Neural Network
This module contains primitive Neural Net (NN) operations.
Data types
Orion supports currently these NN
types.
32-bit integer (signed)
Tensor<i32>
8-bit integer (signed)
Tensor<i8>
32-bit integer (unsigned)
Tensor<u32>
Fixed point (signed)
Tensor<FP8x23 | FP16x16 | FP32x32 | FP64x64>
NNTrait
NNTrait
contains the primitive functions to build a Neural Network.
Applies the rectified linear unit function element-wise.
Applies the leaky rectified linear unit (Leaky ReLU) activation function element-wise.
Applies the Sigmoid function to an n-dimensional input tensor.
Computes softmax activations.
Computes softmax zero.
Applies the natural log to Softmax function to an n-dimensional input Tensor.
Applies the Softsign function element-wise.
Applies the Softplus function element-wise.
Performs a linear transformation of the input tensor using the provided weights and bias.
Applies the Hard Sigmoid function to an n-dimensional input tensor.
Performs the thresholded relu activation function element-wise.
Performs General Matrix multiplication.
Computes the grid sample of the input tensor and input grid.
Rearranges column blocks back into a multidimensional image
Performs the convolution transpose of the input data tensor and weight tensor.
Performs the convolution of the input data tensor and weight tensor.
GlobalAveragePool consumes an input tensor X and applies average pooling across the values in the same channel.
Performs integer convolution
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