1 unstable release
0.1.0 | Oct 15, 2022 |
---|
#876 in Machine learning
105KB
2.5K
SLoC
Your one stop CLI for ONNX model analysis.
Featuring graph visualization, FLOP counts, memory metrics and more!
⚡️ Quick start
First, download and install DOT.
Installation can be done via cargo
:
cargo install steelix
MacOS users can also install via HomeBrew:
brew tap FL33TW00D/steelix
brew install steelix
⚙️ Commands & Options
Steelix has 2 core functions - model summarization & model visualization.
summary
CLI command to summarize the core aspects of your model.
steelix summary --model-path ./my-model.onnx
Option | Description | Type | Default | Required? |
---|---|---|---|---|
--model-path |
Path at which your model is located. | bool |
false |
No |
plot
CLI command to plot your model as an SVG file - complete with inferred shapes.
steelix plot --model-path ./my-model.onnx --open
Option | Description | Type | Default | Required? |
---|---|---|---|---|
--model-path |
Path at which your model is located. | string |
None | Yes |
--output-path |
Path at which your SVG will be saved. | string |
./model.svg |
No |
--open |
Open SVG in browser once generated. | boolean |
false |
No |
--disable-shapes |
Disable shape inference. | boolean |
false |
No |
Supported Operators (ref ONNX IR)
Operator | Implemented |
---|---|
Abs | ✅ |
Acos | |
Acosh | |
Add | ✅ |
And | |
ArgMax | |
ArgMin | |
Asin | |
Asinh | |
Atan | |
Atanh | |
AveragePool | |
BatchNormalization | ✅ |
BitShift | |
Cast | |
Ceil | |
Clip | |
Compress | |
Concat | ✅ |
ConcatFromSequence | |
Constant | |
ConstantOfShape | |
Conv | ✅ |
ConvInteger | |
ConvTranspose | |
Cos | |
Cosh | |
CumSum | |
DepthToSpace | |
DequantizeLinear | |
Det | |
Div | |
Dropout | |
Einsum | |
Elu | |
Equal | |
Erf | ✅ |
Exp | |
Expand | |
EyeLike | |
Flatten | |
Floor | |
GRU | |
Gather | ✅ |
GatherElements | |
GatherND | |
Gemm | ✅ |
GlobalAveragePool | |
GlobalLpPool | |
GlobalMaxPool | |
Greater | |
GridSample | |
HardSigmoid | |
Hardmax | |
Identity | |
If | |
InstanceNormalization | |
IsInf | |
IsNaN | |
LRN | |
LSTM | |
LeakyRelu | ✅ |
Less | |
Log | |
Loop | |
LpNormalization | |
LpPool | |
MatMul | ✅ |
MatMulInteger | |
Max | |
MaxPool | ✅ |
MaxRoiPool | |
MaxUnpool | |
Mean | |
Min | |
Mod | |
Mul | ✅ |
Multinomial | |
Neg | |
NonMaxSuppression | |
NonZero | |
Not | ✅ |
OneHot | |
Optional | |
OptionalGetElement | |
OptionalHasElement | |
Or | |
PRelu | |
Pad | ✅ (mode=constant, pads>=0) |
Pow | |
QLinearConv | |
QLinearMatMul | |
QuantizeLinear | |
RNN | |
RandomNormal | |
RandomNormalLike | |
RandomUniform | |
RandomUniformLike | |
Reciprocal | |
ReduceL1 | |
ReduceL2 | |
ReduceLogSum | |
ReduceLogSumExp | |
ReduceMax | |
ReduceMean | |
ReduceMin | |
ReduceProd | |
ReduceSum | |
ReduceSumSquare | |
Relu | ✅ |
Reshape | ✅ |
Resize | |
ReverseSequence | |
RoiAlign | |
Round | |
Scan | |
Scatter (deprecated) | |
ScatterElements | |
ScatterND | |
Selu | |
SequenceAt | |
SequenceConstruct | |
SequenceEmpty | |
SequenceErase | |
SequenceInsert | |
SequenceLength | |
Shape | |
Shrink | |
Sigmoid | ✅ |
Sign | |
Sin | |
Sinh | |
Size | |
Slice | |
Softplus | |
Softsign | |
SpaceToDepth | |
Split | |
SplitToSequence | |
Sqrt | |
Squeeze | ✅ |
StringNormalizer | |
Sub | |
Sum | |
Tan | |
Tanh | |
TfIdfVectorizer | |
ThresholdedRelu | |
Tile | |
TopK | |
Transpose | |
Trilu | |
Unique | |
Unsqueeze | ✅ |
Upsample (deprecated) | |
Where | |
Xor | |
Function | |
Bernoulli | |
CastLike | |
Celu | |
DynamicQuantizeLinear | |
GreaterOrEqual | |
HardSwish | |
LessOrEqual | |
LogSoftmax | |
MeanVarianceNormalization | |
NegativeLogLikelihoodLoss | |
Range | |
Softmax | ✅ |
SoftmaxCrossEntropyLoss |
Credit
Most of the good ideas/code in this project are heavily inspired by tract, wonnx or netron.
Dependencies
~12–23MB
~357K SLoC