def test_ctor_string(target_class): from google.cloud.bigquery import ModelReference model_id = "my-proj.my_dset.my_model" ref = ModelReference.from_string(model_id) got = target_class(model_id) assert got.reference == ref
def test_from_api_repr_w_minimal_resource(target_class): from google.cloud.bigquery import ModelReference resource = { "modelReference": { "projectId": "my-project", "datasetId": "my_dataset", "modelId": "my_model", } } got = target_class.from_api_repr(resource) assert got.reference == ModelReference.from_string("my-project.my_dataset.my_model") assert got.location == "" assert got.etag == "" assert got.created is None assert got.modified is None assert got.expires is None assert got.description is None assert got.friendly_name is None assert got.model_type == types.Model.ModelType.MODEL_TYPE_UNSPECIFIED assert got.labels == {} assert got.encryption_configuration is None assert len(got.training_runs) == 0 assert len(got.feature_columns) == 0 assert len(got.label_columns) == 0
def test_ctor_string(target_class): from google.cloud.bigquery import ModelReference model_id = "my-proj.my_dset.my_model" ref = ModelReference.from_string(model_id) got = target_class(model_id) assert got.reference == ref
def test_from_api_repr_w_unknown_fields(target_class): from google.cloud.bigquery import ModelReference resource = { "modelReference": { "projectId": "my-project", "datasetId": "my_dataset", "modelId": "my_model", }, "thisFieldIsNotInTheProto": "just ignore me", } got = target_class.from_api_repr(resource) assert got.reference == ModelReference.from_string("my-project.my_dataset.my_model") assert got._properties is resource
def test_from_api_repr_w_unknown_fields(target_class): from google.cloud.bigquery import ModelReference resource = { "modelReference": { "projectId": "my-project", "datasetId": "my_dataset", "modelId": "my_model", }, "thisFieldIsNotInTheProto": "just ignore me", } got = target_class.from_api_repr(resource) assert got.reference == ModelReference.from_string("my-project.my_dataset.my_model") assert got._properties is resource
def test_from_api_repr_w_unknown_type(target_class): from google.cloud.bigquery import ModelReference resource = { "modelReference": { "projectId": "my-project", "datasetId": "my_dataset", "modelId": "my_model", }, "modelType": "BE_A_GOOD_ROLE_MODEL", } got = target_class.from_api_repr(resource) assert got.reference == ModelReference.from_string( "my-project.my_dataset.my_model") assert got.model_type == 0 assert got._properties is resource
def test_from_api_repr_w_minimal_resource(target_class): from google.cloud.bigquery import ModelReference resource = { "modelReference": { "projectId": "my-project", "datasetId": "my_dataset", "modelId": "my_model", } } got = target_class.from_api_repr(resource) assert got.reference == ModelReference.from_string("my-project.my_dataset.my_model") assert got.location == "" assert got.etag == "" assert got.created is None assert got.modified is None assert got.expires is None assert got.description is None assert got.friendly_name is None assert got.model_type == enums.Model.ModelType.MODEL_TYPE_UNSPECIFIED assert got.labels == {} assert len(got.training_runs) == 0 assert len(got.feature_columns) == 0 assert len(got.label_columns) == 0
def test_from_api_repr(target_class): from google.cloud.bigquery import ModelReference creation_time = datetime.datetime( 2010, 5, 19, 16, 0, 0, tzinfo=google.cloud._helpers.UTC ) modified_time = datetime.datetime( 2011, 10, 1, 16, 0, 0, tzinfo=google.cloud._helpers.UTC ) expiration_time = datetime.datetime( 2012, 12, 21, 16, 0, 0, tzinfo=google.cloud._helpers.UTC ) resource = { "modelReference": { "projectId": "my-project", "datasetId": "my_dataset", "modelId": "my_model", }, "location": "US", "etag": "abcdefg", "creationTime": str(google.cloud._helpers._millis(creation_time)), "lastModifiedTime": str(google.cloud._helpers._millis(modified_time)), "expirationTime": str(google.cloud._helpers._millis(expiration_time)), "description": "A friendly description.", "friendlyName": "A friendly name.", "modelType": "LOGISTIC_REGRESSION", "labels": {"greeting": u"こんにちは"}, "trainingRuns": [ { "trainingOptions": {"initialLearnRate": 1.0}, "startTime": str( google.cloud._helpers._datetime_to_rfc3339(creation_time) ), }, { "trainingOptions": {"initialLearnRate": 