| import mxnet as mx |
| |
| |
| def warpctc_layer(net, label, num_label, seq_len, character_classes_count): |
| cls_weight = mx.sym.Variable("cls_weight") |
| cls_bias = mx.sym.Variable("cls_bias") |
| fc_seq = [] |
| for seqidx in range(seq_len): |
| hidden = net[seqidx] |
| hidden = mx.sym.FullyConnected(data=hidden, |
| num_hidden=character_classes_count, |
| weight=cls_weight, |
| bias=cls_bias) |
| fc_seq.append(hidden) |
| net = mx.sym.Concat(*fc_seq, dim=0) |
| |
| label = mx.sym.Reshape(data=label, shape=(-1,)) |
| label = mx.sym.Cast(data=label, dtype='int32') |
| |
| net = mx.sym.WarpCTC(data=net, label=label, label_length=num_label, input_length=seq_len) |
| |
| return net |
