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refactor: packages (#249)

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This commit is contained in:
Aaron Pham
2023-08-22 08:55:46 -04:00
committed by GitHub
parent a964e659c1
commit 3ffb25a872
148 changed files with 2899 additions and 1937 deletions
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2
openllm-python/src/openllm/serialisation/transformers/__init__.py
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@@ -23,7 +23,7 @@ if t.TYPE_CHECKING:
import torch.nn
from bentoml._internal.models import ModelStore
from openllm._typing_compat import DictStrAny, M, T
from openllm_core._typing_compat import DictStrAny, M, T
else:
vllm = openllm.utils.LazyLoader("vllm", globals(), "vllm")
autogptq = openllm.utils.LazyLoader("autogptq", globals(), "auto_gptq")

8
openllm-python/src/openllm/serialisation/transformers/_helpers.py
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@@ -1,5 +1,5 @@
from __future__ import annotations
import copy, typing as t, openllm
import copy, typing as t, openllm_core, openllm
from bentoml._internal.models.model import ModelInfo, ModelSignature
from openllm.serialisation.constants import FRAMEWORK_TO_AUTOCLASS_MAPPING, HUB_ATTRS
@@ -7,8 +7,8 @@ if t.TYPE_CHECKING:
import torch, transformers, bentoml
from transformers.models.auto.auto_factory import _BaseAutoModelClass
from bentoml._internal.models.model import ModelSignaturesType
from openllm._typing_compat import DictStrAny, M, T
else: transformers, torch = openllm.utils.LazyLoader("transformers", globals(), "transformers"), openllm.utils.LazyLoader("torch", globals(), "torch")
from openllm_core._typing_compat import DictStrAny, M, T
else: transformers, torch = openllm_core.utils.LazyLoader("transformers", globals(), "transformers"), openllm_core.utils.LazyLoader("torch", globals(), "torch")
_object_setattr = object.__setattr__
@@ -33,7 +33,7 @@ def process_config(model_id: str, trust_remote_code: bool, **attrs: t.Any) -> tu
return config, hub_attrs, attrs
def infer_tokenizers_from_llm(__llm: openllm.LLM[t.Any, T], /) -> T:
__cls = getattr(transformers, openllm.utils.first_not_none(__llm.config["tokenizer_class"], default="AutoTokenizer"), None)
__cls = getattr(transformers, openllm_core.utils.first_not_none(__llm.config["tokenizer_class"], default="AutoTokenizer"), None)
if __cls is None: raise ValueError(f"Cannot infer correct tokenizer class for {__llm}. Make sure to unset `tokenizer_class`")
return __cls

2
openllm-python/src/openllm/serialisation/transformers/weights.py
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@@ -3,7 +3,7 @@ import typing as t, attr
from huggingface_hub import HfApi
if t.TYPE_CHECKING:
import openllm
from openllm._typing_compat import M, T
from openllm_core._typing_compat import M, T
def has_safetensors_weights(model_id: str, revision: str | None = None) -> bool: return any(s.rfilename.endswith(".safetensors") for s in HfApi().model_info(model_id, revision=revision).siblings)
@attr.define(slots=True)