Converting a Kaldi Model¶
Warning
Note that OpenVINO support for Kaldi is currently being deprecated and will be removed entirely in the future.
Note
Model conversion API supports the nnet1 and nnet2 formats of Kaldi models. The support of the nnet3 format is limited.
To convert a Kaldi model, run model conversion with the path to the input model .nnet
or .mdl
file:
mo --input_model <INPUT_MODEL>.nnet
Using Kaldi-Specific Conversion Parameters¶
The following list provides the Kaldi-specific parameters.
Kaldi-specific parameters:
--counts COUNTS A file name with full path to the counts file or empty string to utilize count values from the model file
--remove_output_softmax
Removes the Softmax that is the output layer
--remove_memory Remove the Memory layer and add new inputs and outputs instead
Examples of CLI Commands¶
To launch model conversion for the
wsj_dnn5b_smbr
model with the specified.nnet
file:mo --input_model wsj_dnn5b_smbr.nnet
To launch model conversion for the
wsj_dnn5b_smbr
model with the existing file that contains counts for the last layer with biases:mo --input_model wsj_dnn5b_smbr.nnet --counts wsj_dnn5b_smbr.counts
The model conversion normalizes сounts in the following way:
\[S = \frac{1}{\sum_{j = 0}^{|C|}C_{j}}\]\[C_{i}=log(S*C_{i})\]where \(C\) - the counts array, \(C_{i} - i^{th}\) element of the counts array, \(|C|\) - number of elements in the counts array;
The normalized counts are subtracted from biases of the last or next to last layer (if last layer is SoftMax).
Note
Model conversion API will show a warning if a model contains values of counts and the
counts
option is not used.
If you want to remove the last SoftMax layer in the topology, launch the model conversion with the
remove_output_softmax
flag:mo --input_model wsj_dnn5b_smbr.nnet --counts wsj_dnn5b_smbr.counts --remove_output_softmax
Model conversion API finds the last layer of the topology and removes this layer only if it is a SoftMax layer.
Note
Model conversion can remove SoftMax layer only if the topology has one output.
You can use the OpenVINO Speech Recognition sample application for the sample inference of Kaldi models. This sample supports models with only one output. If your model has several outputs, specify the desired one with the
output
option.
Supported Kaldi Layers¶
For the list of supported standard layers, refer to the Supported Operations page.
Additional Resources¶
See the Model Conversion Tutorials page for a set of tutorials providing step-by-step instructions for converting specific Kaldi models. Here are some examples: