"""simple docstring"""






import argparse
import json

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms

from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, PILImageResampling


def     UpperCAmelCase__ (       lowerCAmelCase__  :List[str]	)				->					List[Any]:
      '''simple docstring'''


      lowercase														=			[2, 2, 6, 2] if """tiny""" in model_name else [2, 2, 1_8, 2]
      lowercase														=			True if """large""" in model_name or """huge""" in model_name else False
      lowercase														=			True if """large""" in model_name or """huge""" in model_name else False
      lowercase														=			True if """large""" in model_name or """huge""" in model_name else False

      if "large" in model_name or "xlarge" in model_name or "huge" in model_name:
            if "fl3" in model_name:
                  lowercase														=			[3, 3, 3, 3]
                  lowercase														=			[5, 5, 5, 5]
            elif "fl4" in model_name:
                  lowercase														=			[4, 4, 4, 4]
                  lowercase														=			[3, 3, 3, 3]

      if "tiny" in model_name or "small" in model_name or "base" in model_name:
            lowercase														=			[3, 3, 3, 3]
            if "lrf" in model_name:
                  lowercase														=			[3, 3, 3, 3]
            else:
                  lowercase														=			[2, 2, 2, 2]

      if "tiny" in model_name:
            lowercase														=			9_6
      elif "small" in model_name:
            lowercase														=			9_6
      elif "base" in model_name:
            lowercase														=			1_2_8
      elif "large" in model_name:
            lowercase														=			1_9_2
      elif "xlarge" in model_name:
            lowercase														=			2_5_6
      elif "huge" in model_name:
            lowercase														=			3_5_2

      # set label information
      lowercase														=			"""huggingface/label-files"""
      if "large" in model_name or "huge" in model_name:
            lowercase														=			"""imagenet-22k-id2label.json"""
      else:
            lowercase														=			"""imagenet-1k-id2label.json"""

      lowercase														=			json.load(open(hf_hub_download(lowerCAmelCase__      ,	lowerCAmelCase__      ,	repo_type="""dataset"""	)      ,	"""r"""	)	)
      lowercase														=			{int(lowerCAmelCase__	): v for k, v in idalabel.items()}
      lowercase														=			{v: k for k, v in idalabel.items()}

      lowercase														=			FocalNetConfig(
          embed_dim=lowerCAmelCase__      ,	depths=lowerCAmelCase__      ,	focal_levels=lowerCAmelCase__      ,	focal_windows=lowerCAmelCase__      ,	use_conv_embed=lowerCAmelCase__      ,	idalabel=lowerCAmelCase__      ,	labelaid=lowerCAmelCase__      ,	use_post_layernorm=lowerCAmelCase__      ,	use_layerscale=lowerCAmelCase__      ,	)

      return config


def     UpperCAmelCase__ (       lowerCAmelCase__  :Dict	)				->					str:
      '''simple docstring'''


      if "patch_embed.proj" in name:
            lowercase														=			name.replace("""patch_embed.proj"""      ,	"""embeddings.patch_embeddings.projection"""	)
      if "patch_embed.norm" in name:
            lowercase														=			name.replace("""patch_embed.norm"""      ,	"""embeddings.norm"""	)
      if "layers" in name:
            lowercase														=			"""encoder.""" + name
      if "encoder.layers" in name:
            lowercase														=			name.replace("""encoder.layers"""      ,	"""encoder.stages"""	)
      if "downsample.proj" in name:
            lowercase														=			name.replace("""downsample.proj"""      ,	"""downsample.projection"""	)
      if "blocks" in name:
            lowercase														=			name.replace("""blocks"""      ,	"""layers"""	)
      if "modulation.f.weight" in name or "modulation.f.bias" in name:
            lowercase														=			name.replace("""modulation.f"""      ,	"""modulation.projection_in"""	)
      if "modulation.h.weight" in name or "modulation.h.bias" in name:
            lowercase														=			name.replace("""modulation.h"""      ,	"""modulation.projection_context"""	)
      if "modulation.proj.weight" in name or "modulation.proj.bias" in name:
            lowercase														=			name.replace("""modulation.proj"""      ,	"""modulation.projection_out"""	)

      if name == "norm.weight":
            lowercase														=			"""layernorm.weight"""
      if name == "norm.bias":
            lowercase														=			"""layernorm.bias"""

      if "head" in name:
            lowercase														=			name.replace("""head"""      ,	"""classifier"""	)
      else:
            lowercase														=			"""focalnet.""" + name

      return name


def     UpperCAmelCase__ (       lowerCAmelCase__  :Optional[int]      ,	lowerCAmelCase__  :str      ,	lowerCAmelCase__  :Optional[Any]=False	)				->					Any:
      '''simple docstring'''


      lowercase														=			{
          """focalnet-tiny""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_tiny_srf.pth""",
          """focalnet-tiny-lrf""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_tiny_lrf.pth""",
          """focalnet-small""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_small_srf.pth""",
          """focalnet-small-lrf""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_small_lrf.pth""",
          """focalnet-base""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_base_srf.pth""",
          """focalnet-base-lrf""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_base_lrf.pth""",
          """focalnet-large-lrf-fl3""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_large_lrf_384.pth""",
          """focalnet-large-lrf-fl4""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_large_lrf_384_fl4.pth""",
          """focalnet-xlarge-lrf-fl3""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_xlarge_lrf_384.pth""",
          """focalnet-xlarge-lrf-fl4""": """https://projects4jw.blob.core.windows.net/focalnet/release/classification/focalnet_xlarge_lrf_384_fl4.pth""",
      }
      # fmt: on

      lowercase														=			model_name_to_url[model_name]
      print("""Checkpoint URL: """      ,	lowerCAmelCase__	)
      lowercase														=			torch.hub.load_state_dict_from_url(lowerCAmelCase__      ,	map_location="""cpu"""	)["""model"""]