0.5}, "startTime": str( google.cloud._helpers._datetime_to_rfc3339(modified_time) ), }, { "trainingOptions": {"initialLearnRate": 0.25}, # Allow milliseconds since epoch format. # TODO: Remove this hack once CL 238585470 hits prod. "startTime": str(google.cloud._helpers._millis(expiration_time)), }, ], "featureColumns": [], "encryptionConfiguration": {"kmsKeyName": KMS_KEY_NAME}, } got = target_class.from_api_repr(resource) assert got.project == "my-project" assert got.dataset_id == "my_dataset" assert got.model_id == "my_model" assert got.reference == ModelReference.from_string("my-project.my_dataset.my_model") assert got.path == "/projects/my-project/datasets/my_dataset/models/my_model" assert got.location == "US" assert got.etag == "abcdefg" assert got.created == creation_time assert got.modified == modified_time assert got.expires == expiration_time assert got.description == u"A friendly description." assert got.friendly_name == u"A friendly name." assert got.model_type == types.Model.ModelType.LOGISTIC_REGRESSION assert got.labels == {"greeting": u"こんにちは"} assert got.encryption_configuration.kms_key_name == KMS_KEY_NAME assert got.training_runs[0].training_options.initial_learn_rate == 1.0 assert ( got.training_runs[0] .start_time.ToDatetime() .replace(tzinfo=google.cloud._helpers.UTC) == creation_time ) assert got.training_runs[1].training_options.initial_learn_rate == 0.5 assert ( got.training_runs[1] .start_time.ToDatetime() .replace(tzinfo=google.cloud._helpers.UTC) == modified_time ) assert got.training_runs[2].training_options.initial_learn_rate == 0.25 assert ( got.training_runs[2] .start_time.ToDatetime() .replace(tzinfo=google.cloud._helpers.UTC) == expiration_time )
def test_from_api_repr(target_class): from google.cloud.bigquery import ModelReference creation_time = datetime.datetime( 2010, 5, 19, 16, 0, 0, tzinfo=google.cloud._helpers.UTC ) modified_time = datetime.datetime( 2011, 10, 1, 16, 0, 0, tzinfo=google.cloud._helpers.UTC ) expiration_time = datetime.datetime( 2012, 12, 21, 16, 0, 0, tzinfo=google.cloud._helpers.UTC ) resource = { "modelReference": { "projectId": "my-project", "datasetId": "my_dataset", "modelId": "my_model", }, "location": "US", "etag": "abcdefg", "creationTime": str(google.cloud._helpers._millis(creation_time)), "lastModifiedTime": str(google.cloud._helpers._millis(modified_time)), "expirationTime": str(google.cloud._helpers._millis(expiration_time)), "description": "A friendly description.", "friendlyName": "A friendly name.", "modelType": "LOGISTIC_REGRESSION", "labels": {"greeting": u"こんにちは"}, "trainingRuns": [ { "trainingOptions": {"initialLearnRate": 1.0}, "startTime": str( google.cloud._helpers._datetime_to_rfc3339(creation_time) ), }, { "trainingOptions": {"initialLearnRate": 0.5}, "startTime": str( google.cloud._helpers._datetime_to_rfc3339(modified_time) ), }, { "trainingOptions": {"initialLearnRate": 0.25}, # Allow milliseconds since epoch format. # TODO: Remove this hack once CL 238585470 hits prod. "startTime": str(google.cloud._helpers._millis(expiration_time)), }, ], "featureColumns": [], } got = target_class.from_api_repr(resource) assert got.project == "my-project" assert got.dataset_id == "my_dataset" assert got.model_id == "my_model" assert got.reference == ModelReference.from_string("my-project.my_dataset.my_model") assert got.path == "/projects/my-project/datasets/my_dataset/models/my_model" assert got.location == "US" assert got.etag == "abcdefg" assert got.created == creation_time assert got.modified == modified_time assert got.expires == expiration_time assert got.description == u"A friendly description." assert got.friendly_name == u"A friendly name." assert got.model_type == enums.Model.ModelType.LOGISTIC_REGRESSION assert got.labels == {"greeting": u"こんにちは"} assert got.training_runs[0].training_options.initial_learn_rate == 1.0 assert ( got.training_runs[0] .start_time.ToDatetime() .replace(tzinfo=google.cloud._helpers.UTC) == creation_time ) assert got.training_runs[1].training_options.initial_learn_rate == 0.5 assert ( got.training_runs[1] .start_time.ToDatetime() .replace(tzinfo=google.cloud._helpers.UTC) == modified_time ) assert got.training_runs[2].training_options.initial_learn_rate == 0.25 assert ( got.training_runs[2] .start_time.ToDatetime() .replace(tzinfo=google.cloud._helpers.UTC) == expiration_time )