Function list and converter
nnabla_cli is the command line interface of nnabla. With this command line interface, user may know current NNabla support status, and know whether or how to convert a nnabla model(e.g. *.nnp)
to other format of model(e.g. *.onnx).
function_info provides a set of functions to output implemented function information.
With this information, you may build tailored nnabla-c-runtime library for your model, or skip some unsupported
functions for the target model.
Some simple use cases
Please let us introduce some simple use cases:
At first, you want to know how many functions (which functions) nnabla currently supports:
$ nnabla_cli function_info
You get the following list:
2019-06-14 16:16:13,106 [nnabla][INFO]: Initializing CPU extension... NNabla command line interface (Version:1.0.18.dev1, Build:190531084842) LSTM Sub2 Mul2 GreaterEqual Sigmoid NotEqual Unpooling Log CategoricalCrossEntropy ...
That is the list of current nnabla all supported functions. Only function names are shown, no more detail, only for seeking certain function by name. For the detail of each function, you have to check with online document.
As you known, nnabla’s model *.nnp can be converted to a compact version, it has the postfix
.nnb, can be inferred by nnabla-c-runtime library. We simply named this format as
NNB. To know how many functions are supported in this format, you may use this command:
$ nnabla_cli function_info -f NNB
Similar as above, a function list is shown.
Do we simple list the functions used in a .nnp model? Yes, of course.
$ nnabla_cli function_info my_model.nnp
Similar as above, a function list used in this model is listed.
Then, we may know whether our model can be converted to nnabla-c-runtime model format, or formally speaking, we can know the intersection of 2 function sets, one is the function set in .nnp and the other is nnabla-c-runtime has supported.
$ nnabla_cli function_info my_model.nnp -f NNB
The output looks like:
2019-06-14 17:01:29,393 [nnabla][INFO]: Initializing CPU extension... NNabla command line interface (Version:1.0.18.dev1, Build:190531084842) Importing mnist_nnp/lenet_010000.nnp Expanding runtime. nnabla-c-runtime currently support the following functions in model: Convolution MulScalar Affine MaxPooling ReLU ...
Unsupported functions are also listed up if there are any in this model.
Tailored nnabla-c-runtime library
When implementing nnabla-c-runtime library, we hope to implement all functions we can. But from customer’s aspect, that is sometimes no need. If user only wants to use nnabla-c-runtime for enumerable models, the nnabla-c-runtime should be tailed exactly as what these models required. How to do then?
It can be implemented with the following steps:
generate function list
config your nnabla-c-runtime library
build nnabla-c-runtime library
1. Generate function list
$ nnabla_cli function_info my_model.nnp -f NNB -o functions.txt
This is similar as above, except that with
-o parameter, which pointed out which file should be written to. (of course, the format is different from the version output to stdout, it is more compact)
2. config your nnabla-c-runtime library
User may manually modify
functions.txt. Then, this file is used as input, used to generate nnabla-c-runtime library’s config file:
$ nnabla_cli function_info -c functions.txt -o nnabla-c-runtime/build-tools/code-generator/functions.yaml
As we inferred, if there is no
-c parameter, a full function set will be used to generate this config file, of course, the library will finally contain all implemented functions. This is the default behavior.
3. build nnabla-c-runtime library
The build process is relatively directly, as the following:
#> nnabla-c-runtime>mkdir build #> nnabla-c-runtime>cd build #> nnabla-c-runtime>cmake .. #> nnabla-c-runtime>make
The nnabla-c-runtime library
libnnablart_functions.a will contain the functions what you want.
Skip functions unsupported
When you want to convert
*.nnb, there are some functions are not supported in target function list. For example, you want to convert a network to nnabla-c-runtime. The network looks like:
Affine Softmax Tanh Convolution MaxPooling ReLU
You do not want to use nnabla-c-runtime library’s
Convolution, you want to split the network in 2 pieces at the point of
Convolution. 2 Steps are needed to do so:
comment out the function in functions.txt
convert the network with
2. convert the network with
$ nnabla_cli convert -c functions.txt a.nnp b.nnb
Thus, the network is split into pieces, the output shows as the following:
... LeNet_036_0_5.nnb: input: - name: Input shape: (-1, 1, 28, 28) output: - name: Tanh_2 shape: (-1, 30, 4, 4) LeNet_036_7_7.nnb: input: - name: Affine shape: (-1, 150) output: - name: ReLU_2 shape: (-1, 150) LeNet_036_9_9.nnb: input: - name: Affine_2 shape: (-1, 10) output: - name: Softmax shape: (-1, 10)
The network is split at the
Affine function. Since there are 2
Affine in network, 3 sub-networks is generated.
Converting to ONNX
The following commands just do similar as above, exactly to *.onnx.
List all functions supported:
$ nnabla_cli function_info -f ONNX
List the intersection of function sets, in a model and supported by ONNX:
$ nnabla_cli function_info LeNet_036.nnp -f ONNX
Split network to skip some function:
$ nnabla_cli convert -c functions.txt a.nnp a.onnx