

import argparse
import json
from pathlib import Path

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform

from transformers import BitConfig, BitForImageClassification, BitImageProcessor
from transformers.image_utils import PILImageResampling
from transformers.utils import logging


logging.set_verbosity_info()
lowerCAmelCase__	   = logging.get_logger(__name__)



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




				'''simple docstring'''





				A__        =			"huggingface/label-files"
				A__        =			"imagenet-1k-id2label.json"
				A__        =			json.load(open(hf_hub_download(SCREAMING_SNAKE_CASE_	,       SCREAMING_SNAKE_CASE_	,       repo_type="dataset"      )	,       "r"      )      )
				A__        =			{int(SCREAMING_SNAKE_CASE_      ): v for k, v in idalabel.items()}
				A__        =			{v: k for k, v in idalabel.items()}

				A__        =			"std_conv" if "bit" in model_name else False

				# note that when using BiT as backbone for ViT-hybrid checkpoints,
				# one needs to additionally set config.layer_type = "bottleneck", config.stem_type = "same",
				# config.conv_layer = "std_conv_same"
				A__        =			BitConfig(
				    conv_layer=SCREAMING_SNAKE_CASE_	,       num_labels=1_0_0_0	,       idalabel=SCREAMING_SNAKE_CASE_	,       labelaid=SCREAMING_SNAKE_CASE_	,       )

				return config



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							Optional[Any]      )			->      int:




				'''simple docstring'''





				if "stem.conv" in name:
								A__        =			name.replace("stem.conv"	,       "bit.embedder.convolution"      )
				if "blocks" in name:
								A__        =			name.replace("blocks"	,       "layers"      )
				if "head.fc" in name:
								A__        =			name.replace("head.fc"	,       "classifier.1"      )
				if name.startswith("norm"      ):
								A__        =			"bit." + name
				if "bit" not in name and "classifier" not in name:
								A__        =			"bit.encoder." + name

				return name



def 					lowerCAmelCase__							(	)			->      int:




				'''simple docstring'''





				A__        =			"http://images.cocodataset.org/val2017/000000039769.jpg"
				A__        =			Image.open(requests.get(SCREAMING_SNAKE_CASE_	,       stream=SCREAMING_SNAKE_CASE_      ).raw      )
				return im



@torch.no_grad()
def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							Tuple	,       SCREAMING_SNAKE_CASE_:							Optional[Any]	,       SCREAMING_SNAKE_CASE_:							Union[str, Any]=False      )			->      int:




				'''simple docstring'''





				A__        =			get_config(SCREAMING_SNAKE_CASE_      )

				# load original model from timm
				A__        =			create_model(SCREAMING_SNAKE_CASE_	,       pretrained=SCREAMING_SNAKE_CASE_      )
				timm_model.eval()

				# load state_dict of original model
				A__        =			timm_model.state_dict()
				for key in state_dict.copy().keys():
								A__        =			state_dict.pop(SCREAMING_SNAKE_CASE_      )
								A__        =			val.squeeze() if "head" in key else val

				# load HuggingFace model
				A__        =			BitForImageClassification(SCREAMING_SNAKE_CASE_      )
				model.eval()
				model.load_state_dict(SCREAMING_SNAKE_CASE_      )

				# create image processor
				A__        =			create_transform(**resolve_data_config({}	,       model=SCREAMING_SNAKE_CASE_      )      )
				A__        =			transform.transforms

				A__        =			{
				    "bilinear": PILImageResampling.BILINEAR,
				    "bicubic": PILImageResampling.BICUBIC,
				    "nearest": PILImageResampling.NEAREST,
				}

