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docs/deployment/mmcv_ops_definition.md
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# Definition of custom operators in MMCV
# MMCV Operators
To make custom operators in MMCV more standard, precise definitions of each operator are listed in this document.
<!-- TOC -->
- [Definition of custom operators in MMCV](#definition-of-custom-operators-in-mmcv)
- [MMCV Operators](#mmcv-operators)
- [MMCVBorderAlign](#mmcvborderalign)
- [Description](#description)
- [Parameters](#parameters)
......@@ -80,25 +82,25 @@
- [Inputs](#inputs-12)
- [Outputs](#outputs-12)
- [Type Constraints](#type-constraints-12)
- [torch](#torch)
- [grid_sampler](#grid_sampler)
- [grid_sampler*](#grid_sampler)
- [Description](#description-13)
- [Parameters](#parameters-13)
- [Inputs](#inputs-13)
- [Outputs](#outputs-13)
- [Type Constraints](#type-constraints-13)
- [cummax](#cummax)
- [cummax*](#cummax)
- [Description](#description-14)
- [Parameters](#parameters-14)
- [Inputs](#inputs-14)
- [Outputs](#outputs-14)
- [Type Constraints](#type-constraints-14)
- [cummin](#cummin)
- [cummin*](#cummin)
- [Description](#description-15)
- [Parameters](#parameters-15)
- [Inputs](#inputs-15)
- [Outputs](#outputs-15)
- [Type Constraints](#type-constraints-15)
- [Reminders](#reminders)
<!-- TOC -->
## MMCVBorderAlign
......@@ -118,9 +120,9 @@ Read [BorderDet: Border Feature for Dense Object Detection](ttps://arxiv.org/abs
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
| `int` | `pool_size` | number of positions sampled over the boxes' borders(e.g. top, bottom, left, right). |
| Type | Parameter | Description |
|-------|-------------|-------------------------------------------------------------------------------------|
| `int` | `pool_size` | number of positions sampled over the boxes' borders(e.g. top, bottom, left, right). |
### Inputs
......@@ -152,11 +154,11 @@ Read [CARAFE: Content-Aware ReAssembly of FEatures](https://arxiv.org/abs/1905.0
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
| `int` | `kernel_size` | reassemble kernel size, should be odd integer|
| `int` | `group_size` | reassemble group size |
| `float` | `scale_factor` | upsample ratio(>=1) |
| Type | Parameter | Description |
|---------|----------------|-----------------------------------------------|
| `int` | `kernel_size` | reassemble kernel size, should be odd integer |
| `int` | `group_size` | reassemble group size |
| `float` | `scale_factor` | upsample ratio(>=1) |
### Inputs
......@@ -187,8 +189,7 @@ Read [CCNet: Criss-Cross Attention for SemanticSegmentation](https://arxiv.org/p
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
None
### Inputs
......@@ -219,8 +220,7 @@ Read [CCNet: Criss-Cross Attention for SemanticSegmentation](https://arxiv.org/p
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
None
### Inputs
......@@ -251,9 +251,9 @@ Perform CornerPool on `input` features. Read [CornerNet -- Detecting Objects as
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | ---------------------------------------------------------------- |
| `int` | `mode` | corner pool mode, (0: `top`, 1: `bottom`, 2: `left`, 3: `right`) |
| Type | Parameter | Description |
|-------|-----------|------------------------------------------------------------------|
| `int` | `mode` | corner pool mode, (0: `top`, 1: `bottom`, 2: `left`, 3: `right`) |
### Inputs
......@@ -283,15 +283,15 @@ Read [Deformable Convolutional Networks](https://arxiv.org/pdf/1703.06211.pdf) f
### Parameters
| Type | Parameter | Description |
| -------------- | ------------------ | ------------------------------------------------------------------------------------- |
| `list of ints` | `stride` | The stride of the convolving kernel, (sH, sW). Defaults to `(1, 1)`. |
| `list of ints` | `padding` | Paddings on both sides of the input, (padH, padW). Defaults to `(0, 0)`. |
| `list of ints` | `dilation` | The spacing between kernel elements (dH, dW). Defaults to `(1, 1)`. |
| `int` | `groups` | Split input into groups. `input_channel` should be divisible by the number of groups. Defaults to `1`.|
| `int` | `deformable_groups` | Groups of deformable offset. Defaults to `1`. |
| `int` | `bias` | Whether to add a learnable bias to the output. `0` stands for `False` and `1` stands for `True`. Defaults to `0`. |
| `int` | `im2col_step` | Groups of deformable offset. Defaults to `32`. |
| Type | Parameter | Description |
|----------------|---------------------|-------------------------------------------------------------------------------------------------------------------|
