def _prepare_init_params_from_job_description(cls, job_details):
        """Convert the job description to init params that can be handled by the class constructor

        Args:
            job_details: the returned job details from a describe_training_job API call.

        Returns:
             dictionary: The transformed init_params

        """
        init_params = super(PyTorch, cls)._prepare_init_params_from_job_description(job_details)
        image_name = init_params.pop('image')
        framework, py_version, tag = framework_name_from_image(image_name)

        if not framework:
            # If we were unable to parse the framework name from the image it is not one of our
            # officially supported images, in this case just add the image to the init params.
            init_params['image_name'] = image_name
            return init_params

        init_params['py_version'] = py_version
        init_params['framework_version'] = framework_version_from_tag(tag)

        training_job_name = init_params['base_job_name']

        if framework != cls.__framework_name__:
            raise ValueError("Training job: {} didn't use image for requested framework".format(training_job_name))

        return init_params
    def _prepare_init_params_from_job_description(cls, job_details):
        """Convert the job description to init params that can be handled by the class constructor

        Args:
            job_details: the returned job details from a describe_training_job API call.

        Returns:
             dictionary: The transformed init_params

        """
        init_params = super(MXNet, cls)._prepare_init_params_from_job_description(job_details)
        image_name = init_params.pop('image')
        framework, py_version, tag = framework_name_from_image(image_name)

        if not framework:
            # If we were unable to parse the framework name from the image it is not one of our
            # officially supported images, in this case just add the image to the init params.
            init_params['image_name'] = image_name
            return init_params

        init_params['py_version'] = py_version

        # We switched image tagging scheme from regular image version (e.g. '1.0') to more expressive
        # containing framework version, device type and python version (e.g. '0.12-gpu-py2').
        # For backward compatibility map deprecated image tag '1.0' to a '0.12' framework version
        # otherwise extract framework version from the tag itself.
        init_params['framework_version'] = '0.12' if tag == '1.0' else framework_version_from_tag(tag)

        training_job_name = init_params['base_job_name']

        if framework != cls.__framework_name__:
            raise ValueError("Training job: {} didn't use image for requested framework".format(training_job_name))

        return init_params
    def _prepare_init_params_from_job_description(cls, job_details):
        """Convert the job description to init params that can be handled by the class constructor

        Args:
            job_details: the returned job details from a describe_training_job API call.

        Returns:
             dictionary: The transformed init_params

        """
        init_params = super(Chainer, cls)._prepare_init_params_from_job_description(job_details)

        for argument in [Chainer._use_mpi, Chainer._num_processes, Chainer._process_slots_per_host,
                         Chainer._additional_mpi_options]:

            value = init_params['hyperparameters'].pop(argument, None)
            if value:
                init_params[argument[len('sagemaker_'):]] = value

        image_name = init_params.pop('image')
        framework, py_version, tag = framework_name_from_image(image_name)

        if not framework:
            # If we were unable to parse the framework name from the image it is not one of our
            # officially supported images, in this case just add the image to the init params.
            init_params['image_name'] = image_name
            return init_params

        init_params['py_version'] = py_version
        init_params['framework_version'] = framework_version_from_tag(tag)

        training_job_name = init_params['base_job_name']