				A__        =			BitImageProcessor(
				    do_resize=SCREAMING_SNAKE_CASE_	,       size={"shortest_edge": timm_transforms[0].size}	,       resample=pillow_resamplings[timm_transforms[0].interpolation.value]	,       do_center_crop=SCREAMING_SNAKE_CASE_	,       crop_size={"height": timm_transforms[1].size[0], "width": timm_transforms[1].size[1]}	,       do_normalize=SCREAMING_SNAKE_CASE_	,       image_mean=timm_transforms[-1].mean.tolist()	,       image_std=timm_transforms[-1].std.tolist()	,       )

				A__        =			prepare_img()
				A__        =			transform(SCREAMING_SNAKE_CASE_      ).unsqueeze(0      )
				A__        =			processor(SCREAMING_SNAKE_CASE_	,       return_tensors="pt"      ).pixel_values

				# verify pixel values
				assert torch.allclose(SCREAMING_SNAKE_CASE_	,       SCREAMING_SNAKE_CASE_      )

				# verify logits
				with torch.no_grad():
								A__        =			model(SCREAMING_SNAKE_CASE_      )
								A__        =			outputs.logits

				print("Logits:"	,       logits[0, :3]      )
				print("Predicted class:"	,       model.config.idalabel[logits.argmax(-1      ).item()]      )
				A__        =			timm_model(SCREAMING_SNAKE_CASE_      )
				assert timm_logits.shape == outputs.logits.shape
				assert torch.allclose(SCREAMING_SNAKE_CASE_	,       outputs.logits	,       atol=1e-3      )
				print("Looks ok!"      )

				if pytorch_dump_folder_path is not None:
								Path(SCREAMING_SNAKE_CASE_      ).mkdir(exist_ok=SCREAMING_SNAKE_CASE_      )
								print(F'Saving model {model_name} and processor to {pytorch_dump_folder_path}'      )
								model.save_pretrained(SCREAMING_SNAKE_CASE_      )
								processor.save_pretrained(SCREAMING_SNAKE_CASE_      )

				if push_to_hub:
								print(F'Pushing model {model_name} and processor to the hub'      )
								model.push_to_hub(F'ybelkada/{model_name}'      )
								processor.push_to_hub(F'ybelkada/{model_name}'      )


if __name__ == "__main__":
	lowerCAmelCase__	   = argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    """--model_name""",
	    default="""resnetv2_50x1_bitm""",
	    type=str,
	    help="""Name of the BiT 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."""
	)
	parser.add_argument(
	    """--push_to_hub""",
	    action="""store_true""",
	    help="""Whether to push the model to the hub.""",
	)

	lowerCAmelCase__	   = parser.parse_args()
	convert_bit_checkpoint(args.model_name, args.pytorch_dump_folder_path, args.push_to_hub)




import collections
import importlib.util
import os
import re
from pathlib import Path


lowerCAmelCase__	   = """src/transformers"""


# Matches is_xxx_available()
lowerCAmelCase__	   = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase__	   = re.compile(R"""^_import_structure\s+=\s+\{([^\}]+)\}""")
# Catches a line with a key-values pattern: "bla": ["foo", "bar"]
lowerCAmelCase__	   = re.compile(R"""\s+\"\S*\":\s+\[([^\]]*)\]""")
# Catches a line if not is_foo_available
lowerCAmelCase__	   = re.compile(R"""^\s*if\s+not\s+is\_[a-z_]*\_available\(\)""")
# Catches a line _import_struct["bla"].append("foo")
lowerCAmelCase__	   = re.compile(R"""^\s*_import_structure\[\"\S*\"\]\.append\(\"(\S*)\"\)""")
# Catches a line _import_struct["bla"].extend(["foo", "bar"]) or _import_struct["bla"] = ["foo", "bar"]
lowerCAmelCase__	   = re.compile(R"""^\s*_import_structure\[\S*\](?:\.extend\(|\s*=\s+)\[([^\]]*)\]""")
# Catches a line with an object between quotes and a comma:     "MyModel",
lowerCAmelCase__	   = re.compile("""^\s+\"([^\"]+)\",""")
# Catches a line with objects between brackets only:    ["foo", "bar"],
lowerCAmelCase__	   = re.compile("""^\s+\[([^\]]+)\]""")
# Catches a line with from foo import bar, bla, boo
lowerCAmelCase__	   = re.compile(R"""\s+from\s+\S*\s+import\s+([^\(\s].*)\n""")
# Catches a line with try:
lowerCAmelCase__	   = re.compile(R"""^\s*try:""")
# Catches a line with else:
lowerCAmelCase__	   = re.compile(R"""^\s*else:""")



