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Neural Network

This module contains primitive Neural Net (NN) operations.
use orion::operators::nn;
Data types
Orion supports currently these NN types.
Data type
dtype
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.
function
description
​nn.relu​
Applies the rectified linear unit function element-wise.
​nn.leaky_relu​
Applies the leaky rectified linear unit (Leaky ReLU) activation function element-wise.
​nn.sigmoid​
Applies the Sigmoid function to an n-dimensional input tensor.
​nn.softmax​
Computes softmax activations.
​nn.logsoftmax​
Applies the natural log to Softmax function to an n-dimensional input Tensor.
​nn.softsign​
Applies the Softsign function element-wise.
​nn.softplus​
Applies the Softplus function element-wise.
​nn.linear​
Performs a linear transformation of the input tensor using the provided weights and bias.
​nn.hard_sigmoid​
Applies the Hard Sigmoid function to an n-dimensional input tensor.
​nn.thresholded_relu​
Performs the thresholded relu activation function element-wise.
​nn.gemm​
Performs General Matrix multiplication.

Data type	dtype
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>`

function	description
`nn.relu`	Applies the rectified linear unit function element-wise.
`nn.leaky_relu`	Applies the leaky rectified linear unit (Leaky ReLU) activation function element-wise.
`nn.sigmoid`	Applies the Sigmoid function to an n-dimensional input tensor.
`nn.softmax`	Computes softmax activations.
`nn.logsoftmax`	Applies the natural log to Softmax function to an n-dimensional input Tensor.
`nn.softsign`	Applies the Softsign function element-wise.
`nn.softplus`	Applies the Softplus function element-wise.
`nn.linear`	Performs a linear transformation of the input tensor using the provided weights and bias.
`nn.hard_sigmoid`	Applies the Hard Sigmoid function to an n-dimensional input tensor.
`nn.thresholded_relu`	Performs the thresholded relu activation function element-wise.
`nn.gemm`	Performs General Matrix multiplication.

tensor.reduce_l1

nn.relu

Last modified 1mo ago