# Chinese Ordering System

# Run with container image on Ubuntu 20.04.2 Host 11th Gen Core system

docker pull chungyehwangai/chinese_ordering_system:0.7
docker run -it -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY -v ~/Downloads:/mnt --device /dev/dri:/dev/dri --group-add=$(stat -c "%g" /dev/dri/render*) --rm chungyehwangai/chinese_ordering_system:0.7

cd /mnt
ln -s /home/openvino/chinese_ordering .
cd /mnt/chinese_ordering/Chinese.Ordering.System/
export MODEL_DIR=/mnt/chinese_ordering/Chinese.Ordering.System/ir
export VOCAB_DIR=/mnt/chinese_ordering/Chinese.Ordering.System/vocab/
export PARAGRAPH_FILE=mc_paragraph.txt

python3.7 ordering_system_demo_pipeline.py                       \
    -m_mel  ${MODEL_DIR}/mel.xml                              \
    -m_mg   ${MODEL_DIR}/melgan.xml                           \
    -m_d    ${MODEL_DIR}/decoder.xml                          \
    -m_e    ${MODEL_DIR}/encoder.xml                          \
    -m_dp   ${MODEL_DIR}/duration_predictor.xml               \
    -m_b    ${MODEL_DIR}/bert.xml                             \
    -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml    \
    -p mds09x_cn                                              \
    -para ${PARAGRAPH_FILE}                                   \
    -i audio/sample.wav                                       \
    -v_b ${VOCAB_DIR}/vocab_bert.txt                          \
    -v_p ${VOCAB_DIR}/vocab_pinyin.txt                        \
    -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer

# Detail steps

https://github.com/FengYen-Chang/Chinese.Ordering.System

git clone https://github.com/FengYen-Chang/Chinese.Ordering.System.git
cd Chinese.Ordering.System/
mkdir ir
python3.7 -m pip install ds-ctcdecoder==0.9.3
cd model-conversion/mozilla-deepspeech-0.9.3-zh-CN
wget https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/deepspeech-0.9.3-models-zh-CN.pbmm
wget https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/deepspeech-0.9.3-models-zh-CN.scorer
python3.7 pbmm_to_pb.py deepspeech-0.9.3-models-zh-CN.pbmm deepspeech-0.9.3-models-zh-CN.pb
python3.7 /opt/intel/openvino/deployment_tools/model_optimizer/mo.py \
--input_model deepspeech-0.9.3-models-zh-CN.pb \
--freeze_placeholder_with_value="input_lengths->16" \
--input=input_node,previous_state_h,previous_state_c \
--input_shape=[1,16,19,26],[1,2048],[1,2048] \
--disable_nhwc_to_nchw \
--output=logits,cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd,cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd_1

mv deepspeech-0.9.3-models-zh-CN.xml ../../ir
mv deepspeech-0.9.3-models-zh-CN.bin ../../ir
mv deepspeech-0.9.3-models-zh-CN.mapping ../../ir
mv deepspeech-0.9.3-models-zh-CN.scorer ../../ir
cd ../../
python3 speech_recognition_demo.py -i audio/sample.wav -p mds09x_cn -m deepspeech-0.9.3-models-zh-CN.xml

### TTS

git clone https://github.com/FengYen-Chang/Chinese.Ordering.System.git

cd Chinese.Ordering.System

git submodule update --init ./extension/mandarin-tts

git submodule update --init ./extension/melgan

cd ./extension/mandarin-tts

pip install gdown

gdown https://drive.google.com/uc?id=11mBus5gn69_KwvNec9Zy9jjTs3LgHdx3

tar xf fastspeech2u_ckpt.tar.gz

sudo apt-get install ffmpeg
sudo apt-get install liblzma-dev
pip3 install -r requirements.txt

python3 export_onnx.py --model_file ./ckpt/hanzi/checkpoint_300000.pth.tar --text_file ./test.txt --channel 2 --duration_control 1.0 --output_dir ./output

cd onnx

pip3 install -r /opt/intel/openvino/deployment_tools/model_optimizer/requirements_onnx.txt

python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model mel.onnx

python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model decoder.onnx

python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model duration_predictor.onnx

python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model encoder.onnx

cd ../../../extension/melgan

python3 export_onnx.py

cd onnx

python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model melgan.onnx

For test, you can run the tts.py.

