
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
			from cookiecutter.main import cookiecutter

			__A							=True
except ImportError:
			__A							=False

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





def      lowerCamelCase_					(							lowerCamelCase__       ):
				return AddNewModelCommand(args.testing      ,					args.testing_file      ,					path=args.path       )





class        _SCREAMING_SNAKE_CASE	( snake_case_		):



	@staticmethod
	def        SCREAMING_SNAKE_CASE_(       lowercase					)							->			Union[str, Any]:
					lowerCamelCase_         =     parser.add_parser("add-new-model"					)
					add_new_model_parser.add_argument("--testing"		,    action="store_true"		,    help="If in testing mode."					)
					add_new_model_parser.add_argument("--testing_file"		,    type=lowercase		,    help="Configuration file on which to run."					)
					add_new_model_parser.add_argument(
					    "--path"		,    type=lowercase		,    help="Path to cookiecutter. Should only be used for testing purposes."					)
					add_new_model_parser.set_defaults(func=lowercase					)



	def __init__(       self		,    lowercase		,    lowercase		,    lowercase=None		,    *lowercase					)							->			Dict:
					lowerCamelCase_         =     testing
					lowerCamelCase_         =     testing_file
					lowerCamelCase_         =     path



	def        SCREAMING_SNAKE_CASE_(       self					)							->			List[Any]:
					warnings.warn(
					    "The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. "
					    "It is not actively maintained anymore, so might give a result that won't pass all tests and quality "
					    "checks, you should use `transformers-cli add-new-model-like` instead."					)
					if not _has_cookiecutter:
									raise ImportError(
									    "Model creation dependencies are required to use the `add_new_model` command. Install them by running "
									    "the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n"					)
					# Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
					lowerCamelCase_         =     [directory for directory in os.listdir() if "cookiecutter-template-" == directory[:22]]
					if len(lowercase					) > 0:
									raise ValueError(
									    "Several directories starting with `cookiecutter-template-` in current working directory. "
									    "Please clean your directory by removing all folders starting with `cookiecutter-template-` or "
									    "change your working directory."					)

					lowerCamelCase_         =     (
					    Path(lowercase					).parent.parent.parent.parent if self._path is None else Path(self._path					).parent.parent
					)
					lowerCamelCase_         =     path_to_transformer_root / "templates" / "adding_a_new_model"

					# Execute cookiecutter
					if not self._testing:
									cookiecutter(str(lowercase					)					)
					else:
									with open(self._testing_file		,    "r"					) as configuration_file:
													lowerCamelCase_         =     json.load(lowercase					)

									cookiecutter(
									    str(path_to_cookiecutter if self._path is None else self._path					)		,    no_input=lowercase		,    extra_context=lowercase		,    )

					lowerCamelCase_         =     [directory for directory in os.listdir() if "cookiecutter-template-" in directory[:22]][0]

					# Retrieve configuration
					with open(directory + "/configuration.json"		,    "r"					) as configuration_file:
									lowerCamelCase_         =     json.load(lowercase					)

					lowerCamelCase_         =     configuration["lowercase_modelname"]
					lowerCamelCase_         =     configuration["generate_tensorflow_pytorch_and_flax"]
					os.remove(f'{directory}/configuration.json'					)

					lowerCamelCase_         =     "PyTorch" in generate_tensorflow_pytorch_and_flax
					lowerCamelCase_         =     "TensorFlow" in generate_tensorflow_pytorch_and_flax
					lowerCamelCase_         =     "Flax" in generate_tensorflow_pytorch_and_flax

					lowerCamelCase_         =     f'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
					os.makedirs(lowercase		,    exist_ok=lowercase					)
					os.makedirs(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}'		,    exist_ok=lowercase					)

