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# Copyright 2021 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 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 MockLaunchConfig(SageMakerConfig):
compute_environment = ComputeEnvironment.AMAZON_SAGEMAKER
fp16 = True
ec2_instance_type = "ml.p3.2xlarge"
iam_role_name = "accelerate_sagemaker_execution_role"
profile = "hf-sm"
region = "us-east-1"
num_machines = 1
base_job_name = "accelerate-sagemaker-1"
pytorch_version = "1.6"
transformers_version = "4.4"
training_script = "train.py"
success_training_script_args = [
"--model_name_or_path",
"bert",
"--do_train",
"False",
"--epochs",
"3",
"--learning_rate",
"5e-5",
"--max_steps",
"50.5",
]
fail_training_script_args = [
"--model_name_or_path",
"bert",
"--do_train",
"--do_test",
"False",
"--do_predict",
"--epochs",
"3",
"--learning_rate",
"5e-5",
"--max_steps",
"50.5",
]
class SageMakerLaunch(unittest.TestCase):
def test_args_convert(self):
# If no defaults are changed, `to_kwargs` returns an empty dict.
converted_args = _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args)
assert isinstance(converted_args["model_name_or_path"], str)
assert isinstance(converted_args["do_train"], bool)
assert isinstance(converted_args["epochs"], int)
assert isinstance(converted_args["learning_rate"], float)
assert isinstance(converted_args["max_steps"], float)
with pytest.raises(ValueError):
_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args)
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