




from collections import namedtuple

UpperCAmelCase_		:				int									=     namedtuple("from_to", "from_ to")

UpperCAmelCase_		:				Optional[Any]									=     {
    "cubicmeter": from_to(1, 1),
    "litre": from_to(0.001, 1000),
    "kilolitre": from_to(1, 1),
    "gallon": from_to(0.0_0454, 264.172),
    "cubicyard": from_to(0.7_6455, 1.3_0795),
    "cubicfoot": from_to(0.028, 35.3147),
    "cup": from_to(0.0_0023_6588, 4226.75),
}




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   ):
				if from_type not in METRIC_CONVERSION:
								raise ValueError(
								    F"Invalid 'from_type' value: {from_type!r}  Supported values are:\n"
								    + """, """.join(lowerCamelCase   )   )
				if to_type not in METRIC_CONVERSION:
								raise ValueError(
								    F"Invalid 'to_type' value: {to_type!r}.  Supported values are:\n"
								    + """, """.join(lowerCamelCase   )   )
				return value * METRIC_CONVERSION[from_type].from_ * METRIC_CONVERSION[to_type].to


if __name__ == "__main__":
							import doctest

							doctest.testmod()










# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import sys

import transformers


UpperCAmelCase_		:				str									=     "3"

print("Python version:", sys.version)
print("transformers version:", transformers.__version__)

try:
							import torch

							print("Torch version:", torch.__version__)
							print("Cuda available:", torch.cuda.is_available())
							print("Cuda version:", torch.version.cuda)
							print("CuDNN version:", torch.backends.cudnn.version())
							print("Number of GPUs available:", torch.cuda.device_count())
							print("NCCL version:", torch.cuda.nccl.version())
except ImportError:
							print("Torch version:", None)

try:
							import deepspeed

							print("DeepSpeed version:", deepspeed.__version__)
except ImportError:
							print("DeepSpeed version:", None)

try:
							import tensorflow as tf

							print("TensorFlow version:", tf.__version__)
							print("TF GPUs available:", bool(tf.config.list_physical_devices("GPU")))
							print("Number of TF GPUs available:", len(tf.config.list_physical_devices("GPU")))
except ImportError:
							print("TensorFlow version:", None)




