Created by: bushidonggua

paddle版本为当前最新， use_gpu已经设置为0

sh run_train.sh
-----------  Configuration Arguments -----------
augment_conf_path: conf/augmentation.config
batch_size: 16
dev_manifest: data/tiny/manifest.tiny
init_model_path: None
is_local: 1
learning_rate: 1e-05
max_duration: 27.0
mean_std_path: data/tiny/mean_std.npz
min_duration: 0.0
num_conv_layers: 2
num_iter_print: 100
num_passes: 20
num_proc_data: 1
num_rnn_layers: 3
output_model_dir: ./checkpoints/tiny
rnn_layer_size: 2048
share_rnn_weights: 1
shuffle_method: batch_shuffle_clipped
specgram_type: linear
test_off: 0
train_manifest: data/tiny/manifest.tiny
trainer_count: 1
use_gpu: 0
use_gru: 0
use_sortagrad: 1
vocab_path: data/tiny/vocab.txt
------------------------------------------------
I0128 15:36:36.402436 2102243328 Util.cpp:166] commandline:  --use_gpu=0 --rnn_use_batch=True --log_clipping=True --trainer_count=1
[INFO 2018-01-28 15:36:36,413 layers.py:2714] output for __conv_0__: c = 32, h = 81, w = 54, size = 139968
[INFO 2018-01-28 15:36:36,414 layers.py:3282] output for __batch_norm_0__: c = 32, h = 81, w = 54, size = 139968
[INFO 2018-01-28 15:36:36,414 layers.py:7454] output for __scale_sub_region_0__: c = 32, h = 81, w = 54, size = 139968
[INFO 2018-01-28 15:36:36,415 layers.py:2714] output for __conv_1__: c = 32, h = 41, w = 54, size = 70848
[INFO 2018-01-28 15:36:36,416 layers.py:3282] output for __batch_norm_1__: c = 32, h = 41, w = 54, size = 70848
[INFO 2018-01-28 15:36:36,417 layers.py:7454] output for __scale_sub_region_1__: c = 32, h = 41, w = 54, size = 70848
I0128 15:36:36.737751 2102243328 GradientMachine.cpp:94] Initing parameters..
I0128 15:36:37.935442 2102243328 GradientMachine.cpp:101] Init parameters done.
F0128 15:36:42.101572 2102243328 DynamicLoader.cpp:104] Check failed: nullptr != *dso_handle Failed to find dynamic library: /usr/local/cuda/lib/libwarpctc.dylib (dlopen(/usr/local/cuda/lib/libwarpctc.dylib, 5): image not found)
Please specify its path correctly using following ways:
Method. set environment variable LD_LIBRARY_PATH on Linux or DYLD_LIBRARY_PATH on Mac OS.
For instance, issue command: export LD_LIBRARY_PATH=...
Note: After Mac OS 10.11, using the DYLD_LIBRARY_PATH is impossible unless System Integrity Protection (SIP) is disabled.
*** Check failure stack trace: ***
    @        0x1082062cd  google::LogMessage::Flush()
    @        0x10820a54f  google::LogMessageFatal::~LogMessageFatal()
    @        0x108207189  google::LogMessageFatal::~LogMessageFatal()
    @        0x1084ccaaf  GetDsoHandleFromSearchPath()
    @        0x1084ccc1e  GetWarpCTCDsoHandle()
    @     0x7fff8ce266e9  std::__1::__call_once()
    @        0x10854b1e9  hl_warpctc_init()
    @        0x108221383  paddle::WarpCTCLayer::forward()
    @        0x1082e273e  paddle::NeuralNetwork::forward()
    @        0x1082d5783  paddle::GradientMachine::forwardBackward()
    @        0x10854e7d6  GradientMachine::forwardBackward()
    @        0x1081e666e  _wrap_GradientMachine_forwardBackward()
    @        0x101b11562  PyEval_EvalFrameEx
    @        0x101b0e3c1  PyEval_EvalCodeEx
    @        0x101b144ae  _PyEval_SliceIndex
    @        0x101b1130c  PyEval_EvalFrameEx
    @        0x101b0e3c1  PyEval_EvalCodeEx
    @        0x101b144ae  _PyEval_SliceIndex
    @        0x101b1130c  PyEval_EvalFrameEx
    @        0x101b0e3c1  PyEval_EvalCodeEx
    @        0x101b144ae  _PyEval_SliceIndex
    @        0x101b1130c  PyEval_EvalFrameEx
    @        0x101b0e3c1  PyEval_EvalCodeEx
    @        0x101b144ae  _PyEval_SliceIndex
    @        0x101b1130c  PyEval_EvalFrameEx
    @        0x101b0e3c1  PyEval_EvalCodeEx
    @        0x101b144ae  _PyEval_SliceIndex
    @        0x101b1130c  PyEval_EvalFrameEx
    @        0x101b0e3c1  PyEval_EvalCodeEx
    @        0x101b144ae  _PyEval_SliceIndex
    @        0x101b1130c  PyEval_EvalFrameEx
    @        0x101b0e3c1  PyEval_EvalCodeEx
run_train.sh: line 33: 61758 Abort trap: 6           python -u train.py --batch_size=16 --trainer_count=1 --num_passes=20 --num_proc_data=1 --num_conv_layers=2 --num_rnn_layers=3 --rnn_layer_size=2048 --num_iter_print=100 --learning_rate=1e-5 --max_duration=27.0 --min_duration=0.0 --test_off=False --use_sortagrad=True --use_gru=False --use_gpu=False --is_local=True --share_rnn_weights=True --train_manifest='data/tiny/manifest.tiny' --dev_manifest='data/tiny/manifest.tiny' --mean_std_path='data/tiny/mean_std.npz' --vocab_path='data/tiny/vocab.txt' --output_model_dir='./checkpoints/tiny' --augment_conf_path='conf/augmentation.config' --specgram_type='linear' --shuffle_method='batch_shuffle_clipped'
Fail in training!