python3 ./mo_tf.py --input_model /root/deepspeech-0.6.0-models/output_graph.pb --freeze_placeholder_with_value "input_lengths->[16]" --input input_node,previous_state_h/read,previous_state_c/read --input_shape [1,16,19,26],[1,2048],[1,2048] --output Softmax,lstm_fused_cell/GatherNd,lstm_fused_cell/GatherNd_1 --disable_nhwc_to_nchw
Model Optimizer arguments:
Common parameters:
        - Path to the Input Model:      /root/deepspeech-0.6.0-models/output_graph.pb
        - Path for generated IR:        /opt/intel/openvino_2020.3.194/deployment_tools/model_optimizer/.
        - IR output name:       output_graph
        - Log level:    ERROR
        - Batch:        Not specified, inherited from the model
        - Input layers:         input_node,previous_state_h/read,previous_state_c/read
        - Output layers:        Softmax,lstm_fused_cell/GatherNd,lstm_fused_cell/GatherNd_1
        - Input shapes:         [1,16,19,26],[1,2048],[1,2048]
        - Mean values:  Not specified
        - Scale values:         Not specified
        - Scale factor:         Not specified
        - Precision of IR:      FP32
        - Enable fusing:        True
        - Enable grouped convolutions fusing:   True
        - Move mean values to preprocess section:       False
        - Reverse input channels:       False
TensorFlow specific parameters:
        - Input model in text protobuf format:  False
        - Path to model dump for TensorBoard:   None
        - List of shared libraries with TensorFlow custom layers implementation:        None
        - Update the configuration file with input/output node names:   None
        - Use configuration file used to generate the model with Object Detection API:  None
        - Use the config file:  None
Model Optimizer version:
[ ERROR ]  Exception occurred during running replacer "REPLACEMENT_ID" (<class 'extensions.front.user_data_repack.UserDataRepack'>): No node with name previous_state_h/read.
 For more information please refer to Model Optimizer FAQ (https://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_Model_Optimizer_FAQ.html), question #51.