

import argparse
import os
import re


lowerCAmelCase__		      =       """src/diffusers"""

# Pattern that looks at the indentation in a line.
lowerCAmelCase__		      =       re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
lowerCAmelCase__		      =       re.compile(R"""^\s*\"([^\"]+)\":""")
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
lowerCAmelCase__		      =       re.compile(R"""^\s*_import_structure\[\"([^\"]+)\"\]""")
# Pattern that matches `"key",` and puts `key` in group 0.
lowerCAmelCase__		      =       re.compile(R"""^\s*\"([^\"]+)\",\s*$""")
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
lowerCAmelCase__		      =       re.compile(R"""\[([^\]]+)\]""")



def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							List[Any]					)	->					List[str]:




				'''simple docstring'''





				A__						=	_re_indent.search(SCREAMING_SNAKE_CASE_					)
				return "" if search is None else search.groups()[0]



def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							int		,				SCREAMING_SNAKE_CASE_:							Dict=""		,				SCREAMING_SNAKE_CASE_:							List[str]=None		,				SCREAMING_SNAKE_CASE_:							List[str]=None					)	->					int:




				'''simple docstring'''





				A__						=	0
				A__						=	code.split("\n"					)
				if start_prompt is not None:
								while not lines[index].startswith(SCREAMING_SNAKE_CASE_					):
												index += 1
								A__						=	["\n".join(lines[:index]					)]
				else:
								A__						=	[]

				# We split into blocks until we get to the `end_prompt` (or the end of the block).
				A__						=	[lines[index]]
				index += 1
				while index < len(SCREAMING_SNAKE_CASE_					) and (end_prompt is None or not lines[index].startswith(SCREAMING_SNAKE_CASE_					)):
								if len(lines[index]					) > 0 and get_indent(lines[index]					) == indent_level:
												if len(SCREAMING_SNAKE_CASE_					) > 0 and get_indent(current_block[-1]					).startswith(indent_level + " "					):
																current_block.append(lines[index]					)
																blocks.append("\n".join(SCREAMING_SNAKE_CASE_					)					)
																if index < len(SCREAMING_SNAKE_CASE_					) - 1:
																				A__						=	[lines[index + 1]]
																				index += 1
																else:
																				A__						=	[]
												else:
																blocks.append("\n".join(SCREAMING_SNAKE_CASE_					)					)
																A__						=	[lines[index]]
								else:
												current_block.append(lines[index]					)
								index += 1

				# Adds current block if it's nonempty.
				if len(SCREAMING_SNAKE_CASE_					) > 0:
								blocks.append("\n".join(SCREAMING_SNAKE_CASE_					)					)

				# Add final block after end_prompt if provided.
				if end_prompt is not None and index < len(SCREAMING_SNAKE_CASE_					):
								blocks.append("\n".join(lines[index:]					)					)

				return blocks



def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							Union[str, Any]					)	->					int:




				'''simple docstring'''





				def _inner(SCREAMING_SNAKE_CASE_:							List[Any]					):
								return key(SCREAMING_SNAKE_CASE_					).lower().replace("_"		,				""					)

				return _inner



def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							int		,				SCREAMING_SNAKE_CASE_:							Tuple=None					)	->					int:




				'''simple docstring'''





				def noop(SCREAMING_SNAKE_CASE_:							str					):
								return x

				if key is None:
								A__						=	noop
				# Constants are all uppercase, they go first.
				A__						=	[obj for obj in objects if key(SCREAMING_SNAKE_CASE_					).isupper()]
				# Classes are not all uppercase but start with a capital, they go second.
				A__						=	[obj for obj in objects if key(SCREAMING_SNAKE_CASE_					)[0].isupper() and not key(SCREAMING_SNAKE_CASE_					).isupper()]
				# Functions begin with a lowercase, they go last.
				A__						=	[obj for obj in objects if not key(SCREAMING_SNAKE_CASE_					)[0].isupper()]

				A__						=	ignore_underscore(SCREAMING_SNAKE_CASE_					)
				return sorted(SCREAMING_SNAKE_CASE_		,				key=SCREAMING_SNAKE_CASE_					) + sorted(SCREAMING_SNAKE_CASE_		,				key=SCREAMING_SNAKE_CASE_					) + sorted(SCREAMING_SNAKE_CASE_		,				key=SCREAMING_SNAKE_CASE_					)



def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							Any					)	->					str:




