

'''simple docstring'''

import argparse

import requests
import torch
from PIL import Image

from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel





def  A_	(			snake_case			):
  # vision encoder
  if "img_encoder.pos_embed" in name:
    SCREAMING_SNAKE_CASE:Dict       =       name.replace("img_encoder.pos_embed"   ,							"vision_model.embeddings.position_embeddings"			)
  if "img_encoder.patch_embed.proj" in name:
    SCREAMING_SNAKE_CASE:int       =       name.replace("img_encoder.patch_embed.proj"   ,							"vision_model.embeddings.patch_embeddings.projection"			)
  if "img_encoder.patch_embed.norm" in name:
    SCREAMING_SNAKE_CASE:Union[str, Any]       =       name.replace("img_encoder.patch_embed.norm"   ,							"vision_model.embeddings.layernorm"			)
  if "img_encoder.layers" in name:
    SCREAMING_SNAKE_CASE:List[str]       =       name.replace("img_encoder.layers"   ,							"vision_model.encoder.stages"			)
  if "blocks" in name and "res" not in name:
    SCREAMING_SNAKE_CASE:Optional[int]       =       name.replace("blocks"   ,							"layers"			)
  if "attn" in name and "pre_assign" not in name:
    SCREAMING_SNAKE_CASE:int       =       name.replace("attn"   ,							"self_attn"			)
  if "proj" in name and "self_attn" in name and "text" not in name:
    SCREAMING_SNAKE_CASE:Tuple       =       name.replace("proj"   ,							"out_proj"			)
  if "pre_assign_attn.attn.proj" in name:
    SCREAMING_SNAKE_CASE:str       =       name.replace("pre_assign_attn.attn.proj"   ,							"pre_assign_attn.attn.out_proj"			)
  if "norm1" in name:
    SCREAMING_SNAKE_CASE:Any       =       name.replace("norm1"   ,							"layer_norm1"			)
  if "norm2" in name and "pre_assign" not in name:
    SCREAMING_SNAKE_CASE:Union[str, Any]       =       name.replace("norm2"   ,							"layer_norm2"			)
  if "img_encoder.norm" in name:
    SCREAMING_SNAKE_CASE:Dict       =       name.replace("img_encoder.norm"   ,							"vision_model.layernorm"			)
  # text encoder
  if "text_encoder.token_embedding" in name:
    SCREAMING_SNAKE_CASE:Tuple       =       name.replace("text_encoder.token_embedding"   ,							"text_model.embeddings.token_embedding"			)
  if "text_encoder.positional_embedding" in name:
    SCREAMING_SNAKE_CASE:List[Any]       =       name.replace("text_encoder.positional_embedding"   ,							"text_model.embeddings.position_embedding.weight"			)
  if "text_encoder.transformer.resblocks." in name:
    SCREAMING_SNAKE_CASE:Any       =       name.replace("text_encoder.transformer.resblocks."   ,							"text_model.encoder.layers."			)
  if "ln_1" in name:
    SCREAMING_SNAKE_CASE:List[str]       =       name.replace("ln_1"   ,							"layer_norm1"			)
  if "ln_2" in name:
    SCREAMING_SNAKE_CASE:Optional[int]       =       name.replace("ln_2"   ,							"layer_norm2"			)
  if "c_fc" in name:
    SCREAMING_SNAKE_CASE:Optional[Any]       =       name.replace("c_fc"   ,							"fc1"			)
  if "c_proj" in name:
    SCREAMING_SNAKE_CASE:Optional[int]       =       name.replace("c_proj"   ,							"fc2"			)
  if "text_encoder" in name:
    SCREAMING_SNAKE_CASE:Dict       =       name.replace("text_encoder"   ,							"text_model"			)
  if "ln_final" in name:
    SCREAMING_SNAKE_CASE:Tuple       =       name.replace("ln_final"   ,							"final_layer_norm"			)
  # projection layers
  if "img_projector.linear_hidden." in name:
    SCREAMING_SNAKE_CASE:Tuple       =       name.replace("img_projector.linear_hidden."   ,							"visual_projection."			)
  if "img_projector.linear_out." in name:
    SCREAMING_SNAKE_CASE:Dict       =       name.replace("img_projector.linear_out."   ,							"visual_projection.3."			)
  if "text_projector.linear_hidden" in name:
    SCREAMING_SNAKE_CASE:str       =       name.replace("text_projector.linear_hidden"   ,							"text_projection"			)
  if "text_projector.linear_out" in name:
    SCREAMING_SNAKE_CASE:List[Any]       =       name.replace("text_projector.linear_out"   ,							"text_projection.3"			)

