

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    :       Dict        =							True
except ImportError:
     _lowerCamelCase    :       Tuple        =							False

_lowerCamelCase    :       List[str]        =							logging.get_logger(__name__)  # pylint: disable=invalid-name

def       a__					(		UpperCAmelCase							:      Namespace      )  ->						int:
  return AddNewModelCommand(args.testing    ,			args.testing_file    ,			path=args.path      )






class  __UpperCAmelCase					(	lowerCamelCase__						):



   @staticmethod
   def 	__magic_name__   (							__A							:					ArgumentParser						):
     UpperCAmelCase	:							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=__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							:					int,		__A							:					bool,		__A							:					str,		__A							:					List[str]=None,		*__A							:					int						):
     UpperCAmelCase	:							Any						=			testing
     UpperCAmelCase	:							int						=			testing_file
     UpperCAmelCase	:							int						=			path





   def 	__magic_name__   (							self							:					Dict						):
     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
     UpperCAmelCase	:							int						=			[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.'''						)

     UpperCAmelCase	:							str						=			(
         Path(__A						).parent.parent.parent.parent if self._path is None else Path(self._path						).parent.parent
     )
     UpperCAmelCase	:							Optional[int]						=			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:
         UpperCAmelCase	:							Tuple						=			json.load(__A						)

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

     UpperCAmelCase	:							str						=			[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:
       UpperCAmelCase	:							List[Any]						=			json.load(__A						)

     UpperCAmelCase	:							str						=			configuration['''lowercase_modelname''']
     UpperCAmelCase	:							Dict						=			configuration['''generate_tensorflow_pytorch_and_flax''']
     os.remove(F'''{directory}/configuration.json'''						)

     UpperCAmelCase	:							int						=			'''PyTorch''' in generate_tensorflow_pytorch_and_flax
     UpperCAmelCase	:							Dict						=			'''TensorFlow''' in generate_tensorflow_pytorch_and_flax
     UpperCAmelCase	:							Dict						=			'''Flax''' in generate_tensorflow_pytorch_and_flax

     UpperCAmelCase	:							str						=			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							:					str						):
       with open(__A,		'''r'''						) as f:
         UpperCAmelCase	:							str						=			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							:					str,		__A							:					str,		__A							:					List[str]						):
       # Create temp file
       UpperCAmelCase			,						UpperCAmelCase	:							List[str]						=			mkstemp()
       UpperCAmelCase	:							Any						=			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:
               UpperCAmelCase	:							Union[str, Any]						=			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							:					int						):
       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							:					Optional[int]						):
       with open(__A						) as datafile:
         UpperCAmelCase	:							Tuple						=			[]
         UpperCAmelCase	:							List[str]						=			False
         UpperCAmelCase	:							Dict						=			False
         for line in datafile:
           if "# To replace in: " in line and "##" not in line:
             UpperCAmelCase	:							Optional[int]						=			line.split('''"'''						)[1]
             UpperCAmelCase	:							List[Any]						=			skip_units(__A						)
           elif "# Below: " in line and "##" not in line:
             UpperCAmelCase	:							int						=			line.split('''"'''						)[1]
             UpperCAmelCase	:							List[str]						=			skip_units(__A						)
           elif "# End." in line and "##" not in line:
             if not skip_file and not skip_snippet:
               replace(__A,		__A,		__A						)

             UpperCAmelCase	:							Tuple						=			[]
           elif "# Replace with" in line and "##" not in line:
             UpperCAmelCase	:							Optional[Any]						=			[]
           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 Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
     from PIL import Image

     from ..image_utils import load_image

if is_torch_available():
     from ..models.auto.modeling_auto import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING

_lowerCamelCase    :       Dict        =							logging.get_logger(__name__)





@add_end_docstrings(lowerCamelCase__						)
class  __UpperCAmelCase					(	lowerCamelCase__						):



   def __init__(							self							:					Optional[Any],		*__A							:					Tuple,		**__A							:					Tuple						):
     super().__init__(*__A,		**__A						)
     self.check_model_type(__A						)



   def 	__magic_name__   (							self							:					Union[str, Any],		__A							:					int=None,		__A							:					Tuple=None,		__A							:					Any=None,		**__A							:					Optional[int]						):
     UpperCAmelCase			,						UpperCAmelCase	:							List[Any]						=			{}, {}
     if padding is not None:
       UpperCAmelCase	:							Optional[int]						=			padding
     if truncation is not None:
       UpperCAmelCase	:							Optional[int]						=			truncation
     if top_k is not None:
       UpperCAmelCase	:							Tuple						=			top_k
     return preprocess_params, {}, postprocess_params



   def __call__(							self							:					Union[str, Any],		__A							:					Union["Image.Image", str],		__A							:					str = None,		**__A							:					Optional[int]						):
     if isinstance(__A,		(Image.Image, str)						) and isinstance(__A,		__A						):
       UpperCAmelCase	:							int						=			{'''image''': image, '''question''': question}
     else:
       UpperCAmelCase	:							str						=			image
     UpperCAmelCase	:							Union[str, Any]						=			super().__call__(__A,		**__A						)
     return results



   def 	__magic_name__   (							self							:					List[str],		__A							:					Union[str, Any],		__A							:					Tuple=False,		__A							:					List[Any]=False						):
     UpperCAmelCase	:							int						=			load_image(inputs['''image''']						)
     UpperCAmelCase	:							List[str]						=			self.tokenizer(
         inputs['''question'''],		return_tensors=self.framework,		padding=__A,		truncation=__A						)
     UpperCAmelCase	:							Union[str, Any]						=			self.image_processor(images=__A,		return_tensors=self.framework						)
     model_inputs.update(__A						)
     return model_inputs



   def 	__magic_name__   (							self							:					Optional[Any],		__A							:					List[Any]						):
     UpperCAmelCase	:							Optional[int]						=			self.model(**__A						)
     return model_outputs





   def 	__magic_name__   (							self							:					Any,		__A							:					List[str],		__A							:					Union[str, Any]=5						):
     if top_k > self.model.config.num_labels:
       UpperCAmelCase	:							Any						=			self.model.config.num_labels

     if self.framework == "pt":
       UpperCAmelCase	:							Any						=			model_outputs.logits.sigmoid()[0]
       UpperCAmelCase			,						UpperCAmelCase	:							Union[str, Any]						=			probs.topk(__A						)
     else:
       raise ValueError(F'''Unsupported framework: {self.framework}'''						)

     UpperCAmelCase	:							str						=			scores.tolist()
     UpperCAmelCase	:							Tuple						=			ids.tolist()
     return [{"score": score, "answer": self.model.config.idalabel[_id]} for score, _id in zip(__A,		__A						)]





