




"""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


A   =       """Run commands across TPU VMs for initial setup before running `accelerate launch`."""

def 					_UpperCamelCase    (			UpperCamelCase=None							)			->			Union[str, Any]:


			"""simple docstring"""
			if subparsers is not None:
						__UpperCAmelCase	: Optional[Any]		=					subparsers.add_parser("tpu-config"				,       description=_description							)
			else:
						__UpperCAmelCase	: Tuple		=					argparse.ArgumentParser("Accelerate tpu-config command"				,       description=_description							)
			# Core arguments
			__UpperCAmelCase	: int		=					parser.add_argument_group(
			    "Config Arguments"				,       "Arguments that can be configured through `accelerate config`."							)
			config_args.add_argument(
			    "--config_file"				,       type=UpperCamelCase				,       default=UpperCamelCase				,       help="Path to the config file to use for accelerate."				,       )
			config_args.add_argument(
			    "--tpu_name"				,       default=UpperCamelCase				,       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=UpperCamelCase				,       help="The zone of the TPU to use. If not specified, will use the zone specified in the config file."				,       )
			__UpperCAmelCase	: Union[str, 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=UpperCamelCase				,       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=UpperCamelCase							)
			return parser

def 					_UpperCamelCase    (			UpperCamelCase							)			->			Dict:


			"""simple docstring"""
			__UpperCAmelCase	: List[Any]		=					None

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

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

			# Then send it to gcloud
			# Eventually try to use google-api-core to do this instead of subprocess
			__UpperCAmelCase	: Union[str, Any]		=					["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(UpperCamelCase							)}"							)
						return
			subprocess.run(UpperCamelCase							)
			print("Successfully setup pod."							)





def 					_UpperCamelCase    (			)			->			List[Any]:


			"""simple docstring"""
			__UpperCAmelCase	: List[Any]		=					tpu_command_parser()
			__UpperCAmelCase	: Dict		=					parser.parse_args()

			tpu_command_launcher(UpperCamelCase							)








"""simple docstring"""





from ...processing_utils import ProcessorMixin



class      a__				(	__magic_name__   ):
			lowercase_    =	["image_processor", "feature_extractor"]
			lowercase_    =	"TvltImageProcessor"
			lowercase_    =	"TvltFeatureExtractor"


			def __init__(      self      :    Tuple      ,  UpperCamelCase_      :    Optional[int]      ,  UpperCamelCase_      :    Dict):


						"""simple docstring"""




						super().__init__(image_processor=UpperCamelCase_      ,  feature_extractor=UpperCamelCase_)

						__UpperCAmelCase	: Optional[int]		=					image_processor
						__UpperCAmelCase	: Dict		=					feature_extractor


			def __call__(      self      :    Tuple      ,  UpperCamelCase_      :    str=None      ,  UpperCamelCase_      :    Optional[int]=None      ,  UpperCamelCase_      :    Optional[int]=None      ,  UpperCamelCase_      :    str=None      ,  UpperCamelCase_      :    List[str]=False      ,  UpperCamelCase_      :    Optional[int]=False      ,  *UpperCamelCase_      :    List[str]      ,  **UpperCamelCase_      :    str      ,  ):


						"""simple docstring"""




						if images is None and audio is None:
									raise ValueError("You need to specify either an `images` or `audio` input to process.")

						__UpperCAmelCase	: Optional[Any]		=					None
						if images is not None:
									__UpperCAmelCase	: int		=					self.image_processor(UpperCamelCase_      ,  mask_pixel=UpperCamelCase_      ,  *UpperCamelCase_      ,  **UpperCamelCase_)
						if images_mixed is not None:
									__UpperCAmelCase	: int		=					self.image_processor(UpperCamelCase_      ,  is_mixed=UpperCamelCase_      ,  *UpperCamelCase_      ,  **UpperCamelCase_)
						if audio is not None:
									__UpperCAmelCase	: List[Any]		=					self.feature_extractor(
									    UpperCamelCase_      ,  *UpperCamelCase_      ,  sampling_rate=UpperCamelCase_      ,  mask_audio=UpperCamelCase_      ,  **UpperCamelCase_)

						__UpperCAmelCase	: List[str]		=					{}
						if audio is not None:
									output_dict.update(UpperCamelCase_)
						if images is not None:
									output_dict.update(UpperCamelCase_)
						if images_mixed_dict is not None:
									output_dict.update(UpperCamelCase_)
						return output_dict


			@property
			def       a_     (      self      :    str):


						"""simple docstring"""




						__UpperCAmelCase	: List[Any]		=					self.image_processor.model_input_names
						__UpperCAmelCase	: List[Any]		=					self.feature_extractor.model_input_names
						return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names))


