ai.onnx#
This page lists all operators in the ai.onnx domain.
Operator |
Since version |
Deprecated |
Short description |
|---|---|---|---|
13 |
No |
Absolute takes one input data (Tensor ) and produces one output data |
|
22 |
No |
Computes the Acos value of the input tensor element-wise. |
|
22 |
No |
Computes the Acosh value of the input tensor element-wise. |
|
14 |
No |
Performs element-wise binary addition (with Numpy-style broadcasting support). |
|
7 |
No |
Returns the tensor resulted from performing the And logical operation |
|
13 |
No |
Computes the indices of the max elements of the input tensor’s element along … |
|
13 |
No |
Computes the indices of the min elements of the input tensor’s element along … |
|
22 |
No |
Computes the Asin value of the input tensor element-wise. |
|
22 |
No |
Computes the Asinh value of the input tensor element-wise. |
|
22 |
No |
AveragePool consumes an input tensor X and applies average pooling across |
|
17 |
No |
Generates a Blackman window as described in the paper https://ieeexplore.ieee… |
|
25 |
No |
The operator casts the elements of a given input tensor to a data type |
|
13 |
No |
Concatenate a list of tensors into a single tensor. All input tensors must ha… |
|
11 |
No |
Concatenate a sequence of tensors into a single tensor. |
|
25 |
No |
This operator produces a constant tensor. Exactly one of the provided attribu… |
|
22 |
No |
Computes the Cos value of the input tensor element-wise. |
|
22 |
No |
Computes the Cosh value of the input tensor element-wise. |
|
14 |
No |
Performs element-wise binary division (with Numpy-style broadcasting support). |
|
19 |
No |
Returns the tensor resulted from performing the Equal logical operation |
|
22 |
No |
Computes an one-layer GRU. This operator is usually supported via some custom |
|
13 |
No |
General Matrix multiplication: |
|
13 |
No |
Returns the tensor resulted from performing the Greater logical operation |
|
13 |
No |
If conditional |
|
20 |
No |
Loads and decodes and image from a file. If it can’t decode for any reason (e… |
|
22 |
No |
Computes an one-layer LSTM. This operator is usually supported via some |
|
13 |
No |
Returns the tensor resulted from performing the Less logical operation |
|
13 |
No |
Matrix product that behaves like [numpy.matmul](https://numpy.org/doc/stable/… |
|
13 |
No |
Performs an element-wise binary modulo operation. |
|
14 |
No |
Performs element-wise binary multiplication (with Numpy-style broadcasting su… |
|
1 |
No |
Returns the negation of the input tensor element-wise. |
|
15 |
No |
Constructs an optional-type value containing either an empty optional of a ce… |
|
18 |
No |
If the input is a tensor or sequence type, it returns the input. |
|
18 |
No |
Returns true if (1) the input is an optional-type and contains an element, |
|
7 |
No |
Returns the tensor resulted from performing the Or logical operation |
|
7 |
No |
Performs element-wise exponentiation. |
|
25 |
No |
The linear quantization operator consumes a high-precision tensor, a scale, a… |
|
22 |
No |
Computes an one-layer simple RNN. This operator is usually supported |
|
18 |
No |
Computes the L1 norm of the input tensor’s elements along the provided axes. |
|
18 |
No |
Computes the L2 norm of the input tensor’s elements along the provided axes. |
|
18 |
No |
Computes the log sum of the input tensor’s elements along the provided axes. |
|
18 |
No |
Computes the log sum exponent of the input tensor’s elements along the provid… |
|
20 |
No |
Computes the max of the input tensor’s elements along the provided axes. |
|
18 |
No |
Computes the mean of the input tensor’s elements along the provided axes. |
|
20 |
No |
Computes the min of the input tensor’s elements along the provided axes. |
|
18 |
No |
Computes the product of the input tensor’s elements along the provided axes. |
|
13 |
No |
Computes the sum of the input tensor’s elements along the provided axes. |
|
18 |
No |
Computes the sum square of the input tensor’s elements along the provided axes. |
|
20 |
No |
RegexFullMatch performs a full regex match on each element of the input tenso… |
|
22 |
No |
Region of Interest (RoI) align operation described in the |
|
11 |
No |
Outputs a tensor copy from the tensor at ‘position’ in ‘input_sequence’. |
|
11 |
No |
Construct a tensor sequence containing ‘inputs’ tensors. |
|
11 |
No |
Construct an empty tensor sequence, with given data type. |
|
11 |
No |
Outputs a tensor sequence that removes the tensor at ‘position’ from ‘input_s… |
|
11 |
No |
Outputs a tensor sequence that inserts ‘tensor’ into ‘input_sequence’ at ‘pos… |
|
11 |
No |
Produces a scalar(tensor of empty shape) containing the number of tensors in … |
|
17 |
No |
Applies a sub-graph to each sample in the input sequence(s). |
|
22 |
No |
Computes the Sin value of the input tensor element-wise. |
|
22 |
No |
Computes the Sinh value of the input tensor element-wise. |
|
11 |
No |
Split a tensor into a sequence of tensors, along the specified ‘axis’. |
|
20 |
No |
StringConcat concatenates string tensors elementwise (with NumPy-style broadc… |
|
10 |
No |
StringNormalization performs string operations for basic cleaning. |
|
20 |
No |
StringSplit splits a string tensor’s elements into substrings based on a deli… |
|
14 |
No |
Performs element-wise binary subtraction (with Numpy-style broadcasting suppo… |
|
7 |
No |
Returns the tensor resulted from performing the Xor logical operation |