  return name





def  A_	(			snake_case   ,							snake_case			):
  for key in orig_state_dict.copy().keys():
    SCREAMING_SNAKE_CASE:Dict       =       orig_state_dict.pop(snake_case			)

    if "qkv" in key:
      # weights and biases of the key, value and query projections of vision encoder's attention layers require special treatment:
      # we need to split them up into separate matrices/vectors
      SCREAMING_SNAKE_CASE:List[Any]       =       key.split("."			)
      SCREAMING_SNAKE_CASE:Tuple       =       int(key_split[2]			), int(key_split[4]			)
      SCREAMING_SNAKE_CASE:Union[str, Any]       =       config.vision_config.hidden_size
      if "weight" in key:
        SCREAMING_SNAKE_CASE:int       =       val[:dim, :]
        SCREAMING_SNAKE_CASE:str       =       val[dim : dim * 2, :]
        SCREAMING_SNAKE_CASE:Optional[int]       =       val[-dim:, :]
      else:
        SCREAMING_SNAKE_CASE:Optional[Any]       =       val[:dim]
        SCREAMING_SNAKE_CASE:Union[str, Any]       =       val[dim : dim * 2]
        SCREAMING_SNAKE_CASE:Dict       =       val[-dim:]
    elif "in_proj" in key:
      # weights and biases of the key, value and query projections of text encoder's attention layers require special treatment:
      # we need to split them up into separate matrices/vectors
      SCREAMING_SNAKE_CASE:Tuple       =       key.split("."			)
      SCREAMING_SNAKE_CASE:List[str]       =       int(key_split[3]			)
      SCREAMING_SNAKE_CASE:int       =       config.text_config.hidden_size
      if "weight" in key:
        SCREAMING_SNAKE_CASE:str       =       val[:dim, :]
        SCREAMING_SNAKE_CASE:int       =       val[
            dim : dim * 2, :
        ]
        SCREAMING_SNAKE_CASE:int       =       val[-dim:, :]
      else:
        SCREAMING_SNAKE_CASE:Any       =       val[:dim]
        SCREAMING_SNAKE_CASE:Union[str, Any]       =       val[dim : dim * 2]
        SCREAMING_SNAKE_CASE:Tuple       =       val[-dim:]
    else:
      SCREAMING_SNAKE_CASE:Union[str, Any]       =       rename_key(snake_case			)
      # squeeze if necessary
      if (
          "text_projection.0" in new_name
          or "text_projection.3" in new_name
          or "visual_projection.0" in new_name
          or "visual_projection.3" in new_name
      ):
        SCREAMING_SNAKE_CASE:Dict       =       val.squeeze_()
      else:
        SCREAMING_SNAKE_CASE:Dict       =       val

  return orig_state_dict





def  A_	(			):
  SCREAMING_SNAKE_CASE:Dict       =       """http://images.cocodataset.org/val2017/000000039769.jpg"""
  SCREAMING_SNAKE_CASE:Optional[Any]       =       Image.open(requests.get(snake_case   ,							stream=snake_case			).raw			)
  return im





@torch.no_grad()
def  A_	(			snake_case   ,							snake_case   ,							snake_case="groupvit-gcc-yfcc"   ,							snake_case=False			):
  SCREAMING_SNAKE_CASE:Union[str, Any]       =       GroupViTConfig()
  SCREAMING_SNAKE_CASE:Any       =       GroupViTModel(snake_case			).eval()