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							Any      )			->      int:




				'''simple docstring'''





				if _re_test_backend.search(SCREAMING_SNAKE_CASE_      ) is None:
								return None
				A__        =			[b[0] for b in _re_backend.findall(SCREAMING_SNAKE_CASE_      )]
				backends.sort()
				return "_and_".join(SCREAMING_SNAKE_CASE_      )



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




				'''simple docstring'''





				with open(SCREAMING_SNAKE_CASE_	,       "r"	,       encoding="utf-8"	,       newline="\n"      ) as f:
								A__        =			f.readlines()

				A__        =			0
				while line_index < len(SCREAMING_SNAKE_CASE_      ) and not lines[line_index].startswith("_import_structure = {"      ):
								line_index += 1

				# If this is a traditional init, just return.
				if line_index >= len(SCREAMING_SNAKE_CASE_      ):
								return None

				# First grab the objects without a specific backend in _import_structure
				A__        =			[]
				while not lines[line_index].startswith("if TYPE_CHECKING"      ) and find_backend(lines[line_index]      ) is None:
								A__        =			lines[line_index]
								# If we have everything on a single line, let's deal with it.
								if _re_one_line_import_struct.search(SCREAMING_SNAKE_CASE_      ):
												A__        =			_re_one_line_import_struct.search(SCREAMING_SNAKE_CASE_      ).groups()[0]
												A__        =			re.findall("\[([^\]]+)\]"	,       SCREAMING_SNAKE_CASE_      )
												for imp in imports:
																objects.extend([obj[1:-1] for obj in imp.split(", "      )]      )
												line_index += 1
												continue
								A__        =			_re_import_struct_key_value.search(SCREAMING_SNAKE_CASE_      )
								if single_line_import_search is not None:
												A__        =			[obj[1:-1] for obj in single_line_import_search.groups()[0].split(", "      ) if len(SCREAMING_SNAKE_CASE_      ) > 0]
												objects.extend(SCREAMING_SNAKE_CASE_      )
								elif line.startswith(" " * 8 + "\""      ):
												objects.append(line[9:-3]      )
								line_index += 1

				A__        =			{"none": objects}
				# Let's continue with backend-specific objects in _import_structure
				while not lines[line_index].startswith("if TYPE_CHECKING"      ):
								# If the line is an if not is_backend_available, we grab all objects associated.
								A__        =			find_backend(lines[line_index]      )
								# Check if the backend declaration is inside a try block:
								if _re_try.search(lines[line_index - 1]      ) is None:
												A__        =			None

								if backend is not None:
												line_index += 1

												# Scroll until we hit the else block of try-except-else
												while _re_else.search(lines[line_index]      ) is None:
																line_index += 1

