers: ggml.KV().BlockCount() + 1,
gpuCount: gpuCount,
done: make(chan error, 1),
}
s.cmd.Env = os.Environ()
s.cmd.Stdout = os.Stdout
s.cmd.Stderr = s.status
envWorkarounds := [][2]string{}
for _, gpu := range gpus {
envWorkarounds = append(envWorkarounds, gpu.EnvWorkarounds...)
}
visibleDevicesEnv, visibleDevicesEnvVal := gpus.GetVisibleDevicesEnv()
visibleDevicesEnv, visibleDevicesEnvVal := gpu.GpuInfoList(gpus).GetVisibleDevicesEnv()
pathEnvVal := strings.Join(libraryPaths, string(filepath.ListSeparator))
// Update or add the path and visible devices variable with our adjusted version
@@ -352,12 +329,6 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
} else if devicesNeeded && strings.EqualFold(cmp[0], visibleDevicesEnv) {
s.cmd.Env[i] = visibleDevicesEnv + "=" + visibleDevicesEnvVal
devicesNeeded = false
} else if len(envWorkarounds) != 0 {
for _, kv := range envWorkarounds {
if strings.EqualFold(cmp[0], kv[0]) {
s.cmd.Env[i] = kv[0] + "=" + kv[1]
}
}
}
}
if pathNeeded {
@@ -419,7 +390,7 @@ func projectorMemoryRequirements(filename string) uint64 {
}
defer file.Close()
ggml, _, err := DecodeGGML(file, 0)
ggml, _, err := DecodeGGML(file)
if err != nil {
return 0
}
@@ -488,7 +459,7 @@ func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
resp, err := http.DefaultClient.Do(req)
if err != nil {
if errors.Is(err, context.DeadlineExceeded) {
return ServerStatusNotResponding, errors.New("server not responding")
return ServerStatusNotResponding, fmt.Errorf("server not responding")
}
return ServerStatusError, fmt.Errorf("health resp: %w", err)
}
@@ -635,7 +606,7 @@ array ::=
string ::=
"\"" (
[^"\\\x7F\x00-\x1F] |
[^"\\] |
"\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes
)* "\"" ws
@@ -1033,20 +1004,11 @@ func (s *llmServer) Close() error {
}
func (s *llmServer) EstimatedVRAM() uint64 {
return s.estimate.VRAMSize
return s.estimatedVRAM
}
func (s *llmServer) EstimatedTotal() uint64 {
return s.estimate.TotalSize
}
func (s *llmServer) EstimatedVRAMByGPU(gpuID string) uint64 {
for i, gpu := range s.gpus {
if gpu.ID == gpuID {
return s.estimate.GPUSizes[i]
}
}
return 0
return s.estimatedTotal
}
func parseDurationMs(ms float64) time.Duration {

View File

@@ -178,6 +178,9 @@ func fromRequest(r ChatCompletionRequest) api.ChatRequest {
if r.Seed != nil {
options["seed"] = *r.Seed
// temperature=0 is required for reproducible outputs
options["temperature"] = 0.0
}
if r.FrequencyPenalty != nil {
@@ -242,6 +245,7 @@ func (w *writer) writeResponse(data []byte) (int, error) {
d, err := json.Marshal(toChunk(w.id, chatResponse))
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "text/event-stream")

View File

@@ -8,9 +8,7 @@ import (
"io"
"strconv"
"strings"
"golang.org/x/text/encoding/unicode"
"golang.org/x/text/transform"
"unicode"
)
type File struct {
@@ -71,11 +69,14 @@ func ParseFile(r io.Reader) (*File, error) {
var b bytes.Buffer
var role string
var lineCount int
var linePos int
var utf16 bool
var f File
tr := unicode.BOMOverride(unicode.UTF8.NewDecoder())
br := bufio.NewReader(transform.NewReader(r, tr))
br := bufio.NewReader(r)
for {
r, _, err := br.ReadRune()
if errors.Is(err, io.EOF) {
@@ -84,6 +85,17 @@ func ParseFile(r io.Reader) (*File, error) {
return nil, err
}
// the utf16 byte order mark will be read as "unreadable" by ReadRune()
if isUnreadable(r) && lineCount == 0 && linePos == 0 {
utf16 = true
continue
}
// skip the second byte if we're reading utf16
if utf16 && r == 0 {
continue
}
next, r, err := parseRuneForState(r, curr)
if errors.Is(err, io.ErrUnexpectedEOF) {
return nil, fmt.Errorf("%w: %s", err, b.String())
@@ -91,6 +103,13 @@ func ParseFile(r io.Reader) (*File, error) {
return nil, err
}
if isNewline(r) {
lineCount++
linePos = 0
} else {
linePos++
}
// process the state transition, some transitions need to be intercepted and redirected
if next != curr {
switch curr {
@@ -290,6 +309,10 @@ func isNewline(r rune) bool {
return r == '\r' || r == '\n'
}
func isUnreadable(r rune) bool {
return r == unicode.ReplacementChar
}
func isValidMessageRole(role string) bool {
return role == "system" || role == "user" || role == "assistant"
}

