Created by: DemonPrince

hello tried to run deepspeech with docker, it downloaded from docker hub, but I could not configure it correctly to only use CPUs. I would appreciate knowing the complete configuration to only use CPU.

run_train configuration *********** Configuration Arguments ********** augment_conf_path: conf/augmentation.config batch_size: 8 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: 0 use_gpu: 0 use_gru: 0 use_sortagrad: 1 vocab_path: data/tiny/vocab.txt

error: I0717 19:07:04.436843 647 Util.cpp:166] commandline: --use_gpu=0 --rnn_use_batch=True --log_clipping=True --trainer_count=0 [INFO 2019-07-17 19:07:04,477 layers.py:2606] output for conv_0: c = 32, h = 81, w = 54, size = 139968 [INFO 2019-07-17 19:07:04,479 layers.py:3133] output for batch_norm_0: c = 32, h = 81, w = 54, size = 139968 [INFO 2019-07-17 19:07:04,479 layers.py:7224] output for scale_sub_region_0: c = 32, h = 81, w = 54, size = 139968 [INFO 2019-07-17 19:07:04,480 layers.py:2606] output for conv_1: c = 32, h = 41, w = 54, size = 70848 [INFO 2019-07-17 19:07:04,482 layers.py:3133] output for batch_norm_1: c = 32, h = 41, w = 54, size = 70848 [INFO 2019-07-17 19:07:04,483 layers.py:7224] output for scale_sub_region_1: c = 32, h = 41, w = 54, size = 70848 F0717 19:07:04.529284 647 GradientMachine.cpp:67] Unknown model type: nn

* Check failure stack trace: *

@ 0x7f9818ed004d google::LogMessage::Fail() @ 0x7f9818ed2398 google::LogMessage::SendToLog() @ 0x7f9818ecfb5b google::LogMessage::Flush() @ 0x7f9818ed326e google::LogMessageFatal::~LogMessageFatal() @ 0x7f9818b74c0c paddle::GradientMachine::create() @ 0x7f9818ea08bb GradientMachine::createFromPaddleModelPtr() @ 0x7f9818ea14ce GradientMachine::createByConfigProtoStr() @ 0x7f98189883aa _wrap_GradientMachine_createByConfigProtoStr @ 0x4c2e1e PyEval_EvalFrameEx @ 0x4b9b66 PyEval_EvalCodeEx @ 0x4c1f56 PyEval_EvalFrameEx @ 0x4b9b66 PyEval_EvalCodeEx @ 0x4c17c6 PyEval_EvalFrameEx @ 0x4b9b66 PyEval_EvalCodeEx @ 0x4d57a3 (unknown) @ 0x4eef5e (unknown) @ 0x4eeb66 (unknown) @ 0x4aaafb (unknown) @ 0x4c166d PyEval_EvalFrameEx @ 0x4b9b66 PyEval_EvalCodeEx @ 0x4c17c6 PyEval_EvalFrameEx @ 0x4b9b66 PyEval_EvalCodeEx @ 0x4c1f56 PyEval_EvalFrameEx @ 0x4b9b66 PyEval_EvalCodeEx @ 0x4c1f56 PyEval_EvalFrameEx @ 0x4b9b66 PyEval_EvalCodeEx @ 0x4eb69f (unknown) @ 0x4e58f2 PyRun_FileExFlags @ 0x4e41a6 PyRun_SimpleFileExFlags @ 0x4938ce Py_Main @ 0x7f9835098830 __libc_start_main @ 0x493299 _start Aborted (core dumped) Fail in training!