				'''simple docstring'''





				def _replace(SCREAMING_SNAKE_CASE_:							Dict					):
								A__						=	match.groups()[0]
								if "," not in imports:
												return F'[{imports}]'
								A__						=	[part.strip().replace("\""		,				""					) for part in imports.split(","					)]
								# We will have a final empty element if the line finished with a comma.
								if len(keys[-1]					) == 0:
												A__						=	keys[:-1]
								return "[" + ", ".join([F'"{k}"' for k in sort_objects(SCREAMING_SNAKE_CASE_					)]					) + "]"

				A__						=	import_statement.split("\n"					)
				if len(SCREAMING_SNAKE_CASE_					) > 3:
								# Here we have to sort internal imports that are on several lines (one per name):
								# key: [
								#     "object1",
								#     "object2",
								#     ...
								# ]

								# We may have to ignore one or two lines on each side.
								A__						=	2 if lines[1].strip() == "[" else 1
								A__						=	[(i, _re_strip_line.search(SCREAMING_SNAKE_CASE_					).groups()[0]) for i, line in enumerate(lines[idx:-idx]					)]
								A__						=	sort_objects(SCREAMING_SNAKE_CASE_		,				key=lambda SCREAMING_SNAKE_CASE_					: x[1]					)
								A__						=	[lines[x[0] + idx] for x in sorted_indices]
								return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]					)
				elif len(SCREAMING_SNAKE_CASE_					) == 3:
								# Here we have to sort internal imports that are on one separate line:
								# key: [
								#     "object1", "object2", ...
								# ]
								if _re_bracket_content.search(lines[1]					) is not None:
												A__						=	_re_bracket_content.sub(_replace		,				lines[1]					)
								else:
												A__						=	[part.strip().replace("\""		,				""					) for part in lines[1].split(","					)]
												# We will have a final empty element if the line finished with a comma.
												if len(keys[-1]					) == 0:
																A__						=	keys[:-1]
												A__						=	get_indent(lines[1]					) + ", ".join([F'"{k}"' for k in sort_objects(SCREAMING_SNAKE_CASE_					)]					)
								return "\n".join(SCREAMING_SNAKE_CASE_					)
				else:
								# Finally we have to deal with imports fitting on one line
								A__						=	_re_bracket_content.sub(_replace		,				SCREAMING_SNAKE_CASE_					)
								return import_statement



def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							str		,				SCREAMING_SNAKE_CASE_:							Optional[Any]=True					)	->					List[Any]:




				'''simple docstring'''





				with open(SCREAMING_SNAKE_CASE_		,				"r"					) as f:
								A__						=	f.read()

				if "_import_structure" not in code:
								return

				# Blocks of indent level 0
				A__						=	split_code_in_indented_blocks(
				    SCREAMING_SNAKE_CASE_		,				start_prompt="_import_structure = {"		,				end_prompt="if TYPE_CHECKING:"					)

				# We ignore block 0 (everything until start_prompt) and the last block (everything after end_prompt).
				for block_idx in range(1		,				len(SCREAMING_SNAKE_CASE_					) - 1					):
								# Check if the block contains some `_import_structure`s thingy to sort.
								A__						=	main_blocks[block_idx]
								A__						=	block.split("\n"					)

								# Get to the start of the imports.
								A__						=	0
								while line_idx < len(SCREAMING_SNAKE_CASE_					) and "_import_structure" not in block_lines[line_idx]:
												# Skip dummy import blocks
												if "import dummy" in block_lines[line_idx]:
																A__						=	len(SCREAMING_SNAKE_CASE_					)
												else:
																line_idx += 1
								if line_idx >= len(SCREAMING_SNAKE_CASE_					):
												continue

								# Ignore beginning and last line: they don't contain anything.
								A__						=	"\n".join(block_lines[line_idx:-1]					)
								A__						=	get_indent(block_lines[1]					)
								# Slit the internal block into blocks of indent level 1.
								A__						=	split_code_in_indented_blocks(SCREAMING_SNAKE_CASE_		,				indent_level=SCREAMING_SNAKE_CASE_					)
								# We have two categories of import key: list or _import_structure[key].append/extend
								A__						=	_re_direct_key if "_import_structure" in block_lines[0] else _re_indirect_key
								# Grab the keys, but there is a trap: some lines are empty or just comments.
								A__						=	[(pattern.search(SCREAMING_SNAKE_CASE_					).groups()[0] if pattern.search(SCREAMING_SNAKE_CASE_					) is not None else None) for b in internal_blocks]
								# We only sort the lines with a key.
								A__						=	[(i, key) for i, key in enumerate(SCREAMING_SNAKE_CASE_					) if key is not None]
								A__						=	[x[0] for x in sorted(SCREAMING_SNAKE_CASE_		,				key=lambda SCREAMING_SNAKE_CASE_					: x[1]					)]