View File

@@ -10,9 +10,6 @@ import (
"unicode/utf16"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
"golang.org/x/text/encoding"
"golang.org/x/text/encoding/unicode"
)
func TestParseFileFile(t *testing.T) {
@@ -28,7 +25,7 @@ TEMPLATE template1
reader := strings.NewReader(input)
modelfile, err := ParseFile(reader)
require.NoError(t, err)
assert.NoError(t, err)
expectedCommands := []Command{
{Name: "model", Args: "model1"},
@@ -91,7 +88,7 @@ func TestParseFileFrom(t *testing.T) {
for _, c := range cases {
t.Run("", func(t *testing.T) {
modelfile, err := ParseFile(strings.NewReader(c.input))
require.ErrorIs(t, err, c.err)
assert.ErrorIs(t, err, c.err)
if modelfile != nil {
assert.Equal(t, c.expected, modelfile.Commands)
}
@@ -108,7 +105,7 @@ PARAMETER param1
reader := strings.NewReader(input)
_, err := ParseFile(reader)
require.ErrorIs(t, err, io.ErrUnexpectedEOF)
assert.ErrorIs(t, err, io.ErrUnexpectedEOF)
}
func TestParseFileBadCommand(t *testing.T) {
@@ -117,7 +114,8 @@ FROM foo
BADCOMMAND param1 value1
`
_, err := ParseFile(strings.NewReader(input))
require.ErrorIs(t, err, errInvalidCommand)
assert.ErrorIs(t, err, errInvalidCommand)
}
func TestParseFileMessages(t *testing.T) {
@@ -203,7 +201,7 @@ MESSAGE system`,
for _, c := range cases {
t.Run("", func(t *testing.T) {
modelfile, err := ParseFile(strings.NewReader(c.input))
require.ErrorIs(t, err, c.err)
assert.ErrorIs(t, err, c.err)
if modelfile != nil {
assert.Equal(t, c.expected, modelfile.Commands)
}
@@ -357,7 +355,7 @@ TEMPLATE """
for _, c := range cases {
t.Run("", func(t *testing.T) {
modelfile, err := ParseFile(strings.NewReader(c.multiline))
require.ErrorIs(t, err, c.err)
assert.ErrorIs(t, err, c.err)
if modelfile != nil {
assert.Equal(t, c.expected, modelfile.Commands)
}
@@ -415,7 +413,7 @@ func TestParseFileParameters(t *testing.T) {
fmt.Fprintln(&b, "FROM foo")
fmt.Fprintln(&b, "PARAMETER", k)
modelfile, err := ParseFile(&b)
require.NoError(t, err)
assert.NoError(t, err)
assert.Equal(t, []Command{
{Name: "model", Args: "foo"},
@@ -444,7 +442,7 @@ FROM foo
for _, c := range cases {
t.Run("", func(t *testing.T) {
modelfile, err := ParseFile(strings.NewReader(c.input))
require.NoError(t, err)
assert.NoError(t, err)
assert.Equal(t, c.expected, modelfile.Commands)
})
}
@@ -503,14 +501,15 @@ SYSTEM ""
for _, c := range cases {
t.Run("", func(t *testing.T) {
modelfile, err := ParseFile(strings.NewReader(c))
require.NoError(t, err)
assert.NoError(t, err)
modelfile2, err := ParseFile(strings.NewReader(modelfile.String()))
require.NoError(t, err)
assert.NoError(t, err)
assert.Equal(t, modelfile, modelfile2)
})
}
}
func TestParseFileUTF16ParseFile(t *testing.T) {
@@ -519,6 +518,14 @@ PARAMETER param1 1
PARAMETER param2 4096
SYSTEM You are a utf16 file.
`
// simulate a utf16 le file
utf16File := utf16.Encode(append([]rune{'\ufffe'}, []rune(data)...))
buf := new(bytes.Buffer)
err := binary.Write(buf, binary.LittleEndian, utf16File)
assert.NoError(t, err)
actual, err := ParseFile(buf)
assert.NoError(t, err)
expected := []Command{
{Name: "model", Args: "bob"},
@@ -527,52 +534,14 @@ SYSTEM You are a utf16 file.
{Name: "system", Args: "You are a utf16 file."},
}
t.Run("le", func(t *testing.T) {
var b bytes.Buffer
require.NoError(t, binary.Write(&b, binary.LittleEndian, []byte{0xff, 0xfe}))
require.NoError(t, binary.Write(&b, binary.LittleEndian, utf16.Encode([]rune(data))))
assert.Equal(t, expected, actual.Commands)
actual, err := ParseFile(&b)
require.NoError(t, err)
// simulate a utf16 be file
buf = new(bytes.Buffer)
err = binary.Write(buf, binary.BigEndian, utf16File)
assert.NoError(t, err)
assert.Equal(t, expected, actual.Commands)
})
t.Run("be", func(t *testing.T) {
var b bytes.Buffer
require.NoError(t, binary.Write(&b, binary.BigEndian, []byte{0xfe, 0xff}))
require.NoError(t, binary.Write(&b, binary.BigEndian, utf16.Encode([]rune(data))))
actual, err := ParseFile(&b)
require.NoError(t, err)
assert.Equal(t, expected, actual.Commands)
})
}
func TestParseMultiByte(t *testing.T) {
input := `FROM test
SYSTEM 你好👋`
expect := []Command{
{Name: "model", Args: "test"},
{Name: "system", Args: "你好👋"},
}
encodings := []encoding.Encoding{
unicode.UTF8,
unicode.UTF16(unicode.LittleEndian, unicode.UseBOM),
unicode.UTF16(unicode.BigEndian, unicode.UseBOM),
}
for _, encoding := range encodings {
t.Run(fmt.Sprintf("%s", encoding), func(t *testing.T) {
s, err := encoding.NewEncoder().String(input)
require.NoError(t, err)
actual, err := ParseFile(strings.NewReader(s))
require.NoError(t, err)
assert.Equal(t, expect, actual.Commands)
})
}
actual, err = ParseFile(buf)
assert.NoError(t, err)
assert.Equal(t, expected, actual.Commands)
}

