awslabs / sagemaker-defect-detection Goto Github PK

%%time
# SageMaker 1.x doesn't allow_pickle=True by default
np_load_old = np.load
np.load = lambda *args, **kwargs: np_load_old(*args, allow_pickle=True, **kwargs)
demo_predictions = demo_detector.predict(input)
np.load = np_load_old
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<timed exec> in <module>

/opt/conda/envs/sagemaker-soln/lib/python3.7/site-packages/sagemaker/predictor.py in predict(self, data, initial_args, target_model, target_variant)
    121         request_args = self._create_request_args(data, initial_args, target_model, target_variant)
    122         response = self.sagemaker_session.sagemaker_runtime_client.invoke_endpoint(**request_args)
--> 123         return self._handle_response(response)
    124 
    125     def _handle_response(self, response):

/opt/conda/envs/sagemaker-soln/lib/python3.7/site-packages/sagemaker/predictor.py in _handle_response(self, response)
    130         response_body = response["Body"]
    131         content_type = response.get("ContentType", "application/octet-stream")
--> 132         return self.deserializer.deserialize(response_body, content_type)
    133 
    134     def _create_request_args(self, data, initial_args=None, target_model=None, target_variant=None):

/opt/conda/envs/sagemaker-soln/lib/python3.7/site-packages/sagemaker/deserializers.py in deserialize(self, stream, content_type)
    223                 return np.array(json.load(codecs.getreader("utf-8")(stream)), dtype=self.dtype)
    224             if content_type == "application/x-npy":
--> 225                 return np.load(io.BytesIO(stream.read()), allow_pickle=self.allow_pickle)
    226         finally:
    227             stream.close()

<timed exec> in <lambda>(*args, **kwargs)

TypeError: <lambda>() got multiple values for keyword argument 'allow_pickle'