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[single file] enable telemetry for single file loading when using GGUF. (#11284)
* enable telemetry for single file loading when using GGUF. * quality
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@@ -21,6 +21,7 @@ import torch
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from huggingface_hub.utils import validate_hf_hub_args
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from typing_extensions import Self
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from .. import __version__
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from ..quantizers import DiffusersAutoQuantizer
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from ..utils import deprecate, is_accelerate_available, logging
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from .single_file_utils import (
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@@ -260,6 +261,11 @@ class FromOriginalModelMixin:
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device = kwargs.pop("device", None)
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disable_mmap = kwargs.pop("disable_mmap", False)
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user_agent = {"diffusers": __version__, "file_type": "single_file", "framework": "pytorch"}
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# In order to ensure popular quantization methods are supported. Can be disable with `disable_telemetry`
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if quantization_config is not None:
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user_agent["quant"] = quantization_config.quant_method.value
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if torch_dtype is not None and not isinstance(torch_dtype, torch.dtype):
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torch_dtype = torch.float32
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logger.warning(
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@@ -278,6 +284,7 @@ class FromOriginalModelMixin:
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local_files_only=local_files_only,
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revision=revision,
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disable_mmap=disable_mmap,
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user_agent=user_agent,
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)
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if quantization_config is not None:
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hf_quantizer = DiffusersAutoQuantizer.from_config(quantization_config)
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@@ -405,13 +405,16 @@ def load_single_file_checkpoint(
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local_files_only=None,
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revision=None,
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disable_mmap=False,
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user_agent=None,
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):
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if user_agent is None:
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user_agent = {"file_type": "single_file", "framework": "pytorch"}
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if os.path.isfile(pretrained_model_link_or_path):
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pretrained_model_link_or_path = pretrained_model_link_or_path
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else:
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repo_id, weights_name = _extract_repo_id_and_weights_name(pretrained_model_link_or_path)
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user_agent = {"file_type": "single_file", "framework": "pytorch"}
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pretrained_model_link_or_path = _get_model_file(
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repo_id,
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weights_name=weights_name,
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