test_on_batch

FullyConnected.test_on_batch(x, y=None, sample_weight=None, return_dict=False)

Test the model on a single batch of samples.

Parameters:

• x – Input data. Must be array-like.

• y – Target data. Must be array-like.

• sample_weight – Optional array of the same length as x, containing weights to apply to the model’s loss for each sample. In the case of temporal data, you can pass a 2D array with shape (samples, sequence_length), to apply a different weight to every timestep of every sample.

• return_dict – If True, loss and metric results are returned as a dict, with each key being the name of the metric. If False, they are returned as a list.

Returns:

A scalar loss value (when no metrics and return_dict=False), a list of loss and metric values (if there are metrics and return_dict=False), or a dict of metric and loss values (if return_dict=True).