From e9f3b3efa7232020bd3def394f29f26e163fd90f Mon Sep 17 00:00:00 2001 From: dohe0342 Date: Fri, 30 Dec 2022 11:17:59 +0900 Subject: [PATCH] from local --- .../.checkpoint.py.swp | Bin 24576 -> 24576 bytes .../.decode.py.swp | Bin 40960 -> 45056 bytes .../decode.py | 3 ++- 3 files changed, 2 insertions(+), 1 deletion(-) diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.checkpoint.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.checkpoint.py.swp index e45399841db1847a94202363deb413a881613b00..2dcf80bbbda33e07e2f5e5629d33fe91bf54e474 100644 GIT binary patch delta 32 mcmZoTz}RqrQ8dXQ%+puFQqO<^2m}}y+`ZN%PunQ^IvxO#jtM0I delta 32 mcmZoTz}RqrQ8dXQ%+puFQqO<^2m}}yG`!X&2W%959S;DH83@1t diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp index 50ae6f0786afd3f6b1c72df5a5a4299be8013e28..7a3e5899066bd5c79800e9e13636b4d94aa5f0fc 100644 GIT binary patch delta 806 zcmXxhT}V@59LMqB+1Y&W>`VzmLUt21BYGo?3iKxMvX&PWf)!2_&F1i?H>QM2NW?f^ z7!D)^?V^=*pbIPVVn{@VyO^L9X+$>(D@uec>N{Ewd^rE}!r|fj^v`+vS3EO0(~$es ztgJ9f9n*eem`=v74wUKN3KyHfmT#v(IcfXiR)-U39^Rt5Mvm^Afkrbl{jG8K~^-@+0(b{(&e^DcgT4#(Hy_f zCY>jJnh*2G@c)!HNxh1@xPu7t$B-lSTRg)kdTGcd7E?kwUshb9E^lic$dKo<_dk2#WGLj?6G!y4I>IE4n(VuRwd zxan(^PBMg01p_&9KgS3zVmmS9ViDo$w87F92`g~=WQ3I+=fz=kz>1Pp)a^YG&obGE&t~%ZnI}Z^i0H(tn6` zSDnrucdr>gj|VbYThfX_ib+XID;iO$j1%NBjd6JRa-|~Hu!u?Y;;lnE!Y*bpir0vA zfE^?-f~T-_i8NASWz|O`+_tk2bLfYSN{FG@#2|wBcBDFvv5Fz|;5jH=VHpGP@X{t- zpnw_taqTPk8(V07 PH)B+<52sweyr1|7$5KMh diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py index 88b5f8b5b..b333d0572 100755 --- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py +++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/decode.py @@ -663,6 +663,7 @@ def main(): logging.info("About to create model") model = get_transducer_model(params) + print(model) if params.model_name: load_checkpoint(f"{params.exp_dir}/{params.model_name}", model) @@ -757,7 +758,7 @@ def main(): torch.load(lg_filename, map_location=device) ) decoding_graph.scores *= params.ngram_lm_scale - else: + else word_table = None decoding_graph = k2.trivial_graph(params.vocab_size - 1, device=device) else: