{"action":"created","issue":{"url":"https://api.github.com/repos/dmlc/mxnet/issues/3810","repository_url":"https://api.github.com/repos/dmlc/mxnet","labels_url":"https://api.github.com/repos/dmlc/mxnet/issues/3810/labels{/name}","comments_url":"https://api.github.com/repos/dmlc/mxnet/issues/3810/comments","events_url":"https://api.github.com/repos/dmlc/mxnet/issues/3810/events","html_url":"https://github.com/dmlc/mxnet/issues/3810","id":188953753,"number":3810,"title":"speech demo for decoding with kaldi","user":{"login":"nichongjia","id":13701336,"avatar_url":"https://avatars.githubusercontent.com/u/13701336?v=3","gravatar_id":"","url":"https://api.github.com/users/nichongjia","html_url":"https://github.com/nichongjia","followers_url":"https://api.github.com/users/nichongjia/followers","following_url":"https://api.github.com/users/nichongjia/following{/other_user}","gists_url":"https://api.github.com/users/nichongjia/gists{/gist_id}","starred_url":"https://api.github.com/users/nichongjia/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/nichongjia/subscriptions","organizations_url":"https://api.github.com/users/nichongjia/orgs","repos_url":"https://api.github.com/users/nichongjia/repos","events_url":"https://api.github.com/users/nichongjia/events{/privacy}","received_events_url":"https://api.github.com/users/nichongjia/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":15,"created_at":"2016-11-13T05:45:55Z","updated_at":"2016-12-05T07:09:27Z","closed_at":null,"body":"After I trained the lstm model using speech_demo in mxnet, I want to decode for eval data.\r\nBut it occurs an error. The following is the one of the log file for decoding.\r\n```\r\n-------------------------------------------------------------------------------------------------------------------\r\n\r\n# OMP_NUM_THREADS=1 python decode_mxnet.py --config ami_local_bptt.cfg --data_test exp_mxnet/data-for-mxnet/test.feats --data_label_mean exp_mxnet/data-for-mxnet/label_mean.feats --train_method simple --train_prefix ami --train_context cpu0 --train_batch_size 1 --data_test data_ihm-fmllr-tri4/ihm/eval/split20/1/mxnetInput.scp | latgen-faster-mapped --min-active=200 --max-active=7000 --max-mem=50000000 --beam=13.0 --lattice-beam=8.0 --acoustic-scale=0.1 --allow-partial=true --word-symbol-table=exp_kaldi/ihm/tri4a/graph_ami_fsh.o3g.kn.pr1-7/words.txt exp_mxnet/final.mdl exp_kaldi/ihm/tri4a/graph_ami_fsh.o3g.kn.pr1-7/HCLG.fst ark:- \"ark:|gzip -c > exp_mxnet/decode_eval/lat.1.gz\" \r\n# Started at Sat Nov 12 20:57:16 SGT 2016\r\n#\r\nlatgen-faster-mapped --min-active=200 --max-active=7000 --max-mem=50000000 --beam=13.0 --lattice-beam=8.0 --acoustic-scale=0.1 --allow-partial=true --word-symbol-table=exp_kaldi/ihm/tri4a/graph_ami_fsh.o3g.kn.pr1-7/words.txt exp_mxnet/final.mdl exp_kaldi/ihm/tri4a/graph_ami_fsh.o3g.kn.pr1-7/HCLG.fst ark:- 'ark:|gzip -c > exp_mxnet/decode_eval/lat.1.gz' \r\n!! CMDLine overwriting data.test:\r\n    'exp_mxnet/data-for-mxnet/test.feats' => 'data_ihm-fmllr-tri4/ihm/eval/split20/1/mxnetInput.scp'\r\n!! CMDLine overwriting data.label_mean:\r\n    'exp_mxnet/data-for-mxnet/label_mean.feats' => 