



"""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 			_lowerCAmelCase				(       lowercase_						):
						return ConvertCommand(args.tfds_path		,     args.datasets_directory						)







class 				A_      (					SCREAMING_SNAKE_CASE_    ):



						"""simple docstring"""






						@staticmethod
						def      UpperCAmelCase__					( lowercase_			:ArgumentParser )    ->      int:
												UpperCAmelCase					=			parser.add_parser(
												    'convert'       ,  help='Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset.'       ,  )
												train_parser.add_argument(
												    '--tfds_path'       ,  type=lowercase_       ,  required=lowercase_       ,  help='Path to a TensorFlow Datasets folder to convert or a single tfds file to convert.'       ,  )
												train_parser.add_argument(
												    '--datasets_directory'       ,  type=lowercase_       ,  required=lowercase_       ,  help='Path to the HuggingFace Datasets folder.' )
												train_parser.set_defaults(func=lowercase_ )






						def __init__( self			:Optional[Any]       ,  lowercase_			:str       ,  lowercase_			:str       ,  *lowercase_			:Tuple )    ->      Optional[Any]:
												UpperCAmelCase					=			get_logger('datasets-cli/converting' )

												UpperCAmelCase					=			tfds_path
												UpperCAmelCase					=			datasets_directory






						def      UpperCAmelCase__					( self			:Dict )    ->      Any:
												if os.path.isdir(self._tfds_path ):
																		UpperCAmelCase					=			os.path.abspath(self._tfds_path )
												elif os.path.isfile(self._tfds_path ):
																		UpperCAmelCase					=			os.path.dirname(self._tfds_path )
												else:
																		raise ValueError('--tfds_path is neither a directory nor a file. Please check path.' )

												UpperCAmelCase					=			os.path.abspath(self._datasets_directory )

												self._logger.info(f"""Converting datasets from {abs_tfds_path} to {abs_datasets_path}""" )

												UpperCAmelCase					=			[]
												UpperCAmelCase					=			[]
												UpperCAmelCase					=			{}

												if os.path.isdir(self._tfds_path ):
																		UpperCAmelCase					=			os.listdir(lowercase_ )
												else:
																		UpperCAmelCase					=			[os.path.basename(self._tfds_path )]

												for f_name in file_names:
																		self._logger.info(f"""Looking at file {f_name}""" )
																		UpperCAmelCase					=			os.path.join(lowercase_       ,  lowercase_ )
																		UpperCAmelCase					=			os.path.join(lowercase_       ,  lowercase_ )

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

																		with open(lowercase_       ,  encoding='utf-8' ) as f:
																								UpperCAmelCase					=			f.readlines()

																		UpperCAmelCase					=			[]
																		UpperCAmelCase					=			False
																		UpperCAmelCase					=			False
																		UpperCAmelCase					=			[]
																		for line in lines:
																								UpperCAmelCase					=			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:
																														UpperCAmelCase					=			'import datasets\n'
																								elif "import tensorflow" in out_line:
																														# order is important here
																														UpperCAmelCase					=			''
																														continue
																								elif "from absl import logging" in out_line:
																														UpperCAmelCase					=			'from datasets import logging\n'
																								elif "getLogger" in out_line:
																														UpperCAmelCase					=			out_line.replace('getLogger'       ,  'get_logger' )
																								elif any(expression in out_line for expression in TO_HIGHLIGHT ):
																														UpperCAmelCase					=			True
																														UpperCAmelCase					=			list(filter(lambda lowercase_ : e in out_line       ,  lowercase_ ) )
																														out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(lowercase_ ) + '\n' )
																														out_lines.append(lowercase_ )
																														out_lines.append(lowercase_ )
																														continue
																								else:
																														for pattern, replacement in TO_CONVERT:
																																				UpperCAmelCase					=			re.sub(lowercase_       ,  lowercase_       ,  lowercase_ )