python3 tts.py \
-m_mel /your_root/Chinese.Ordering.System/extension/mandarin-tts/onnx/mel.xml \
-m_mg /your_root/Chinese.Ordering.System/extension/melgan/onnx/melgan.xml \
-m_d /your_root/Chinese.Ordering.System/extension/mandarin-tts/onnx/decoder.xml \
-m_e /your_root/Chinese.Ordering.System/extension/mandarin-tts/onnx/encoder.xml \
-m_dp /your_root/Chinese.Ordering.System/extension/mandarin-tts/onnx/duration_predictor.xml \
-i 一百五一百五一百五一百五一百五一百五一百五一百五一百五一百五

### BERT

git clone https://github.com/FengYen-Chang/Chinese.Ordering.System.git

git submodule update --init ./extension/cmrc2018/

cd menu-generator
python mc_menu_generator.py

cd ../extension/cmrc2018/baseline

apt update
apt install software-properties-common
add-apt-repository ppa:deadsnakes/ppa
apt update
apt install python3.7
python3.7 -m pip install tensorflow==1.15.0
//pip install tensorflow==1.15.0

python3.7 run_cmrc2018_drcd_baseline.py \
--vocab_file=/mnt/roberta-wwm-base-distill/model/3layers_large/vocab.txt \
--bert_config_file=/mnt/roberta-wwm-base-distill/model/3layers_large/bert_config.json \
--init_checkpoint=/mnt/roberta-wwm-base-distill/model/3layers_large/bert_model.ckpt \
--do_train=True \
--train_file=../../../menu-generator/test_1.json \
--do_predict=True \
--predict_file=../../../menu-generator/test_1.json \
--train_batch_size=32 \
--num_train_epochs=40 \
--max_seq_length=256 \
--doc_stride=128 \
--learning_rate=3e-5 \
--save_checkpoints_steps=1000 \
--output_dir=aa \
--do_lower_case=False \
--use_tpu=False

