bad performance for streaming transformer using trigger

[housebaby]

Hello, I trained a streaming transformer with following config, it seams that the loss is OK
but the decoding performance is bad. Is it neccesary to use prefix-decoder ?
When I use prefix-recognizie, error occurs. If I don't use prefix-recognize , the performance is bad

File "/home/storage15/username/tools/espnet/egs/librispeech/asr1/../../../espnet/bin/asr_recog.py", line 368, in
main(sys.argv[1:])
File "/home/storage15/username/tools/espnet/egs/librispeech/asr1/../../../espnet/bin/asr_recog.py", line 335, in main
recog_v2(args)
File "/home/storage15/username/tools/espnet/espnet/asr/pytorch_backend/recog.py", line 174, in recog_v2
best, ids, score = model.prefix_recognize(feat, args, train_args, train_args.char_list, lm)
File "/home/storage15/username/tools/espnet/espnet/nets/pytorch_backend/streaming_transformer.py", line 553, in prefix_recognize
self.compute_hyps(tmp,i,h_len,enc_output, hat_att[chunk_index], mask, train_args.chunk)
File "/home/storage15/username/tools/espnet/espnet/nets/pytorch_backend/streaming_transformer.py", line 776, in compute_hyps
enc_output4use, partial_mask4use, cache4use)
File "/home/storage15/username/tools/espnet/espnet/nets/pytorch_backend/transformer/decoder.py", line 310, in forward_one_step
x, tgt_mask, memory, memory_mask, cache=c
File "/home/storage15/username/tools/anaconda3/envs/py36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "/home/storage15/username/tools/espnet/espnet/nets/pytorch_backend/transformer/decoder_layer.py", line 94, in forward
), f"{cache.shape} == {(tgt.shape[0], tgt.shape[1] - 1, self.size)}"
AssertionError: torch.Size([5, 1, 512]) == (5, 2, 512)

train config:

This configuration requires 4 gpus with 12GB memory

accum-grad: 1
adim: 512
aheads: 8
batch-bins: 3000000
dlayers: 6
dropout-rate: 0.1
dunits: 2048
elayers: 12
epochs: 120
eunits: 2048
grad-clip: 5
lsm-weight: 0.1
model-module: espnet.nets.pytorch_backend.streaming_transformer:E2E
mtlalpha: 0.3
opt: noam
patience: 0
sortagrad: 0
transformer-attn-dropout-rate: 0.0
transformer-init: pytorch
transformer-input-layer: conv2d
transformer-length-normalized-loss: false
transformer-lr: 1.0
transformer-warmup-steps: 2500
n-iter-processes: 0

#enc-init: exp/train_960_pytorch_train_specaug/results/model.val5.avg.best
#/path/to/model
enc-init-mods: encoder,ctc,decoder

streaming: true
chunk: true
chunk-size: 32

decode_config:
lm-weight: 0.5
beam-size: 5
penalty: 2.0
maxlenratio: 0.0
minlenratio: 0.0
ctc-weight: 0.5
threshold: 0.0005
ctc-lm-weight: 0.5
prefix-decode: true

[qzfnihao]

Which version do you use？it looks like you merge steaming transducer to other espnet, because in this git, there is not invoking recog_v2