def xgboost_inference_request(inference_request: InferenceRequest) -> InferenceRequest:
# Reshape to 2D array, matching the input data to xgboost_model
single_input = inference_request.inputs[0]
single_input.data = single_input.data = [[1, 2, 3]]
# Keep only a single input
inference_request.inputs = [single_input]
return inference_request
def xgboost_inference_request(
inference_request: InferenceRequest) -> InferenceRequest:
# Reshape to 2D array, matching the input data to xgboost_model
single_input = inference_request.inputs[0]
single_input.data = TensorData.parse_obj([[1, 2, 3]])
single_input.shape = [1, 3]
# Keep only a single input
inference_request.inputs = [single_input]
return inference_request
def sklearn_inference_request(inference_request: InferenceRequest) -> InferenceRequest:
# Keep only a single input
inference_request.inputs = inference_request.inputs[:1]
return inference_request
def test_first_input_decode(inference_request: InferenceRequest, expected: np.ndarray):
inference_request.inputs = [inference_request.inputs[0]]
first_input = NumpyRequestCodec.decode(inference_request)
np.testing.assert_equal(first_input, expected)