





'''simple docstring'''

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_					= True
except ImportError:
      lowercase_					= False

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





def lowerCamelCase						(     __lowerCamelCase :    Namespace    )						->Optional[Any]:
    return AddNewModelCommand(args.testing					,       args.testing_file					,       path=args.path    )






class 					a_     (				snake_case_       ):

    '''simple docstring'''


    @staticmethod
    def 			snake_case_(		A       )		->   Tuple:
        _SCREAMING_SNAKE_CASE									=			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       )		->   Union[str, Any]:
        _SCREAMING_SNAKE_CASE									=			testing
        _SCREAMING_SNAKE_CASE									=			testing_file
        _SCREAMING_SNAKE_CASE									=			path





    def 			snake_case_(		self       )		->   List[str]:
        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
        _SCREAMING_SNAKE_CASE									=			[directory for directory in os.listdir() if """cookiecutter-template-""" == directory[:22]]
        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."""       )

        _SCREAMING_SNAKE_CASE									=			(
            Path(A       ).parent.parent.parent.parent if self._path is None else Path(self._path       ).parent.parent
        )
        _SCREAMING_SNAKE_CASE									=			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:
                _SCREAMING_SNAKE_CASE									=			json.load(A       )

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

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

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

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

        _SCREAMING_SNAKE_CASE									=			"""PyTorch""" in generate_tensorflow_pytorch_and_flax
        _SCREAMING_SNAKE_CASE									=			"""TensorFlow""" in generate_tensorflow_pytorch_and_flax
        _SCREAMING_SNAKE_CASE									=			"""Flax""" in generate_tensorflow_pytorch_and_flax

        _SCREAMING_SNAKE_CASE									=			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:
                _SCREAMING_SNAKE_CASE									=			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
            _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE									=			mkstemp()
            _SCREAMING_SNAKE_CASE									=			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:
                            _SCREAMING_SNAKE_CASE									=			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:
                _SCREAMING_SNAKE_CASE									=			[]
                _SCREAMING_SNAKE_CASE									=			False
                _SCREAMING_SNAKE_CASE									=			False
                for line in datafile:
                    if "# To replace in: " in line and "##" not in line:
                        _SCREAMING_SNAKE_CASE									=			line.split("""\""""       )[1]
                        _SCREAMING_SNAKE_CASE									=			skip_units(A       )
                    elif "# Below: " in line and "##" not in line:
                        _SCREAMING_SNAKE_CASE									=			line.split("""\""""       )[1]
                        _SCREAMING_SNAKE_CASE									=			skip_units(A       )
                    elif "# End." in line and "##" not in line:
                        if not skip_file and not skip_snippet:
                            replace(A ,		A ,		A       )

                        _SCREAMING_SNAKE_CASE									=			[]
                    elif "# Replace with" in line and "##" not in line:
                        _SCREAMING_SNAKE_CASE									=			[]
                    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       )










'''simple docstring'''

import argparse
import shlex

import runhouse as rh


if __name__ == "__main__":
      # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
      # setup instructions, if using on-demand hardware

      # If user passes --user <user> --host <host> --key_path <key_path> <example> <args>, fill them in as BYO cluster
      # If user passes --instance <instance> --provider <provider> <example> <args>, fill them in as on-demand cluster
      # Throw an error if user passes both BYO and on-demand cluster args
      # Otherwise, use default values
      lowercase_					= argparse.ArgumentParser()
      parser.add_argument("""--user""", type=str, default="""ubuntu""")
      parser.add_argument("""--host""", type=str, default="""localhost""")
      parser.add_argument("""--key_path""", type=str, default=None)
      parser.add_argument("""--instance""", type=str, default="""V100:1""")
      parser.add_argument("""--provider""", type=str, default="""cheapest""")
      parser.add_argument("""--use_spot""", type=bool, default=False)
      parser.add_argument("""--example""", type=str, default="""pytorch/text-generation/run_generation.py""")
      lowercase_				,			lowercase_					= parser.parse_known_args()
      if args.host != "localhost":
            if args.instance != "V100:1" or args.provider != "cheapest":
                  raise ValueError("""Cannot specify both BYO and on-demand cluster args""")
            lowercase_					= rh.cluster(
                name="""rh-cluster""", ips=[args.host], ssh_creds={"""ssh_user""": args.user, """ssh_private_key""": args.key_path}
            )
      else:
            lowercase_					= rh.cluster(
                name="""rh-cluster""", instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
            )
      lowercase_					= args.example.rsplit("""/""", 1)[0]

      # Set up remote environment
      cluster.install_packages(["""pip:./"""])  # Installs transformers from local source
      # Note transformers is copied into the home directory on the remote machine, so we can install from there
      cluster.run([f"""pip install -r transformers/examples/{example_dir}/requirements.txt"""])
      cluster.run(["""pip install torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117"""])

      # Run example. You can bypass the CLI wrapper and paste your own code here.
      cluster.run([f"""python transformers/examples/{args.example} {" ".join(shlex.quote(arg) for arg in unknown)}"""])

      # Alternatively, we can just import and run a training function (especially if there's no wrapper CLI):
      # from my_script... import train
      # reqs = ['pip:./', 'torch', 'datasets', 'accelerate', 'evaluate', 'tqdm', 'scipy', 'scikit-learn', 'tensorboard']
      # launch_train_gpu = rh.function(fn=train,
      #                                system=gpu,
      #                                reqs=reqs,
      #                                name='train_bert_glue')
      #
      # We can pass in arguments just like we would to a function:
      # launch_train_gpu(num_epochs = 3, lr = 2e-5, seed = 42, batch_size = 16
      #                  stream_logs=True)



