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[LoRA] add an error message when dealing with _best_guess_weight_name ofline #6184

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Merged
sayakpaul merged 3 commits into from
Dec 16, 2023
Merged

[LoRA] add an error message when dealing with _best_guess_weight_name ofline #6184

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88b93c9
add an error message when dealing with _best_guess_weight_name ofline
sayakpaul Dec 15, 2023
d4772be
simplify condition
sayakpaul Dec 15, 2023
1ec9ab9
Merge branch 'main' into fix/lora-loading-offline
sayakpaul Dec 16, 2023
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14 changes: 11 additions & 3 deletions src/diffusers/loaders/lora.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@
import safetensors
import torch
from huggingface_hub import model_info
from huggingface_hub.constants import HF_HUB_OFFLINE
from huggingface_hub.utils import validate_hf_hub_args
from packaging import version
from torch import nn
Expand Down Expand Up @@ -229,7 +230,9 @@ def lora_state_dict(
# determine `weight_name`.
if weight_name is None:
weight_name = cls._best_guess_weight_name(
pretrained_model_name_or_path_or_dict, file_extension=".safetensors"
pretrained_model_name_or_path_or_dict,
file_extension=".safetensors",
local_files_only=local_files_only,
)
model_file = _get_model_file(
pretrained_model_name_or_path_or_dict,
Expand All @@ -255,7 +258,7 @@ def lora_state_dict(
if model_file is None:
if weight_name is None:
weight_name = cls._best_guess_weight_name(
pretrained_model_name_or_path_or_dict, file_extension=".bin"
pretrained_model_name_or_path_or_dict, file_extension=".bin", local_files_only=local_files_only
)
model_file = _get_model_file(
pretrained_model_name_or_path_or_dict,
Expand Down Expand Up @@ -294,7 +297,12 @@ def lora_state_dict(
return state_dict, network_alphas

@classmethod
def _best_guess_weight_name(cls, pretrained_model_name_or_path_or_dict, file_extension=".safetensors"):
def _best_guess_weight_name(
cls, pretrained_model_name_or_path_or_dict, file_extension=".safetensors", local_files_only=False
):
if local_files_only or HF_HUB_OFFLINE:
raise ValueError("When using the offline mode, you must specify a `weight_name`.")

targeted_files = []

if os.path.isfile(pretrained_model_name_or_path_or_dict):
Expand Down