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set max_shard_size to None for pipeline save_pretrained (#9447)

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* update default max_shard_size

* add None check to fix tests

---------

Co-authored-by: YiYi Xu <yixu310@gmail.com>
This commit is contained in:
Aryan
2024-09-18 01:45:18 +05:30
committed by GitHub
parent ba06124e4a
commit da18fbd54c
1 changed files with 4 additions and 3 deletions
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7
src/diffusers/pipelines/pipeline_utils.py
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@@ -189,7 +189,7 @@ class DiffusionPipeline(ConfigMixin, PushToHubMixin):
save_directory: Union[str, os.PathLike],
safe_serialization: bool = True,
variant: Optional[str] = None,
max_shard_size: Union[int, str] = "10GB",
max_shard_size: Optional[Union[int, str]] = None,
push_to_hub: bool = False,
**kwargs,
):
@@ -205,7 +205,7 @@ class DiffusionPipeline(ConfigMixin, PushToHubMixin):
Whether to save the model using `safetensors` or the traditional PyTorch way with `pickle`.
variant (`str`, *optional*):
If specified, weights are saved in the format `pytorch_model.<variant>.bin`.
max_shard_size (`int` or `str`, defaults to `"10GB"`):
max_shard_size (`int` or `str`, defaults to `None`):
The maximum size for a checkpoint before being sharded. Checkpoints shard will then be each of size
lower than this size. If expressed as a string, needs to be digits followed by a unit (like `"5GB"`).
If expressed as an integer, the unit is bytes. Note that this limit will be decreased after a certain
@@ -293,7 +293,8 @@ class DiffusionPipeline(ConfigMixin, PushToHubMixin):
save_kwargs["safe_serialization"] = safe_serialization
if save_method_accept_variant:
save_kwargs["variant"] = variant
if save_method_accept_max_shard_size:
if save_method_accept_max_shard_size and max_shard_size is not None:
# max_shard_size is expected to not be None in ModelMixin
save_kwargs["max_shard_size"] = max_shard_size
save_method(os.path.join(save_directory, pipeline_component_name), **save_kwargs)