### numpy 1.21.0 causing issue below. Used 1.18.1 instead to resolve.

INFO:tensorflow:***** Running predictions *****
I0701 06:39:57.537319 140599964568448 run_cmrc2018_drcd_baseline.py:1257] ***** Running predictions *****
INFO:tensorflow:  Num orig examples = 76
I0701 06:39:57.537443 140599964568448 run_cmrc2018_drcd_baseline.py:1258]   Num orig examples = 76
INFO:tensorflow:  Num split examples = 111
I0701 06:39:57.537497 140599964568448 run_cmrc2018_drcd_baseline.py:1259]   Num split examples = 111
INFO:tensorflow:  Batch size = 8
I0701 06:39:57.537549 140599964568448 run_cmrc2018_drcd_baseline.py:1260]   Batch size = 8
INFO:tensorflow:Calling model_fn.
I0701 06:39:57.556351 140599964568448 estimator.py:1148] Calling model_fn.
INFO:tensorflow:Running infer on CPU
I0701 06:39:57.556496 140599964568448 tpu_estimator.py:3124] Running infer on CPU
INFO:tensorflow:*** Features ***
I0701 06:39:57.556693 140599964568448 run_cmrc2018_drcd_baseline.py:647] *** Features ***
INFO:tensorflow:  name = input_ids, shape = (?, 256)
I0701 06:39:57.556771 140599964568448 run_cmrc2018_drcd_baseline.py:649]   name = input_ids, shape = (?, 256)
INFO:tensorflow:  name = input_mask, shape = (?, 256)
I0701 06:39:57.556828 140599964568448 run_cmrc2018_drcd_baseline.py:649]   name = input_mask, shape = (?, 256)
INFO:tensorflow:  name = input_span_mask, shape = (?, 256)
I0701 06:39:57.556879 140599964568448 run_cmrc2018_drcd_baseline.py:649]   name = input_span_mask, shape = (?, 256)
INFO:tensorflow:  name = segment_ids, shape = (?, 256)
I0701 06:39:57.556931 140599964568448 run_cmrc2018_drcd_baseline.py:649]   name = segment_ids, shape = (?, 256)
INFO:tensorflow:  name = unique_ids, shape = (?,)
I0701 06:39:57.556982 140599964568448 run_cmrc2018_drcd_baseline.py:649]   name = unique_ids, shape = (?,)
ERROR:tensorflow:Error recorded from prediction_loop: Cannot convert a symbolic Tensor (bert/encoder/strided_slice:0) to a numpy array.
E0701 06:39:57.594310 140599964568448 error_handling.py:75] Error recorded from prediction_loop: Cannot convert a symbolic Tensor (bert/encoder/strided_slice:0) to a numpy array.
INFO:tensorflow:prediction_loop marked as finished
I0701 06:39:57.594428 140599964568448 error_handling.py:101] prediction_loop marked as finished
WARNING:tensorflow:Reraising captured error
W0701 06:39:57.594482 140599964568448 error_handling.py:135] Reraising captured error
Traceback (most recent call last):
  File "run_cmrc2018_drcd_baseline.py", line 1366, in <module>
    tf.app.run()
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/platform/app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 312, in run
    _run_main(main, args)
  File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 258, in _run_main
    sys.exit(main(argv))
  File "run_cmrc2018_drcd_baseline.py", line 1274, in main
    predict_input_fn, yield_single_examples=True):
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py", line 3078, in predict
    rendezvous.raise_errors()
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/tpu/error_handling.py", line 136, in raise_errors
    six.reraise(typ, value, traceback)
  File "/usr/lib/python3/dist-packages/six.py", line 703, in reraise
    raise value
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py", line 3072, in predict
    yield_single_examples=yield_single_examples):
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 622, in predict
    features, None, ModeKeys.PREDICT, self.config)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py", line 2857, in _call_model_fn
    config)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1149, in _call_model_fn
    model_fn_results = self._model_fn(features=features, **kwargs)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py", line 3126, in _model_fn
    features, labels, is_export_mode=is_export_mode)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py", line 1663, in call_without_tpu
    return self._call_model_fn(features, labels, is_export_mode=is_export_mode)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py", line 1994, in _call_model_fn
    estimator_spec = self._model_fn(features=features, **kwargs)
  File "run_cmrc2018_drcd_baseline.py", line 666, in model_fn
    use_one_hot_embeddings=use_one_hot_embeddings)
  File "run_cmrc2018_drcd_baseline.py", line 601, in create_model
    use_one_hot_embeddings=use_one_hot_embeddings)
  File "/mnt/chinese_ordering/Chinese.Ordering.System/extension/cmrc2018/baseline/modeling.py", line 202, in __init__
    input_ids, input_mask)
  File "/mnt/chinese_ordering/Chinese.Ordering.System/extension/cmrc2018/baseline/modeling.py", line 552, in create_attention_mask_from_input_mask
    shape=[batch_size, from_seq_length, 1], dtype=tf.float32)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/array_ops.py", line 2560, in ones
    output = _constant_if_small(one, shape, dtype, name)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/ops/array_ops.py", line 2295, in _constant_if_small
    if np.prod(shape) < 1000:
  File "<__array_function__ internals>", line 6, in prod
  File "/usr/local/lib/python3.7/dist-packages/numpy/core/fromnumeric.py", line 3052, in prod
    keepdims=keepdims, initial=initial, where=where)
  File "/usr/local/lib/python3.7/dist-packages/numpy/core/fromnumeric.py", line 86, in _wrapreduction
    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
  File "/usr/local/lib/python3.7/dist-packages/tensorflow_core/python/framework/ops.py", line 736, in __array__
    " array.".format(self.name))
NotImplementedError: Cannot convert a symbolic Tensor (bert/encoder/strided_slice:0) to a numpy array.

python3.7 export_pb.py \
--vocab_file=/mnt/roberta-wwm-base-distill/model/3layers_large/vocab.txt \
--bert_config_file=/mnt/roberta-wwm-base-distill/model/3layers_large/bert_config.json \
--init_checkpoint=aa/model.ckpt-138 \
--do_train=True \
--train_file=../../../menu-generator/test_1.json \
--do_predict=True \
--predict_file=../../../menu-generator/test_1.json \
--train_batch_size=32 \
--num_train_epochs=40 \
--max_seq_length=256 \
--doc_stride=128 \
--learning_rate=3e-5 \
--save_checkpoints_steps=1000 \
--output_dir=aa \
--do_lower_case=False \
--use_tpu=False

python3.7 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model=aa/inference_graph.pb \
--input "IteratorGetNext:0{i32}[1 256],IteratorGetNext:1{i32}[1 256],IteratorGetNext:3{i32}[1 256]" \
--disable_nhwc_to_nchw

