



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

						lowerCamelCase		       =      True
except ImportError:
						lowerCamelCase		       =      False

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






def     SCREAMING_SNAKE_CASE(      __UpperCamelCase )	->						Any:
				return AddNewModelCommand(args.testing	,				args.testing_file	,				path=args.path )






class 				_a						(       SCREAMING_SNAKE_CASE			):





							'''simple docstring'''

							@staticmethod
							def 		_A	(							__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							int      						= 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=__UpperCAmelCase ,					help="Configuration file on which to run."				)
											add_new_model_parser.add_argument(
											    "--path" ,					type=__UpperCAmelCase ,					help="Path to cookiecutter. Should only be used for testing purposes."				)
											add_new_model_parser.set_defaults(func=__UpperCAmelCase				)



							def __init__(							self ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase=None ,					*__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							Tuple      						= testing
											a__	:							Optional[int]      						= testing_file
											a__	:							Any      						= path




							def 		_A	(							self				):







											"""simple docstring"""



											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
											a__	:							int      						= [directory for directory in os.listdir() if "cookiecutter-template-" == directory[:22]]
											if len(__UpperCAmelCase				) > 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."				)

											a__	:							Optional[int]      						= (
											    Path(__UpperCAmelCase				).parent.parent.parent.parent if self._path is None else Path(self._path				).parent.parent
											)
											a__	:							List[str]      						= path_to_transformer_root / "templates" / "adding_a_new_model"

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

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

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

											# Retrieve configuration
											with open(directory + "/configuration.json" ,					"r"				) as configuration_file:
															a__	:							Optional[int]      						= json.load(__UpperCAmelCase				)

											a__	:							Optional[int]      						= configuration["lowercase_modelname"]
											a__	:							Optional[Any]      						= configuration["generate_tensorflow_pytorch_and_flax"]
											os.remove(f'{directory}/configuration.json'				)

											a__	:							Dict      						= "PyTorch" in generate_tensorflow_pytorch_and_flax
											a__	:							List[str]      						= "TensorFlow" in generate_tensorflow_pytorch_and_flax
											a__	:							int      						= "Flax" in generate_tensorflow_pytorch_and_flax

											a__	:							Tuple      						= f'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
											os.makedirs(__UpperCAmelCase ,					exist_ok=__UpperCAmelCase				)
											os.makedirs(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}' ,					exist_ok=__UpperCAmelCase				)

											# 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(__UpperCAmelCase				):
															with open(__UpperCAmelCase ,					"r"				) as f:
																			a__	:							Optional[Any]      						= f.readlines()
															with open(__UpperCAmelCase ,					"w"				) as f:
																			for line in lines:
																							if "# Copied from transformers." not in line:
																											f.write(__UpperCAmelCase				)

											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(__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				):
															# Create temp file
															a__						,   a__	:							List[Any]      						= mkstemp()
															a__	:							Tuple      						= False
															with fdopen(__UpperCAmelCase ,					"w"				) as new_file:
																			with open(__UpperCAmelCase				) as old_file:
																							for line in old_file:
																											new_file.write(__UpperCAmelCase				)
																											if line_to_copy_below in line:
																															a__	:							Dict      						= True
																															for line_to_copy in lines_to_copy:
																																			new_file.write(__UpperCAmelCase				)

															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(__UpperCAmelCase ,					__UpperCAmelCase				)
															# Remove original file
															remove(__UpperCAmelCase				)
															# Move new file
															move(__UpperCAmelCase ,					__UpperCAmelCase				)

											def skip_units(__UpperCAmelCase				):
															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(__UpperCAmelCase				):
															with open(__UpperCAmelCase				) as datafile:
																			a__	:							Optional[int]      						= []
																			a__	:							Union[str, Any]      						= False
																			a__	:							Dict      						= False
																			for line in datafile:
																							if "# To replace in: " in line and "##" not in line:
																											a__	:							Optional[int]      						= line.split("\""				)[1]
																											a__	:							Union[str, Any]      						= skip_units(__UpperCAmelCase				)
																							elif "# Below: " in line and "##" not in line:
																											a__	:							str      						= line.split("\""				)[1]
																											a__	:							Optional[Any]      						= skip_units(__UpperCAmelCase				)
																							elif "# End." in line and "##" not in line:
																											if not skip_file and not skip_snippet:
																															replace(__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				)

																											a__	:							Dict      						= []
																							elif "# Replace with" in line and "##" not in line:
																											a__	:							Tuple      						= []
																							elif "##" not in line:
																											lines_to_copy.append(__UpperCAmelCase				)

															remove(__UpperCAmelCase				)

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







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase		       =      {
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase		       =      ["""BlipImageProcessor"""]


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase		       =      [
						    """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """BlipModel""",
						    """BlipPreTrainedModel""",
						    """BlipForConditionalGeneration""",
						    """BlipForQuestionAnswering""",
						    """BlipVisionModel""",
						    """BlipTextModel""",
						    """BlipForImageTextRetrieval""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase		       =      [
						    """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TFBlipModel""",
						    """TFBlipPreTrainedModel""",
						    """TFBlipForConditionalGeneration""",
						    """TFBlipForQuestionAnswering""",
						    """TFBlipVisionModel""",
						    """TFBlipTextModel""",
						    """TFBlipForImageTextRetrieval""",
						]

if TYPE_CHECKING:
						from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
						from .processing_blip import BlipProcessor

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_blip import BlipImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_blip import (
												    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BlipForConditionalGeneration,
												    BlipForImageTextRetrieval,
												    BlipForQuestionAnswering,
												    BlipModel,
												    BlipPreTrainedModel,
												    BlipTextModel,
												    BlipVisionModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_blip import (
												    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFBlipForConditionalGeneration,
												    TFBlipForImageTextRetrieval,
												    TFBlipForQuestionAnswering,
												    TFBlipModel,
												    TFBlipPreTrainedModel,
												    TFBlipTextModel,
												    TFBlipVisionModel,
												)

else:
						import sys

						lowerCamelCase		       =      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