												line_index += 1

												A__        =			[]
												# Until we unindent, add backend objects to the list
												while len(lines[line_index]      ) <= 1 or lines[line_index].startswith(" " * 4      ):
																A__        =			lines[line_index]
																if _re_import_struct_add_one.search(SCREAMING_SNAKE_CASE_      ) is not None:
																				objects.append(_re_import_struct_add_one.search(SCREAMING_SNAKE_CASE_      ).groups()[0]      )
																elif _re_import_struct_add_many.search(SCREAMING_SNAKE_CASE_      ) is not None:
																				A__        =			_re_import_struct_add_many.search(SCREAMING_SNAKE_CASE_      ).groups()[0].split(", "      )
																				A__        =			[obj[1:-1] for obj in imports if len(SCREAMING_SNAKE_CASE_      ) > 0]
																				objects.extend(SCREAMING_SNAKE_CASE_      )
																elif _re_between_brackets.search(SCREAMING_SNAKE_CASE_      ) is not None:
																				A__        =			_re_between_brackets.search(SCREAMING_SNAKE_CASE_      ).groups()[0].split(", "      )
																				A__        =			[obj[1:-1] for obj in imports if len(SCREAMING_SNAKE_CASE_      ) > 0]
																				objects.extend(SCREAMING_SNAKE_CASE_      )
																elif _re_quote_object.search(SCREAMING_SNAKE_CASE_      ) is not None:
																				objects.append(_re_quote_object.search(SCREAMING_SNAKE_CASE_      ).groups()[0]      )
																elif line.startswith(" " * 8 + "\""      ):
																				objects.append(line[9:-3]      )
																elif line.startswith(" " * 1_2 + "\""      ):
																				objects.append(line[1_3:-3]      )
																line_index += 1

												A__        =			objects
								else:
												line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
				A__        =			[]
				while (
				    line_index < len(SCREAMING_SNAKE_CASE_      )
				    and find_backend(lines[line_index]      ) is None
				    and not lines[line_index].startswith("else"      )
				):
								A__        =			lines[line_index]
								A__        =			_re_import.search(SCREAMING_SNAKE_CASE_      )
								if single_line_import_search is not None:
												objects.extend(single_line_import_search.groups()[0].split(", "      )      )
								elif line.startswith(" " * 8      ):
												objects.append(line[8:-2]      )
								line_index += 1

				A__        =			{"none": objects}
				# Let's continue with backend-specific objects
				while line_index < len(SCREAMING_SNAKE_CASE_      ):
								# If the line is an if is_backend_available, we grab all objects associated.
								A__        =			find_backend(lines[line_index]      )
								# Check if the backend declaration is inside a try block:
								if _re_try.search(lines[line_index - 1]      ) is None:
												A__        =			None

								if backend is not None:
												line_index += 1

												# Scroll until we hit the else block of try-except-else
												while _re_else.search(lines[line_index]      ) is None:
																line_index += 1

												line_index += 1

												A__        =			[]
												# Until we unindent, add backend objects to the list
												while len(lines[line_index]      ) <= 1 or lines[line_index].startswith(" " * 8      ):
																A__        =			lines[line_index]
																A__        =			_re_import.search(SCREAMING_SNAKE_CASE_      )
																if single_line_import_search is not None:
																				objects.extend(single_line_import_search.groups()[0].split(", "      )      )
																elif line.startswith(" " * 1_2      ):
																				objects.append(line[1_2:-2]      )
																line_index += 1

												A__        =			objects
								else:
												line_index += 1

				return import_dict_objects, type_hint_objects



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							Dict	,       SCREAMING_SNAKE_CASE_:							List[Any]      )			->      Optional[int]:




				'''simple docstring'''





				def find_duplicates(SCREAMING_SNAKE_CASE_:							str      ):
								return [k for k, v in collections.Counter(SCREAMING_SNAKE_CASE_      ).items() if v > 1]

				if list(import_dict_objects.keys()      ) != list(type_hint_objects.keys()      ):
								return ["Both sides of the init do not have the same backends!"]

				A__        =			[]
				for key in import_dict_objects.keys():
								A__        =			find_duplicates(import_dict_objects[key]      )
								if duplicate_imports:
												errors.append(F'Duplicate _import_structure definitions for: {duplicate_imports}'      )
								A__        =			find_duplicates(type_hint_objects[key]      )
								if duplicate_type_hints:
												errors.append(F'Duplicate TYPE_CHECKING objects for: {duplicate_type_hints}'      )

								if sorted(set(import_dict_objects[key]      )      ) != sorted(set(type_hint_objects[key]      )      ):
												A__        =			"base imports" if key == "none" else F'{key} backend'
												errors.append(F'Differences for {name}:'      )
												for a in type_hint_objects[key]:
																if a not in import_dict_objects[key]:
																				errors.append(F'  {a} in TYPE_HINT but not in _import_structure.'      )
												for a in import_dict_objects[key]:
																if a not in type_hint_objects[key]:
																				errors.append(F'  {a} in _import_structure but not in TYPE_HINT.'      )
				return errors



def 					lowerCAmelCase__							(	)			->      Dict:




