
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

       lowercase__		:str			  =   True
except ImportError:
       lowercase__		:List[Any]			  =   False

lowercase__		:Union[str, Any]			  =   logging.get_logger(__name__)  # pylint: disable=invalid-name



def 	UpperCamelCase   (							lowerCAmelCase__		):
     '''simple docstring'''
     return AddNewModelCommand(args.testing			,      args.testing_file			,      path=args.path		)







class     lowercase		( SCREAMING_SNAKE_CASE__		):




       @staticmethod
       def 			A__				(    A__):
            lowercase						     =						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=A__       ,help='''Configuration file on which to run.''')
            add_new_model_parser.add_argument(
                '''--path'''       ,type=A__       ,help='''Path to cookiecutter. Should only be used for testing purposes.''')
            add_new_model_parser.set_defaults(func=A__)




       def __init__(    self       ,A__       ,A__       ,A__=None       ,*A__):
            lowercase						     =						testing
            lowercase						     =						testing_file
            lowercase						     =						path





       def 			A__				(    self):
            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
            lowercase						     =						[directory for directory in os.listdir() if '''cookiecutter-template-''' == directory[:2_2]]
            if len(A__) > 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.''')

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

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

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

            lowercase						     =						[directory for directory in os.listdir() if '''cookiecutter-template-''' in directory[:2_2]][0]

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

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

            lowercase						     =						'''PyTorch''' in generate_tensorflow_pytorch_and_flax
            lowercase						     =						'''TensorFlow''' in generate_tensorflow_pytorch_and_flax
            lowercase						     =						'''Flax''' in generate_tensorflow_pytorch_and_flax

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

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

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

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

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

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

                 remove(A__)

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






from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowercase__		:Union[str, Any]			  =   {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:List[Any]			  =   ["DPTFeatureExtractor"]
							lowercase__		:List[Any]			  =   ["DPTImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Optional[int]			  =   [
							    "DPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "DPTForDepthEstimation",
							    "DPTForSemanticSegmentation",
							    "DPTModel",
							    "DPTPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_dpt import DPTFeatureExtractor
														from .image_processing_dpt import DPTImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_dpt import (
														    DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DPTForDepthEstimation,
														    DPTForSemanticSegmentation,
														    DPTModel,
														    DPTPreTrainedModel,
														)


else:
							import sys

							lowercase__		:List[Any]			  =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




