def _validate_with_rest_endpoint(scoring_proc, host_port, df, x, sk_model):
with RestEndpoint(proc=scoring_proc, port=host_port) as endpoint:
for content_type in [
CONTENT_TYPE_JSON_SPLIT_ORIENTED, CONTENT_TYPE_CSV,
CONTENT_TYPE_JSON
]:
scoring_response = endpoint.invoke(df, content_type)
assert scoring_response.status_code == 200, "Failed to serve prediction, got " \
"response %s" % scoring_response.text
np.testing.assert_array_equal(
np.array(json.loads(scoring_response.text)),
sk_model.predict(x))
# Try examples of bad input, verify we get a non-200 status code
for content_type in [
CONTENT_TYPE_JSON_SPLIT_ORIENTED, CONTENT_TYPE_CSV,
CONTENT_TYPE_JSON
]:
scoring_response = endpoint.invoke(data="",
content_type=content_type)
assert scoring_response.status_code == 500, \
"Expected server failure with error code 500, got response with status code %s " \
"and body %s" % (scoring_response.status_code, scoring_response.text)
scoring_response_dict = json.loads(scoring_response.content)
assert "error_code" in scoring_response_dict
assert scoring_response_dict["error_code"] == ErrorCode.Name(
MALFORMED_REQUEST)
assert "message" in scoring_response_dict
assert "stack_trace" in scoring_response_dict
def _validate_with_rest_endpoint(scoring_proc, host_port, df, x, sk_model, enable_mlserver=False):
with RestEndpoint(proc=scoring_proc, port=host_port) as endpoint:
for content_type in [CONTENT_TYPE_JSON_SPLIT_ORIENTED, CONTENT_TYPE_CSV, CONTENT_TYPE_JSON]:
scoring_response = endpoint.invoke(df, content_type)
assert scoring_response.status_code == 200, (
"Failed to serve prediction, got " "response %s" % scoring_response.text
)
np.testing.assert_array_equal(
np.array(json.loads(scoring_response.text)), sk_model.predict(x)
)
# Try examples of bad input, verify we get a non-200 status code
for content_type in [CONTENT_TYPE_JSON_SPLIT_ORIENTED, CONTENT_TYPE_CSV, CONTENT_TYPE_JSON]:
scoring_response = endpoint.invoke(data="", content_type=content_type)
expected_status_code = 500 if enable_mlserver else 400
assert scoring_response.status_code == expected_status_code, (
"Expected server failure with error code %s, got response with status code %s "
"and body %s"
% (expected_status_code, scoring_response.status_code, scoring_response.text)
)
if enable_mlserver:
# MLServer returns a different set of errors.
# Skip these assertions until this issue gets tackled:
# https://github.com/SeldonIO/MLServer/issues/360)
continue
scoring_response_dict = json.loads(scoring_response.content)
assert "error_code" in scoring_response_dict
assert scoring_response_dict["error_code"] == ErrorCode.Name(BAD_REQUEST)
assert "message" in scoring_response_dict
assert "stack_trace" in scoring_response_dict
def test_build_docker(iris_data, sk_model):
with mlflow.start_run() as active_run:
mlflow.sklearn.log_model(sk_model, "model")
model_uri = "runs:/{run_id}/model".format(
run_id=active_run.info.run_id)
x, _ = iris_data
df = pd.DataFrame(x)
image_name = pyfunc_build_image(model_uri, extra_args=["--install-mlflow"])
host_port = get_safe_port()
scoring_proc = pyfunc_serve_from_docker_image(image_name, host_port)
with RestEndpoint(proc=scoring_proc, port=host_port) as endpoint:
for content_type in [
CONTENT_TYPE_JSON_SPLIT_ORIENTED, CONTENT_TYPE_CSV,
CONTENT_TYPE_JSON
]:
scoring_response = endpoint.invoke(df, content_type)
assert scoring_response.status_code == 200, "Failed to serve prediction, got " \
"response %s" % scoring_response.text
np.testing.assert_array_equal(
np.array(json.loads(scoring_response.text)),
sk_model.predict(x))
# Try examples of bad input, verify we get a non-200 status code
for content_type in [
CONTENT_TYPE_JSON_SPLIT_ORIENTED, CONTENT_TYPE_CSV,
CONTENT_TYPE_JSON
]:
scoring_response = endpoint.invoke(data="",
content_type=content_type)
assert scoring_response.status_code == 500, \
"Expected server failure with error code 500, got response with status code %s " \
"and body %s" % (scoring_response.status_code, scoring_response.text)
scoring_response_dict = json.loads(scoring_response.content)
assert "error_code" in scoring_response_dict
assert scoring_response_dict["error_code"] == ErrorCode.Name(
MALFORMED_REQUEST)
assert "message" in scoring_response_dict
assert "stack_trace" in scoring_response_dict