| `list of ints` | `stride` | The stride of the convolving kernel, (sH, sW). Defaults to `(1, 1)`. |
| `list of ints` | `padding` | Paddings on both sides of the input, (padH, padW). Defaults to `(0, 0)`. |
| `list of ints` | `dilation` | The spacing between kernel elements (dH, dW). Defaults to `(1, 1)`. |
| `int` | `groups` | Split input into groups. `input_channel` should be divisible by the number of groups. Defaults to `1`. |
| `int` | `deformable_groups` | Groups of deformable offset. Defaults to `1`. |
| `int` | `bias` | Whether to add a learnable bias to the output. `0` stands for `False` and `1` stands for `True`. Defaults to `0`. |
| `int` | `im2col_step` | Groups of deformable offset. Defaults to `32`. |
### Inputs
......@@ -323,11 +323,11 @@ Perform Modulated Deformable Convolution on input feature, read [Deformable Conv
### Parameters
| Type | Parameter | Description |
| -------------- | ------------------ | ------------------------------------------------------------------------------------- |
| `list of ints` | `stride` | The stride of the convolving kernel. (sH, sW) |
| `list of ints` | `padding` | Paddings on both sides of the input. (padH, padW) |
| `list of ints` | `dilation` | The spacing between kernel elements. (dH, dW) |
| Type | Parameter | Description |
|----------------|---------------------|---------------------------------------------------------------------------------------|
| `list of ints` | `stride` | The stride of the convolving kernel. (sH, sW) |
| `list of ints` | `padding` | Paddings on both sides of the input. (padH, padW) |
| `list of ints` | `dilation` | The spacing between kernel elements. (dH, dW) |
| `int` | `deformable_groups` | Groups of deformable offset. |
| `int` | `groups` | Split input into groups. `input_channel` should be divisible by the number of groups. |
......@@ -365,13 +365,13 @@ Deformable roi pooling layer
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
| Type | Parameter | Description |
|---------|------------------|---------------------------------------------------------------------------------------------------------------|
| `int` | `output_height` | height of output roi |
| `int` | `output_width` | width of output roi |
| `float` | `spatial_scale` | used to scale the input boxes |
| `int` | `sampling_ratio` | number of input samples to take for each output sample. `0` means to take samples densely for current models. |
| `float` | `gamma` | gamma |
| `float` | `gamma` | gamma |
### Inputs
......@@ -404,10 +404,10 @@ Read [Pixel Recurrent Neural Networks](https://arxiv.org/abs/1601.06759) for mor
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
| `list of ints` | `stride` | The stride of the convolving kernel. (sH, sW). **Only support stride=1 in mmcv** |
| `list of ints` | `padding` | Paddings on both sides of the input. (padH, padW). Defaults to `(0, 0)`. |
| Type | Parameter | Description |
|----------------|-----------|----------------------------------------------------------------------------------|
| `list of ints` | `stride` | The stride of the convolving kernel. (sH, sW). **Only support stride=1 in mmcv** |
| `list of ints` | `padding` | Paddings on both sides of the input. (padH, padW). Defaults to `(0, 0)`. |
### Inputs
......@@ -443,10 +443,10 @@ Read [PSANet: Point-wise Spatial Attention Network for Scene Parsing](https://hs
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
| `int` | `psa_type` | `0` means collect and `1` means `distribute` |
| `list of ints` | `mask_size` | The size of mask |
| Type | Parameter | Description |
|----------------|-------------|----------------------------------------------|
| `int` | `psa_type` | `0` means collect and `1` means `distribute` |
| `list of ints` | `mask_size` | The size of mask |
### Inputs
......@@ -477,7 +477,7 @@ Note this definition is slightly different with [onnx: NonMaxSuppression](https:
### Parameters
| Type | Parameter | Description |
| ------- | ---------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ |
|---------|------------------------------|--------------------------------------------------------------------------------------------------------------------------------------|
| `int` | `center_point_box` | 0 - the box data is supplied as [y1, x1, y2, x2], 1-the box data is supplied as [x_center, y_center, width, height]. |
| `int` | `max_output_boxes_per_class` | The maximum number of boxes to be selected per batch per class. Default to 0, number of output boxes equal to number of input boxes. |
