
'''simple docstring'''

import os
import re
import shutil
from argparse import ArgumentParser, Namespace

from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger


snake_case									=    """<<<<<<< This should probably be modified because it mentions: """

snake_case									=    """=======
>>>>>>>
"""

snake_case									=    [
    """TextEncoderConfig""",
    """ByteTextEncoder""",
    """SubwordTextEncoder""",
    """encoder_config""",
    """maybe_build_from_corpus""",
    """manual_dir""",
]

snake_case									=    [
    # (pattern, replacement)
    # Order is important here for some replacements
    (r"""tfds\.core""", r"""datasets"""),
    (r"""tf\.io\.gfile\.GFile""", r"""open"""),
    (r"""tf\.([\w\d]+)""", r"""datasets.Value('\1')"""),
    (r"""tfds\.features\.Text\(\)""", r"""datasets.Value('string')"""),
    (r"""tfds\.features\.Text\(""", r"""datasets.Value('string'),"""),
    (r"""features\s*=\s*tfds.features.FeaturesDict\(""", r"""features=datasets.Features("""),
    (r"""tfds\.features\.FeaturesDict\(""", r"""dict("""),
    (r"""The TensorFlow Datasets Authors""", r"""The TensorFlow Datasets Authors and the HuggingFace Datasets Authors"""),
    (r"""tfds\.""", r"""datasets."""),
    (r"""dl_manager\.manual_dir""", r"""self.config.data_dir"""),
    (r"""self\.builder_config""", r"""self.config"""),
]


def        UpperCAmelCase_ (  lowerCamelCase_			):







 """simple docstring"""


 return ConvertCommand(args.tfds_path      ,			args.datasets_directory			)







class    lowerCAmelCase       (     UpperCamelCase_  ):


 @staticmethod
 def    _A	(    a__  : ArgumentParser    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Tuple     		=	parser.add_parser(
      "convert"			,							help="Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset."			,							)
  train_parser.add_argument(
      "--tfds_path"			,							type=a__			,							required=a__			,							help="Path to a TensorFlow Datasets folder to convert or a single tfds file to convert."			,							)
  train_parser.add_argument(
      "--datasets_directory"			,							type=a__			,							required=a__			,							help="Path to the HuggingFace Datasets folder."    )
  train_parser.set_defaults(func=a__    )


 def __init__(    self  : List[Any]			,							a__  : str			,							a__  : str			,							*a__  : List[str]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Any     		=	get_logger("datasets-cli/converting"    )

  lowerCAmelCase__     :   str     		=	tfds_path
  lowerCAmelCase__     :   Dict     		=	datasets_directory


 def    _A	(    self  : Any    ):
  '''simple docstring'''

  if os.path.isdir(self._tfds_path    ):
   lowerCAmelCase__     :   Union[str, Any]     		=	os.path.abspath(self._tfds_path    )
  elif os.path.isfile(self._tfds_path    ):
   lowerCAmelCase__     :   Any     		=	os.path.dirname(self._tfds_path    )
  else:
   raise ValueError("--tfds_path is neither a directory nor a file. Please check path."    )

  lowerCAmelCase__     :   List[str]     		=	os.path.abspath(self._datasets_directory    )

  self._logger.info(F'''Converting datasets from {abs_tfds_path} to {abs_datasets_path}'''    )

  lowerCAmelCase__     :   List[str]     		=	[]
  lowerCAmelCase__     :   Tuple     		=	[]
  lowerCAmelCase__     :   Optional[int]     		=	{}

  if os.path.isdir(self._tfds_path    ):
   lowerCAmelCase__     :   List[Any]     		=	os.listdir(a__    )
  else:
   lowerCAmelCase__     :   Dict     		=	[os.path.basename(self._tfds_path    )]

  for f_name in file_names:
   self._logger.info(F'''Looking at file {f_name}'''    )
   lowerCAmelCase__     :   Tuple     		=	os.path.join(a__			,							a__    )
   lowerCAmelCase__     :   List[Any]     		=	os.path.join(a__			,							a__    )

   if not os.path.isfile(a__    ) or "__init__" in f_name or "_test" in f_name or ".py" not in f_name:
    self._logger.info("Skipping file"    )
    continue

   with open(a__			,							encoding="utf-8"    ) as f:
    lowerCAmelCase__     :   Any     		=	f.readlines()

   lowerCAmelCase__     :   Union[str, Any]     		=	[]
   lowerCAmelCase__     :   Union[str, Any]     		=	False
   lowerCAmelCase__     :   List[str]     		=	False
   lowerCAmelCase__     :   Tuple     		=	[]
   for line in lines:
    lowerCAmelCase__     :   Tuple     		=	line

    # Convert imports
    if "import tensorflow.compat.v2 as tf" in out_line:
     continue
    elif "@tfds.core" in out_line:
     continue
    elif "builder=self" in out_line:
     continue
    elif "import tensorflow_datasets.public_api as tfds" in out_line:
     lowerCAmelCase__     :   Any     		=	"import datasets\n"
    elif "import tensorflow" in out_line:
     # order is important here
     lowerCAmelCase__     :   Optional[Any]     		=	""
     continue
    elif "from absl import logging" in out_line:
     lowerCAmelCase__     :   Optional[int]     		=	"from datasets import logging\n"
    elif "getLogger" in out_line:
     lowerCAmelCase__     :   List[Any]     		=	out_line.replace("getLogger"			,							"get_logger"    )
    elif any(expression in out_line for expression in TO_HIGHLIGHT    ):
     lowerCAmelCase__     :   Optional[Any]     		=	True
     lowerCAmelCase__     :   Dict     		=	list(filter(lambda a__    : e in out_line			,							a__    )    )
     out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(a__    ) + "\n"    )
     out_lines.append(a__    )
     out_lines.append(a__    )
     continue
    else:
     for pattern, replacement in TO_CONVERT:
      lowerCAmelCase__     :   List[str]     		=	re.sub(a__			,							a__			,							a__    )

