Training and Inference¶
Parameters¶
Trainer¶
Event¶
All training events.
There are:
- BeginIteration
- EndIteration
- BeginPass
- EndPass
TODO(yuyang18): Complete it!
Inference¶
-
paddle.v2.
infer
(output_layer, parameters, input, feeding=None, field='value') Infer a neural network by given neural network output and parameters. The user should pass either a batch of input data or reader method.
Example usages:
result = paddle.infer(prediction, parameters, input=SomeData, batch_size=32) print result
Parameters: - output_layer (paddle.v2.config_base.Layer) – output of the neural network that would be inferred
- parameters (paddle.v2.parameters.Parameters) – parameters of the neural network.
- input (collections.Iterable) – input data batch. Should be a python iterable object, and each element is the data batch.
- feeding – Reader dictionary. Default could generate from input value.
- field (str) – The prediction field. It should in [value, ids]. value means return the prediction probabilities, ids means return the prediction labels. Default is value
Returns: a numpy array
Return type: numpy.ndarray