					# Tests require submodules as they have parent imports
					with open(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py'		,    "w"					):
									pass

					shutil.move(
					    f'{directory}/__init__.py'		,    f'{model_dir}/__init__.py'		,    )
					shutil.move(
					    f'{directory}/configuration_{lowercase_model_name}.py'		,    f'{model_dir}/configuration_{lowercase_model_name}.py'		,    )

					def remove_copy_lines(lowercase					):
									with open(lowercase		,    "r"					) as f:
													lowerCamelCase_         =     f.readlines()
									with open(lowercase		,    "w"					) as f:
													for line in lines:
																	if "# Copied from transformers." not in line:
																					f.write(lowercase					)

					if output_pytorch:
									if not self._testing:
													remove_copy_lines(f'{directory}/modeling_{lowercase_model_name}.py'					)

									shutil.move(
									    f'{directory}/modeling_{lowercase_model_name}.py'		,    f'{model_dir}/modeling_{lowercase_model_name}.py'		,    )

									shutil.move(
									    f'{directory}/test_modeling_{lowercase_model_name}.py'		,    f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py'		,    )
					else:
									os.remove(f'{directory}/modeling_{lowercase_model_name}.py'					)
									os.remove(f'{directory}/test_modeling_{lowercase_model_name}.py'					)

					if output_tensorflow:
									if not self._testing:
													remove_copy_lines(f'{directory}/modeling_tf_{lowercase_model_name}.py'					)

									shutil.move(
									    f'{directory}/modeling_tf_{lowercase_model_name}.py'		,    f'{model_dir}/modeling_tf_{lowercase_model_name}.py'		,    )

									shutil.move(
									    f'{directory}/test_modeling_tf_{lowercase_model_name}.py'		,    f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py'		,    )
					else:
									os.remove(f'{directory}/modeling_tf_{lowercase_model_name}.py'					)
									os.remove(f'{directory}/test_modeling_tf_{lowercase_model_name}.py'					)

					if output_flax:
									if not self._testing:
													remove_copy_lines(f'{directory}/modeling_flax_{lowercase_model_name}.py'					)

									shutil.move(
									    f'{directory}/modeling_flax_{lowercase_model_name}.py'		,    f'{model_dir}/modeling_flax_{lowercase_model_name}.py'		,    )

									shutil.move(
									    f'{directory}/test_modeling_flax_{lowercase_model_name}.py'		,    f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py'		,    )
					else:
									os.remove(f'{directory}/modeling_flax_{lowercase_model_name}.py'					)
									os.remove(f'{directory}/test_modeling_flax_{lowercase_model_name}.py'					)

					shutil.move(
					    f'{directory}/{lowercase_model_name}.md'		,    f'{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md'		,    )

					shutil.move(
					    f'{directory}/tokenization_{lowercase_model_name}.py'		,    f'{model_dir}/tokenization_{lowercase_model_name}.py'		,    )

					shutil.move(
					    f'{directory}/tokenization_fast_{lowercase_model_name}.py'		,    f'{model_dir}/tokenization_{lowercase_model_name}_fast.py'		,    )

					from os import fdopen, remove
					from shutil import copymode, move
					from tempfile import mkstemp

					def replace(lowercase		,    lowercase		,    lowercase					):
									# Create temp file
									lowerCamelCase_      ,       lowerCamelCase_         =     mkstemp()
									lowerCamelCase_         =     False
									with fdopen(lowercase		,    "w"					) as new_file:
													with open(lowercase					) as old_file:
																	for line in old_file:
																					new_file.write(lowercase					)
																					if line_to_copy_below in line:
																									lowerCamelCase_         =     True
																									for line_to_copy in lines_to_copy:
																													new_file.write(lowercase					)

									if not line_found:
													raise ValueError(f'Line {line_to_copy_below} was not found in file.'					)

									# Copy the file permissions from the old file to the new file
									copymode(lowercase		,    lowercase					)
									# Remove original file
									remove(lowercase					)
									# Move new file
									move(lowercase		,    lowercase					)

					def skip_units(lowercase					):
									return (
									    ("generating PyTorch" in line and not output_pytorch)
									    or ("generating TensorFlow" in line and not output_tensorflow)
									    or ("generating Flax" in line and not output_flax)
									)

					def replace_in_files(lowercase					):
									with open(lowercase					) as datafile:
													lowerCamelCase_         =     []
													lowerCamelCase_         =     False
													lowerCamelCase_         =     False
													for line in datafile:
																	if "# To replace in: " in line and "##" not in line:
																					lowerCamelCase_         =     line.split("\""					)[1]
																					lowerCamelCase_         =     skip_units(lowercase					)
																	elif "# Below: " in line and "##" not in line:
																					lowerCamelCase_         =     line.split("\""					)[1]
																					lowerCamelCase_         =     skip_units(lowercase					)
																	elif "# End." in line and "##" not in line:
																					if not skip_file and not skip_snippet:
																									replace(lowercase		,    lowercase		,    lowercase					)

