
import os
import sys

import transformers


_UpperCAmelCase      :				Tuple          = "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)


import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset


@pytest.mark.parametrize('dataset_size'					, [None, 400 * 2**20, 600 * 2**20]				)
@pytest.mark.parametrize('input_in_memory_max_size'					, ['default', 0, 100 * 2**20, 900 * 2**20]				)
def    A (      lowercase					, lowercase					, lowercase				)     ->						Union[str, Any]:
		'''simple docstring'''

		if input_in_memory_max_size != "default":
				monkeypatch.setattr(datasets.config					, 'IN_MEMORY_MAX_SIZE'					, lowercase				)
		UpperCamelCase						=  datasets.config.IN_MEMORY_MAX_SIZE
		if input_in_memory_max_size == "default":
				assert in_memory_max_size == 0
		else:
				assert in_memory_max_size == input_in_memory_max_size
		if dataset_size and in_memory_max_size:
				UpperCamelCase						=  dataset_size < in_memory_max_size
		else:
				UpperCamelCase						=  False
		UpperCamelCase						=  is_small_dataset(lowercase				)
		assert result == expected
