feed_data

True: The feed_dict parameter can contain only partial inputs of the model.
False: The feed_dict parameter must contain all inputs of the model.

Product	Supported
Atlas A3 training product/Atlas A3 inference product	√
Atlas A2 training product/Atlas A2 inference product	√
Atlas 200I/500 A2 inference product	x
Atlas inference product	x
Atlas training product	x

Inputs data to a graph.

feed_data(feed_dict, flow_info=None, timeout=-1, partial_inputs = False) -> int

Parameter	Data Type	Description
feed_dict	Dict[FlowData, Union["numpy.ndarray", Tensor, List]]	The key is a FlowData node, and the value is any input that can be converted into numpy.ndarray or dataflow.tensor. If the value of feed_dict is empty, flow_flags of flow_info must contain DATA_FLOW_FLAG_EOS. In this case, partial_inputs does not take effect.
flow_info	FlowInfo	Set FlowInfo as required. For details, see dataflow.FlowInfo.
timeout	int	Timeout period for inputting data, in ms. The value range is [0, 2147483647), and the value -1 indicates that no timeout will occur.
partial_inputs	bool	Whether feed_dict supports containing only partial inputs of the model whenever the feed_data API is called. The value can be: True: The feed_dict parameter can contain only partial inputs of the model. False: The feed_dict parameter must contain all inputs of the model. The default value is False.

0 is returned in normal scenarios.

A specific error code is returned and error logs are printed in abnormal scenarios.

import dataflow as df
graph = df.FlowGraph(...)
graph.feed_data(...)

None

Parent topic: dataflow.FlowGraph