								# We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
								A__						=	0
								A__						=	[]
								for i in range(len(SCREAMING_SNAKE_CASE_					)					):
												if keys[i] is None:
																reordered_blocks.append(internal_blocks[i]					)
												else:
																A__						=	sort_objects_in_import(internal_blocks[sorted_indices[count]]					)
																reordered_blocks.append(SCREAMING_SNAKE_CASE_					)
																count += 1

        # And we put our main block back together with its first and last line.
								A__						=	"\n".join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]					)

				if code != "\n".join(SCREAMING_SNAKE_CASE_					):
								if check_only:
												return True
								else:
												print(F'Overwriting {file}.'					)
												with open(SCREAMING_SNAKE_CASE_		,				"w"					) as f:
																f.write("\n".join(SCREAMING_SNAKE_CASE_					)					)



def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							List[str]=True					)	->					Optional[Any]:




				'''simple docstring'''





				A__						=	[]
				for root, _, files in os.walk(SCREAMING_SNAKE_CASE_					):
								if "__init__.py" in files:
												A__						=	sort_imports(os.path.join(SCREAMING_SNAKE_CASE_		,				"__init__.py"					)		,				check_only=SCREAMING_SNAKE_CASE_					)
												if result:
																A__						=	[os.path.join(SCREAMING_SNAKE_CASE_		,				"__init__.py"					)]
				if len(SCREAMING_SNAKE_CASE_					) > 0:
								raise ValueError(F'Would overwrite {len(SCREAMING_SNAKE_CASE_					)} files, run `make style`.'					)


if __name__ == "__main__":
	lowerCAmelCase__		      =       argparse.ArgumentParser()
	parser.add_argument("""--check_only""", action="""store_true""", help="""Whether to only check or fix style.""")
	lowerCAmelCase__		      =       parser.parse_args()

	sort_imports_in_all_inits(check_only=args.check_only)





'''simple docstring'''

import argparse
import json
from pathlib import Path

import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging


logging.set_verbosity_info()
a_  :				int						= logging.get_logger(__name__)





def __snake_case					(      UpperCAmelCase_						:						List[Any]					,				UpperCAmelCase_						:						Tuple=False		):
 lowerCamelCase_      =  []
 for i in range(config.num_hidden_layers		):
  # encoder layers: output projection, 2 feedforward neural networks and 2 layernorms
  rename_keys.append((F'''blocks.{i}.norm1.weight''', F'''vit.encoder.layer.{i}.layernorm_before.weight''')		)
  rename_keys.append((F'''blocks.{i}.norm1.bias''', F'''vit.encoder.layer.{i}.layernorm_before.bias''')		)
  rename_keys.append((F'''blocks.{i}.attn.proj.weight''', F'''vit.encoder.layer.{i}.attention.output.dense.weight''')		)
  rename_keys.append((F'''blocks.{i}.attn.proj.bias''', F'''vit.encoder.layer.{i}.attention.output.dense.bias''')		)
  rename_keys.append((F'''blocks.{i}.norm2.weight''', F'''vit.encoder.layer.{i}.layernorm_after.weight''')		)
  rename_keys.append((F'''blocks.{i}.norm2.bias''', F'''vit.encoder.layer.{i}.layernorm_after.bias''')		)
  rename_keys.append((F'''blocks.{i}.mlp.fc1.weight''', F'''vit.encoder.layer.{i}.intermediate.dense.weight''')		)
  rename_keys.append((F'''blocks.{i}.mlp.fc1.bias''', F'''vit.encoder.layer.{i}.intermediate.dense.bias''')		)
  rename_keys.append((F'''blocks.{i}.mlp.fc2.weight''', F'''vit.encoder.layer.{i}.output.dense.weight''')		)
  rename_keys.append((F'''blocks.{i}.mlp.fc2.bias''', F'''vit.encoder.layer.{i}.output.dense.bias''')		)

