|
|
@ -180,8 +180,10 @@ class CRNNEncoder(nn.Layer):
|
|
|
|
|
|
|
|
|
|
|
|
eouts_chunk_list = []
|
|
|
|
eouts_chunk_list = []
|
|
|
|
eouts_chunk_lens_list = []
|
|
|
|
eouts_chunk_lens_list = []
|
|
|
|
|
|
|
|
if (max_len - chunk_size) % chunk_stride != 0:
|
|
|
|
padding_len = chunk_stride - (max_len - chunk_size) % chunk_stride
|
|
|
|
padding_len = chunk_stride - (max_len - chunk_size) % chunk_stride
|
|
|
|
|
|
|
|
else:
|
|
|
|
|
|
|
|
padding_len = 0
|
|
|
|
padding = paddle.zeros((x.shape[0], padding_len, x.shape[2]))
|
|
|
|
padding = paddle.zeros((x.shape[0], padding_len, x.shape[2]))
|
|
|
|
padded_x = paddle.concat([x, padding], axis=1)
|
|
|
|
padded_x = paddle.concat([x, padding], axis=1)
|
|
|
|
num_chunk = (max_len + padding_len - chunk_size) / chunk_stride + 1
|
|
|
|
num_chunk = (max_len + padding_len - chunk_size) / chunk_stride + 1
|
|
|
|