| `float` | `iou_threshold` | The threshold for deciding whether boxes overlap too much with respect to IoU. Value range [0, 1]. Default to 0. |
......@@ -515,7 +515,7 @@ Perform RoIAlign on output feature, used in bbox_head of most two-stage detector
### Parameters
| Type | Parameter | Description |
| ------- | ---------------- | ------------------------------------------------------------------------------------------------------------- |
|---------|------------------|---------------------------------------------------------------------------------------------------------------|
| `int` | `output_height` | height of output roi |
| `int` | `output_width` | width of output roi |
| `float` | `spatial_scale` | used to scale the input boxes |
......@@ -543,7 +543,6 @@ Perform RoIAlign on output feature, used in bbox_head of most two-stage detector
- T:tensor(float32)
## MMCVRoIAlignRotated
### Description
......@@ -552,15 +551,15 @@ Perform RoI align pooling for rotated proposals
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
| Type | Parameter | Description |
|---------|------------------|---------------------------------------------------------------------------------------------------------------|
| `int` | `output_height` | height of output roi |
| `int` | `output_width` | width of output roi |
| `float` | `spatial_scale` | used to scale the input boxes |
| `int` | `sampling_ratio` | number of input samples to take for each output sample. `0` means to take samples densely for current models. |
| `str` | `mode` | pooling mode in each bin. `avg` or `max` |
| `int` | `aligned` | If `aligned=0`, use the legacy implementation in MMDetection. Else, align the results more perfectly. |
| `int` | `clockwise` | If `aligned=0`, use the legacy implementation in MMDetection. Else, align the results more perfectly. |
| `int` | `clockwise` | If `aligned=0`, use the legacy implementation in MMDetection. Else, align the results more perfectly. |
### Inputs
......@@ -581,9 +580,7 @@ Perform RoI align pooling for rotated proposals
- T:tensor(float32)
# torch
## grid_sampler
## grid_sampler*
### Description
......@@ -594,7 +591,7 @@ Check [torch.nn.functional.grid_sample](https://pytorch.org/docs/stable/generate
### Parameters
| Type | Parameter | Description |
| ----- | -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|-------|----------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `int` | `interpolation_mode` | Interpolation mode to calculate output values. (0: `bilinear` , 1: `nearest`) |
| `int` | `padding_mode` | Padding mode for outside grid values. (0: `zeros`, 1: `border`, 2: `reflection`) |
| `int` | `align_corners` | If `align_corners=1`, the extrema (`-1` and `1`) are considered as referring to the center points of the input's corner pixels. If `align_corners=0`, they are instead considered as referring to the corner points of the input's corner pixels, making the sampling more resolution agnostic. |
......@@ -619,7 +616,7 @@ Check [torch.nn.functional.grid_sample](https://pytorch.org/docs/stable/generate
- T:tensor(float32, Linear)
## cummax
## cummax*
### Description
......@@ -627,9 +624,9 @@ Returns a tuple (`values`, `indices`) where `values` is the cumulative maximum e
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | ---------------------------------------------------------------- |
| `int` | `dim` | the dimension to do the operation over |
| Type | Parameter | Description |
|-------|-----------|----------------------------------------|
| `int` | `dim` | the dimension to do the operation over |
### Inputs
......@@ -651,7 +648,7 @@ Returns a tuple (`values`, `indices`) where `values` is the cumulative maximum e
- T:tensor(float32)
## cummin
## cummin*
### Description
......@@ -659,9 +656,9 @@ Returns a tuple (`values`, `indices`) where `values` is the cumulative minimum e
### Parameters
| Type | Parameter | Description |
| ------- | --------------- | ---------------------------------------------------------------- |
| `int` | `dim` | the dimension to do the operation over |
| Type | Parameter | Description |
|-------|-----------|----------------------------------------|
| `int` | `dim` | the dimension to do the operation over |
### Inputs
......@@ -682,3 +679,7 @@ Returns a tuple (`values`, `indices`) where `values` is the cumulative minimum e
### Type Constraints
- T:tensor(float32)
## Reminders
- Operators endwith `*` are defined in Torch and are included here for the conversion to ONNX.