 # projection layer + position embeddings
 rename_keys.extend(
     [
         ("cls_token", "vit.embeddings.cls_token"),
         ("patch_embed.proj.weight", "vit.embeddings.patch_embeddings.projection.weight"),
         ("patch_embed.proj.bias", "vit.embeddings.patch_embeddings.projection.bias"),
         ("pos_embed", "vit.embeddings.position_embeddings"),
     ]		)

 if base_model:
  # layernorm + pooler
  rename_keys.extend(
      [
          ("norm.weight", "layernorm.weight"),
          ("norm.bias", "layernorm.bias"),
          ("pre_logits.fc.weight", "pooler.dense.weight"),
          ("pre_logits.fc.bias", "pooler.dense.bias"),
      ]		)

  # if just the base model, we should remove "vit" from all keys that start with "vit"
  lowerCamelCase_      =  [(pair[0], pair[1][4:]) if pair[1].startswith("vit"		) else pair for pair in rename_keys]
 else:
  # layernorm + classification head
  rename_keys.extend(
      [
          ("norm.weight", "vit.layernorm.weight"),
          ("norm.bias", "vit.layernorm.bias"),
          ("head.weight", "classifier.weight"),
          ("head.bias", "classifier.bias"),
      ]		)

 return rename_keys





def __snake_case					(      UpperCAmelCase_						:						Optional[Any]					,				UpperCAmelCase_						:						Union[str, Any]					,				UpperCAmelCase_						:						Dict=False		):
 for i in range(config.num_hidden_layers		):
  if base_model:
   lowerCamelCase_      =  ""
  else:
   lowerCamelCase_      =  "vit."
  # read in weights + bias of input projection layer (in timm, this is a single matrix + bias)
  lowerCamelCase_      =  state_dict.pop(F'''blocks.{i}.attn.qkv.weight'''		)
  lowerCamelCase_      =  state_dict.pop(F'''blocks.{i}.attn.qkv.bias'''		)
  # next, add query, keys and values (in that order) to the state dict
  lowerCamelCase_      =  in_proj_weight[
      : config.hidden_size, :
  ]
  lowerCamelCase_      =  in_proj_bias[: config.hidden_size]
  lowerCamelCase_      =  in_proj_weight[
      config.hidden_size : config.hidden_size * 2, :
  ]
  lowerCamelCase_      =  in_proj_bias[
      config.hidden_size : config.hidden_size * 2
  ]
  lowerCamelCase_      =  in_proj_weight[
      -config.hidden_size :, :
  ]
  lowerCamelCase_      =  in_proj_bias[-config.hidden_size :]





def __snake_case					(      UpperCAmelCase_						:						int		):
 lowerCamelCase_      =  ["head.weight", "head.bias"]
 for k in ignore_keys:
  state_dict.pop(UpperCAmelCase_					,				UpperCAmelCase_		)





def __snake_case					(      UpperCAmelCase_						:						List[str]					,				UpperCAmelCase_						:						Union[str, Any]					,				UpperCAmelCase_						:						int		):
 lowerCamelCase_      =  dct.pop(UpperCAmelCase_		)
 lowerCamelCase_      =  val





def __snake_case					(      ):
 lowerCamelCase_      =  "http://images.cocodataset.org/val2017/000000039769.jpg"
 lowerCamelCase_      =  Image.open(requests.get(UpperCAmelCase_					,				stream=UpperCAmelCase_		).raw		)
 return im





