

'''simple docstring'''


import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / """utils"""))

from test_module.custom_image_processing import CustomImageProcessor  # noqa E402


lowerCAmelCase__						:       Tuple										=						get_tests_dir("""fixtures""")




class     a			(				unittest.TestCase       ):






      """simple docstring"""




      def       __magic_name__							(							self					:      str  ):



        '''simple docstring'''



        snake_case__						:       Dict       						=  mock.Mock()
        snake_case__						:       str       						=  5_0_0
        snake_case__						:       int       						=  {}
        snake_case__						:       List[Any]       						=  HTTPError
        snake_case__						:       List[str]       						=  {}

        # Download this model to make sure it's in the cache.
        snake_case__						:       List[Any]       						=  ViTImageProcessor.from_pretrained('''hf-internal-testing/tiny-random-vit'''  )
        # Under the mock environment we get a 500 error when trying to reach the model.
        with mock.patch('''requests.Session.request'''			,			return_value=snake_case_  ) as mock_head:
          snake_case__						:       int       						=  ViTImageProcessor.from_pretrained('''hf-internal-testing/tiny-random-vit'''  )
          # This check we did call the fake head request
          mock_head.assert_called()







      def       __magic_name__							(							self					:      Union[str, Any]  ):



        '''simple docstring'''



        snake_case__						:       List[str]       						=  ViTImageProcessor.from_pretrained(
            '''https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json'''  )







      def       __magic_name__							(							self					:      str  ):



        '''simple docstring'''



        with self.assertRaises(snake_case_  ):
          # config is in subfolder, the following should not work without specifying the subfolder
          snake_case__						:       List[str]       						=  AutoImageProcessor.from_pretrained('''hf-internal-testing/stable-diffusion-all-variants'''  )

        snake_case__						:       List[Any]       						=  AutoImageProcessor.from_pretrained(
            '''hf-internal-testing/stable-diffusion-all-variants'''			,			subfolder='''feature_extractor'''  )

        self.assertIsNotNone(snake_case_  )





@is_staging_test
class     a			(				unittest.TestCase       ):






      """simple docstring"""




      @classmethod
      def       __magic_name__							(							cls					:      Optional[Any]  ):



        '''simple docstring'''



        snake_case__						:       Optional[Any]       						=  TOKEN
        HfFolder.save_token(snake_case_  )







      @classmethod
      def       __magic_name__							(							cls					:      Optional[int]  ):



        '''simple docstring'''



        try:
          delete_repo(token=cls._token			,			repo_id='''test-image-processor'''  )
        except HTTPError:
          pass

        try:
          delete_repo(token=cls._token			,			repo_id='''valid_org/test-image-processor-org'''  )
        except HTTPError:
          pass

        try:
          delete_repo(token=cls._token			,			repo_id='''test-dynamic-image-processor'''  )
        except HTTPError:
          pass







      def       __magic_name__							(							self					:      Optional[Any]  ):



        '''simple docstring'''



        snake_case__						:       Union[str, Any]       						=  ViTImageProcessor.from_pretrained(snake_case_  )
        image_processor.push_to_hub('''test-image-processor'''			,			use_auth_token=self._token  )

        snake_case__						:       Optional[Any]       						=  ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""  )
        for k, v in image_processor.__dict__.items():
          self.assertEqual(snake_case_			,			getattr(snake_case_			,			snake_case_  )  )

        # Reset repo
        delete_repo(token=self._token			,			repo_id='''test-image-processor'''  )

        # Push to hub via save_pretrained
        with tempfile.TemporaryDirectory() as tmp_dir:
          image_processor.save_pretrained(
              snake_case_			,			repo_id='''test-image-processor'''			,			push_to_hub=snake_case_			,			use_auth_token=self._token  )

        snake_case__						:       str       						=  ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""  )
        for k, v in image_processor.__dict__.items():
          self.assertEqual(snake_case_			,			getattr(snake_case_			,			snake_case_  )  )







      def       __magic_name__							(							self					:      Tuple  ):