For Ordering system pipeline demo:

pip install pyyaml
pip install pycnnum
pip install ds-ctcdecoder==0.9.3

export MODEL_DIR=/mnt/chinese_ordering/Chinese.Ordering.System/ir
export VOCAB_DIR=/mnt/chinese_ordering/Chinese.Ordering.System/vocab/
export PARAGRAPH_FILE=mc_paragraph.txt

python3.7 ordering_system_demo_pipeline.py                       \
    -m_mel  ${MODEL_DIR}/mel.xml                              \
    -m_mg   ${MODEL_DIR}/melgan.xml                           \
    -m_d    ${MODEL_DIR}/decoder.xml                          \
    -m_e    ${MODEL_DIR}/encoder.xml                          \
    -m_dp   ${MODEL_DIR}/duration_predictor.xml               \
    -m_b    ${MODEL_DIR}/bert.xml                             \
    -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml    \
    -p mds09x_cn                                              \
    -para ${PARAGRAPH_FILE}                                   \
    -i audio/sample.wav                                       \
    -v_b ${VOCAB_DIR}/vocab_bert.txt                          \
    -v_p ${VOCAB_DIR}/vocab_pinyin.txt                        \
    -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer

Example for paragraph, mc_paragraph.txt.

麦当劳目前的餐点有：大麦克价格为72元、双层牛肉吉事堡价格为62元、嫩煎鸡腿堡价格为82元、麦香鸡价格为44元、麦克鸡块(6块)价格为60元、麦克鸡块(10块)价格为100元、劲辣鸡腿堡价格为72元、麦脆(2块)价格为110元、麦脆鸡翅(2块)价格为90元、黄金起司猪排堡价格为52元、麦香鱼价格为44元、烟熏鸡肉长堡价格为74元、姜烧猪肉长堡价格为74元、BLT 安格斯黑牛堡价格为109元、BLT 辣脆鸡腿堡价格为109元、BLT 嫩煎鸡腿堡价格为109元、蕈菇安格斯黑牛堡价格为119元、凯萨脆鸡沙拉价格为99元和义式烤鸡沙拉价格为99元。

The content of the mc_paragraph.txt is from Bert's training data.