                # Take care of saving utilities (to later move them together with main script)
																								if "tensorflow_datasets" in out_line:
																														UpperCAmelCase					=			re.match(R'from\stensorflow_datasets.*import\s([^\.\r\n]+)'       ,  lowercase_ )
																														tfds_imports.extend(imp.strip() for imp in match.group(1 ).split(',' ) )
																														UpperCAmelCase					=			'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:
																														UpperCAmelCase					=			True
																								out_lines.append(lowercase_ )

																		if is_builder or "wmt" in f_name:
																								# We create a new directory for each dataset
																								UpperCAmelCase					=			f_name.replace('.py'       ,  '' )
																								UpperCAmelCase					=			os.path.join(lowercase_       ,  lowercase_ )
																								UpperCAmelCase					=			os.path.join(lowercase_       ,  lowercase_ )
																								os.makedirs(lowercase_       ,  exist_ok=lowercase_ )
																								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(lowercase_ )

																		if needs_manual_update:
																								with_manual_update.append(lowercase_ )

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

												for utils_file in utils_files:
																		try:
																								UpperCAmelCase					=			os.path.basename(lowercase_ )
																								UpperCAmelCase					=			imports_to_builder_map[f_name.replace('.py'       ,  '' )]
																								self._logger.info(f"""Moving {dest_folder} to {utils_file}""" )
																								shutil.copy(lowercase_       ,  lowercase_ )
																		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 re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


snake_case_    					=	logging.get_logger(__name__)

def 			_lowerCAmelCase				(       lowercase_						):
						UpperCAmelCase					=			R'\w+[.]\d+'
						UpperCAmelCase					=			re.findall(lowercase_		,     lowercase_						)
						for pat in pats:
												UpperCAmelCase					=			key.replace(lowercase_		,     '_'.join(pat.split('.'						)						)						)
						return key

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_		,     lowercase_						):
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('scale',)
						if (
						    any('norm' in str_ for str_ in pt_tuple_key						)
						    and (pt_tuple_key[-1] == "bias")
						    and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
						    and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
						):
												UpperCAmelCase					=			pt_tuple_key[:-1] + ('scale',)
												return renamed_pt_tuple_key, pt_tensor
						elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
												UpperCAmelCase					=			pt_tuple_key[:-1] + ('scale',)
												return renamed_pt_tuple_key, pt_tensor

						# embedding
						if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
												UpperCAmelCase					=			pt_tuple_key[:-1] + ('embedding',)
												return renamed_pt_tuple_key, pt_tensor

						# conv layer
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('kernel',)
						if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
												UpperCAmelCase					=			pt_tensor.transpose(2		,     3		,     1		,     0						)
												return renamed_pt_tuple_key, pt_tensor

						# linear layer
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('kernel',)
						if pt_tuple_key[-1] == "weight":
												UpperCAmelCase					=			pt_tensor.T
												return renamed_pt_tuple_key, pt_tensor

						# old PyTorch layer norm weight
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('weight',)
						if pt_tuple_key[-1] == "gamma":
												return renamed_pt_tuple_key, pt_tensor

						# old PyTorch layer norm bias
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('bias',)
						if pt_tuple_key[-1] == "beta":
												return renamed_pt_tuple_key, pt_tensor

						return pt_tuple_key, pt_tensor






def 			_lowerCAmelCase				(       lowercase_		,     lowercase_		,     lowercase_=42						):
						# Step 1: Convert pytorch tensor to numpy
						UpperCAmelCase					=			{k: v.numpy() for k, v in pt_state_dict.items()}

						# Step 2: Since the model is stateless, get random Flax params
						UpperCAmelCase					=			flax_model.init_weights(PRNGKey(lowercase_						)						)

						UpperCAmelCase					=			flatten_dict(lowercase_						)
						UpperCAmelCase					=			{}

						# Need to change some parameters name to match Flax names
						for pt_key, pt_tensor in pt_state_dict.items():
												UpperCAmelCase					=			rename_key(lowercase_						)
												UpperCAmelCase					=			tuple(renamed_pt_key.split('.'						)						)

												# Correctly rename weight parameters
												UpperCAmelCase				,   UpperCAmelCase					=			rename_key_and_reshape_tensor(lowercase_		,     lowercase_		,     lowercase_						)

												if flax_key in random_flax_state_dict:
																		if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
																								raise ValueError(
																								    F"""PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape """
																								    F"""{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}."""						)

        # also add unexpected weight so that warning is thrown
												UpperCAmelCase					=			jnp.asarray(lowercase_						)

						return unflatten_dict(lowercase_						)