        '''simple docstring'''



        snake_case__						:       List[str]       						=  ViTImageProcessor.from_pretrained(snake_case_  )
        image_processor.push_to_hub('''valid_org/test-image-processor'''			,			use_auth_token=self._token  )

        snake_case__						:       Tuple       						=  ViTImageProcessor.from_pretrained('''valid_org/test-image-processor'''  )
        for k, v in image_processor.__dict__.items():
          self.assertEqual(snake_case_			,			getattr(snake_case_			,			snake_case_  )  )

        # Reset repo
        delete_repo(token=self._token			,			repo_id='''valid_org/test-image-processor'''  )

        # Push to hub via save_pretrained
        with tempfile.TemporaryDirectory() as tmp_dir:
          image_processor.save_pretrained(
              snake_case_			,			repo_id='''valid_org/test-image-processor-org'''			,			push_to_hub=snake_case_			,			use_auth_token=self._token  )

        snake_case__						:       Any       						=  ViTImageProcessor.from_pretrained('''valid_org/test-image-processor-org'''  )
        for k, v in image_processor.__dict__.items():
          self.assertEqual(snake_case_			,			getattr(snake_case_			,			snake_case_  )  )







      def       __magic_name__							(							self					:      Union[str, Any]  ):



        '''simple docstring'''



        CustomImageProcessor.register_for_auto_class()
        snake_case__						:       List[str]       						=  CustomImageProcessor.from_pretrained(snake_case_  )

        image_processor.push_to_hub('''test-dynamic-image-processor'''			,			use_auth_token=self._token  )

        # This has added the proper auto_map field to the config
        self.assertDictEqual(
            image_processor.auto_map			,			{'''AutoImageProcessor''': '''custom_image_processing.CustomImageProcessor'''}			,			)

        snake_case__						:       List[str]       						=  AutoImageProcessor.from_pretrained(
            F"""{USER}/test-dynamic-image-processor"""			,			trust_remote_code=snake_case_  )
        # Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
        self.assertEqual(new_image_processor.__class__.__name__			,			'''CustomImageProcessor'''  )






'''simple docstring'''


# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


lowerCAmelCase__						:       List[Any]										=						"""Run commands across TPU VMs for initial setup before running `accelerate launch`."""




def 	_a       (				__lowerCAmelCase		:      Any=None     ):

		"""simple docstring"""

		if subparsers is not None:
				snake_case__						:       Tuple       						=  subparsers.add_parser('''tpu-config'''   ,							description=_description     )
		else:
				snake_case__						:       str       						=  argparse.ArgumentParser('''Accelerate tpu-config command'''   ,							description=_description     )
		# Core arguments
		snake_case__						:       Any       						=  parser.add_argument_group(
		    '''Config Arguments'''   ,							'''Arguments that can be configured through `accelerate config`.'''     )
		config_args.add_argument(
		    '''--config_file'''   ,							type=__lowerCAmelCase   ,							default=__lowerCAmelCase   ,							help='''Path to the config file to use for accelerate.'''   ,							)
		config_args.add_argument(
		    '''--tpu_name'''   ,							default=__lowerCAmelCase   ,							help='''The name of the TPU to use. If not specified, will use the TPU specified in the config file.'''   ,							)
		config_args.add_argument(
		    '''--tpu_zone'''   ,							default=__lowerCAmelCase   ,							help='''The zone of the TPU to use. If not specified, will use the zone specified in the config file.'''   ,							)
		snake_case__						:       Optional[Any]       						=  parser.add_argument_group('''TPU Arguments'''   ,							'''Arguments for options ran inside the TPU.'''     )
		pod_args.add_argument(
		    '''--use_alpha'''   ,							action='''store_true'''   ,							help='''Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`.'''   ,							)
		pod_args.add_argument(
		    '''--command_file'''   ,							default=__lowerCAmelCase   ,							help='''The path to the file containing the commands to run on the pod on startup.'''   ,							)
		pod_args.add_argument(
		    '''--command'''   ,							action='''append'''   ,							nargs='''+'''   ,							help='''A command to run on the pod. Can be passed multiple times.'''   ,							)
		pod_args.add_argument(
		    '''--install_accelerate'''   ,							action='''store_true'''   ,							help='''Whether to install accelerate on the pod. Defaults to False.'''   ,							)
		pod_args.add_argument(
		    '''--accelerate_version'''   ,							default='''latest'''   ,							help='''The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify \'dev\' to install from GitHub.'''   ,							)
		pod_args.add_argument(
		    '''--debug'''   ,							action='''store_true'''   ,							help='''If set, will print the command that would be run instead of running it.'''     )