        if framework != cls.__framework_name__:
            raise ValueError("Training job: {} didn't use image for requested framework".format(training_job_name))
        return init_params
def test_legacy_name_from_image_any_tag():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-py2-cpu:any-tag'
    framework, py_ver, tag = framework_name_from_image(image_name)
    assert framework == 'tensorflow'
    assert py_ver == 'py2'
    assert tag == 'any-tag'
def test_legacy_name_from_wrong_device():
    framework, py_ver, tag = framework_name_from_image('123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-myown-py4-gpu:1')
    assert framework is None
    assert py_ver is None
    assert tag is None
def test_legacy_name_from_wrong_python():
    framework, py_ver, tag = framework_name_from_image(
        '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-myown-py4-gpu:1')
    assert framework is None
    assert py_ver is None
    assert tag is None
def test_framework_name_from_image_mxnet():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:1.1-gpu-py3'
    assert ('mxnet', 'py3', '1.1-gpu-py3') == framework_name_from_image(image_name)
def test_legacy_name_from_wrong_device():
    framework, py_ver, tag, _ = fw_utils.framework_name_from_image(
        "123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-myown-py4-gpu:1")
    assert framework is None
    assert py_ver is None
    assert tag is None
def test_framework_name_from_image_rl():
    image_uri = "123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-mxnet:toolkit1.1-gpu-py3"
    assert ("mxnet", "py3", "toolkit1.1-gpu-py3",
            None) == fw_utils.framework_name_from_image(image_uri)
Example #10
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def test_legacy_name_from_image_any_tag():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-py2-cpu:any-tag'
    framework, py_ver, tag = fw_utils.framework_name_from_image(image_name)
    assert framework == 'tensorflow'
    assert py_ver == 'py2'
    assert tag == 'any-tag'
Example #11
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def test_legacy_name_from_framework_image():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-py3-gpu:2.5.6-gpu-py2'
    framework, py_ver, tag = fw_utils.framework_name_from_image(image_name)
    assert framework == 'mxnet'
    assert py_ver == 'py3'
    assert tag == '2.5.6-gpu-py2'
Example #12
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def test_framework_name_from_image_rl():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-mxnet:toolkit1.1-gpu-py3'
    assert (
        'mxnet', 'py3',
        'toolkit1.1-gpu-py3') == fw_utils.framework_name_from_image(image_name)
Example #13
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def test_framework_name_from_image_tf():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:1.6-cpu-py2'
    assert ('tensorflow', 'py2',
            '1.6-cpu-py2') == fw_utils.framework_name_from_image(image_name)
Example #14
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def test_framework_name_from_other():
    framework, py_ver = framework_name_from_image(
        '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-myown-py2-gpu:1')
    assert framework is None
    assert py_ver is None
Example #15
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def test_framework_name_from_framework_image():
    framework, py_ver = framework_name_from_image(
        '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-py2-gpu:1')
    assert framework == 'mxnet'
    assert py_ver == 'py2'
def test_framework_name_from_image_mxnet_in_gov():
    image_uri = "123.dkr.ecr.region-name.c2s.ic.gov/sagemaker-mxnet:1.1-gpu-py3"
    assert ("mxnet", "py3", "1.1-gpu-py3",
            None) == fw_utils.framework_name_from_image(image_uri)
def test_framework_name_from_image_tf():
    image_uri = "123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:1.6-cpu-py2"
    assert ("tensorflow", "py2", "1.6-cpu-py2",
            None) == fw_utils.framework_name_from_image(image_uri)
def test_framework_name_from_image_mxnet():
    image_name = "123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:1.1-gpu-py3"
    assert ("mxnet", "py3", "1.1-gpu-py3",
            None) == fw_utils.framework_name_from_image(image_name)
def test_legacy_name_from_framework_image():
    image_uri = "123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-py3-gpu:2.5.6-gpu-py2"
    framework, py_ver, tag, _ = fw_utils.framework_name_from_image(image_uri)
    assert framework == "mxnet"
    assert py_ver == "py3"
    assert tag == "2.5.6-gpu-py2"
def test_framework_name_from_image_mxnet():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:1.1-gpu-py3'
    assert ('mxnet', 'py3', '1.1-gpu-py3') == framework_name_from_image(image_name)
def test_legacy_name_from_image_any_tag():
    image_uri = "123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-py2-cpu:any-tag"
    framework, py_ver, tag, _ = fw_utils.framework_name_from_image(image_uri)
    assert framework == "tensorflow"
    assert py_ver == "py2"
    assert tag == "any-tag"
def test_framework_name_from_image_tf():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:1.6-cpu-py2'
    assert ('tensorflow', 'py2', '1.6-cpu-py2') == framework_name_from_image(image_name)
def test_legacy_name_from_framework_image():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-py3-gpu:2.5.6-gpu-py2'
    framework, py_ver, tag = framework_name_from_image(image_name)
    assert framework == 'mxnet'
    assert py_ver == 'py3'
    assert tag == '2.5.6-gpu-py2'
def test_framework_name_from_image_tf_scriptmode():
    image_name = '123.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-scriptmode:1.12-cpu-py3'
    assert ('tensorflow', 'py3', '1.12-cpu-py3',
            'scriptmode') == fw_utils.framework_name_from_image(image_name)