'exp_mxnet/data-for-mxnet/label_mean.feats'\r\n!! CMDLine overwriting train.batch_size:\r\n    '40' => '1'\r\n!! CMDLine overwriting train.context:\r\n    'gpu0' => 'cpu0'\r\n!! CMDLine overwriting train.method:\r\n    'truncated-bptt' => 'simple'\r\n!! CMDLine overwriting train.prefix:\r\n    'ami' => 'ami'\r\n================================================================================\r\n[data]\r\nkaldi_root = /home/nichongjia/Work/ASR/Tools/20150325kaldi-dyn\r\ntrain = exp_mxnet/data-for-mxnet/train.feats\r\ndev = exp_mxnet/data-for-mxnet/dev.feats\r\ntest = data_ihm-fmllr-tri4/ihm/eval/split20/1/mxnetInput.scp\r\nout_file = exp_mxnet/data-for-mxnet/out_file.ark\r\nformat = kaldi\r\nxdim = 40\r\nydim = 3991\r\nlabel_mean = exp_mxnet/data-for-mxnet/label_mean.feats\r\n\r\n[arch]\r\nnum_hidden = 1024\r\nnum_hidden_proj = 512\r\nnum_lstm_layer = 3\r\n\r\n[train]\r\nbatch_size = 1\r\nbuckets = 100, 200, 300, 400, 500, 600, 700, 800\r\nnum_epoch = 12\r\ntruncate_len = 20\r\ncontext = cpu0\r\nmethod = simple\r\nprefix = ami\r\nlearning_rate = 1\r\ndecay_factor = 2\r\ndecay_lower_bound = 1e-6\r\noptimizer = speechSGD\r\nmomentum = 0.9\r\nclip_gradient = 0\r\ninitializer = Uniform\r\ninit_scale = 0.05\r\nweight_decay = 0.008\r\nshow_every = 1000\r\n\r\nLoading data...\r\nSummary of dataset ==================\r\nbucket of len   9 : 2 samples\r\nbucket of len  10 : 1 samples\r\nbucket of len  11 : 3 samples\r\nbucket of len  12 : 3 samples\r\nbucket of len  13 : 8 samples\r\nbucket of len  14 : 10 samples\r\nbucket of len  15 : 5 samples\r\nbucket of len  16 : 5 samples\r\nbucket of len  17 : 7 samples\r\nbucket of len  18 : 9 samples\r\nbucket of len  19 : 3 samples\r\nbucket of len  20 : 7 samples\r\nbucket of len  21 : 9 samples\r\nbucket of len  22 : 16 samples\r\nbucket of len  23 : 6 samples\r\nbucket of len  24 : 7 samples\r\nbucket of len  25 : 13 samples\r\nbucket of len  26 : 13 samples\r\nbucket of len  27 : 13 samples\r\nbucket of len  28 : 12 samples\r\nbucket of len  29 : 4 samples\r\nbucket of len  30 : 13 samples\r\nbucket of len  31 : 11 samples\r\nbucket of len  32 : 9 samples\r\nbucket of len  33 : 6 samples\r\nbucket of len  34 : 7 samples\r\nbucket of len  35 : 7 samples\r\nbucket of len  36 : 4 samples\r\nbucket of len  37 : 5 samples\r\nbucket of len  38 : 8 samples\r\nbucket of len  39 : 3 samples\r\nbucket of len  40 : 5 samples\r\nbucket of len  41 : 9 samples\r\nbucket of len  42 : 7 samples\r\nbucket of len  43 : 4 samples\r\nbucket of len  44 : 8 samples\r\nbucket of len  45 : 4 samples\r\nbucket of len  46 : 5 samples\r\nbucket of len  47 : 3 samples\r\nbucket of len  48 : 2 samples\r\nbucket of len  49 : 3 samples\r\nbucket of len  50 : 5 samples\r\nbucket of len  51 : 3 samples\r\nbucket of len  52 : 4 samples\r\nbucket of len  53 : 6 samples\r\nbucket of len  54 : 3 samples\r\nbucket of len  55 : 4 samples\r\nbucket of len  56 : 6 samples\r\nbucket of len  57 : 2 samples\r\nbucket of len  58 : 8 samples\r\nbucket of len  59 : 5 samples\r\nbucket of len  60 : 3 samples\r\nbucket of len  61 : 4 samples\r\nbucket of len  62 : 2 samples\r\nbucket of len  63 : 5 