																					lowerCamelCase_         =     []
																	elif "# Replace with" in line and "##" not in line:
																					lowerCamelCase_         =     []
																	elif "##" not in line:
																					lines_to_copy.append(lowercase					)

									remove(lowercase					)

					replace_in_files(f'{directory}/to_replace_{lowercase_model_name}.py'					)
					os.rmdir(lowercase					)




import warnings
from contextlib import contextmanager

from ....processing_utils import ProcessorMixin




class        _SCREAMING_SNAKE_CASE	( snake_case_		):
	lowerCAmelCase__   =					'MCTCTFeatureExtractor'
	lowerCAmelCase__   =					'AutoTokenizer'



	def __init__(       self		,    lowercase		,    lowercase					)							->			str:
					super().__init__(lowercase		,    lowercase					)
					lowerCamelCase_         =     self.feature_extractor
					lowerCamelCase_         =     False



	def __call__(       self		,    *lowercase		,    **lowercase					)							->			List[str]:
					# For backward compatibility
					if self._in_target_context_manager:
									return self.current_processor(*lowercase		,    **lowercase					)

					if "raw_speech" in kwargs:
									warnings.warn("Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead."					)
									lowerCamelCase_         =     kwargs.pop("raw_speech"					)
					else:
									lowerCamelCase_         =     kwargs.pop("audio"		,    lowercase					)
					lowerCamelCase_         =     kwargs.pop("sampling_rate"		,    lowercase					)
					lowerCamelCase_         =     kwargs.pop("text"		,    lowercase					)
					if len(lowercase					) > 0:
									lowerCamelCase_         =     args[0]
									lowerCamelCase_         =     args[1:]

					if audio is None and text is None:
									raise ValueError("You need to specify either an `audio` or `text` input to process."					)

					if audio is not None:
									lowerCamelCase_         =     self.feature_extractor(lowercase		,    *lowercase		,    sampling_rate=lowercase		,    **lowercase					)
					if text is not None:
									lowerCamelCase_         =     self.tokenizer(lowercase		,    **lowercase					)

					if text is None:
									return inputs
					elif audio is None:
									return encodings
					else:
									lowerCamelCase_         =     encodings["input_ids"]
									return inputs



	def        SCREAMING_SNAKE_CASE_(       self		,    *lowercase		,    **lowercase					)							->			Optional[Any]:
					return self.tokenizer.batch_decode(*lowercase		,    **lowercase					)



	def        SCREAMING_SNAKE_CASE_(       self		,    *lowercase		,    **lowercase					)							->			Optional[Any]:
					# For backward compatibility
					if self._in_target_context_manager:
									return self.current_processor.pad(*lowercase		,    **lowercase					)

					lowerCamelCase_         =     kwargs.pop("input_features"		,    lowercase					)
					lowerCamelCase_         =     kwargs.pop("labels"		,    lowercase					)
					if len(lowercase					) > 0:
									lowerCamelCase_         =     args[0]
									lowerCamelCase_         =     args[1:]

					if input_features is not None:
									lowerCamelCase_         =     self.feature_extractor.pad(lowercase		,    *lowercase		,    **lowercase					)
					if labels is not None:
									lowerCamelCase_         =     self.tokenizer.pad(lowercase		,    **lowercase					)

					if labels is None:
									return input_features
					elif input_features is None:
									return labels
					else:
									lowerCamelCase_         =     labels["input_ids"]
									return input_features



	def        SCREAMING_SNAKE_CASE_(       self		,    *lowercase		,    **lowercase					)							->			List[str]:
					return self.tokenizer.decode(*lowercase		,    **lowercase					)



	@contextmanager
	def        SCREAMING_SNAKE_CASE_(       self					)							->			Optional[int]:
					warnings.warn(
					    "`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your "
					    "labels by using the argument `text` of the regular `__call__` method (either in the same call as "
					    "your audio inputs, or in a separate call."					)
					lowerCamelCase_         =     True
					lowerCamelCase_         =     self.tokenizer
					yield
					lowerCamelCase_         =     self.feature_extractor
					lowerCamelCase_         =     False