View File

@@ -59,7 +59,7 @@ func (p *Progress) StopAndClear() bool {
stopped := p.stop()
if stopped {
// clear all progress lines
for i := range p.pos {
for i := 0; i < p.pos; i++ {
if i > 0 {
fmt.Fprint(p.w, "\033[A")
}
@@ -85,7 +85,7 @@ func (p *Progress) render() {
defer fmt.Fprint(p.w, "\033[?25h")
// clear already rendered progress lines
for i := range p.pos {
for i := 0; i < p.pos; i++ {
if i > 0 {
fmt.Fprint(p.w, "\033[A")
}

View File

@@ -52,6 +52,7 @@ func (b *Buffer) GetLineSpacing(line int) bool {
}
return hasSpace.(bool)
}
func (b *Buffer) MoveLeft() {
@@ -116,12 +117,15 @@ func (b *Buffer) MoveRight() {
if b.DisplayPos%b.LineWidth == 0 {
fmt.Printf(CursorDown + CursorBOL + cursorRightN(len(b.Prompt.prompt())))
} else if (b.DisplayPos-rLength)%b.LineWidth == b.LineWidth-1 && hasSpace {
fmt.Printf(CursorDown + CursorBOL + cursorRightN(len(b.Prompt.prompt())+rLength))
b.DisplayPos += 1
} else if b.LineHasSpace.Size() > 0 && b.DisplayPos%b.LineWidth == b.LineWidth-1 && hasSpace {
fmt.Printf(CursorDown + CursorBOL + cursorRightN(len(b.Prompt.prompt())))
b.DisplayPos += 1
} else {
fmt.Print(cursorRightN(rLength))
}
@@ -150,7 +154,7 @@ func (b *Buffer) MoveToStart() {
if b.Pos > 0 {
currLine := b.DisplayPos / b.LineWidth
if currLine > 0 {
for range currLine {
for cnt := 0; cnt < currLine; cnt++ {
fmt.Print(CursorUp)
}
}
@@ -165,7 +169,7 @@ func (b *Buffer) MoveToEnd() {
currLine := b.DisplayPos / b.LineWidth
totalLines := b.DisplaySize() / b.LineWidth
if currLine < totalLines {
for range totalLines - currLine {
for cnt := 0; cnt < totalLines-currLine; cnt++ {
fmt.Print(CursorDown)
}
remainder := b.DisplaySize() % b.LineWidth
@@ -181,7 +185,7 @@ func (b *Buffer) MoveToEnd() {
func (b *Buffer) DisplaySize() int {
sum := 0
for i := range b.Buf.Size() {
for i := 0; i < b.Buf.Size(); i++ {
if e, ok := b.Buf.Get(i); ok {
if r, ok := e.(rune); ok {
sum += runewidth.RuneWidth(r)
@@ -193,6 +197,7 @@ func (b *Buffer) DisplaySize() int {
}
func (b *Buffer) Add(r rune) {
if b.Pos == b.Buf.Size() {
b.AddChar(r, false)
} else {
@@ -205,6 +210,7 @@ func (b *Buffer) AddChar(r rune, insert bool) {