  SCREAMING_SNAKE_CASE:str       =       torch.load(snake_case   ,							map_location="cpu"			)["""model"""]
  SCREAMING_SNAKE_CASE:Optional[int]       =       convert_state_dict(snake_case   ,							snake_case			)
  SCREAMING_SNAKE_CASE:Any       =       model.load_state_dict(snake_case   ,							strict=snake_case			)
  assert missing_keys == ["text_model.embeddings.position_ids"]
  assert (unexpected_keys == ["multi_label_logit_scale"]) or (len(snake_case			) == 0)

  # verify result
  SCREAMING_SNAKE_CASE:str       =       CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32"			)
  SCREAMING_SNAKE_CASE:Tuple       =       prepare_img()
  SCREAMING_SNAKE_CASE:Union[str, Any]       =       processor(text=["a photo of a cat", "a photo of a dog"]   ,							images=snake_case   ,							padding=snake_case   ,							return_tensors="pt"			)

  with torch.no_grad():
    SCREAMING_SNAKE_CASE:Optional[int]       =       model(**snake_case			)

  if model_name == "groupvit-gcc-yfcc":
    SCREAMING_SNAKE_CASE:Union[str, Any]       =       torch.tensor([[13.3523, 6.3629]]			)
  elif model_name == "groupvit-gcc-redcaps":
    SCREAMING_SNAKE_CASE:List[str]       =       torch.tensor([[16.1873, 8.6230]]			)
  else:
    raise ValueError(F'''Model name {model_name} not supported.'''			)
  assert torch.allclose(outputs.logits_per_image   ,							snake_case   ,							atol=1e-3			)

  processor.save_pretrained(snake_case			)
  model.save_pretrained(snake_case			)
  print("Successfully saved processor and model to"   ,							snake_case			)

  if push_to_hub:
    print("Pushing to the hub..."			)
    processor.push_to_hub(snake_case   ,							organization="nielsr"			)
    model.push_to_hub(snake_case   ,							organization="nielsr"			)


if __name__ == "__main__":
    A_							    =				argparse.ArgumentParser()
    parser.add_argument(
        "--pytorch_dump_folder_path", default=None, type=str, help="Path to dump the processor and PyTorch model."
    )
    parser.add_argument("--checkpoint_path", default=None, type=str, help="Path to GroupViT checkpoint")
    parser.add_argument(
        "--model_name",
        default="groupvit-gccy-fcc",
        type=str,
        help="Name of the model. Expecting either 'groupvit-gcc-yfcc' or 'groupvit-gcc-redcaps'",
    )
    parser.add_argument(
        "--push_to_hub",
        action="store_true",
        help="Whether or not to push the converted model and processor to the 🤗 hub using the provided `model_name`.",
    )
    A_							    =				parser.parse_args()

    convert_groupvit_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.model_name, args.push_to_hub)







"""simple docstring"""



import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)
class 						__UpperCAmelCase    (unittest.TestCase     ):







			'''simple docstring'''





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Dict								=			Vector([1, 2, 3]							)
										self.assertEqual(x.component(0							)   ,      1							)
										self.assertEqual(x.component(2							)   ,      3							)
										A__       :     List[Any]								=			Vector()





