
import glob
import os
import random
from string import ascii_lowercase, digits

import cva
import numpy as np

# Parrameters
_lowercase											=    (720, 1280)  # Height, Width
_lowercase											=    (0.4, 0.6)  # if height or width lower than this scale, drop it.
_lowercase											=    1 / 100
_lowercase											=    """"""
_lowercase											=    """"""
_lowercase											=    """"""
_lowercase											=    250
def 							SCREAMING_SNAKE_CASE_	(					)			->						None:
       SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_							:				str		=get_dataset(UpperCAmelCase_			,							UpperCAmelCase_				)
       for index in range(UpperCAmelCase_				):
              SCREAMING_SNAKE_CASE_							:				Optional[Any]		=random.sample(range(len(UpperCAmelCase_				)				)			,							4				)
              SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_							:				List[str]		=update_image_and_anno(
                  UpperCAmelCase_			,							UpperCAmelCase_			,							UpperCAmelCase_			,							UpperCAmelCase_			,							UpperCAmelCase_			,							filter_scale=UpperCAmelCase_			,							)

              # Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
              SCREAMING_SNAKE_CASE_							:				str		=random_chars(3_2				)
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=path.split(os.sep				)[-1].rsplit('''.'''			,							1				)[0]
              SCREAMING_SNAKE_CASE_							:				List[str]		=f'{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}'
              cva.imwrite(f'{file_root}.jpg'			,							UpperCAmelCase_			,							[cva.IMWRITE_JPEG_QUALITY, 8_5]				)
              print(f'Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}'				)
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=[]
              for anno in new_annos:
                     SCREAMING_SNAKE_CASE_							:				int		=anno[3] - anno[1]
                     SCREAMING_SNAKE_CASE_							:				List[Any]		=anno[4] - anno[2]
                     SCREAMING_SNAKE_CASE_							:				str		=anno[1] + width / 2
                     SCREAMING_SNAKE_CASE_							:				List[str]		=anno[2] + height / 2
                     SCREAMING_SNAKE_CASE_							:				Optional[Any]		=f'{anno[0]} {x_center} {y_center} {width} {height}'
                     annos_list.append(UpperCAmelCase_				)
              with open(f'{file_root}.txt'			,							'''w'''				) as outfile:
                     outfile.write('''\n'''.join(line for line in annos_list				)				)
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     str			,							UpperCAmelCase_	:     str				)			->						tuple[list, list]:
       SCREAMING_SNAKE_CASE_							:				str		=[]
       SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=[]
       for label_file in glob.glob(os.path.join(UpperCAmelCase_			,							'''*.txt'''				)				):
              SCREAMING_SNAKE_CASE_							:				int		=label_file.split(os.sep				)[-1].rsplit('''.'''			,							1				)[0]
              with open(UpperCAmelCase_				) as in_file:
                     SCREAMING_SNAKE_CASE_							:				List[str]		=in_file.readlines()
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=os.path.join(UpperCAmelCase_			,							f'{label_name}.jpg'				)

              SCREAMING_SNAKE_CASE_							:				str		=[]
              for obj_list in obj_lists:
                     SCREAMING_SNAKE_CASE_							:				List[Any]		=obj_list.rstrip('''\n'''				).split(''' '''				)
                     SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=float(obj[1]				) - float(obj[3]				) / 2
                     SCREAMING_SNAKE_CASE_							:				List[Any]		=float(obj[2]				) - float(obj[4]				) / 2
                     SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=float(obj[1]				) + float(obj[3]				) / 2
                     SCREAMING_SNAKE_CASE_							:				Dict		=float(obj[2]				) + float(obj[4]				) / 2

                     boxes.append([int(obj[0]				), xmin, ymin, xmax, ymax]				)
              if not boxes:
                     continue
              img_paths.append(UpperCAmelCase_				)
              labels.append(UpperCAmelCase_				)
       return img_paths, labels
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     list			,							UpperCAmelCase_	:     list			,							UpperCAmelCase_	:     list[int]			,							UpperCAmelCase_	:     tuple[int, int]			,							UpperCAmelCase_	:     tuple[float, float]			,							UpperCAmelCase_	:     float = 0.0			,							)			->						tuple[list, list, str]:
       SCREAMING_SNAKE_CASE_							:				Optional[Any]		=np.zeros([output_size[0], output_size[1], 3]			,							dtype=np.uinta				)
       SCREAMING_SNAKE_CASE_							:				str		=scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
       SCREAMING_SNAKE_CASE_							:				Tuple		=scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
       SCREAMING_SNAKE_CASE_							:				Dict		=int(scale_x * output_size[1]				)
       SCREAMING_SNAKE_CASE_							:				int		=int(scale_y * output_size[0]				)

