

import unittest

from diffusers.models.unet_ad_blocks import *  # noqa F403
from diffusers.utils import torch_device

from .test_unet_blocks_common import UNetBlockTesterMixin



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Dict										=    DownBlockaD  # noqa F405
      UpperCamelCase_      :		Tuple										=    "down"



      def 						UpperCamelCase_		(      self				:    str		)   ->					Optional[int]:
        _snake_case						=							[-0.0232, -0.9869, 0.8054, -0.0637, -0.1688, -1.4264, 0.4470, -1.3394, 0.0904]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Tuple										=    ResnetDownsampleBlockaD  # noqa F405
      UpperCamelCase_      :		Union[str, Any]										=    "down"



      def 						UpperCamelCase_		(      self				:    Any		)   ->					Union[str, Any]:
        _snake_case						=							[0.0710, 0.2410, -0.7320, -1.0757, -1.1343, 0.3540, -0.0133, -0.2576, 0.0948]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		str										=    AttnDownBlockaD  # noqa F405
      UpperCamelCase_      :		List[str]										=    "down"



      def 						UpperCamelCase_		(      self				:    Any		)   ->					str:
        _snake_case						=							[0.0636, 0.8964, -0.6234, -1.0131, 0.0844, 0.4935, 0.3437, 0.0911, -0.2957]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Tuple										=    CrossAttnDownBlockaD  # noqa F405
      UpperCamelCase_      :		int										=    "down"



      def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					Union[str, Any]:
        _snake_case,					_snake_case						=							super().prepare_init_args_and_inputs_for_common()
        _snake_case						=							32
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    List[str]		)   ->					str:
        _snake_case						=							[0.2238, -0.7396, -0.2255, -0.3829, 0.1925, 1.1665, 0.0603, -0.7295, 0.1983]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Union[str, Any]										=    SimpleCrossAttnDownBlockaD  # noqa F405
      UpperCamelCase_      :		Optional[Any]										=    "down"



      @property
      def 						UpperCamelCase_		(      self				:    str		)   ->					int:
        return super().get_dummy_input(include_encoder_hidden_states=A__		)



      def 						UpperCamelCase_		(      self				:    List[Any]		)   ->					Any:
        _snake_case,					_snake_case						=							super().prepare_init_args_and_inputs_for_common()
        _snake_case						=							32
        return init_dict, inputs_dict







      @unittest.skipIf(torch_device == '''mps'''      , '''MPS result is not consistent'''		)
      def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					Dict:
        _snake_case						=							[0.7921, -0.0992, -0.1962, -0.7695, -0.4242, 0.7804, 0.4737, 0.2765, 0.3338]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		List[Any]										=    SkipDownBlockaD  # noqa F405
      UpperCamelCase_      :		List[Any]										=    "down"



      @property
      def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					List[str]:
        return super().get_dummy_input(include_skip_sample=A__		)







      def 						UpperCamelCase_		(      self				:    Tuple		)   ->					Dict:
        _snake_case						=							[-0.0845, -0.2087, -0.2465, 0.0971, 0.1900, -0.0484, 0.2664, 0.4179, 0.5069]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Dict										=    AttnSkipDownBlockaD  # noqa F405
      UpperCamelCase_      :		List[str]										=    "down"



      @property
      def 						UpperCamelCase_		(      self				:    Any		)   ->					Any:
        return super().get_dummy_input(include_skip_sample=A__		)







      def 						UpperCamelCase_		(      self				:    Tuple		)   ->					Optional[Any]:
        _snake_case						=							[0.5539, 0.1609, 0.4924, 0.0537, -0.1995, 0.4050, 0.0979, -0.2721, -0.0642]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Tuple										=    DownEncoderBlockaD  # noqa F405
      UpperCamelCase_      :		int										=    "down"



      @property
      def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					Dict:
        return super().get_dummy_input(include_temb=A__		)



      def 						UpperCamelCase_		(      self				:    int		)   ->					Optional[int]:
        _snake_case						=							{
            '''in_channels''': 32,
            '''out_channels''': 32,
        }
        _snake_case						=							self.dummy_input
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    Optional[Any]		)   ->					Union[str, Any]:
        _snake_case						=							[1.1102, 0.5302, 0.4872, -0.0023, -0.8042, 0.0483, -0.3489, -0.5632, 0.7626]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Optional[int]										=    AttnDownEncoderBlockaD  # noqa F405
      UpperCamelCase_      :		str										=    "down"



