def predict()

in tutorials/app/edge_agent_utils.py [0:0]

• 26 lines of code
• 5 McCabe index (conditional complexity)

def predict(cli, model_name, x, shm=False):
    """
    Invokes the model and get the predictions
    """
    try:
        model_map = list_models(cli)
        if model_map.get(model_name) is None:
            raise Exception('Model %s not loaded' % model_name)
        # Create a request
        req = agent.PredictRequest()
        req.name = model_name
        # Then load the data into a temp Tensor
        tensor = agent.Tensor()
        meta = model_map[model_name]['in'][0]
        tensor.tensor_metadata.name = meta.name
        tensor.tensor_metadata.data_type = meta.data_type
        for s in meta.shape: tensor.tensor_metadata.shape.append(s)
        
        if shm:
            tensor.shared_memory_handle.offset = 0
            tensor.shared_memory_handle.segment_id = x
        else:
            tensor.byte_data = x.astype(np.float32).tobytes()

        req.tensors.append(tensor)

        # Invoke the model
        resp = cli.Predict(req)

        # Parse the output
        meta = model_map[model_name]['out'][0]
        tensor = resp.tensors[0]
        data = np.frombuffer(tensor.byte_data, dtype=np.float32)
        return data.reshape(tensor.tensor_metadata.shape)
    except Exception as e:
        print(e)        
        return None