
# 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


SCREAMING_SNAKE_CASE__   :			Union[str, Any]												=    "Run commands across TPU VMs for initial setup before running `accelerate launch`."




def  __magic_name__ (   __lowerCAmelCase	:						List[str]=None							)			->   Dict:
				if subparsers is not None:
								__lowerCamelCase    					=	subparsers.add_parser('''tpu-config'''		,  description=_description							)
				else:
								__lowerCamelCase    					=	argparse.ArgumentParser('''Accelerate tpu-config command'''		,  description=_description							)
				# Core arguments
				__lowerCamelCase    					=	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.'''		,  )
				__lowerCamelCase    					=	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  __magic_name__ (   __lowerCAmelCase	:						int							)			->   List[Any]:
				__lowerCamelCase    					=	None

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

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

				# Then send it to gcloud
				# Eventually try to use google-api-core to do this instead of subprocess
				__lowerCamelCase    					=	['''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  __magic_name__ (   )			->   Any:
				__lowerCamelCase    					=	tpu_command_parser()
				__lowerCamelCase    					=	parser.parse_args()

				tpu_command_launcher(__lowerCAmelCase							)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__   :			List[Any]												=    {
    "configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig", "ResNetOnnxConfig"]
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			int												=    [
					    "RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "ResNetForImageClassification",
					    "ResNetModel",
					    "ResNetPreTrainedModel",
					    "ResNetBackbone",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			List[Any]												=    [
					    "TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "TFResNetForImageClassification",
					    "TFResNetModel",
					    "TFResNetPreTrainedModel",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__   :			Union[str, Any]												=    [
					    "FlaxResNetForImageClassification",
					    "FlaxResNetModel",
					    "FlaxResNetPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_resnet import (
										    RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ResNetBackbone,
										    ResNetForImageClassification,
										    ResNetModel,
										    ResNetPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_resnet import (
										    TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFResNetForImageClassification,
										    TFResNetModel,
										    TFResNetPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
					import sys

					SCREAMING_SNAKE_CASE__   :			Any												=    _LazyModule(__name__, globals()["__file__"], _import_structure)