                # Take care of saving utilities (to later move them together with main script)
    if "tensorflow_datasets" in out_line:
     lowerCAmelCase__     :   int     		=	re.match(r"from\stensorflow_datasets.*import\s([^\.\r\n]+)"			,							a__    )
     tfds_imports.extend(imp.strip() for imp in match.group(1    ).split(","    )    )
     lowerCAmelCase__     :   Union[str, Any]     		=	"from . import " + match.group(1    )

    # Check we have not forget anything
    if "tf." in out_line or "tfds." in out_line or "tensorflow_datasets" in out_line:
     raise ValueError(F'''Error converting {out_line.strip()}'''    )

    if "GeneratorBasedBuilder" in out_line or "BeamBasedBuilder" in out_line:
     lowerCAmelCase__     :   Any     		=	True
    out_lines.append(a__    )

   if is_builder or "wmt" in f_name:
    # We create a new directory for each dataset
    lowerCAmelCase__     :   Optional[Any]     		=	f_name.replace(".py"			,							""    )
    lowerCAmelCase__     :   str     		=	os.path.join(a__			,							a__    )
    lowerCAmelCase__     :   Dict     		=	os.path.join(a__			,							a__    )
    os.makedirs(a__			,							exist_ok=a__    )
    self._logger.info(F'''Adding directory {output_dir}'''    )
    imports_to_builder_map.update({imp: output_dir for imp in tfds_imports}    )
   else:
    # Utilities will be moved at the end
    utils_files.append(a__    )

   if needs_manual_update:
    with_manual_update.append(a__    )

   with open(a__			,							"w"			,							encoding="utf-8"    ) as f:
    f.writelines(a__    )
   self._logger.info(F'''Converted in {output_file}'''    )

  for utils_file in utils_files:
   try:
    lowerCAmelCase__     :   Union[str, Any]     		=	os.path.basename(a__    )
    lowerCAmelCase__     :   str     		=	imports_to_builder_map[f_name.replace(".py"			,							""    )]
    self._logger.info(F'''Moving {dest_folder} to {utils_file}'''    )
    shutil.copy(a__			,							a__    )
   except KeyError:
    self._logger.error(F'''Cannot find destination folder for {utils_file}. Please copy manually.'''    )

  if with_manual_update:
   for file_path in with_manual_update:
    self._logger.warning(
        F'''You need to manually update file {file_path} to remove configurations using \'TextEncoderConfig\'.'''    )







'''simple docstring'''

import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


snake_case									=    logging.get_logger(__name__)  # pylint: disable=invalid-name




class    lowerCAmelCase       (     UpperCamelCase_  ):


 def __init__(    self  : Union[str, Any]			,							a__  : int			,							a__  : List[Any]=768    ):
  '''simple docstring'''

  super().__init__(a__    )
  lowerCAmelCase__     :   int     		=	proj_size

  lowerCAmelCase__     :   str     		=	CLIPVisionModel(a__    )
  lowerCAmelCase__     :   int     		=	PaintByExampleMapper(a__    )
  lowerCAmelCase__     :   Optional[int]     		=	nn.LayerNorm(config.hidden_size    )
  lowerCAmelCase__     :   Optional[Any]     		=	nn.Linear(config.hidden_size			,							self.proj_size    )

  # uncondition for scaling
  lowerCAmelCase__     :   Dict     		=	nn.Parameter(torch.randn((1, 1, self.proj_size)    )    )


 def    _A	(    self  : Tuple			,							a__  : int			,							a__  : Optional[Any]=False    ):
  '''simple docstring'''

  lowerCAmelCase__     :   List[Any]     		=	self.model(pixel_values=a__    )
  lowerCAmelCase__     :   Any     		=	clip_output.pooler_output
  lowerCAmelCase__     :   Union[str, Any]     		=	self.mapper(latent_states[:, None]    )
  lowerCAmelCase__     :   List[Any]     		=	self.final_layer_norm(a__    )
  lowerCAmelCase__     :   Optional[int]     		=	self.proj_out(a__    )
  if return_uncond_vector:
   return latent_states, self.uncond_vector

  return latent_states




class    lowerCAmelCase       (     nn.Module  ):


 def __init__(    self  : Optional[Any]			,							a__  : Optional[Any]    ):
  '''simple docstring'''

  super().__init__()
  lowerCAmelCase__     :   Optional[Any]     		=	(config.num_hidden_layers + 1) // 5
  lowerCAmelCase__     :   str     		=	config.hidden_size
  lowerCAmelCase__     :   Dict     		=	1
  lowerCAmelCase__     :   int     		=	nn.ModuleList(
      [
          BasicTransformerBlock(a__			,							a__			,							a__			,							activation_fn="gelu"			,							attention_bias=a__    )
          for _ in range(a__    )
      ]    )


 def    _A	(    self  : int			,							a__  : Union[str, Any]    ):
  '''simple docstring'''

  for block in self.blocks:
   lowerCAmelCase__     :   List[Any]     		=	block(a__    )

  return hidden_states