       SCREAMING_SNAKE_CASE_							:				Dict		=[]
       SCREAMING_SNAKE_CASE_							:				Optional[int]		=[]
       for i, index in enumerate(UpperCAmelCase_				):
              SCREAMING_SNAKE_CASE_							:				Any		=all_img_list[index]
              path_list.append(UpperCAmelCase_				)
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=all_annos[index]
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=cva.imread(UpperCAmelCase_				)
              if i == 0:  # top-left
                     SCREAMING_SNAKE_CASE_							:				Optional[Any]		=cva.resize(UpperCAmelCase_			,							(divid_point_x, divid_point_y)				)
                     SCREAMING_SNAKE_CASE_							:				str		=img
                     for bbox in img_annos:
                            SCREAMING_SNAKE_CASE_							:				Dict		=bbox[1] * scale_x
                            SCREAMING_SNAKE_CASE_							:				Any		=bbox[2] * scale_y
                            SCREAMING_SNAKE_CASE_							:				int		=bbox[3] * scale_x
                            SCREAMING_SNAKE_CASE_							:				str		=bbox[4] * scale_y
                            new_anno.append([bbox[0], xmin, ymin, xmax, ymax]				)
              elif i == 1:  # top-right
                     SCREAMING_SNAKE_CASE_							:				Tuple		=cva.resize(UpperCAmelCase_			,							(output_size[1] - divid_point_x, divid_point_y)				)
                     SCREAMING_SNAKE_CASE_							:				Optional[int]		=img
                     for bbox in img_annos:
                            SCREAMING_SNAKE_CASE_							:				int		=scale_x + bbox[1] * (1 - scale_x)
                            SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=bbox[2] * scale_y
                            SCREAMING_SNAKE_CASE_							:				int		=scale_x + bbox[3] * (1 - scale_x)
                            SCREAMING_SNAKE_CASE_							:				List[str]		=bbox[4] * scale_y
                            new_anno.append([bbox[0], xmin, ymin, xmax, ymax]				)
              elif i == 2:  # bottom-left
                     SCREAMING_SNAKE_CASE_							:				Optional[Any]		=cva.resize(UpperCAmelCase_			,							(divid_point_x, output_size[0] - divid_point_y)				)
                     SCREAMING_SNAKE_CASE_							:				Any		=img
                     for bbox in img_annos:
                            SCREAMING_SNAKE_CASE_							:				Dict		=bbox[1] * scale_x
                            SCREAMING_SNAKE_CASE_							:				List[Any]		=scale_y + bbox[2] * (1 - scale_y)
                            SCREAMING_SNAKE_CASE_							:				str		=bbox[3] * scale_x
                            SCREAMING_SNAKE_CASE_							:				int		=scale_y + bbox[4] * (1 - scale_y)
                            new_anno.append([bbox[0], xmin, ymin, xmax, ymax]				)
              else:  # bottom-right
                     SCREAMING_SNAKE_CASE_							:				int		=cva.resize(
                         UpperCAmelCase_			,							(output_size[1] - divid_point_x, output_size[0] - divid_point_y)				)
                     SCREAMING_SNAKE_CASE_							:				Any		=img
                     for bbox in img_annos:
                            SCREAMING_SNAKE_CASE_							:				Optional[Any]		=scale_x + bbox[1] * (1 - scale_x)
                            SCREAMING_SNAKE_CASE_							:				Dict		=scale_y + bbox[2] * (1 - scale_y)
                            SCREAMING_SNAKE_CASE_							:				str		=scale_x + bbox[3] * (1 - scale_x)
                            SCREAMING_SNAKE_CASE_							:				Optional[int]		=scale_y + bbox[4] * (1 - scale_y)
                            new_anno.append([bbox[0], xmin, ymin, xmax, ymax]				)

    # Remove bounding box small than scale of filter
       if filter_scale > 0:
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=[
                  anno
                  for anno in new_anno
                  if filter_scale < (anno[3] - anno[1]) and filter_scale < (anno[4] - anno[2])
              ]

       return output_img, new_anno, path_list[0]
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     int				)			->						str:
       assert number_char > 1, "The number of character should greater than 1"
       SCREAMING_SNAKE_CASE_							:				Optional[int]		=ascii_lowercase + digits
       return "".join(random.choice(UpperCAmelCase_				) for _ in range(UpperCAmelCase_				)				)


if __name__ == "__main__":
 main()
 print("""DONE ✅""")


from dataclasses import asdict, dataclass
from typing import Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowercase											=    logging.get_logger(__name__)

