mindspore.nn.WithEvalCell

class mindspore.nn.WithEvalCell(network, loss_fn, add_cast_fp32=False)[source]

Cell that returns loss, output and label for evaluation.

This Cell accepts a network and loss function as arguments and computes loss for model. It returns loss, output and label to calculate the metrics.

Parameters

  • network (Cell) – The network Cell.

  • loss_fn (Cell) – The loss Cell.

  • add_cast_fp32 (bool) – Adjust the data type to float32.

Inputs:

  • data (Tensor) - Tensor of shape \((N, \ldots)\).

  • label (Tensor) - Tensor of shape \((N, \ldots)\).

Outputs:

Tuple, containing a scalar loss Tensor, a network output Tensor of shape \((N, \ldots)\) and a label Tensor of shape \((N, \ldots)\).

Raises

TypeError – If add_cast_fp32 is not a bool.

Supported Platforms:

Ascend GPU

Examples

>>> # For a defined network Net without loss function
>>> net = Net()
>>> loss_fn = nn.SoftmaxCrossEntropyWithLogits()
>>> eval_net = nn.WithEvalCell(net, loss_fn)