kevinthesun commented on a change in pull request #6443:
URL: https://github.com/apache/incubator-tvm/pull/6443#discussion_r489716429
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File path: src/relay/op/vision/rcnn_op.cc
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@@ -43,14 +45,43 @@ bool ROIAlignRel(const Array<Type>& types, int num_inputs,
const Attrs& attrs,
CHECK(roi_align_attrs);
CHECK_EQ(dshape.size(), 4) << "Input data should be 4-D.";
CHECK_EQ(rshape.size(), 2) << "Input rois should be 2-D.";
- CHECK_EQ(roi_align_attrs->layout, "NCHW") << "ROI Align only supports NCHW
layout";
// assign output type
- std::vector<IndexExpr> oshape(
- {rshape[0], dshape[1], roi_align_attrs->pooled_size[0],
roi_align_attrs->pooled_size[1]});
+ std::vector<IndexExpr> oshape;
+ if (roi_align_attrs->layout == "NCHW") {
+ oshape = {rshape[0], dshape[1], roi_align_attrs->pooled_size[0],
+ roi_align_attrs->pooled_size[1]};
+ } else {
+ CHECK_EQ(roi_align_attrs->layout, "NHWC") << "Unexpected ROI Align layout";
+ oshape = {rshape[0], roi_align_attrs->pooled_size[0],
roi_align_attrs->pooled_size[1],
+ dshape[3]};
+ }
+
reporter->Assign(types[2], TensorType(oshape, data->dtype));
return true;
}
+template <typename T>
+Array<Array<Layout> > ROIAlignInferCorrectLayout(const Attrs& attrs,
Review comment:
The issue can be reproduced by applying this patch to
https://github.com/apache/incubator-tvm/pull/6449 and run
```test_detection_models()``` in
```tests/python/frontend/pytorch/test_object_detection.py```.
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