docs/deployment/onnx.md
View file @ 72182747
## Introduction of onnx module in MMCV (Experimental)
## Introduction of mmcv.onnx module
### register_extra_symbolics
......@@ -14,6 +14,10 @@ opset_version = 11
register_extra_symbolics(opset_version)
```
#### Reminder
- *Please note that this feature is experimental and may change in the future.*
#### FAQs
- None
docs/deployment/onnxruntime_custom_ops.md
View file @ 72182747
## Onnxruntime Custom Ops
## ONNX Runtime Custom Ops
<!-- TOC -->
- [Onnxruntime Custom Ops](#onnxruntime-custom-ops)
- [ONNX Runtime Custom Ops](#onnx-runtime-custom-ops)
- [SoftNMS](#softnms)
- [Description](#description)
- [Parameters](#parameters)
......@@ -69,7 +69,7 @@ Perform soft NMS on `boxes` with `scores`. Read [Soft-NMS -- Improving Object De
#### Parameters
| Type | Parameter | Description |
| ------- | --------------- | -------------------------------------------------------------- |
|---------|-----------------|----------------------------------------------------------------|
| `float` | `iou_threshold` | IoU threshold for NMS |
| `float` | `sigma` | hyperparameter for gaussian method |
| `float` | `min_score` | score filter threshold |
......@@ -107,7 +107,7 @@ Perform RoIAlign on output feature, used in bbox_head of most two-stage detector
#### Parameters
| Type | Parameter | Description |
| ------- | ---------------- | ------------------------------------------------------------------------------------------------------------- |
|---------|------------------|---------------------------------------------------------------------------------------------------------------|
| `int` | `output_height` | height of output roi |
| `int` | `output_width` | width of output roi |
| `float` | `spatial_scale` | used to scale the input boxes |
......@@ -144,7 +144,7 @@ Filter out boxes has high IoU overlap with previously selected boxes.
#### Parameters
| Type | Parameter | Description |
| ------- | --------------- | ---------------------------------------------------------------------------------------------------------------- |
|---------|-----------------|------------------------------------------------------------------------------------------------------------------|
| `float` | `iou_threshold` | The threshold for deciding whether boxes overlap too much with respect to IoU. Value range [0, 1]. Default to 0. |
| `int` | `offset` | 0 or 1, boxes' width or height is (x2 - x1 + offset). |
......@@ -177,7 +177,7 @@ Perform sample from `input` with pixel locations from `grid`.
#### Parameters
| Type | Parameter | Description |
| ----- | -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|-------|----------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `int` | `interpolation_mode` | Interpolation mode to calculate output values. (0: `bilinear` , 1: `nearest`) |
| `int` | `padding_mode` | Padding mode for outside grid values. (0: `zeros`, 1: `border`, 2: `reflection`) |
| `int` | `align_corners` | If `align_corners=1`, the extrema (`-1` and `1`) are considered as referring to the center points of the input's corner pixels. If `align_corners=0`, they are instead considered as referring to the corner points of the input's corner pixels, making the sampling more resolution agnostic. |
......@@ -211,7 +211,7 @@ Perform CornerPool on `input` features. Read [CornerNet -- Detecting Objects as
#### Parameters
| Type | Parameter | Description |
| ----- | --------- | ---------------------------------------------------------------- |
|-------|-----------|------------------------------------------------------------------|
| `int` | `mode` | corner pool mode, (0: `top`, 1: `bottom`, 2: `left`, 3: `right`) |
#### Inputs
......@@ -241,7 +241,7 @@ Returns a tuple (`values`, `indices`) where `values` is the cumulative maximum e
#### Parameters
| Type | Parameter | Description |
| ----- | --------- | -------------------------------------- |
|-------|-----------|----------------------------------------|
| `int` | `dim` | the dimension to do the operation over |
#### Inputs
......@@ -273,7 +273,7 @@ Returns a tuple (`values`, `indices`) where `values` is the cumulative minimum e
#### Parameters
| Type | Parameter | Description |
| ----- | --------- | -------------------------------------- |
|-------|-----------|----------------------------------------|
| `int` | `dim` | the dimension to do the operation over |
#### Inputs
......@@ -305,7 +305,7 @@ Perform Modulated Deformable Convolution on input feature, read [Deformable Conv
#### Parameters
| Type | Parameter | Description |
| -------------- | ------------------- | ------------------------------------------------------------------------------------- |
|----------------|---------------------|---------------------------------------------------------------------------------------|
| `list of ints` | `stride` | The stride of the convolving kernel. (sH, sW) |
| `list of ints` | `padding` | Paddings on both sides of the input. (padH, padW) |
| `list of ints` | `dilation` | The spacing between kernel elements. (dH, dW) |
......@@ -338,16 +338,16 @@ Perform Modulated Deformable Convolution on input feature, read [Deformable Conv
- T:tensor(float32, Linear)
## MMCVDeformConv2d
### MMCVDeformConv2d
### Description
#### Description
Perform Deformable Convolution on input feature, read [Deformable Convolutional Network](https://arxiv.org/abs/1703.06211) for detail.
