




from math import pow, sqrt




def 		lowerCAmelCase_   (	*lowerCamelCase   ):
				__magic_name__	:	Tuple								=len(lowerCamelCase   ) > 0 and all(value > 0.0 for value in values   )
				return result




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				return (
				    round(sqrt(molar_mass_a / molar_mass_a   )	,     6   )
				    if validate(lowerCamelCase	,     lowerCamelCase   )
				    else ValueError("""Input Error: Molar mass values must greater than 0."""   )
				)




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   ):
				return (
				    round(effusion_rate * sqrt(molar_mass_a / molar_mass_a   )	,     6   )
				    if validate(lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   )
				    else ValueError(
				        """Input Error: Molar mass and effusion rate values must greater than 0."""   )
				)




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   ):
				return (
				    round(effusion_rate / sqrt(molar_mass_a / molar_mass_a   )	,     6   )
				    if validate(lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   )
				    else ValueError(
				        """Input Error: Molar mass and effusion rate values must greater than 0."""   )
				)




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   ):
				return (
				    round(molar_mass / pow(effusion_rate_a / effusion_rate_a	,     2   )	,     6   )
				    if validate(lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   )
				    else ValueError(
				        """Input Error: Molar mass and effusion rate values must greater than 0."""   )
				)




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   ):
				return (
				    round(pow(effusion_rate_a / effusion_rate_a	,     2   ) / molar_mass	,     6   )
				    if validate(lowerCamelCase	,     lowerCamelCase	,     lowerCamelCase   )
				    else ValueError(
				        """Input Error: Molar mass and effusion rate values must greater than 0."""   )
				)





# 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)