      @property
      def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					Optional[int]:
        return super().get_dummy_input(include_temb=A__		)



      def 						UpperCamelCase_		(      self				:    Tuple		)   ->					Tuple:
        _snake_case						=							{
            '''in_channels''': 32,
            '''out_channels''': 32,
        }
        _snake_case						=							self.dummy_input
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    List[str]		)   ->					Union[str, Any]:
        _snake_case						=							[0.8966, -0.1486, 0.8568, 0.8141, -0.9046, -0.1342, -0.0972, -0.7417, 0.1538]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		str										=    UNetMidBlockaD  # noqa F405
      UpperCamelCase_      :		Optional[Any]										=    "mid"



      def 						UpperCamelCase_		(      self				:    Any		)   ->					List[Any]:
        _snake_case						=							{
            '''in_channels''': 32,
            '''temb_channels''': 128,
        }
        _snake_case						=							self.dummy_input
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    Dict		)   ->					Any:
        _snake_case						=							[-0.1062, 1.7248, 0.3494, 1.4569, -0.0910, -1.2421, -0.9984, 0.6736, 1.0028]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		List[str]										=    UNetMidBlockaDCrossAttn  # noqa F405
      UpperCamelCase_      :		Dict										=    "mid"



      def 						UpperCamelCase_		(      self				:    str		)   ->					Optional[Any]:
        _snake_case,					_snake_case						=							super().prepare_init_args_and_inputs_for_common()
        _snake_case						=							32
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    List[str]		)   ->					Optional[Any]:
        _snake_case						=							[0.0187, 2.4220, 0.4484, 1.1203, -0.6121, -1.5122, -0.8270, 0.7851, 1.8335]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Optional[Any]										=    UNetMidBlockaDSimpleCrossAttn  # noqa F405
      UpperCamelCase_      :		Any										=    "mid"



      @property
      def 						UpperCamelCase_		(      self				:    Tuple		)   ->					str:
        return super().get_dummy_input(include_encoder_hidden_states=A__		)



      def 						UpperCamelCase_		(      self				:    Union[str, Any]		)   ->					List[str]:
        _snake_case,					_snake_case						=							super().prepare_init_args_and_inputs_for_common()
        _snake_case						=							32
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    Any		)   ->					Dict:
        _snake_case						=							[0.7143, 1.9974, 0.5448, 1.3977, 0.1282, -1.1237, -1.4238, 0.5530, 0.8880]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		str										=    UpBlockaD  # noqa F405
      UpperCamelCase_      :		Any										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    Union[str, Any]		)   ->					Union[str, Any]:
        return super().get_dummy_input(include_res_hidden_states_tuple=A__		)







      def 						UpperCamelCase_		(      self				:    Optional[Any]		)   ->					Dict:
        _snake_case						=							[-0.2041, -0.4165, -0.3022, 0.0041, -0.6628, -0.7053, 0.1928, -0.0325, 0.0523]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Union[str, Any]										=    ResnetUpsampleBlockaD  # noqa F405
      UpperCamelCase_      :		Optional[int]										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    Any		)   ->					int:
        return super().get_dummy_input(include_res_hidden_states_tuple=A__		)







      def 						UpperCamelCase_		(      self				:    Union[str, Any]		)   ->					str:
        _snake_case						=							[0.2287, 0.3549, -0.1346, 0.4797, -0.1715, -0.9649, 0.7305, -0.5864, -0.6244]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		List[str]										=    CrossAttnUpBlockaD  # noqa F405
      UpperCamelCase_      :		List[str]										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    Dict		)   ->					Any:
        return super().get_dummy_input(include_res_hidden_states_tuple=A__		)



      def 						UpperCamelCase_		(      self				:    Dict		)   ->					Dict:
        _snake_case,					_snake_case						=							super().prepare_init_args_and_inputs_for_common()
        _snake_case						=							32
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    Any		)   ->					List[Any]:
        _snake_case						=							[-0.1403, -0.3515, -0.0420, -0.1425, 0.3167, 0.5094, -0.2181, 0.5931, 0.5582]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		List[str]										=    SimpleCrossAttnUpBlockaD  # noqa F405
      UpperCamelCase_      :		int										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    List[Any]		)   ->					Optional[Any]:
        return super().get_dummy_input(include_res_hidden_states_tuple=A__      , include_encoder_hidden_states=A__		)



      def 						UpperCamelCase_		(      self				:    str		)   ->					Optional[Any]:
        _snake_case,					_snake_case						=							super().prepare_init_args_and_inputs_for_common()
        _snake_case						=							32
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    List[str]		)   ->					List[str]:
        _snake_case						=							[0.2645, 0.1480, 0.0909, 0.8044, -0.9758, -0.9083, 0.0994, -1.1453, -0.7402]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Optional[int]										=    AttnUpBlockaD  # noqa F405
      UpperCamelCase_      :		Optional[Any]										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    Union[str, Any]		)   ->					Optional[int]:
        return super().get_dummy_input(include_res_hidden_states_tuple=A__		)