root@93805c56e6de:/mnt/chinese_ordering/Chinese.Ordering.System# history 
    1  cd
    2  apt update
    3  apt install git
    4  cd /mnt/
    5  mkdir chinese_ordering
    6  cd chinese_ordering/
    7  git clone https://github.com/FengYen-Chang/Chinese.Ordering.System.git
    8  cd Chinese.Ordering.System/
    9  ls
   10  git submodule update --init ./extension/mandarin-tts
   11  git submodule update --init ./extension/melgan 
   12  cd ./extension/mandarin-tts
   13  pip install gdown
   14  gdown https://drive.google.com/uc?id=11mBus5gn69_KwvNec9Zy9jjTs3LgHdx3
   15  tar xf fastspeech2u_ckpt.tar.gz 
   16  sudo apt-get install ffmpeg
   17  apt-get install ffmpeg
   18  ls
   19  pip3 install -r requirements.txt
   20  apt-get install liblzma-dev
   21  pip3 install -r requirements.txt
   22  python3 export_onnx.py --model_file ./ckpt/hanzi/checkpoint_300000.pth.tar --text_file ./test.txt --channel 2 --duration_control 1.0 --output_dir ./output
   23  ls
   24  cd onnx/
   25  ls
   26  python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model mel.onnx 
   27  pip3 install /opt/intel/openvino/deployment_tools/model_optimizer/requirements_onnx.txt 
   28  pip3 install -r /opt/intel/openvino/deployment_tools/model_optimizer/requirements_onnx.txt 
   29  python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model mel.onnx 
   30  python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model decoder.onnx 
   31  ls
   32  python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model duration_predictor.onnx 
   33  ls
   34  python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model encoder.onnx
   35  cd ../../../extension/melga
   36  cd ../../../extension/melgan/
   37  ls
   38  python3 export_onnx.py 
   39  cd onnx/
   40  ls
   41  python3 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model melgan.onnx
   42  ls
   43  cd ../../
   44  ls
   45  cd ../
   46  ls
   47  python3 tts.py -m_mel /mnt/chinese_ordering/Chinese.Ordering.System/extension/mandarin-tts/onnx/mel.xml -m_mg /mnt/chinese_ordering/Chinese.Ordering.System/extension/melgan/onnx/melgan.xml -m_d /mnt/chinese_ordering/Chinese.Ordering.System/extension/mandarin-tts/onnx/decoder.xml -m_e /mnt/chinese_ordering/Chinese.Ordering.System/extension/mandarin-tts/onnx/encoder.xml -m_dp /mnt/chinese_ordering/Chinese.Ordering.System/extension/mandarin-tts/onnx/duration_predictor.xml -i 一百五一百五一百五一百五一百五一百五一百五一百五一百五一百五
   48  git submodule update --init ./extension/cmrc2018/
   49  cd menu-generato
   50  ls
   51  cd menu-generator/
   52  python mc_menu_generator.py
   53  python3 mc_menu_generator.py
   54  cd ../extension/cmrc2018/baseline/
   55  pip install tensorflow==1.15.0
   56  pip3 install tensorflow==1.15.0
   57  python3 -m pip install tensorflow==1.15.0
   58  pip3 list | grep tensor
   59  pip3 install tensorflow==1.15
   60  python3 -m venv
   61  cd
   62  python3 -m venv -h
   63  apt install software-properties-common
   64  add-apt-repository ppa:deadsnakes/ppa
   65  apt update
   66  apt install python3.7
   67  which python
   68  which python3
   69  which python3.7
   70  ls -l /usr/bin/python3
   71  python3.7
   72  python3.7 -m pip install tensorflow==1.15.0
   73  cd /mnt/chinese_ordering/Chinese.Ordering.System/
   74  ls
   75  cd extension/
   76  ls
   77  cd Chinese.BERT.OpenVINO/
   78  ls
   79  ls ../cmrc2018/
   80  cd ../../
   81  find | grep robeta
   82  find | grep roberta
   83  git submodule update --init ./extension/Chinese.BERT.OpenVINO
   84  history 

