add transformerLM config path and dynamic import

deepspeech/decoders/recog.py

@@ -14,6 +14,7 @@
 """V2 backend for `asr_recog.py` using py:class:`decoders.beam_search.BeamSearch`."""
 import jsonlines
 import paddle
+import yaml
 from yacs.config import CfgNode
 
 from .beam_search import BatchBeamSearch
@@ -25,6 +26,7 @@ from deepspeech.exps import dynamic_import_tester
 from deepspeech.io.reader import LoadInputsAndTargets
 from deepspeech.models.asr_interface import ASRInterface
 from deepspeech.models.lm.transformer import TransformerLM
+from deepspeech.models.lm_interface import dynamic_import_lm
 from deepspeech.utils.log import Log
 # from espnet.asr.asr_utils import get_model_conf
 # from espnet.asr.asr_utils import torch_load
@@ -80,15 +82,12 @@ def recog_v2(args):
 
     if args.rnnlm:
         lm_path = args.rnnlm
-        lm = TransformerLM(
+        lm_config_path = args.rnnlm_conf
-            n_vocab=5002,
+        stream = open(lm_config_path, mode='r', encoding="utf-8")
-            pos_enc=None,
+        lm_config = yaml.load(stream, Loader=yaml.FullLoader)
-            embed_unit=128,
+        stream.close()
-            att_unit=512,
+        lm_class = dynamic_import_lm("transformer")
-            head=8,
+        lm = lm_class(**lm_config)
-            unit=2048,
-            layer=16,
-            dropout_rate=0.5, )
         model_dict = paddle.load(lm_path)
         lm.set_state_dict(model_dict)
         lm.eval()

examples/librispeech/s2/conf/lm/transformer.yaml

@@ -0,0 +1,11 @@
+n_vocab: 5002
+pos_enc: null
+embed_unit: 128
+att_unit: 512
+head: 8
+unit: 2048
+layer: 16
+dropout_rate: 0.5
+emb_dropout_rate: 0.0
+att_dropout_rate: 0.0
+tie_weights: False 

examples/librispeech/s2/local/recog.sh

@@ -11,9 +11,11 @@ tag=
 decode_config=conf/decode/decode.yaml
 
 # lm params
-lang_model=rnnlm.model.best
+lang_model=transformerLM.pdparams
-lmexpdir=exp/train_rnnlm_pytorch_lm_transformer_cosine_batchsize32_lr1e-4_layer16_unigram5000_ngpu4/
+lmexpdir=exp/transformerLM
 lmtag='nolm'
+rnnlm_config_path=conf/lm/transformer.yaml
+
 
 recog_set="test-clean test-other dev-clean dev-other"
 recog_set="test-clean"
@@ -27,7 +29,7 @@ bpemodel=${bpeprefix}.model
 # bin params
 config_path=conf/transformer.yaml
 dict=data/bpe_unigram_5000_units.txt
-ckpt_prefix=
+ckpt_prefix=exp/avg_10
 
 source ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
 
@@ -90,9 +92,9 @@ for dmethd in join_ctc; do
                 --recog-json ${feat_recog_dir}/split${nj}/JOB/manifest.${rtask} \
                 --result-label ${decode_dir}/data.JOB.json \
                 --model-conf ${config_path} \
-                --model ${ckpt_prefix}.pdparams
+                --model ${ckpt_prefix}.pdparams \
-
+                --rnnlm-conf ${rnnlm_config_path} \
-                #--rnnlm ${lmexpdir}/${lang_model} \
+                --rnnlm ${lmexpdir}/${lang_model} \
 
         score_sclite.sh --bpe ${nbpe} --bpemodel ${bpemodel} --wer false ${decode_dir} ${dict}