b.DisplayPos += rLength
if b.Pos > 0 {
if b.DisplayPos%b.LineWidth == 0 {
fmt.Printf("%c", r)
fmt.Printf("\n%s", b.Prompt.AltPrompt)
@@ -229,6 +235,7 @@ func (b *Buffer) AddChar(r rune, insert bool) {
} else {
b.LineHasSpace.Add(true)
}
} else {
fmt.Printf("%c", r)
}
@@ -349,6 +356,7 @@ func (b *Buffer) drawRemaining() {
func (b *Buffer) Remove() {
if b.Buf.Size() > 0 && b.Pos > 0 {
if e, ok := b.Buf.Get(b.Pos - 1); ok {
if r, ok := e.(rune); ok {
rLength := runewidth.RuneWidth(r)
@@ -374,6 +382,7 @@ func (b *Buffer) Remove() {
} else {
fmt.Print(" " + CursorLeft)
}
} else if (b.DisplayPos-rLength)%b.LineWidth == 0 && hasSpace {
fmt.Printf(CursorBOL + ClearToEOL)
fmt.Printf(CursorUp + CursorBOL + cursorRightN(b.Width))
@@ -382,9 +391,10 @@ func (b *Buffer) Remove() {
b.LineHasSpace.Remove(b.DisplayPos/b.LineWidth - 1)
}
b.DisplayPos -= 1
} else {
fmt.Print(cursorLeftN(rLength))
for range rLength {
for i := 0; i < rLength; i++ {
fmt.Print(" ")
}
fmt.Print(cursorLeftN(rLength))
@@ -441,7 +451,7 @@ func (b *Buffer) DeleteBefore() {
func (b *Buffer) DeleteRemaining() {
if b.DisplaySize() > 0 && b.Pos < b.DisplaySize() {
charsToDel := b.Buf.Size() - b.Pos
for range charsToDel {
for cnt := 0; cnt < charsToDel; cnt++ {
b.Delete()
}
}
@@ -485,7 +495,7 @@ func (b *Buffer) ClearScreen() {
if currPos > 0 {
targetLine := currPos / b.LineWidth
if targetLine > 0 {
for range targetLine {
for cnt := 0; cnt < targetLine; cnt++ {
fmt.Print(CursorDown)
}
}
@@ -515,7 +525,7 @@ func (b *Buffer) Replace(r []rune) {
fmt.Printf(CursorBOL + ClearToEOL)
for range lineNums {
for i := 0; i < lineNums; i++ {
fmt.Print(CursorUp + CursorBOL + ClearToEOL)
}

View File

@@ -91,7 +91,7 @@ func (h *History) Add(l []rune) {
func (h *History) Compact() {
s := h.Buf.Size()
if s > h.Limit {
for range s - h.Limit {
for cnt := 0; cnt < s-h.Limit; cnt++ {
h.Buf.Remove(0)
}
}
@@ -139,7 +139,7 @@ func (h *History) Save() error {
defer f.Close()
buf := bufio.NewWriter(f)
for cnt := range h.Size() {
for cnt := 0; cnt < h.Size(); cnt++ {
v, _ := h.Buf.Get(cnt)
line, _ := v.([]rune)
if _, err := buf.WriteString(string(line) + "\n"); err != nil {