for bert + deepspeech

    1  cd /mnt/chinese_ordering/Chinese.Ordering.System/
    2  ls
    3  cd extension/cmrc2018/
    4  cd ba
    5  ls
    6  cd baseline/
    7  python3.7 run_cmrc2018_drcd_baseline.py     --vocab_file=/mnt/roberta-wwm-base-distill/model/3layers_large/vocab.txt     --bert_config_file=/mnt/roberta-wwm-base-distill/model/3layers_large/bert_config.json     --init_checkpoint=/mnt/roberta-wwm-base-distill/model/3layers_large/bert_model.ckpt     --do_train=True     --train_file=../../../menu-generator/test_1.json     --do_predict=True     --predict_file=../../../menu-generator/test_1.json     --train_batch_size=32     --num_train_epochs=40     --max_seq_length=256     --doc_stride=128     --learning_rate=3e-5     --save_checkpoints_steps=1000     --output_dir=aa     --do_lower_case=False     --use_tpu=False
    8  ls aa
    9  ls
   10  python3.7 -m pip list | grep numpy
   11  python3.7 export_pb.py     --vocab_file=/mnt/roberta-wwm-base-distill/model/3layers_large/vocab.txt     --bert_config_file=/mnt/roberta-wwm-base-distill/model/3layers_large/bert_config.json     --init_checkpoint=aa/model.ckpt-138     --do_train=True     --train_file=../../../menu-generator/test_1.json     --do_predict=True     --predict_file=../../../menu-generator/test_1.json     --train_batch_size=32     --num_train_epochs=40     --max_seq_length=256     --doc_stride=128     --learning_rate=3e-5     --save_checkpoints_steps=1000     --output_dir=aa     --do_lower_case=False     --use_tpu=False
   12  ls
   13  python3.7 --version
   14  python3.7 -m pip list 
   15  python3.7 -m pip install numpy==1.18.1
   16  python3.7 export_pb.py     --vocab_file=/mnt/roberta-wwm-base-distill/model/3layers_large/vocab.txt     --bert_config_file=/mnt/roberta-wwm-base-distill/model/3layers_large/bert_config.json     --init_checkpoint=aa/model.ckpt-138     --do_train=True     --train_file=../../../menu-generator/test_1.json     --do_predict=True     --predict_file=../../../menu-generator/test_1.json     --train_batch_size=32     --num_train_epochs=40     --max_seq_length=256     --doc_stride=128     --learning_rate=3e-5     --save_checkpoints_steps=1000     --output_dir=aa     --do_lower_case=False     --use_tpu=False
   17  ls
   18  ls aa
   19  python3.7 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model=aa/inference_graph.pb                --input "IteratorGetNext:0{i32}[1 256],IteratorGetNext:1{i32}[1 256],IteratorGetNext:3{i32}[1 256]"                --disable_nhwc_to_nchw
   20  cat /opt/intel/openvino_2021/deployment_tools/model_optimizer/requirements.txt 
   21  python3.7 -m pip install networkx>=1.11
   22  ls
   23  rm '=1.11' 
   24  python3.7 -m pip install 'networkx>=1.11'
   25  python3.7 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model=aa/inference_graph.pb                --input "IteratorGetNext:0{i32}[1 256],IteratorGetNext:1{i32}[1 256],IteratorGetNext:3{i32}[1 256]"                --disable_nhwc_to_nchw
   26  python3.7 -m pip install 'defusedxml>=0.5.0'
   27  python3.7 /opt/intel/openvino_2021/deployment_tools/model_optimizer/mo.py --input_model=aa/inference_graph.pb                --input "IteratorGetNext:0{i32}[1 256],IteratorGetNext:1{i32}[1 256],IteratorGetNext:3{i32}[1 256]"                --disable_nhwc_to_nchw
   28  cd ../../
   29  ls
   30  mkdir ir
   31  cd ir
   32  cp ../cmrc2018/baseline/inference_graph.* .
   33  ls
   34  mkdir bert
   35  mv inference_graph.* bert/
   36  ls
   37  mv ir ../
   38  cd ../
   39  mv ir ../
   40  cd ../ir/
   41  ls e
   42  ls ../extension/
   43  ls ../extension/mandarin-tts/
   44  ls ../extension/mandarin-tts/onnx/
   45  ls ../extension/mandarin-tts/onnx/*xml .
   46  cp ../extension/mandarin-tts/onnx/*xml .
   47  cp ../extension/mandarin-tts/onnx/*bin .
   48  cp ../extension/mandarin-tts/onnx/*mappings .
   49  cp ../extension/mandarin-tts/onnx/*mapping .
   50  ls
   51  cp ../extension/melgan/onnx/melgan.* .
   52  ls
   53  rm melgan.onnx 
   54  ls
   55  cd ../
   56  ls
   57  python3.7 -m pip install ds-ctcdecoder==0.9.3
   58  cd cd model-conversion/mozilla-deepspeech-0.9.3-zh-CN
   59  cd model-conversion/mozilla-deepspeech-0.9.3-zh-CN
   60  wget https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/deepspeech-0.9.3-models-zh-CN.pbmm
   61  apt install wget
   62  wget https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/deepspeech-0.9.3-models-zh-CN.pbmm
   63  python3.7 pbmm_to_pb.py deepspeech-0.9.3-models-zh-CN.pbmm deepspeech-0.9.3-models-zh-CN.pb
