# Supported Frameworks
We support almost all the commonly used Machine Learning frameworks & libraries such as ONNX, PyTorch, Keras, TensorFlow, and TensorFlow Lite.

![Supported deep-learning frameworks](../res/image/supported_frameworks_new.png "Supported deep-learning frameworks")

## Supported Operations
### Supported Operations

| Layer type | Comments |
| :--- | :--- |
| Convolution |  |
| DepthwiseConvolution |  |
| GroupConvolution |  |
| Pooling |  |
| TransposeConvolution |  |
| AveragePool |  |
| MaxPool |  |
| Pad |  |
| Relu |  |
| Erf |  |
| LeakyRelu |  |
| PRelu |  |
| Clip |  |
| Softplus |  |
| Sigmoid |  |
| Gelu |  |
| Swish |  |
| HardSwish |  |
| HardSigmoid |  |
| Tanh |  |
| Elu |  |
| QuickGelu |  |
| Celu |  |
| Pow |  |
| Sqrt |  |
| Add |  |
| Div |  |
| Mul |  |
| Sub |  |
| ConstantOfShape |  |
| Shape |  |
| SpaceToDepth |  |
| DepthToSpace |  |
| Exp |  |
| Elu |  |
| Log |  |
| Neg |  |
| Mish |  |
| Pow |  |
| Sqrt |  |
| InstanceNormalization |  |
| L2Normalization |  |
| LayerNormalization |  |
| GroupNormalization |  |
| RmsNormalization |  |
| ReduceMax |  |
| Concatenate |  |
| Tile | Depends on graph structure and node information |
| Upsampling |  |
| Resize |  |
| Cast |  |
| Einsum | Depends on graph structure and node information |
| ReduceMean |  |
| Slice |  |
| Erf |  |
| Flatten |  |
| Expand |  |
| Flip | Depends on graph structure and node information |
| Gather | Depends on graph structure and node information |
| GatherND | Depends on graph structure and node information |
| Gemm |  |
| Not |  |
| PRelu |  |
| Split |  |
| Squeeze |  |
| TopK |  |
| Transpose |  |
| Unsqueeze |  |
| Reshape |  |
| ReduceProd |  |
| Reciprocal |  |
| ReduceL2 |  |
| MatMul |  |
| Softmax |  |
| Softplus |  |
| Abs | To be supported |
| Sin | To be supported |
| Cos | To be supported |
| Crop | To be supported |
| ReduceMin | To be supported |