      @unittest.skipIf(torch_device == '''mps'''      , '''MPS result is not consistent'''		)
      def 						UpperCamelCase_		(      self				:    Any		)   ->					Optional[Any]:
        _snake_case						=							[0.0979, 0.1326, 0.0021, 0.0659, 0.2249, 0.0059, 0.1132, 0.5952, 0.1033]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		str										=    SkipUpBlockaD  # noqa F405
      UpperCamelCase_      :		List[str]										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    List[str]		)   ->					List[str]:
        return super().get_dummy_input(include_res_hidden_states_tuple=A__		)







      def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					str:
        _snake_case						=							[-0.0893, -0.1234, -0.1506, -0.0332, 0.0123, -0.0211, 0.0566, 0.0143, 0.0362]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		List[Any]										=    AttnSkipUpBlockaD  # noqa F405
      UpperCamelCase_      :		Tuple										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    Optional[int]		)   ->					Dict:
        return super().get_dummy_input(include_res_hidden_states_tuple=A__		)







      def 						UpperCamelCase_		(      self				:    int		)   ->					List[Any]:
        _snake_case						=							[0.0361, 0.0617, 0.2787, -0.0350, 0.0342, 0.3421, -0.0843, 0.0913, 0.3015]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Any										=    UpDecoderBlockaD  # noqa F405
      UpperCamelCase_      :		List[str]										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    int		)   ->					Any:
        return super().get_dummy_input(include_temb=A__		)



      def 						UpperCamelCase_		(      self				:    Tuple		)   ->					Tuple:
        _snake_case						=							{'''in_channels''': 32, '''out_channels''': 32}

        _snake_case						=							self.dummy_input
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    Optional[Any]		)   ->					Union[str, Any]:
        _snake_case						=							[0.4404, 0.1998, -0.9886, -0.3320, -0.3128, -0.7034, -0.6955, -0.2338, -0.3137]
        super().test_output(A__		)



class   lowercase_   (  __lowercase       ,							unittest.TestCase					):
      UpperCamelCase_      :		Optional[Any]										=    AttnUpDecoderBlockaD  # noqa F405
      UpperCamelCase_      :		Dict										=    "up"



      @property
      def 						UpperCamelCase_		(      self				:    str		)   ->					Tuple:
        return super().get_dummy_input(include_temb=A__		)



      def 						UpperCamelCase_		(      self				:    Dict		)   ->					int:
        _snake_case						=							{'''in_channels''': 32, '''out_channels''': 32}

        _snake_case						=							self.dummy_input
        return init_dict, inputs_dict







      def 						UpperCamelCase_		(      self				:    List[str]		)   ->					Union[str, Any]:
        _snake_case						=							[0.6738, 0.4491, 0.1055, 1.0710, 0.7316, 0.3339, 0.3352, 0.1023, 0.3568]
        super().test_output(A__		)




import argparse
import os
import re

import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints

from transformers import (
    AutoTokenizer,
    PixaStructConfig,
    PixaStructForConditionalGeneration,
    PixaStructImageProcessor,
    PixaStructProcessor,
    PixaStructTextConfig,
    PixaStructVisionConfig,
)



def 				snake_case_(_UpperCamelCase					)							->     Optional[int]:



  """simple docstring"""






  _snake_case						=							checkpoints.load_tax_checkpoint(_UpperCamelCase					)
  _snake_case						=							flatten_dict(_UpperCamelCase					)
  return flax_params



def 				snake_case_(_UpperCamelCase					)							->     List[str]:



  """simple docstring"""






  _snake_case						=							{}

  _snake_case						=							{
      '''token_embedder''': '''embeddings''',
      '''encoder_norm''': '''layernorm''',
      '''kernel''': '''weight''',
      '''.out''': '''.output''',
      '''scale''': '''weight''',
      '''embedders_0.pos_embedding''': '''row_embedder.weight''',
      '''embedders_1.pos_embedding''': '''column_embedder.weight''',
  }