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     List[Any]								=			Vector([0, 0, 0, 0, 0, 1]							)
										self.assertEqual(str(snake_case_							)   ,      """(0,0,0,0,0,1)"""							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     List[Any]								=			Vector([1, 2, 3, 4]							)
										self.assertEqual(len(snake_case_							)   ,      4							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Any								=			Vector([1, 2]							)
										A__       :     Optional[int]								=			Vector([1, 2, 3, 4, 5]							)
										A__       :     Tuple								=			Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]							)
										A__       :     Dict								=			Vector([1, -1, 1, -1, 2, -3, 4, -5]							)
										self.assertAlmostEqual(x.euclidean_length()   ,      2.2_36   ,      3							)
										self.assertAlmostEqual(y.euclidean_length()   ,      7.4_16   ,      3							)
										self.assertEqual(z.euclidean_length()   ,      0							)
										self.assertAlmostEqual(w.euclidean_length()   ,      7.6_16   ,      3							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Union[str, Any]								=			Vector([1, 2, 3]							)
										A__       :     Any								=			Vector([1, 1, 1]							)
										self.assertEqual((x + y).component(0							)   ,      2							)
										self.assertEqual((x + y).component(1							)   ,      3							)
										self.assertEqual((x + y).component(2							)   ,      4							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[int]								=			Vector([1, 2, 3]							)
										A__       :     int								=			Vector([1, 1, 1]							)
										self.assertEqual((x - y).component(0							)   ,      0							)
										self.assertEqual((x - y).component(1							)   ,      1							)
										self.assertEqual((x - y).component(2							)   ,      2							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Tuple								=			Vector([1, 2, 3]							)
										A__       :     Any								=			Vector([2, -1, 4]							)  # for test of dot product
										A__       :     Optional[Any]								=			Vector([1, -2, -1]							)
										self.assertEqual(str(x * 3.0							)   ,      """(3.0,6.0,9.0)"""							)
										self.assertEqual((a * b)   ,      0							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										self.assertEqual(str(zero_vector(10							)							).count("""0"""							)   ,      10							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										self.assertEqual(str(unit_basis_vector(3   ,      1							)							)   ,      """(0,1,0)"""							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Union[str, Any]								=			Vector([1, 2, 3]							)
										A__       :     Tuple								=			Vector([1, 0, 1]							)
										self.assertEqual(str(axpy(2   ,      snake_case_   ,      snake_case_							)							)   ,      """(3,4,7)"""							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     int								=			Vector([1, 0, 0, 0, 0, 0]							)
										A__       :     List[str]								=			x.copy()
										self.assertEqual(str(snake_case_							)   ,      str(snake_case_							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     str								=			Vector([1, 0, 0]							)
										x.change_component(0   ,      0							)
										x.change_component(1   ,      1							)
										self.assertEqual(str(snake_case_							)   ,      """(0,1,0)"""							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     List[Any]								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										self.assertEqual("""|1,2,3|\n|2,4,5|\n|6,7,8|\n"""   ,      str(snake_case_							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Any								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										A__       :     Dict								=			[[-3, -14, -10], [-5, -10, -5], [-2, -1, 0]]
										for x in range(a.height()							):
																	for y in range(a.width()							):
																								self.assertEqual(minors[x][y]   ,      a.minor(snake_case_   ,      snake_case_							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[int]								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										A__       :     Union[str, Any]								=			[[-3, 14, -10], [5, -10, 5], [-2, 1, 0]]
										for x in range(a.height()							):
																	for y in range(a.width()							):
																								self.assertEqual(cofactors[x][y]   ,      a.cofactor(snake_case_   ,      snake_case_							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Any								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										self.assertEqual(-5   ,      a.determinant()							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[int]								=			Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]   ,      3   ,      3							)
										A__       :     int								=			Vector([1, 2, 3]							)
										self.assertEqual("""(14,32,50)"""   ,      str(a * x							)							)
										self.assertEqual("""|2,4,6|\n|8,10,12|\n|14,16,18|\n"""   ,      str(a * 2							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[Any]								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										a.change_component(0   ,      2   ,      5							)
										self.assertEqual("""|1,2,5|\n|2,4,5|\n|6,7,8|\n"""   ,      str(snake_case_							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Union[str, Any]								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										self.assertEqual(7   ,      a.component(2   ,      1							)   ,      0.01							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[Any]								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										A__       :     List[str]								=			Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]   ,      3   ,      3							)
										self.assertEqual("""|2,4,10|\n|4,8,10|\n|12,14,18|\n"""   ,      str(a + b							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     List[Any]								=			Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,      3   ,      3							)
										A__       :     Tuple								=			Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]   ,      3   ,      3							)
										self.assertEqual("""|0,0,-4|\n|0,0,0|\n|0,0,-2|\n"""   ,      str(a - b							)							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										self.assertEqual(
										    """|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n"""   ,      str(square_zero_matrix(5							)							)   ,      )


if __name__ == "__main__":
				unittest.main()