### Parameters
#### Parameters
| Type | Parameter | Description |
| -------------- | ------------------ | --------------------------------------------------------------------------------------------------------------------------------- |
|----------------|--------------------|-----------------------------------------------------------------------------------------------------------------------------------|
| `list of ints` | `stride` | The stride of the convolving kernel. (sH, sW) |
| `list of ints` | `padding` | Paddings on both sides of the input. (padH, padW) |
| `list of ints` | `dilation` | The spacing between kernel elements. (dH, dW) |
......@@ -355,7 +355,7 @@ Perform Deformable Convolution on input feature, read [Deformable Convolutional
| `int` | `group` | Split input into groups. `input_channel` should be divisible by the number of groups. |
| `int` | `im2col_step` | DeformableConv2d use im2col to compute convolution. im2col_step is used to split input and offset, reduce memory usage of column. |
### Inputs
#### Inputs
<dl>
<dt><tt>inputs[0]</tt>: T</dt>
......@@ -366,13 +366,13 @@ Perform Deformable Convolution on input feature, read [Deformable Convolutional
<dd>Input weight; 4-D tensor of shape (output_channel, input_channel, kH, kW).</dd>
</dl>
### Outputs
#### Outputs
<dl>
<dt><tt>outputs[0]</tt>: T</dt>
<dd>Output feature; 4-D tensor of shape (N, output_channel, outH, outW).</dd>
</dl>
### Type Constraints
#### Type Constraints
- T:tensor(float32, Linear)
docs/deployment/onnxruntime_op.md
View file @ 72182747
## Custom operators for ONNX Runtime in MMCV
## ONNX Runtime Deployment
### Introduction of ONNX Runtime
......@@ -15,15 +15,15 @@
### List of operators for ONNX Runtime supported in MMCV
| Operator | CPU | GPU | MMCV Releases |
| :----------------------------------------------------: | :---: | :---: | :-----------: |
| [SoftNMS](onnxruntime_custom_ops.md#softnms) | Y | N | 1.2.3 |
| [RoIAlign](onnxruntime_custom_ops.md#roialign) | Y | N | 1.2.5 |
| [NMS](onnxruntime_custom_ops.md#nms) | Y | N | 1.2.7 |
| [grid_sampler](onnxruntime_custom_ops.md#grid_sampler) | Y | N | 1.3.1 |
| [CornerPool](onnxruntime_custom_ops.md#cornerpool) | Y | N | 1.3.4 |
| [cummax](onnxruntime_custom_ops.md#cummax) | Y | N | master |
| [cummin](onnxruntime_custom_ops.md#cummin) | Y | N | master |
| Operator | CPU | GPU | MMCV Releases |
|:-------------------------------------------------------|:---:|:---:|:-------------:|
| [SoftNMS](onnxruntime_custom_ops.md#softnms) | Y | N | 1.2.3 |
| [RoIAlign](onnxruntime_custom_ops.md#roialign) | Y | N | 1.2.5 |
| [NMS](onnxruntime_custom_ops.md#nms) | Y | N | 1.2.7 |
| [grid_sampler](onnxruntime_custom_ops.md#grid_sampler) | Y | N | 1.3.1 |
| [CornerPool](onnxruntime_custom_ops.md#cornerpool) | Y | N | 1.3.4 |
| [cummax](onnxruntime_custom_ops.md#cummax) | Y | N | 1.3.4 |
| [cummin](onnxruntime_custom_ops.md#cummin) | Y | N | 1.3.4 |
### How to build custom operators for ONNX Runtime
......@@ -88,6 +88,8 @@ onnx_results = sess.run(None, {'input' : input_data})
#### Reminder
- *Please note that this feature is experimental and may change in the future. Strongly suggest users always try with the latest master branch.*
- The custom operator is not included in [supported operator list](https://github.com/microsoft/onnxruntime/blob/master/docs/OperatorKernels.md) in ONNX Runtime.