				'''simple docstring'''





				A__        =			[]
				for root, _, files in os.walk(SCREAMING_SNAKE_CASE_      ):
								if "__init__.py" in files:
												A__        =			os.path.join(SCREAMING_SNAKE_CASE_	,       "__init__.py"      )
												A__        =			parse_init(SCREAMING_SNAKE_CASE_      )
												if objects is not None:
																A__        =			analyze_results(*SCREAMING_SNAKE_CASE_      )
																if len(SCREAMING_SNAKE_CASE_      ) > 0:
																				A__        =			F'Problem in {fname}, both halves do not define the same objects.\n{errors[0]}'
																				failures.append("\n".join(SCREAMING_SNAKE_CASE_      )      )
				if len(SCREAMING_SNAKE_CASE_      ) > 0:
								raise ValueError("\n\n".join(SCREAMING_SNAKE_CASE_      )      )



def 					lowerCAmelCase__							(	)			->      Optional[Any]:




				'''simple docstring'''





				A__        =			[]
				for path, directories, files in os.walk(SCREAMING_SNAKE_CASE_      ):
								for folder in directories:
												# Ignore private modules
												if folder.startswith("_"      ):
																directories.remove(SCREAMING_SNAKE_CASE_      )
																continue
												# Ignore leftovers from branches (empty folders apart from pycache)
												if len(list((Path(SCREAMING_SNAKE_CASE_      ) / folder).glob("*.py"      )      )      ) == 0:
																continue
												A__        =			str((Path(SCREAMING_SNAKE_CASE_      ) / folder).relative_to(SCREAMING_SNAKE_CASE_      )      )
												A__        =			short_path.replace(os.path.sep	,       "."      )
												submodules.append(SCREAMING_SNAKE_CASE_      )
								for fname in files:
												if fname == "__init__.py":
																continue
												A__        =			str((Path(SCREAMING_SNAKE_CASE_      ) / fname).relative_to(SCREAMING_SNAKE_CASE_      )      )
												A__        =			short_path.replace(".py"	,       ""      ).replace(os.path.sep	,       "."      )
												if len(submodule.split("."      )      ) == 1:
																submodules.append(SCREAMING_SNAKE_CASE_      )
				return submodules


lowerCAmelCase__	   = [
    """convert_pytorch_checkpoint_to_tf2""",
    """modeling_flax_pytorch_utils""",
]



def 					lowerCAmelCase__							(	)			->      Optional[int]:




				'''simple docstring'''





				A__        =			importlib.util.spec_from_file_location(
				    "transformers"	,       os.path.join(SCREAMING_SNAKE_CASE_	,       "__init__.py"      )	,       submodule_search_locations=[PATH_TO_TRANSFORMERS]	,       )
				A__        =			spec.loader.load_module()

				A__        =			[
				    module
				    for module in get_transformers_submodules()
				    if module not in IGNORE_SUBMODULES and module not in transformers._import_structure.keys()
				]
				if len(SCREAMING_SNAKE_CASE_      ) > 0:
								A__        =			"\n".join(F'- {module}' for module in module_not_registered      )
								raise ValueError(
								    "The following submodules are not properly registered in the main init of Transformers:\n"
								    F'{list_of_modules}\n'
								    "Make sure they appear somewhere in the keys of `_import_structure` with an empty list as value."      )


if __name__ == "__main__":
	check_all_inits()
	check_submodules()