  _snake_case						=							{
      '''query''': '''attention.query''',
      '''key''': '''attention.key''',
      '''value''': '''attention.value''',
      '''output.dense''': '''output''',
      '''encoder_decoder_attention.o''': '''encoder_decoder_attention.attention.o''',
      '''pre_self_attention_layer_norm''': '''self_attention.layer_norm''',
      '''pre_cross_attention_layer_norm''': '''encoder_decoder_attention.layer_norm''',
      '''mlp.''': '''mlp.DenseReluDense.''',
      '''pre_mlp_layer_norm''': '''mlp.layer_norm''',
      '''self_attention.o''': '''self_attention.attention.o''',
      '''decoder.embeddings.embedding''': '''decoder.embed_tokens.weight''',
      '''decoder.relpos_bias.rel_embedding''': '''decoder.layer.0.self_attention.attention.relative_attention_bias.weight''',
      '''decoder.decoder_norm.weight''': '''decoder.final_layer_norm.weight''',
      '''decoder.logits_dense.weight''': '''decoder.lm_head.weight''',
  }

  for key in flax_dict.keys():
    if "target" in key:
      # remove the first prefix from the key
      _snake_case						=							'''.'''.join(key[1:]					)

      # rename the key
      for old, new in CONVERSION_MAPPING.items():
        _snake_case						=							new_key.replace(_UpperCamelCase			,	_UpperCamelCase					)

      if "decoder" in new_key:
        for old, new in DECODER_CONVERSION_MAPPING.items():
          _snake_case						=							new_key.replace(_UpperCamelCase			,	_UpperCamelCase					)

      if "layers" in new_key and "decoder" not in new_key:
        # use regex to replace the layer number
        _snake_case						=							re.sub(R'''layers_(\d+)'''			,	R'''layer.\1'''			,	_UpperCamelCase					)
        _snake_case						=							new_key.replace('''encoder'''			,	'''encoder.encoder'''					)

      elif "layers" in new_key and "decoder" in new_key:
        # use regex to replace the layer number
        _snake_case						=							re.sub(R'''layers_(\d+)'''			,	R'''layer.\1'''			,	_UpperCamelCase					)

      _snake_case						=							flax_dict[key]

  _snake_case						=							{}
  # convert converted_dict into torch format
  for key in converted_dict.keys():
    if ("embed_tokens" not in key) and ("embedder" not in key):
      _snake_case						=							torch.from_numpy(converted_dict[key].T					)
    else:
      _snake_case						=							torch.from_numpy(converted_dict[key]					)

  return converted_torch_dict



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase=False			,	_UpperCamelCase=False					)							->     List[Any]:



  """simple docstring"""






  _snake_case						=							get_flax_param(_UpperCamelCase					)

  if not use_large:
    _snake_case						=							PixaStructVisionConfig()
    _snake_case						=							PixaStructTextConfig()
  else:
    _snake_case						=							PixaStructVisionConfig(
        hidden_size=1_536			,	d_ff=3_968			,	num_attention_heads=24			,	num_hidden_layers=18					)
    _snake_case						=							PixaStructTextConfig(hidden_size=1_536			,	d_ff=3_968			,	num_heads=24			,	num_layers=18					)
  _snake_case						=							PixaStructConfig(
      vision_config=encoder_config.to_dict()			,	text_config=decoder_config.to_dict()			,	is_vqa=_UpperCamelCase					)

  _snake_case						=							PixaStructForConditionalGeneration(_UpperCamelCase					)

  _snake_case						=							rename_and_convert_flax_params(_UpperCamelCase					)
  model.load_state_dict(_UpperCamelCase					)

  _snake_case						=							AutoTokenizer.from_pretrained('''ybelkada/test-pix2struct-tokenizer'''					)
  _snake_case						=							PixaStructImageProcessor()
  _snake_case						=							PixaStructProcessor(image_processor=_UpperCamelCase			,	tokenizer=_UpperCamelCase					)

  if use_large:
    _snake_case						=							4_096

  _snake_case						=							True

  # mkdir if needed
  os.makedirs(_UpperCamelCase			,	exist_ok=_UpperCamelCase					)

  model.save_pretrained(_UpperCamelCase					)
  processor.save_pretrained(_UpperCamelCase					)

  print('''Model saved in {}'''.format(_UpperCamelCase					)					)


if __name__ == "__main__":
 __A      		=     argparse.ArgumentParser()
 parser.add_argument('''--t5x_checkpoint_path''', default=None, type=str, help='''Path to the original T5x checkpoint.''')
 parser.add_argument('''--pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model.''')
 parser.add_argument('''--use_large''', action='''store_true''', help='''Use large model.''')
 parser.add_argument('''--is_vqa''', action='''store_true''', help='''Use large model.''')
 __A      		=     parser.parse_args()

 convert_pixastruct_original_pytorch_checkpoint_to_hf(
     args.tax_checkpoint_path, args.pytorch_dump_folder_path, args.use_large
 )

