
'''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 platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available


def A (__lowerCamelCase :Optional[int]=None						):
						if subparsers is not None:
												_lowerCAmelCase    		=					subparsers.add_parser("""env"""						)
						else:
												_lowerCAmelCase    		=					argparse.ArgumentParser("""Accelerate env command"""						)

						parser.add_argument(
						    """--config_file"""					,      default=__lowerCamelCase					,      help="""The config file to use for the default values in the launching script."""						)

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


def A (__lowerCamelCase :Tuple						):
						_lowerCAmelCase    		=					torch.__version__
						_lowerCAmelCase    		=					torch.cuda.is_available()
						_lowerCAmelCase    		=					is_xpu_available()
						_lowerCAmelCase    		=					is_npu_available()

						_lowerCAmelCase    		=					"""Not found"""
						# Get the default from the config file.
						if args.config_file is not None or os.path.isfile(__lowerCamelCase						):
												_lowerCAmelCase    		=					load_config_from_file(args.config_file						).to_dict()

						_lowerCAmelCase    		=					{
						    """`Accelerate` version""": version,
						    """Platform""": platform.platform(),
						    """Python version""": platform.python_version(),
						    """Numpy version""": np.__version__,
						    """PyTorch version (GPU?)""": f'{pt_version} ({pt_cuda_available})',
						    """PyTorch XPU available""": str(__lowerCamelCase						),
						    """PyTorch NPU available""": str(__lowerCamelCase						),
						    """System RAM""": f'{psutil.virtual_memory().total / 1024 ** 3:.2f} GB',
						}
						if pt_cuda_available:
												_lowerCAmelCase    		=					torch.cuda.get_device_name()

						print("""\nCopy-and-paste the text below in your GitHub issue\n"""						)
						print("""\n""".join([f'- {prop}: {val}' for prop, val in info.items()]						)						)

						print("""- `Accelerate` default config:""" if args.config_file is None else """- `Accelerate` config passed:"""						)
						_lowerCAmelCase    		=					(
						    """\n""".join([f'\t- {prop}: {val}' for prop, val in accelerate_config.items()]						)
						    if isinstance(__lowerCamelCase					,      __lowerCamelCase						)
						    else f'\t{accelerate_config}'
						)
						print(__lowerCamelCase						)

						_lowerCAmelCase    		=					accelerate_config

						return info


def A ():
						_lowerCAmelCase    		=					env_command_parser()
						_lowerCAmelCase    		=					parser.parse_args()
						env_command(__lowerCamelCase						)
						return 0


if __name__ == "__main__":
						raise SystemExit(main())


'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase          =						{"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMAEConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase          =						[
						    """VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """ViTMAEForPreTraining""",
						    """ViTMAELayer""",
						    """ViTMAEModel""",
						    """ViTMAEPreTrainedModel""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase          =						[
						    """TFViTMAEForPreTraining""",
						    """TFViTMAEModel""",
						    """TFViTMAEPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_vit_mae import (
												    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ViTMAEForPreTraining,
												    ViTMAELayer,
												    ViTMAEModel,
												    ViTMAEPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
						import sys

						_lowercase          =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
