"""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


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

__lowerCamelCase											=  "=======\n>>>>>>>\n"

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

__lowerCamelCase											=  [
    # (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					(	UpperCamelCase__				):






       """simple docstring"""





       return ConvertCommand(args.tfds_path       ,    args.datasets_directory				)


class     UpperCamelCase__(			__A ):





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





      def __init__(       self		,__UpperCAmelCase		,__UpperCAmelCase		,*__UpperCAmelCase     )					->				Any:
             A__	     =							get_logger('datasets-cli/converting'     )

             A__	     =							tfds_path
             A__	     =							datasets_directory





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

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

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

             A__	     =							[]
             A__	     =							[]
             A__	     =							{}

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

             for f_name in file_names:
                    self._logger.info(f'''Looking at file {f_name}'''     )
                    A__	     =							os.path.join(__UpperCAmelCase		,__UpperCAmelCase     )
                    A__	     =							os.path.join(__UpperCAmelCase		,__UpperCAmelCase     )

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

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

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

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

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

                    if needs_manual_update:
                           with_manual_update.append(__UpperCAmelCase     )

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

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

import torch
from torch import nn

from diffusers.models.activations import get_activation
class     UpperCamelCase__(			unittest.TestCase ):





						def 				snake_case__	(       self     )					->				str:
													A__	     =							get_activation('swish'     )

													self.assertIsInstance(__UpperCAmelCase		,nn.SiLU     )

													self.assertEqual(act(torch.tensor(-1_00		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertNotEqual(act(torch.tensor(-1		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(0		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(20		,dtype=torch.floataa     )     ).item()		,20     )





						def 				snake_case__	(       self     )					->				Optional[Any]:
													A__	     =							get_activation('silu'     )

													self.assertIsInstance(__UpperCAmelCase		,nn.SiLU     )

													self.assertEqual(act(torch.tensor(-1_00		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertNotEqual(act(torch.tensor(-1		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(0		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(20		,dtype=torch.floataa     )     ).item()		,20     )





						def 				snake_case__	(       self     )					->				List[str]:
													A__	     =							get_activation('mish'     )

													self.assertIsInstance(__UpperCAmelCase		,nn.Mish     )

													self.assertEqual(act(torch.tensor(-2_00		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertNotEqual(act(torch.tensor(-1		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(0		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(20		,dtype=torch.floataa     )     ).item()		,20     )





						def 				snake_case__	(       self     )					->				List[str]:
													A__	     =							get_activation('gelu'     )

													self.assertIsInstance(__UpperCAmelCase		,nn.GELU     )

													self.assertEqual(act(torch.tensor(-1_00		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertNotEqual(act(torch.tensor(-1		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(0		,dtype=torch.floataa     )     ).item()		,0     )
													self.assertEqual(act(torch.tensor(20		,dtype=torch.floataa     )     ).item()		,20     )





