espnet.nets.pytorch_backend.transformer.plot.PlotAttentionReport

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class espnet.nets.pytorch_backend.transformer.plot.PlotAttentionReport(att_vis_fn, data, outdir, converter, transform, device, reverse=False, ikey='input', iaxis=0, okey='output', oaxis=0, subsampling_factor=1)

Bases: PlotAttentionReport

get_attention_weights()

Return attention weights.

• Returns: attention weights. float. Its shape would be : differ from backend. * pytorch-> 1) multi-head case => (B, H, Lmax, Tmax), 2)

  other case => (B, Lmax, Tmax).

  • chainer-> (B, Lmax, Tmax)
• Return type: numpy.ndarray

log_attentions(logger, step)

Add image files of att_ws matrix to the tensorboard.

plotfn(*args, **kwargs)