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| import os |
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| import pytest |
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| from attr import dataclass |
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| os.environ["AWS_DEFAULT_REGION"] = "us-east-1" |
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|
| @dataclass |
| class SageMakerTestEnvironment: |
| framework: str |
| role = "arn:aws:iam::558105141721:role/sagemaker_execution_role" |
| hyperparameters = { |
| "task_name": "mnli", |
| "per_device_train_batch_size": 32, |
| "per_device_eval_batch_size": 32, |
| "do_train": True, |
| "do_eval": True, |
| "do_predict": True, |
| "output_dir": "/opt/ml/model", |
| "overwrite_output_dir": True, |
| "max_steps": 500, |
| "save_steps": 5500, |
| } |
| distributed_hyperparameters = {**hyperparameters, "max_steps": 1000} |
|
|
| @property |
| def metric_definitions(self) -> str: |
| if self.framework == "pytorch": |
| return [ |
| {"Name": "train_runtime", "Regex": "train_runtime.*=\D*(.*?)$"}, |
| {"Name": "eval_accuracy", "Regex": "eval_accuracy.*=\D*(.*?)$"}, |
| {"Name": "eval_loss", "Regex": "eval_loss.*=\D*(.*?)$"}, |
| ] |
| else: |
| return [ |
| {"Name": "train_runtime", "Regex": "train_runtime.*=\D*(.*?)$"}, |
| {"Name": "eval_accuracy", "Regex": "loss.*=\D*(.*?)]?$"}, |
| {"Name": "eval_loss", "Regex": "sparse_categorical_accuracy.*=\D*(.*?)]?$"}, |
| ] |
|
|
| @property |
| def base_job_name(self) -> str: |
| return f"{self.framework}-transfromers-test" |
|
|
| @property |
| def test_path(self) -> str: |
| return f"./tests/sagemaker/scripts/{self.framework}" |
|
|
| @property |
| def image_uri(self) -> str: |
| if self.framework == "pytorch": |
| return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.6.0-transformers4.4.2-gpu-py36-cu110-ubuntu18.04" |
| else: |
| return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.4.2-gpu-py37-cu110-ubuntu18.04" |
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|
| @pytest.fixture(scope="class") |
| def sm_env(request): |
| request.cls.env = SageMakerTestEnvironment(framework=request.cls.framework) |
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