159 lines
4.7 KiB
Markdown
159 lines
4.7 KiB
Markdown
## ncnn Ops
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<!-- TOC -->
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- [ncnn Ops](#ncnn-ops)
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- [Expand](#expand)
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- [Description](#description)
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- [Parameters](#parameters)
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- [Inputs](#inputs)
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- [Outputs](#outputs)
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- [Type Constraints](#type-constraints)
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- [Gather](#gather)
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- [Description](#description)
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- [Parameters](#parameters)
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- [Inputs](#inputs)
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- [Outputs](#outputs)
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- [Type Constraints](#type-constraints)
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- [Shape](#shape)
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- [Description](#description)
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- [Parameters](#parameters)
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- [Inputs](#inputs)
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- [Outputs](#outputs)
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- [Type Constraints](#type-constraints)
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- [TopK](#topk)
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- [Description](#description)
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- [Parameters](#parameters)
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- [Inputs](#inputs)
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- [Outputs](#outputs)
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- [Type Constraints](#type-constraints)
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<!-- TOC -->
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### Expand
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#### Description
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Broadcast the input blob following the given shape and the broadcast rule of ncnn.
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#### Parameters
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Expand has no parameters.
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#### Inputs
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<dl>
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<dt><tt>inputs[0]</tt>: ncnn.Mat</dt>
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<dd>bottom_blobs[0]; An ncnn.Mat of input data.</dd>
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<dt><tt>inputs[1]</tt>: ncnn.Mat</dt>
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<dd>bottom_blobs[1]; An 1-dim ncnn.Mat. A valid shape of ncnn.Mat.</dd>
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</dl>
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#### Outputs
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<dl>
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<dt><tt>outputs[0]</tt>: T</dt>
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<dd>top_blob; The blob of ncnn.Mat which expanded by given shape and broadcast rule of ncnn.</dd>
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</dl>
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#### Type Constraints
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- ncnn.Mat: Mat(float32)
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### Gather
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#### Description
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Given the data and indice blob, gather entries of the axis dimension of data indexed by indices.
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#### Parameters
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| Type | Parameter | Description |
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| ----- | --------- | -------------------------------------- |
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| `int` | `axis` | Which axis to gather on. Default is 0. |
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#### Inputs
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<dl>
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<dt><tt>inputs[0]</tt>: ncnn.Mat</dt>
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<dd>bottom_blobs[0]; An ncnn.Mat of input data.</dd>
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<dt><tt>inputs[1]</tt>: ncnn.Mat</dt>
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<dd>bottom_blobs[1]; An 1-dim ncnn.Mat of indices on given axis.</dd>
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</dl>
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#### Outputs
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<dl>
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<dt><tt>outputs[0]</tt>: T</dt>
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<dd>top_blob; The blob of ncnn.Mat which gathered by given data and indice blob.</dd>
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</dl>
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#### Type Constraints
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- ncnn.Mat: Mat(float32)
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### Shape
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#### Description
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Get the shape of the ncnn blobs.
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#### Parameters
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Shape has no parameters.
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#### Inputs
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<dl>
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<dt><tt>inputs[0]</tt>: ncnn.Mat</dt>
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<dd>bottom_blob; An ncnn.Mat of input data.</dd>
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</dl>
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#### Outputs
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<dl>
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<dt><tt>outputs[0]</tt>: T</dt>
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<dd>top_blob; 1-D ncnn.Mat of shape (bottom_blob.dims,), `bottom_blob.dims` is the input blob dimensions.</dd>
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</dl>
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#### Type Constraints
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- ncnn.Mat: Mat(float32)
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### TopK
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#### Description
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Get the indices and value(optional) of largest or smallest k data among the axis. This op will map to onnx op `TopK`, `ArgMax`, and `ArgMin`.
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#### Parameters
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| Type | Parameter | Description |
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| ----- | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `int` | `axis` | The axis of data which topk calculate on. Default is -1, indicates the last dimension. |
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| `int` | `largest` | The binary value which indicates the TopK operator selects the largest or smallest K values. Default is 1, the TopK selects the largest K values. |
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| `int` | `sorted` | The binary value of whether returning sorted topk value or not. If not, the topk returns topk values in any order. Default is 1, this operator returns sorted topk values. |
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| `int` | `keep_dims` | The binary value of whether keep the reduced dimension or not. Default is 1, each output blob has the same dimension as input blob. |
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#### Inputs
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<dl>
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<dt><tt>inputs[0]</tt>: ncnn.Mat</dt>
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<dd>bottom_blob[0]; An ncnn.Mat of input data.</dd>
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<dt><tt>inputs[1] (optional)</tt>: ncnn.Mat</dt>
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<dd>bottom_blob[1]; An optional ncnn.Mat. A blob of K in TopK. If this blob not exist, K is 1.</dd>
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</dl>
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#### Outputs
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<dl>
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<dt><tt>outputs[0]</tt>: T</dt>
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<dd>top_blob[0]; If outputs has only 1 blob, outputs[0] is the indice blob of topk, if outputs has 2 blobs, outputs[0] is the value blob of topk. This blob is ncnn.Mat format with the shape of bottom_blob[0] or reduced shape of bottom_blob[0].</dd>
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<dt><tt>outputs[1]</tt>: T</dt>
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<dd>top_blob[1] (optional); If outputs has 2 blobs, outputs[1] is the value blob of topk. This blob is ncnn.Mat format with the shape of bottom_blob[0] or reduced shape of bottom_blob[0].</dd>
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</dl>
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#### Type Constraints
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- ncnn.Mat: Mat(float32)
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