# TODO Update this
_lowercase											=    {
    """facebook/esm-1b""": """https://huggingface.co/facebook/esm-1b/resolve/main/config.json""",
    # See all ESM models at https://huggingface.co/models?filter=esm
}


class 			lowercase_		(      A       ):
       __lowerCamelCase				       =						"esm"


       def __init__(    self						,       __A=None						,       __A=None						,       __A=None						,       __A=768						,       __A=12						,       __A=12						,       __A=3_072						,       __A=0.1						,       __A=0.1						,       __A=1_026						,       __A=0.02						,       __A=1e-1_2						,       __A="absolute"						,       __A=True						,       __A=None						,       __A=False						,       __A=False						,       __A=None						,       __A=None						,       **__A						,       )						->    int:
              super().__init__(pad_token_id=__A						,       mask_token_id=__A						,       **__A				)

              SCREAMING_SNAKE_CASE_							:				Any		=vocab_size
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=hidden_size
              SCREAMING_SNAKE_CASE_							:				int		=num_hidden_layers
              SCREAMING_SNAKE_CASE_							:				int		=num_attention_heads
              SCREAMING_SNAKE_CASE_							:				List[str]		=intermediate_size
              SCREAMING_SNAKE_CASE_							:				int		=hidden_dropout_prob
              SCREAMING_SNAKE_CASE_							:				int		=attention_probs_dropout_prob
              SCREAMING_SNAKE_CASE_							:				List[Any]		=max_position_embeddings
              SCREAMING_SNAKE_CASE_							:				List[Any]		=initializer_range
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=layer_norm_eps
              SCREAMING_SNAKE_CASE_							:				str		=position_embedding_type
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=use_cache
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=emb_layer_norm_before
              SCREAMING_SNAKE_CASE_							:				Tuple		=token_dropout
              SCREAMING_SNAKE_CASE_							:				List[Any]		=is_folding_model
              if is_folding_model:
                     if esmfold_config is None:
                            logger.info('''No esmfold_config supplied for folding model, using default values.'''				)
                            SCREAMING_SNAKE_CASE_							:				Optional[int]		=EsmFoldConfig()
                     elif isinstance(__A						,       __A				):
                            SCREAMING_SNAKE_CASE_							:				List[Any]		=EsmFoldConfig(**__A				)
                     SCREAMING_SNAKE_CASE_							:				Optional[int]		=esmfold_config
                     if vocab_list is None:
                            logger.warning('''No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!'''				)
                            SCREAMING_SNAKE_CASE_							:				Tuple		=get_default_vocab_list()
                     else:
                            SCREAMING_SNAKE_CASE_							:				Optional[Any]		=vocab_list
              else:
                     SCREAMING_SNAKE_CASE_							:				List[str]		=None
                     SCREAMING_SNAKE_CASE_							:				Optional[int]		=None
              if self.esmfold_config is not None and getattr(self.esmfold_config						,       '''use_esm_attn_map'''						,       __A				):
                     raise ValueError('''The HuggingFace port of ESMFold does not support use_esm_attn_map at this time!'''				)





       def 	_snake_case				(    self				)						->    List[Any]:
              SCREAMING_SNAKE_CASE_							:				str		=super().to_dict()
              if isinstance(self.esmfold_config						,       __A				):
                     SCREAMING_SNAKE_CASE_							:				Optional[Any]		=self.esmfold_config.to_dict()
              return output






@dataclass
class 			lowercase_		:
       __lowerCamelCase				       =						None
       __lowerCamelCase				       =						True
       __lowerCamelCase				       =						False
       __lowerCamelCase				       =						False
       __lowerCamelCase				       =						False
       __lowerCamelCase				       =						0

       __lowerCamelCase				       =						True
       __lowerCamelCase				       =						False

       __lowerCamelCase				       =						1_2_8
       __lowerCamelCase				       =						None


       def 	_snake_case				(    self				)						->    Optional[Any]:
              if self.trunk is None:
                     SCREAMING_SNAKE_CASE_							:				Tuple		=TrunkConfig()
              elif isinstance(self.trunk						,       __A				):
                     SCREAMING_SNAKE_CASE_							:				List[str]		=TrunkConfig(**self.trunk				)





       def 	_snake_case				(    self				)						->    List[Any]:
              SCREAMING_SNAKE_CASE_							:				int		=asdict(self				)
              SCREAMING_SNAKE_CASE_							:				Tuple		=self.trunk.to_dict()
              return output






