ONNX to NNOIR Converter
Project description
nnoir-onnx
nnoir-onnx is a converter from ONNX model to NNOIR model.
Install
pip install nnoir-onnx
Example
wget https://www.cntk.ai/OnnxModels/mnist/opset_7/mnist.tar.gz
tar xvzf mnist.tar.gz
onnx2nnoir -o model.nnoir mnist/model.onnx
Supported ONNX Operators
- Add
- AveragePool
- BatchNormalization
scale
,B
,mean
, andvar
must be"constant"
- Clip
- must be opset version 6 or 11
- if opset version is 11
max
must be"constant"
min
must be 0
- Concat
- Conv
- Cos
- Dropout
- equivalent identity function
- Elu
- Flatten
- Gemm
- GlobalAveragePool
- LeakyRelu
- LRN
- LSTM
- only
seq_length == 1
direction
must be forward- Supported
activations
are belowSigmoid
Tanh
Relu
- Not support
clip
andinput_forget
- only
- MatMul
- MaxPool
ceil_mode = 1
is not supporteddilations
is not supported
- Mul
- Pad
mode
must be"constant"
- PRelu
slope
must be"constant"
and a single value tensor
- ReduceMean
- ReduceSum
- Relu
- Reshape
- Resize
- must be from opset version >= 11
mode
must be"linear"
coordinate_transformation_mode
must be either"pytorch_half_pixel"
or"align_corners"
- Sigmoid
- Sin
- Softmax
- Squeeze
- Sub
- 1st input must not be
"constant"
- 1st input must not be
- Sum
- 2 inputs
- Tan
- Tanh
- Transpose
- Unsqueeze
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
nnoir_onnx-1.0.8-py3-none-any.whl
(29.3 kB
view hashes)
Close
Hashes for nnoir_onnx-1.0.8-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bfe1de27e2bd41eeda1105b339bb3a9ae637b5106a6507e48882292238ca4b4a |
|
MD5 | 0e2d2ee65895dd59faa87a0b41f43f57 |
|
BLAKE2b-256 | 1fe4cb25de3db971ad14087ed64ee6abed9fe8db371ba68d223a56cb4d44f50f |