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fix(models): save from local path

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Signed-off-by: aarnphm-ec2-dev <29749331+aarnphm@users.noreply.github.com>
This commit is contained in:
aarnphm-ec2-dev
2023-06-27 03:35:12 +00:00
parent 45b0ba3b7d
commit 5d4b8ab449
1 changed files with 20 additions and 14 deletions
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34
src/openllm/_llm.py
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@@ -114,10 +114,11 @@ TOKENIZER_PREFIX = "_tokenizer_"
def convert_transformers_model_name(name: str | None) -> str:
if name is None:
raise ValueError("'name' cannot be None")
if os.path.exists(os.path.dirname(name)):
name = os.path.basename(name)
logger.debug("Given name is a path, only returning the basename %s")
return name
if os.path.exists(os.path.dirname(os.path.abspath(name))):
resolved = os.path.basename(os.path.abspath(name))
logger.debug("Given name is a path, only returning the basename %s", resolved)
return resolved
return re.sub("[^a-zA-Z0-9]+", "-", name)
@@ -705,6 +706,7 @@ class LLM(LLMInterface[_M, _T], ReprMixin):
llm_config: The config to use for this LLM. Defaults to None. If not passed, OpenLLM
will use `config_class` to construct default configuration.
bettertransformer: Whether to use BetterTransformer with this model. Defaults to False.
openllm_model_version: Optional specific version for this given LLM. This is useful when saving from custom path.
*args: The args to be passed to the model.
**attrs: The kwargs to be passed to the model.
@@ -741,7 +743,7 @@ class LLM(LLMInterface[_M, _T], ReprMixin):
# NOTE: recast here for type safety
model_kwds, tokenizer_kwds = t.cast("tuple[dict[str, t.Any], dict[str, t.Any]]", self.__llm_init_kwargs__)
logger.debug(
"'%s' default kwargs for model: '%s', tokenizer: '%s'",
'\'%s\' default kwargs for model: "%s", tokenizer: "%s\'"',
self.__class__.__name__,
model_kwds,
tokenizer_kwds,
@@ -810,10 +812,10 @@ class LLM(LLMInterface[_M, _T], ReprMixin):
def __repr_args__(self) -> ReprArgs:
for k in self.__repr_keys__:
if k == 'config':
if k == "config":
yield k, self.config.model_dump(flatten=True)
else:
yield k ,getattr(self, k)
yield k, getattr(self, k)
@property
def model_id(self) -> str:
@@ -878,14 +880,18 @@ class LLM(LLMInterface[_M, _T], ReprMixin):
model_version = getattr(config, "_commit_hash", None)
if model_version is None:
if openllm_model_version is not None:
if openllm_model_version is None:
model_version = bentoml.Tag.from_taglike(name).make_new_version().version
logger.warning(
"Given %s from '%s' doesn't contain a commit hash, and 'openllm_model_version' is not given. "
"We will generate the tag without specific version.",
"Given %r from '%s' doesn't contain a commit hash, and 'openllm_model_version' is not given. "
"We will generate the tag without specific commit version (generated version: %s).",
config.__class__,
model_id,
model_version,
)
logger.warning(
"To ensure hermeticity, make sure to provide 'openllm_model_version' when creating 'openllm.LLM'."
)
model_version = bentoml.Tag.from_taglike(name).make_new_version().version
else:
logger.debug("Using %s for '%s' as model version", openllm_model_version, model_id)
model_version = openllm_model_version
@@ -910,7 +916,7 @@ class LLM(LLMInterface[_M, _T], ReprMixin):
"--implementation",
self.__llm_implementation__,
],
env=os.environ.copy()
env=os.environ.copy(),
)
# NOTE: This usually only concern BentoML devs.
pattern = r"^__tag__:[^:\n]+:[^:\n]+"
@@ -1181,7 +1187,7 @@ class LLM(LLMInterface[_M, _T], ReprMixin):
generate_iterator_sig = first_not_none(signatures.get("generate_iterator"), default=generate_iterator_sig)
class _Runnable(bentoml.Runnable):
SUPPORTED_RESOURCES = ("amd.com/gpu","nvidia.com/gpu", "cpu")
SUPPORTED_RESOURCES = ("amd.com/gpu", "nvidia.com/gpu", "cpu")
SUPPORTS_CPU_MULTI_THREADING = True
def __init__(__self: _Runnable):
@@ -1304,7 +1310,7 @@ class LLM(LLMInterface[_M, _T], ReprMixin):
if self.config["requires_gpu"]
else ("nvidia.com/gpu", "amd.com/gpu", "cpu"),
}
)
),
),
name=self.runner_name,
embedded=False,