






import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict




@dataclass
class 							snake_case_       (    __UpperCamelCase      ):

						"""simple docstring"""



						snake_case__        =      ComputeEnvironment.AMAZON_SAGEMAKER
						snake_case__        =      True
						snake_case__        =      """ml.p3.2xlarge"""
						snake_case__        =      """accelerate_sagemaker_execution_role"""
						snake_case__        =      """hf-sm"""
						snake_case__        =      """us-east-1"""
						snake_case__        =      1
						snake_case__        =      """accelerate-sagemaker-1"""
						snake_case__        =      """1.6"""
						snake_case__        =      """4.4"""
						snake_case__        =      """train.py"""
						snake_case__        =      [
						    """--model_name_or_path""",
						    """bert""",
						    """--do_train""",
						    """False""",
						    """--epochs""",
						    """3""",
						    """--learning_rate""",
						    """5e-5""",
						    """--max_steps""",
						    """50.5""",
						]
						snake_case__        =      [
						    """--model_name_or_path""",
						    """bert""",
						    """--do_train""",
						    """--do_test""",
						    """False""",
						    """--do_predict""",
						    """--epochs""",
						    """3""",
						    """--learning_rate""",
						    """5e-5""",
						    """--max_steps""",
						    """50.5""",
						]




class 							snake_case_       (    unittest.TestCase      ):

						"""simple docstring"""



						def        UpperCAmelCase__					(self:					Optional[Any]   )    ->     Dict:




											'''simple docstring'''



											__a					:						Union[str, Any]      =					_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args   )
											assert isinstance(converted_args["model_name_or_path"] ,					__UpperCAmelCase   )
											assert isinstance(converted_args["do_train"] ,					__UpperCAmelCase   )
											assert isinstance(converted_args["epochs"] ,					__UpperCAmelCase   )
											assert isinstance(converted_args["learning_rate"] ,					__UpperCAmelCase   )
											assert isinstance(converted_args["max_steps"] ,					__UpperCAmelCase   )

											with pytest.raises(__UpperCAmelCase   ):
																_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args   )













# 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__      			=						'''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)