samples\r\nbucket of len  64 : 3 samples\r\nbucket of len  65 : 5 samples\r\nbucket of len  66 : 5 samples\r\nbucket of len  67 : 5 samples\r\nbucket of len  68 : 4 samples\r\nbucket of len  69 : 2 samples\r\nbucket of len  70 : 3 samples\r\nbucket of len  71 : 2 samples\r\nbucket of len  72 : 3 samples\r\nbucket of len  73 : 2 samples\r\nbucket of len  74 : 1 samples\r\nbucket of len  75 : 9 samples\r\nbucket of len  76 : 6 samples\r\nbucket of len  77 : 4 samples\r\nbucket of len  78 : 1 samples\r\nbucket of len  79 : 3 samples\r\nbucket of len  80 : 4 samples\r\nbucket of len  81 : 6 samples\r\nbucket of len  82 : 3 samples\r\nbucket of len  83 : 6 samples\r\nbucket of len  84 : 3 samples\r\nbucket of len  85 : 5 samples\r\nbucket of len  86 : 2 samples\r\nbucket of len  87 : 5 samples\r\nbucket of len  88 : 5 samples\r\nbucket of len  89 : 2 samples\r\nbucket of len  90 : 5 samples\r\nbucket of len  91 : 3 samples\r\nbucket of len  92 : 4 samples\r\nbucket of len  93 : 4 samples\r\nbucket of len  94 : 5 samples\r\nbucket of len  95 : 2 samples\r\nbucket of len  96 : 3 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samples\r\nbucket of len 615 : 1 samples\r\nbucket of len 622 : 3 samples\r\nbucket of len 625 : 1 samples\r\nbucket of len 630 : 1 samples\r\nbucket of len 638 : 1 samples\r\nbucket of len 641 : 1 samples\r\nbucket of len 645 : 1 samples\r\nbucket of len 646 : 1 samples\r\nbucket of len 651 : 1 samples\r\nbucket of len 654 : 1 samples\r\nbucket of len 656 : 2 samples\r\nbucket of len 664 : 1 samples\r\nbucket of len 666 : 1 samples\r\nbucket of len 668 : 2 samples\r\nbucket of len 669 : 1 samples\r\nbucket of len 677 : 1 samples\r\nbucket of len 684 : 1 samples\r\nbucket of len 687 : 1 samples\r\nbucket of len 698 : 1 samples\r\nbucket of len 703 : 1 samples\r\nbucket of len 708 : 1 samples\r\nbucket of len 727 : 1 samples\r\nbucket of len 729 : 1 samples\r\nbucket of len 737 : 1 samples\r\nbucket of len 740 : 1 samples\r\nbucket of len 744 : 2 samples\r\nbucket of len 746 : 1 samples\r\nbucket of len 749 : 1 samples\r\nbucket of len 750 : 1 samples\r\nbucket of len 751 : 1 samples\r\nbucket of len 765 : 1 samples\r\nbucket of len 778 : 1 samples\r\nbucket of len 786 : 1 samples\r\nbucket of len 791 : 1 samples\r\nbucket of len 799 : 1 samples\r\nbucket of len 800 : 1 samples\r\nbucket of len 806 : 1 samples\r\nbucket of len 833 : 1 samples\r\nbucket of len 874 : 1 samples\r\nbucket of len 878 : 1 samples\r\nbucket of len 882 : 1 samples\r\nbucket of len 894 : 1 samples\r\nbucket of len 947 : 1 samples\r\nbucket of len 951 : 1 samples\r\nbucket of len 991 : 1 samples\r\nbucket of len 1022 : 1 samples\r\nbucket of len 1028 : 1 samples\r\nbucket of len 1044 : 1 samples\r\nbucket of len 1054 : 1 samples\r\nbucket of len 1269 : 1 samples\r\n[20:57:20] src/operator/./reshape-inl.h:270: Using target_shape will be deprecated.\r\n[20:57:21] src/operator/./reshape-inl.h:270: Using target_shape will be deprecated.\r\n[20:57:21] src/operator/./reshape-inl.h:270: Using target_shape will be deprecated.