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remove roi_align plugin for ORT (#258)
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* remove roi_align plugin

* remove ut

* skip single_roi_extractor UT for ORT in CI

* move align to symbolic and update docs

* recover UT

* resolve comments
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AllentDan authored Mar 24, 2022
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255 changes: 0 additions & 255 deletions csrc/backend_ops/onnxruntime/roi_align/roi_align.cpp

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59 changes: 0 additions & 59 deletions csrc/backend_ops/onnxruntime/roi_align/roi_align.h

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1 change: 0 additions & 1 deletion docs/en/backends/onnxruntime.md
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| Operator | CPU | GPU | MMDeploy Releases |
| :--------------------------------------------------------------------------- | :---: | :---: | :---------------- |
| [RoIAlign](../ops/onnxruntime.md#roialign) | Y | N | master |
| [grid_sampler](../ops/onnxruntime.md#grid_sampler) | Y | N | master |
| [MMCVModulatedDeformConv2d](../ops/onnxruntime.md#mmcvmodulateddeformconv2d) | Y | N | master |

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47 changes: 2 additions & 45 deletions docs/en/ops/onnxruntime.md
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<!-- TOC -->

- [ONNX Runtime Ops](#onnx-runtime-ops)
- [RoIAlign](#roialign)
- [grid_sampler](#grid_sampler)
- [Description](#description)
- [Parameters](#parameters)
- [Inputs](#inputs)
- [Outputs](#outputs)
- [Type Constraints](#type-constraints)
- [grid_sampler](#grid_sampler)
- [MMCVModulatedDeformConv2d](#mmcvmodulateddeformconv2d)
- [Description](#description-1)
- [Parameters](#parameters-1)
- [Inputs](#inputs-1)
- [Outputs](#outputs-1)
- [Type Constraints](#type-constraints-1)
- [MMCVModulatedDeformConv2d](#mmcvmodulateddeformconv2d)
- [Description](#description-2)
- [Parameters](#parameters-2)
- [Inputs](#inputs-2)
- [Outputs](#outputs-2)
- [Type Constraints](#type-constraints-2)

<!-- TOC -->

### RoIAlign

#### Description

Perform RoIAlign on output feature, used in bbox_head of most two-stage detectors.

#### 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 |
| `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. |

#### Inputs

<dl>
<dt><tt>input</tt>: T</dt>
<dd>Input feature map; 4D tensor of shape (N, C, H, W), where N is the batch size, C is the numbers of channels, H and W are the height and width of the data.</dd>
<dt><tt>rois</tt>: T</dt>
<dd>RoIs (Regions of Interest) to pool over; 2-D tensor of shape (num_rois, 5) given as [[batch_index, x1, y1, x2, y2], ...]. The RoIs' coordinates are the coordinate system of input.</dd>
</dl>

#### Outputs

<dl>
<dt><tt>feat</tt>: T</dt>
<dd>RoI pooled output, 4-D tensor of shape (num_rois, C, output_height, output_width). The r-th batch element feat[r-1] is a pooled feature map corresponding to the r-th RoI RoIs[r-1].<dd>
</dl>

#### Type Constraints

- T:tensor(float32)

### grid_sampler

#### Description
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