@torch.no_grad()
def __snake_case					(      UpperCAmelCase_						:						Any					,				UpperCAmelCase_						:						Optional[int]		):
 lowerCamelCase_      =  ViTConfig()
 lowerCamelCase_      =  False
 # dataset (ImageNet-21k only or also fine-tuned on ImageNet 2012), patch_size and image_size
 if vit_name[-5:] == "in21k":
  lowerCamelCase_      =  True
  lowerCamelCase_      =  int(vit_name[-12:-10]		)
  lowerCamelCase_      =  int(vit_name[-9:-6]		)
 else:
  lowerCamelCase_      =  1000
  lowerCamelCase_      =  "huggingface/label-files"
  lowerCamelCase_      =  "imagenet-1k-id2label.json"
  lowerCamelCase_      =  json.load(open(hf_hub_download(UpperCAmelCase_					,				UpperCAmelCase_					,				repo_type="dataset"		)					,				"r"		)		)
  lowerCamelCase_      =  {int(UpperCAmelCase_		): v for k, v in idalabel.items()}
  lowerCamelCase_      =  idalabel
  lowerCamelCase_      =  {v: k for k, v in idalabel.items()}
  lowerCamelCase_      =  int(vit_name[-6:-4]		)
  lowerCamelCase_      =  int(vit_name[-3:]		)
 # size of the architecture
 if "deit" in vit_name:
  if vit_name[9:].startswith("tiny"		):
   lowerCamelCase_      =  192
   lowerCamelCase_      =  768
   lowerCamelCase_      =  12
   lowerCamelCase_      =  3
  elif vit_name[9:].startswith("small"		):
   lowerCamelCase_      =  384
   lowerCamelCase_      =  1536
   lowerCamelCase_      =  12
   lowerCamelCase_      =  6
  else:
   pass
 else:
  if vit_name[4:].startswith("small"		):
   lowerCamelCase_      =  768
   lowerCamelCase_      =  2304
   lowerCamelCase_      =  8
   lowerCamelCase_      =  8
  elif vit_name[4:].startswith("base"		):
   pass
  elif vit_name[4:].startswith("large"		):
   lowerCamelCase_      =  1024
   lowerCamelCase_      =  4096
   lowerCamelCase_      =  24
   lowerCamelCase_      =  16
  elif vit_name[4:].startswith("huge"		):
   lowerCamelCase_      =  1280
   lowerCamelCase_      =  5120
   lowerCamelCase_      =  32
   lowerCamelCase_      =  16

    # load original model from timm
 lowerCamelCase_      =  timm.create_model(UpperCAmelCase_					,				pretrained=UpperCAmelCase_		)
 timm_model.eval()

 # load state_dict of original model, remove and rename some keys
 lowerCamelCase_      =  timm_model.state_dict()
 if base_model:
  remove_classification_head_(UpperCAmelCase_		)
 lowerCamelCase_      =  create_rename_keys(UpperCAmelCase_					,				UpperCAmelCase_		)
 for src, dest in rename_keys:
  rename_key(UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_		)
 read_in_q_k_v(UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_		)

 # load HuggingFace model
 if vit_name[-5:] == "in21k":
  lowerCamelCase_      =  ViTModel(UpperCAmelCase_		).eval()
 else:
  lowerCamelCase_      =  ViTForImageClassification(UpperCAmelCase_		).eval()
 model.load_state_dict(UpperCAmelCase_		)

 # Check outputs on an image, prepared by ViTImageProcessor/DeiTImageProcessor
 if "deit" in vit_name:
  lowerCamelCase_      =  DeiTImageProcessor(size=config.image_size		)
 else:
  lowerCamelCase_      =  ViTImageProcessor(size=config.image_size		)
 lowerCamelCase_      =  image_processor(images=prepare_img()					,				return_tensors="pt"		)
 lowerCamelCase_      =  encoding["pixel_values"]
 lowerCamelCase_      =  model(UpperCAmelCase_		)

 if base_model:
  lowerCamelCase_      =  timm_model.forward_features(UpperCAmelCase_		)
  assert timm_pooled_output.shape == outputs.pooler_output.shape
  assert torch.allclose(UpperCAmelCase_					,				outputs.pooler_output					,				atol=1E-3		)
 else:
  lowerCamelCase_      =  timm_model(UpperCAmelCase_		)
  assert timm_logits.shape == outputs.logits.shape
  assert torch.allclose(UpperCAmelCase_					,				outputs.logits					,				atol=1E-3		)

 Path(UpperCAmelCase_		).mkdir(exist_ok=UpperCAmelCase_		)
 print(F'''Saving model {vit_name} to {pytorch_dump_folder_path}'''		)
 model.save_pretrained(UpperCAmelCase_		)
 print(F'''Saving image processor to {pytorch_dump_folder_path}'''		)
 image_processor.save_pretrained(UpperCAmelCase_		)


if __name__ == "__main__":
     a_  :				Union[str, Any]						= argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         """--vit_name""",
         default="""vit_base_patch16_224""",
         type=str,
         help="""Name of the ViT timm model you'd like to convert.""",
     )
     parser.add_argument(
         """--pytorch_dump_folder_path""", default=None, type=str, help="""Path to the output PyTorch model directory."""
     )

     a_  :				List[str]						= parser.parse_args()
     convert_vit_checkpoint(args.vit_name, args.pytorch_dump_folder_path)