@dataclass
class 			lowercase_		:
       __lowerCamelCase				       =						4_8
       __lowerCamelCase				       =						1_0_2_4
       __lowerCamelCase				       =						1_2_8
       __lowerCamelCase				       =						3_2
       __lowerCamelCase				       =						3_2
       __lowerCamelCase				       =						3_2
       __lowerCamelCase				       =						0
       __lowerCamelCase				       =						0
       __lowerCamelCase				       =						False
       __lowerCamelCase				       =						4
       __lowerCamelCase				       =						1_2_8
       __lowerCamelCase				       =						None


       def 	_snake_case				(    self				)						->    int:
              if self.structure_module is None:
                     SCREAMING_SNAKE_CASE_							:				Dict		=StructureModuleConfig()
              elif isinstance(self.structure_module						,       __A				):
                     SCREAMING_SNAKE_CASE_							:				Optional[Any]		=StructureModuleConfig(**self.structure_module				)

              if self.max_recycles <= 0:
                     raise ValueError(F'`max_recycles` should be positive, got {self.max_recycles}.'				)
              if self.sequence_state_dim % self.sequence_state_dim != 0:
                     raise ValueError(
                         '''`sequence_state_dim` should be a round multiple of `sequence_state_dim`, got'''
                         F' {self.sequence_state_dim} and {self.sequence_state_dim}.'				)
              if self.pairwise_state_dim % self.pairwise_state_dim != 0:
                     raise ValueError(
                         '''`pairwise_state_dim` should be a round multiple of `pairwise_state_dim`, got'''
                         F' {self.pairwise_state_dim} and {self.pairwise_state_dim}.'				)

              SCREAMING_SNAKE_CASE_							:				Tuple		=self.sequence_state_dim // self.sequence_head_width
              SCREAMING_SNAKE_CASE_							:				str		=self.pairwise_state_dim // self.pairwise_head_width

              if self.sequence_state_dim != sequence_num_heads * self.sequence_head_width:
                     raise ValueError(
                         '''`sequence_state_dim` should be equal to `sequence_num_heads * sequence_head_width, got'''
                         F' {self.sequence_state_dim} != {sequence_num_heads} * {self.sequence_head_width}.'				)
              if self.pairwise_state_dim != pairwise_num_heads * self.pairwise_head_width:
                     raise ValueError(
                         '''`pairwise_state_dim` should be equal to `pairwise_num_heads * pairwise_head_width, got'''
                         F' {self.pairwise_state_dim} != {pairwise_num_heads} * {self.pairwise_head_width}.'				)
              if self.pairwise_state_dim % 2 != 0:
                     raise ValueError(F'`pairwise_state_dim` should be even, got {self.pairwise_state_dim}.'				)

              if self.dropout >= 0.4:
                     raise ValueError(F'`dropout` should not be greater than 0.4, got {self.dropout}.'				)





       def 	_snake_case				(    self				)						->    int:
              SCREAMING_SNAKE_CASE_							:				str		=asdict(self				)
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=self.structure_module.to_dict()
              return output






@dataclass
class 			lowercase_		:
       __lowerCamelCase				       =						3_8_4
       __lowerCamelCase				       =						1_2_8
       __lowerCamelCase				       =						1_6
       __lowerCamelCase				       =						1_2_8
       __lowerCamelCase				       =						1_2
       __lowerCamelCase				       =						4
       __lowerCamelCase				       =						8
       __lowerCamelCase				       =						0.1
       __lowerCamelCase				       =						8
       __lowerCamelCase				       =						1
       __lowerCamelCase				       =						2
       __lowerCamelCase				       =						7
       __lowerCamelCase				       =						1_0
       __lowerCamelCase				       =						1E-8
       __lowerCamelCase				       =						1E5


       def 	_snake_case				(    self				)						->    str:
              return asdict(self				)






def 							SCREAMING_SNAKE_CASE_	(					)			->						int:
       return (
           "<cls>",
           "<pad>",
           "<eos>",
           "<unk>",
           "L",
           "A",
           "G",
           "V",
           "S",
           "E",
           "R",
           "T",
           "I",
           "D",
           "P",
           "K",
           "Q",
           "N",
           "F",
           "Y",
           "M",
           "H",
           "W",
           "C",
           "X",
           "B",
           "U",
           "Z",
           "O",
           ".",
           "-",
           "<null_1>",
           "<mask>",
       )