   64  python3.7 /opt/intel/openvino/deployment_tools/model_optimizer/mo.py     --input_model deepspeech-0.9.3-models-zh-CN.pb     --freeze_placeholder_with_value="input_lengths->16"     --input=input_node,previous_state_h,previous_state_c     --input_shape=[1,16,19,26],[1,2048],[1,2048]     --disable_nhwc_to_nchw     --output=logits,cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd,cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/GatherNd_1
   65  python3.7 -m pip install "test-generator==0.1.1"
   66  ls ../
   67  ls ../../
   68  ls ../../ir/
   69  mv deepspeech-0.9.3-models-zh-CN.xml ../../ir
   70  mv deepspeech-0.9.3-models-zh-CN.bin ../../ir
   71  mv deepspeech-0.9.3-models-zh-CN.mapping ../../ir
   72  cd ../../
   73  python3 speech_recognition_demo.py  -i audio/sample.wav  -p mds09x_cn -m ir/deepspeech-0.9.3-models-zh-CN.xml 
   74  python3.7 -m pip install pyyaml
   75  python3 speech_recognition_demo.py  -i audio/sample.wav  -p mds09x_cn -m ir/deepspeech-0.9.3-models-zh-CN.xml 
   76  python3.7 speech_recognition_demo.py  -i audio/sample.wav  -p mds09x_cn -m ir/deepspeech-0.9.3-models-zh-CN.xml 
   77  python3.7 -m pip install tqdm
   78  python3.7 speech_recognition_demo.py  -i audio/sample.wav  -p mds09x_cn -m ir/deepspeech-0.9.3-models-zh-CN.xml 
   79  cat requirements.txt 
   80  python3.7 -m pip install -r requirements.txt 
   81  python3.7 speech_recognition_demo.py  -i audio/sample.wav  -p mds09x_cn -m ir/deepspeech-0.9.3-models-zh-CN.xml 
   82  cd ir/
   83  ls
   84  mv bert/inference_graph.xml bert.xml
   85  mv bert/inference_graph.bin bert.bin
   86  mv bert/inference_graph.mapping bert.mapping
   87  rm -rf bert
   88  export MODEL_DIR=/mnt/chinese_ordering/Chinese.Ordering.System/ir
   89  ls ../../../roberta-wwm-base-distill
   90  ls ../../../roberta-wwm-base-distill/model/
   91  ls ../../../roberta-wwm-base-distill/model/3layers_large/
   92  vi ../../../roberta-wwm-base-distill/model/3layers_large/vocab.txt 
   93  cp ../../../roberta-wwm-base-distill/model/3layers_large/vocab.txt bert_vocab.txt
   94  ls ../extension/mandarin-tts/
   95  cd ../
   96  ls vocab/
   97  export VOCAB_DIR=/mnt/chinese_ordering/Chinese.Ordering.System/vocab/
   98  find | grep mc_pa
   99  ls
  100  export PARAGRAPH_FILE=mc_paragraph.txt
  101  ls
  102  python ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                            -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer
  103  python3.7 ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                            -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer
  104  python3 ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                            -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer
  105  pip3 install yaml
  106  pip3 install -r requirements.txt 
  107  python3 ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                            -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer
  108  ls ir/
  109  findls
  110  ls
  111  ls model-conversion/
  112  ls model-conversion/mozilla-deepspeech-0.9.3-zh-CN/
  113  find model-conversion/
  114  cd ir
  115  wget https://github.com/mozilla/DeepSpeech/releases/download/v0.9.3/deepspeech-0.9.3-models-zh-CN.scorer
  116  cd ../
  117  python3 ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                            -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer
  118  ls
  119  ./tts.wav
  120  clear
  121  history 
  122  history  | grep erport
  123  history  | grep export
  124  clear
  125  python ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                            -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer
  126  clear
  127  clearpython ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                        \
  128  python3.7 ordering_system_demo_pipeline.py                           -m_mel  ${MODEL_DIR}/mel.xml                                  -m_mg   ${MODEL_DIR}/melgan.xml                               -m_d    ${MODEL_DIR}/decoder.xml                              -m_e    ${MODEL_DIR}/encoder.xml                              -m_dp   ${MODEL_DIR}/duration_predictor.xml                   -m_b    ${MODEL_DIR}/bert.xml                                 -m_a    ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.xml        -p mds09x_cn                                                  -para ${PARAGRAPH_FILE}                                       -i audio/sample.wav                                           -v_b ${VOCAB_DIR}/vocab_bert.txt                              -v_p ${VOCAB_DIR}/vocab_pinyin.txt                            -L ${MODEL_DIR}/deepspeech-0.9.3-models-zh-CN.scorer
  129  history 
root@56be06b27ef8:/mnt/chinese_ordering/Chinese.Ordering.System#