Index
Operators API
The 'operators' module provides classes to represent operators in the network graph. These classes all
inherit from the AotOperator class, which provides a common interface for all operators. Each operator class
is responsible for generating the C code for its specific operation. Built-in classes are registered into
RegistryContext.aot_operator_classes via register_default_aot_operators.
Available Operators
- Add: Element-wise addition
- ArgMax: Argmax reduction
- ArgMin: Argmin reduction
- AssignVariable: Assigns a value to a variable
- AveragePool: Average pooling operation
- BatchMatMul: Batch matrix multiplication
- BatchToSpaceND: Batch to space transformation
- Comparison: Comparison operations (e.g., equal, not equal, less than)
- Concatenation: Concatenates tensors along a specified axis
- Conv: 2D convolution operation
- DepthwiseConv: Depthwise separable convolution operation
- DepthToSpace: Rearranges data from depth into blocks of spatial data
- Dequantize: Dequantizes a tensor
- EthosU: Ethos-U NPU operator
- ExpandDims: Expands the shape of a tensor
- Fill: Fills a tensor with a specified value
- Gather: Gathers elements along an axis
- GatherNd: Gathers slices using multi-dimensional indices
- FullyConnected: Fully connected layer
- HardSwish: Hard swish activation function
- LeakyRelu: Leaky ReLU activation function
- Logistic: Logistic activation function
- MaxPool: Max pooling operation
- Maximum: Element-wise maximum
- Mean: Computes the mean of a tensor along specified axes
- Minimum: Element-wise minimum
- Mul: Element-wise multiplication
- Pack: Packs a list of tensors into a single tensor
- Pad: Pads a tensor
- Quantize: Quantizes a tensor
- ReadVariable: Reads a variable
- ReduceMax: Reduces a tensor by taking the maximum along specified axes
- ReduceMin: Reduces a tensor by taking the minimum along specified axes
- Relu: Rectified Linear Unit activation
- Reshape: Reshapes a tensor
- Shape: Returns the shape of a tensor
- Softmax: Softmax activation
- SpaceToBatchND: Space to batch transformation
- SpaceToDepth: Rearranges data from spatial blocks into depth
- Split: Splits a tensor into multiple tensors along a specified axis
- Squeeze: Removes dimensions of size 1 from the shape of a tensor
- StridedSlice: Slices a tensor with strides
- Sub: Element-wise subtraction
- Svdf: SVDF operation
- Tanh: Hyperbolic tangent activation function
- TransposeConv: Transpose convolution operation
- Transpose: Transposes a tensor
- Unpack: Unpacks a tensor into multiple tensors along a specified axis
- ZerosLike: Generates a tensor of zeros
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