

# 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  lowerCamelCase__ (					_a=None):
	if subparsers is not None:
		SCREAMING_SNAKE_CASE   :      Any				     =       subparsers.add_parser("env")
	else:
		SCREAMING_SNAKE_CASE   :      Tuple				     =       argparse.ArgumentParser("Accelerate env command")

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

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

def  lowerCamelCase__ (					_a):
	SCREAMING_SNAKE_CASE   :      int				     =       torch.__version__
	SCREAMING_SNAKE_CASE   :      str				     =       torch.cuda.is_available()
	SCREAMING_SNAKE_CASE   :      Any				     =       is_xpu_available()
	SCREAMING_SNAKE_CASE   :      str				     =       is_npu_available()

	SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       "Not found"
	# Get the default from the config file.
	if args.config_file is not None or os.path.isfile(_a):
		SCREAMING_SNAKE_CASE   :      str				     =       load_config_from_file(args.config_file).to_dict()

	SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       {
	    "`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(_a),
	    "PyTorch NPU available": str(_a),
	    "System RAM": f"{psutil.virtual_memory().total / 1024 ** 3:.2f} GB",
	}
	if pt_cuda_available:
		SCREAMING_SNAKE_CASE   :      List[str]				     =       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:")
	SCREAMING_SNAKE_CASE   :      str				     =       (
	    "\n".join([f"\t- {prop}: {val}" for prop, val in accelerate_config.items()])
	    if isinstance(_a							,			_a)
	    else f"\t{accelerate_config}"
	)
	print(_a)

	SCREAMING_SNAKE_CASE   :      int				     =       accelerate_config

	return info

def  lowerCamelCase__ (					):
	SCREAMING_SNAKE_CASE   :      Any				     =       env_command_parser()
	SCREAMING_SNAKE_CASE   :      Optional[int]				     =       parser.parse_args()
	env_command(_a)
	return 0


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


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a_						     =    {
    'configuration_bridgetower': [
        'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BridgeTowerConfig',
        'BridgeTowerTextConfig',
        'BridgeTowerVisionConfig',
    ],
    'processing_bridgetower': ['BridgeTowerProcessor'],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_						     =    ['BridgeTowerImageProcessor']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_						     =    [
			    'BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'BridgeTowerForContrastiveLearning',
			    'BridgeTowerForImageAndTextRetrieval',
			    'BridgeTowerForMaskedLM',
			    'BridgeTowerModel',
			    'BridgeTowerPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_bridgetower import (
			    BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    BridgeTowerConfig,
			    BridgeTowerTextConfig,
			    BridgeTowerVisionConfig,
			)
			from .processing_bridgetower import BridgeTowerProcessor

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .image_processing_bridgetower import BridgeTowerImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_bridgetower import (
						    BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
						    BridgeTowerForContrastiveLearning,
						    BridgeTowerForImageAndTextRetrieval,
						    BridgeTowerForMaskedLM,
						    BridgeTowerModel,
						    BridgeTowerPreTrainedModel,
						)


else:
			import sys

			a_						     =    _LazyModule(__name__, globals()['__file__'], _import_structure)