\r\nTraceback (most recent call last):\r\n  File \"decode_mxnet.py\", line 134, in <module>\r\n    for preds, i_batch, batch in module.iter_predict(data_test):\r\n  File \"/usr/local/lib/python2.7/dist-packages/mxnet-0.7.0-py2.7.egg/mxnet/module/base_module.py\", line 203, in iter_predict\r\n    self.forward(eval_batch, is_train=False)\r\n  File \"/usr/local/lib/python2.7/dist-packages/mxnet-0.7.0-py2.7.egg/mxnet/module/bucketing_module.py\", line 263, in forward\r\n    data_batch.provide_label)\r\n  File \"/usr/local/lib/python2.7/dist-packages/mxnet-0.7.0-py2.7.egg/mxnet/module/bucketing_module.py\", line 216, in switch_bucket\r\n    force_rebind=False, shared_module=self._curr_module)\r\n  File \"/usr/local/lib/python2.7/dist-packages/mxnet-0.7.0-py2.7.egg/mxnet/module/module.py\", line 265, in bind\r\n    grad_req=grad_req)\r\n  File \"/usr/local/lib/python2.7/dist-packages/mxnet-0.7.0-py2.7.egg/mxnet/module/executor_group.py\", line 170, in __init__\r\n    self.label_layouts = self.decide_slices(label_shapes)\r\n  File \"/usr/local/lib/python2.7/dist-packages/mxnet-0.7.0-py2.7.egg/mxnet/module/executor_group.py\", line 184, in decide_slices\r\n    assert len(data_shapes) > 0\r\nAssertionError\r\nLOG (latgen-faster-mapped:main():latgen-faster-mapped.cc:163) Time taken 10.3109s: real-time factor assuming 100 frames/sec is inf\r\nLOG (latgen-faster-mapped:main():latgen-faster-mapped.cc:166) Done 0 utterances, failed for 0\r\nLOG (latgen-faster-mapped:main():latgen-faster-mapped.cc:168) Overall log-likelihood per frame is -nan over 0 frames.\r\n# Accounting: time=10 threads=1\r\n# Ended (code 1) at Sat Nov 12 20:57:26 SGT 2016, elapsed time 10 seconds\r\n```"},"comment":{"url":"https://api.github.com/repos/dmlc/mxnet/issues/comments/264782353","html_url":"https://github.com/dmlc/mxnet/issues/3810#issuecomment-264782353","issue_url":"https://api.github.com/repos/dmlc/mxnet/issues/3810","id":264782353,"user":{"login":"yzhang87","id":4911770,"avatar_url":"https://avatars.githubusercontent.com/u/4911770?v=3","gravatar_id":"","url":"https://api.github.com/users/yzhang87","html_url":"https://github.com/yzhang87","followers_url":"https://api.github.com/users/yzhang87/followers","following_url":"https://api.github.com/users/yzhang87/following{/other_user}","gists_url":"https://api.github.com/users/yzhang87/gists{/gist_id}","starred_url":"https://api.github.com/users/yzhang87/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yzhang87/subscriptions","organizations_url":"https://api.github.com/users/yzhang87/orgs","repos_url":"https://api.github.com/users/yzhang87/repos","events_url":"https://api.github.com/users/yzhang87/events{/privacy}","received_events_url":"https://api.github.com/users/yzhang87/received_events","type":"User","site_admin":false},"created_at":"2016-12-05T07:09:27Z","updated_at":"2016-12-05T07:09:27Z","body":"Please also change this line:\r\nhttps://github.com/yzhang87/mxnet/blob/master/example/speech-demo/decode_mxnet.py#L145\r\n(Add [0] after batch.utt_len)\r\n\r\nThis appears to be an issue with the latest version of Numpy. It is an error to treat a single-element array as a scalar for the purposes of indexing now."}}
{"actor":{"display_login":"yzhang87"}}