def test_mxnet_transformer_default_output_fn_invalid_content_type():
t = MXNetTransformer()
with pytest.raises(errors.UnsupportedFormatError) as e:
t.default_output_fn(None, 'bad/content-type')
assert 'Content type bad/content-type is not supported by this framework' in str(
e)
def test_mxnet_transformer_default_input_fn_with_accelerator(decode, mx_ndarray, mx_eia):
ndarray = Mock()
mx_ndarray.return_value = ndarray
t = MXNetTransformer()
t.default_input_fn(Mock(), 'application/json')
ndarray.as_in_context.assert_called_with(mx.cpu())
def test_mxnet_transformer_default_input_fn_with_npy(decode):
input_data = Mock()
content_type = 'application/x-npy'
t = MXNetTransformer()
deserialized_data = t.default_input_fn(input_data, content_type)
decode.assert_called_with(input_data, content_type)
assert deserialized_data == mx.nd.array([0])
def test_mxnet_transformer_default_output_fn(encode):
prediction = mx.ndarray.zeros(1)
accept = 'application/json'
t = MXNetTransformer()
response = t.default_output_fn(prediction, accept)
flattened_prediction = prediction.asnumpy().tolist()
encode.assert_called_with(flattened_prediction, accept)
assert isinstance(response, worker.Response)
def test_mxnet_transformer_init():
t = MXNetTransformer()
assert t._model is None
assert t._model_fn == transformer.default_model_fn
assert t._input_fn == t.default_input_fn
assert t._predict_fn == t.default_predict_fn
assert t._output_fn == t.default_output_fn
assert t.VALID_CONTENT_TYPES == (content_types.JSON, content_types.NPY)
def test_mxnet_transformer_init_with_args():
model = Mock()
model_fn = Mock()
input_fn = Mock()
predict_fn = Mock()
output_fn = Mock()
error_class = Mock()
t = MXNetTransformer(model=model, model_fn=model_fn, input_fn=input_fn, predict_fn=predict_fn,
output_fn=output_fn, error_class=error_class)
assert t._model == model
assert t._model_fn == model_fn
assert t._input_fn == input_fn
assert t._predict_fn == predict_fn
assert t._output_fn == output_fn
assert t._error_class == error_class
def test_mxnet_transformer_initialize_with_model(transformer_initialize):
t = MXNetTransformer(model=Mock())
t.initialize()
transformer_initialize.assert_not_called()
def test_mxnet_transformer_initialize_without_model(transformer_initialize):
t = MXNetTransformer()
t.initialize()
transformer_initialize.assert_called_once()