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
)