



import argparse

import torch
from safetensors.torch import load_file

from diffusers import StableDiffusionPipeline



def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  ):
   lowercase__					  =				StableDiffusionPipeline.from_pretrained(__A						,  torch_dtype=torch.floataa  )

   # load LoRA weight from .safetensors
   lowercase__					  =				load_file(__A  )

   lowercase__					  =				[]

   # directly update weight in diffusers model
   for key in state_dict:
      # it is suggested to print out the key, it usually will be something like below
      # "lora_te_text_model_encoder_layers_0_self_attn_k_proj.lora_down.weight"

      # as we have set the alpha beforehand, so just skip
      if ".alpha" in key or key in visited:
         continue

      if "text" in key:
         lowercase__					  =				key.split("."  )[0].split(LORA_PREFIX_TEXT_ENCODER + "_"  )[-1].split("_"  )
         lowercase__					  =				pipeline.text_encoder
      else:
         lowercase__					  =				key.split("."  )[0].split(LORA_PREFIX_UNET + "_"  )[-1].split("_"  )
         lowercase__					  =				pipeline.unet

      # find the target layer
      lowercase__					  =				layer_infos.pop(0  )
      while len(__A  ) > -1:
         try:
            lowercase__					  =				curr_layer.__getattr__(__A  )
            if len(__A  ) > 0:
               lowercase__					  =				layer_infos.pop(0  )
            elif len(__A  ) == 0:
               break
         except Exception:
            if len(__A  ) > 0:
               temp_name += "_" + layer_infos.pop(0  )
            else:
               lowercase__					  =				layer_infos.pop(0  )

      lowercase__					  =				[]
      if "lora_down" in key:
         pair_keys.append(key.replace("lora_down"						,  "lora_up"  )  )
         pair_keys.append(__A  )
      else:
         pair_keys.append(__A  )
         pair_keys.append(key.replace("lora_up"						,  "lora_down"  )  )

      # update weight
      if len(state_dict[pair_keys[0]].shape  ) == 4:
         lowercase__					  =				state_dict[pair_keys[0]].squeeze(3  ).squeeze(2  ).to(torch.floataa  )
         lowercase__					  =				state_dict[pair_keys[1]].squeeze(3  ).squeeze(2  ).to(torch.floataa  )
         curr_layer.weight.data += alpha * torch.mm(__A						,  __A  ).unsqueeze(2  ).unsqueeze(3  )
      else:
         lowercase__					  =				state_dict[pair_keys[0]].to(torch.floataa  )
         lowercase__					  =				state_dict[pair_keys[1]].to(torch.floataa  )
         curr_layer.weight.data += alpha * torch.mm(__A						,  __A  )

      # update visited list
      for item in pair_keys:
         visited.append(__A  )

   return pipeline


if __name__ == "__main__":
       lowercase_								=     argparse.ArgumentParser()

       parser.add_argument(
           """--base_model_path""", default=None, type=str, required=True, help="""Path to the base model in diffusers format."""
       )
       parser.add_argument(
           """--checkpoint_path""", default=None, type=str, required=True, help="""Path to the checkpoint to convert."""
       )
       parser.add_argument("""--dump_path""", default=None, type=str, required=True, help="""Path to the output model.""")
       parser.add_argument(
           """--lora_prefix_unet""", default="""lora_unet""", type=str, help="""The prefix of UNet weight in safetensors"""
       )
       parser.add_argument(
           """--lora_prefix_text_encoder""",
           default="""lora_te""",
           type=str,
           help="""The prefix of text encoder weight in safetensors""",
       )
       parser.add_argument("""--alpha""", default=0.75, type=float, help="""The merging ratio in W = W0 + alpha * deltaW""")
       parser.add_argument(
           """--to_safetensors""", action="""store_true""", help="""Whether to store pipeline in safetensors format or not."""
       )
       parser.add_argument("""--device""", type=str, help="""Device to use (e.g. cpu, cuda:0, cuda:1, etc.)""")

       lowercase_								=     parser.parse_args()

       lowercase_								=     args.base_model_path
       lowercase_								=     args.checkpoint_path
       lowercase_								=     args.dump_path
       lowercase_								=     args.lora_prefix_unet
       lowercase_								=     args.lora_prefix_text_encoder
       lowercase_								=     args.alpha

       lowercase_								=     convert(base_model_path, checkpoint_path, lora_prefix_unet, lora_prefix_text_encoder, alpha)

       lowercase_								=     pipe.to(args.device)
       pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)









# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser



def __lowerCAmelCase (     ):
			lowercase__					  =				ArgumentParser("Accelerate CLI tool"						,  usage="accelerate <command> [<args>]"						,  allow_abbrev=SCREAMING_SNAKE_CASE_  )
			lowercase__					  =				parser.add_subparsers(help="accelerate command helpers"  )

			# Register commands
			get_config_parser(subparsers=SCREAMING_SNAKE_CASE_  )
			env_command_parser(subparsers=SCREAMING_SNAKE_CASE_  )
			launch_command_parser(subparsers=SCREAMING_SNAKE_CASE_  )
			tpu_command_parser(subparsers=SCREAMING_SNAKE_CASE_  )
			test_command_parser(subparsers=SCREAMING_SNAKE_CASE_  )

			# Let's go
			lowercase__					  =				parser.parse_args()

			if not hasattr(SCREAMING_SNAKE_CASE_						,  "func"  ):
						parser.print_help()
						exit(1  )

			# Run
			args.func(SCREAMING_SNAKE_CASE_  )


if __name__ == "__main__":
							main()




