def test_xgboost_abalone_mme_with_transform_fn(docker_image, opt_ml):
customer_script = "abalone_distributed.py"
request_body = get_libsvm_request_body()
additional_env_vars = [
"SAGEMAKER_BIND_TO_PORT=8080",
"SAGEMAKER_SAFE_PORT_RANGE=9000-9999",
"SAGEMAKER_MULTI_MODEL=true",
]
model_name = "libsvm_pickled"
model_data = json.dumps({
"model_name": model_name,
"url": "/opt/ml/model/{}".format(model_name)
})
with append_transform_fn_to_abalone_script(
abalone_path, customer_script) as custom_script_path:
with local_mode.serve(
customer_script,
models_dir,
docker_image,
opt_ml,
source_dir=custom_script_path,
additional_env_vars=additional_env_vars,
):
load_status_code, _ = local_mode.request(
model_data,
content_type="application/json",
request_url=MME_MODELS_URL.format(model_name),
)
assert load_status_code == 200
invoke_status_code, invoke_response_body = local_mode.request(
request_body,
content_type="text/libsvm",
request_url=MME_INVOKE_URL.format(model_name),
)
assert invoke_status_code == 200
assert (len(invoke_response_body.split(",")) == len(request_body.split()) +
1 # final column is the bias term
)
assert not local_mode.file_exists(opt_ml,
"output/failure"), "Failure happened"
def test_xgboost_abalone_inference(docker_image, opt_ml):
customer_script = "abalone_distributed.py"
request_body = get_libsvm_request_body()
with local_mode.serve(customer_script,
libsvm_model_dir,
docker_image,
opt_ml,
source_dir=abalone_path):
response_status_code, response_body = local_mode.request(
request_body, content_type="text/libsvm")
assert response_status_code == 200
assert not local_mode.file_exists(opt_ml,
"output/failure"), "Failure happened"
assert len(response_body.split(",")) == 1
def test_xgboost_abalone_custom_inference_with_transform_fn(
docker_image, opt_ml):
customer_script = "abalone_distributed.py"
request_body = get_libsvm_request_body()
with append_transform_fn_to_abalone_script(
abalone_path, customer_script) as custom_script_path:
with local_mode.serve(
customer_script,
libsvm_model_dir,
docker_image,
opt_ml,
source_dir=custom_script_path,
):
response_status_code, response_body = local_mode.request(
request_body, content_type="text/libsvm")
assert response_status_code == 200
assert not local_mode.file_exists(opt_ml,
"output/failure"), "Failure happened"
assert (len(response_body.split(",")) == len(request_body.split()) +
1 # final column is the bias term
)
def predict_and_assert_response_length(data, content_type):
predict_response = localmode.request(data, content_type=content_type)
assert len(predict_response) == len(data)