      # rename keys
      for key in state_dict.copy().keys():
            lowercase														=			state_dict.pop(lowerCAmelCase__	)
            lowercase														=			val

      lowercase														=			get_focalnet_config(lowerCAmelCase__	)
      lowercase														=			FocalNetForImageClassification(lowerCAmelCase__	)
      model.eval()

      # load state dict
      model.load_state_dict(lowerCAmelCase__	)

      # verify conversion
      lowercase														=			"""http://images.cocodataset.org/val2017/000000039769.jpg"""

      lowercase														=			BitImageProcessor(
          do_resize=lowerCAmelCase__      ,	size={"""shortest_edge""": 2_5_6}      ,	resample=PILImageResampling.BILINEAR      ,	do_center_crop=lowerCAmelCase__      ,	crop_size=2_2_4      ,	do_normalize=lowerCAmelCase__      ,	image_mean=lowerCAmelCase__      ,	image_std=lowerCAmelCase__      ,	)
      lowercase														=			Image.open(requests.get(lowerCAmelCase__      ,	stream=lowerCAmelCase__	).raw	)
      lowercase														=			processor(images=lowerCAmelCase__      ,	return_tensors="""pt"""	)

      lowercase														=			transforms.Compose(
          [
              transforms.Resize(2_5_6	),
              transforms.CenterCrop(2_2_4	),
              transforms.ToTensor(),
              transforms.Normalize(mean=[0.485, 0.456, 0.406]      ,	std=[0.229, 0.224, 0.225]	),
          ]	)

      lowercase														=			image_transforms(lowerCAmelCase__	).unsqueeze(0	)

      # verify pixel_values
      assert torch.allclose(inputs.pixel_values      ,	lowerCAmelCase__      ,	atol=1e-4	)

      lowercase														=			model(**lowerCAmelCase__	)

      lowercase														=			outputs.logits.argmax(-1	).item()
      print("""Predicted class:"""      ,	model.config.idalabel[predicted_class_idx]	)

      print("""First values of logits:"""      ,	outputs.logits[0, :3]	)

      if model_name == "focalnet-tiny":
            lowercase														=			torch.tensor([0.2_166, -0.4_368, 0.2_191]	)
      elif model_name == "focalnet-tiny-lrf":
            lowercase														=			torch.tensor([1.1_669, 0.0_125, -0.1_695]	)
      elif model_name == "focalnet-small":
            lowercase														=			torch.tensor([0.4_917, -0.0_430, 0.1_341]	)
      elif model_name == "focalnet-small-lrf":
            lowercase														=			torch.tensor([-0.2_588, -0.5_342, -0.2_331]	)
      elif model_name == "focalnet-base":
            lowercase														=			torch.tensor([-0.1_655, -0.4_090, -0.1_730]	)
      elif model_name == "focalnet-base-lrf":
            lowercase														=			torch.tensor([0.5_306, -0.0_483, -0.3_928]	)
      assert torch.allclose(outputs.logits[0, :3]      ,	lowerCAmelCase__      ,	atol=1e-4	)
      print("""Looks ok!"""	)

      if pytorch_dump_folder_path is not None:
            print(f'Saving model and processor of {model_name} to {pytorch_dump_folder_path}'	)
            model.save_pretrained(lowerCAmelCase__	)
            processor.save_pretrained(lowerCAmelCase__	)

      if push_to_hub:
            print(f'Pushing model and processor of {model_name} to the hub...'	)
            model.push_to_hub(f'{model_name}'	)
            processor.push_to_hub(f'{model_name}'	)


if __name__ == "__main__":
       __lowerCAmelCase					: Union[str, Any]        =argparse.ArgumentParser()
       # Required parameters
       parser.add_argument(
           """--model_name""",
           default="""focalnet-tiny""",
           type=str,
           help="""Name of the FocalNet 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 and processor to the hub.""",
       )

       __lowerCAmelCase					: str        =parser.parse_args()
       convert_focalnet_checkpoint(args.model_name, args.pytorch_dump_folder_path, args.push_to_hub)




"""simple docstring"""






# 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     UpperCAmelCase__ (       )				->					Tuple:
      '''simple docstring'''


      lowercase														=			ArgumentParser("""Accelerate CLI tool"""      ,	usage="""accelerate <command> [<args>]"""      ,	allow_abbrev=lowerCAmelCase__	)
      lowercase														=			parser.add_subparsers(help="""accelerate command helpers"""	)

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

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

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

      # Run
      args.func(lowerCAmelCase__	)


if __name__ == "__main__":
       main()