- The custom operator should be able to be exported to ONNX.
......
docs/deployment/tensorrt_plugin.md
View file @ 72182747
## TensorRT Plugins for custom operators in MMCV (Experimental)
## TensorRT Deployment
<!-- TOC -->
- [TensorRT Plugins for custom operators in MMCV (Experimental)](#tensorrt-plugins-for-custom-operators-in-mmcv-experimental)
- [TensorRT Deployment](#tensorrt-deployment)
- [Introduction](#introduction)
- [List of TensorRT plugins supported in MMCV](#list-of-tensorrt-plugins-supported-in-mmcv)
- [How to build TensorRT plugins in MMCV](#how-to-build-tensorrt-plugins-in-mmcv)
......@@ -24,17 +24,17 @@ To ease the deployment of trained models with custom operators from `mmcv.ops` u
### List of TensorRT plugins supported in MMCV
| ONNX Operator | TensorRT Plugin | MMCV Releases |
| :-----------------------: | :-----------------------------------------------------------------------------: | :-----------: |
| MMCVRoiAlign | [MMCVRoiAlign](./tensorrt_custom_ops.md#mmcvroialign) | 1.2.6 |
| ScatterND | [ScatterND](./tensorrt_custom_ops.md#scatternd) | 1.2.6 |
| NonMaxSuppression | [NonMaxSuppression](./tensorrt_custom_ops.md#nonmaxsuppression) | 1.3.0 |
| MMCVDeformConv2d | [MMCVDeformConv2d](./tensorrt_custom_ops.md#mmcvdeformconv2d) | 1.3.0 |
| grid_sampler | [grid_sampler](./tensorrt_custom_ops.md#grid-sampler) | 1.3.1 |
| cummax | [cummax](./tensorrt_custom_ops.md#cummax) | 1.3.5 |
| cummin | [cummin](./tensorrt_custom_ops.md#cummin) | 1.3.5 |
| ONNX Operator | TensorRT Plugin | MMCV Releases |
|:--------------------------|:--------------------------------------------------------------------------------|:-------------:|
| MMCVRoiAlign | [MMCVRoiAlign](./tensorrt_custom_ops.md#mmcvroialign) | 1.2.6 |
| ScatterND | [ScatterND](./tensorrt_custom_ops.md#scatternd) | 1.2.6 |
| NonMaxSuppression | [NonMaxSuppression](./tensorrt_custom_ops.md#nonmaxsuppression) | 1.3.0 |
| MMCVDeformConv2d | [MMCVDeformConv2d](./tensorrt_custom_ops.md#mmcvdeformconv2d) | 1.3.0 |
| grid_sampler | [grid_sampler](./tensorrt_custom_ops.md#grid-sampler) | 1.3.1 |
| cummax | [cummax](./tensorrt_custom_ops.md#cummax) | 1.3.5 |
| cummin | [cummin](./tensorrt_custom_ops.md#cummin) | 1.3.5 |
| MMCVInstanceNormalization | [MMCVInstanceNormalization](./tensorrt_custom_ops.md#mmcvinstancenormalization) | 1.3.5 |
| MMCVModulatedDeformConv2d | [MMCVModulatedDeformConv2d](./tensorrt_custom_ops.md#mmcvmodulateddeformconv2d) | master |
| MMCVModulatedDeformConv2d | [MMCVModulatedDeformConv2d](./tensorrt_custom_ops.md#mmcvmodulateddeformconv2d) | 1.3.8 |
Notes
......@@ -163,6 +163,8 @@ Below are the main steps:
#### Reminders
- *Please note that this feature is experimental and may change in the future. Strongly suggest users always try with the latest master branch.*
- Some of the [custom ops](https://mmcv.readthedocs.io/en/latest/ops.html) in `mmcv` have their cuda implementations, which could be referred.
### Known Issues
......
docs/index.rst
View file @ 72182747
......@@ -29,12 +29,10 @@ You can switch between Chinese and English documents in the lower-left corner of
:maxdepth: 2
:caption: Deployment
deployment/mmcv_ops_definition.md
deployment/onnx.md
deployment/onnxruntime_op.md
deployment/onnxruntime_custom_ops.md
deployment/tensorrt_plugin.md
deployment/tensorrt_custom_ops.md
deployment/mmcv_ops_definition.md
.. toctree::
:maxdepth: 2
......
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