View File

@@ -5,6 +5,7 @@ import (
"fmt"
"io"
"os"
"syscall"
)
type Prompt struct {
@@ -62,7 +63,7 @@ func New(prompt Prompt) (*Instance, error) {
func (i *Instance) Readline() (string, error) {
if !i.Terminal.rawmode {
fd := os.Stdin.Fd()
fd := int(syscall.Stdin)
termios, err := SetRawMode(fd)
if err != nil {
return "", err
@@ -79,8 +80,8 @@ func (i *Instance) Readline() (string, error) {
fmt.Print(prompt)
defer func() {
fd := os.Stdin.Fd()
//nolint:errcheck
fd := int(syscall.Stdin)
// nolint: errcheck
UnsetRawMode(fd, i.Terminal.termios)
i.Terminal.rawmode = false
}()
@@ -135,7 +136,7 @@ func (i *Instance) Readline() (string, error) {
buf.MoveRight()
case CharBracketedPaste:
var code string
for range 3 {
for cnt := 0; cnt < 3; cnt++ {
r, err = i.Terminal.Read()
if err != nil {
return "", io.EOF
@@ -197,7 +198,7 @@ func (i *Instance) Readline() (string, error) {
buf.Remove()
case CharTab:
// todo: convert back to real tabs
for range 8 {
for cnt := 0; cnt < 8; cnt++ {
buf.Add(' ')
}
case CharDelete:
@@ -215,7 +216,7 @@ func (i *Instance) Readline() (string, error) {
case CharCtrlW:
buf.DeleteWord()
case CharCtrlZ:
fd := os.Stdin.Fd()
fd := int(syscall.Stdin)
return handleCharCtrlZ(fd, i.Terminal.termios)
case CharEnter, CharCtrlJ:
output := buf.String()
@@ -247,7 +248,7 @@ func (i *Instance) HistoryDisable() {
}
func NewTerminal() (*Terminal, error) {
fd := os.Stdin.Fd()
fd := int(syscall.Stdin)
termios, err := SetRawMode(fd)
if err != nil {
return nil, err

View File

@@ -6,7 +6,7 @@ import (
"syscall"
)
func handleCharCtrlZ(fd uintptr, termios any) (string, error) {
func handleCharCtrlZ(fd int, termios any) (string, error) {
t := termios.(*Termios)
if err := UnsetRawMode(fd, t); err != nil {
return "", err

View File

@@ -1,6 +1,6 @@
package readline
func handleCharCtrlZ(fd uintptr, state any) (string, error) {
func handleCharCtrlZ(fd int, state any) (string, error) {
// not supported
return "", nil
}

View File

@@ -8,7 +8,7 @@ import (
type Termios syscall.Termios
func SetRawMode(fd uintptr) (*Termios, error) {
func SetRawMode(fd int) (*Termios, error) {
termios, err := getTermios(fd)
if err != nil {
return nil, err
@@ -25,13 +25,13 @@ func SetRawMode(fd uintptr) (*Termios, error) {
return termios, setTermios(fd, &newTermios)
}
func UnsetRawMode(fd uintptr, termios any) error {
func UnsetRawMode(fd int, termios any) error {
t := termios.(*Termios)
return setTermios(fd, t)
}
// IsTerminal returns true if the given file descriptor is a terminal.
func IsTerminal(fd uintptr) bool {
func IsTerminal(fd int) bool {
_, err := getTermios(fd)
return err == nil
}

View File

@@ -7,17 +7,17 @@ import (
"unsafe"
)
func getTermios(fd uintptr) (*Termios, error) {
func getTermios(fd int) (*Termios, error) {
termios := new(Termios)
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, fd, syscall.TIOCGETA, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, uintptr(fd), syscall.TIOCGETA, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
if err != 0 {
return nil, err
}
return termios, nil
}
func setTermios(fd uintptr, termios *Termios) error {
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, fd, syscall.TIOCSETA, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
func setTermios(fd int, termios *Termios) error {
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, uintptr(fd), syscall.TIOCSETA, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
if err != 0 {
return err
}

View File

@@ -10,17 +10,17 @@ import (
const tcgets = 0x5401
const tcsets = 0x5402
func getTermios(fd uintptr) (*Termios, error) {
func getTermios(fd int) (*Termios, error) {
termios := new(Termios)
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, fd, tcgets, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, uintptr(fd), tcgets, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
if err != 0 {
return nil, err
}
return termios, nil
}
func setTermios(fd uintptr, termios *Termios) error {
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, fd, tcsets, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
func setTermios(fd int, termios *Termios) error {
_, _, err := syscall.Syscall6(syscall.SYS_IOCTL, uintptr(fd), tcsets, uintptr(unsafe.Pointer(termios)), 0, 0, 0)
if err != 0 {
return err
}

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