		if subparsers is not None:
				parser.set_defaults(func=__lowerCAmelCase     )
		return parser




def 	_a       (				__lowerCAmelCase		:      Optional[Any]     ):

		"""simple docstring"""

		snake_case__						:       Optional[int]       						=  None

		# Get the default from the config file if it exists.
		if args.config_file is not None or os.path.isfile(__lowerCAmelCase     ):
				snake_case__						:       Tuple       						=  load_config_from_file(args.config_file     )
				if not args.command_file and defaults.command_file is not None and not args.command:
						snake_case__						:       Optional[int]       						=  defaults.command_file
				if not args.command and defaults.commands is not None:
						snake_case__						:       Union[str, Any]       						=  defaults.commands
				if not args.tpu_name:
						snake_case__						:       Union[str, Any]       						=  defaults.tpu_name
				if not args.tpu_zone:
						snake_case__						:       Optional[Any]       						=  defaults.tpu_zone
		if args.accelerate_version == "dev":
				snake_case__						:       Tuple       						=  '''git+https://github.com/huggingface/accelerate.git'''
		elif args.accelerate_version == "latest":
				snake_case__						:       Union[str, Any]       						=  '''accelerate -U'''
		elif isinstance(parse(args.accelerate_version     )   ,							__lowerCAmelCase     ):
				snake_case__						:       Any       						=  F"""accelerate=={args.accelerate_version}"""

		if not args.command_file and not args.command:
				raise ValueError('''You must specify either a command file or a command to run on the pod.'''     )

		if args.command_file:
				with open(args.command_file   ,							'''r'''     ) as f:
						snake_case__						:       str       						=  [f.read().splitlines()]

    # To turn list of lists into list of strings
		if isinstance(args.command[0]   ,							__lowerCAmelCase     ):
				snake_case__						:       List[Any]       						=  [line for cmd in args.command for line in cmd]
		# Default to the shared folder and install accelerate
		snake_case__						:       Optional[int]       						=  ['''cd /usr/share''']
		if args.install_accelerate:
				new_cmd += [F"""pip install {args.accelerate_version}"""]
		new_cmd += args.command
		snake_case__						:       Tuple       						=  '''; '''.join(__lowerCAmelCase     )

		# Then send it to gcloud
		# Eventually try to use google-api-core to do this instead of subprocess
		snake_case__						:       str       						=  ['''gcloud''']
		if args.use_alpha:
				cmd += ["alpha"]
		cmd += [
		    "compute",
		    "tpus",
		    "tpu-vm",
		    "ssh",
		    args.tpu_name,
		    "--zone",
		    args.tpu_zone,
		    "--command",
		    args.command,
		    "--worker",
		    "all",
		]
		if args.debug:
				print(F"""Running {' '.join(__lowerCAmelCase     )}"""     )
				return
		subprocess.run(__lowerCAmelCase     )
		print('''Successfully setup pod.'''     )





def 	_a       (				):

		"""simple docstring"""

		snake_case__						:       Dict       						=  tpu_command_parser()
		snake_case__						:       Dict       						=  parser.parse_args()

		tpu_command_launcher(__lowerCAmelCase     )



