Beya2019 commented on a change in pull request #6443:
URL: https://github.com/apache/incubator-tvm/pull/6443#discussion_r486742150
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File path: python/tvm/relay/op/vision/rcnn.py
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@@ -24,7 +24,7 @@ def roi_align(data, rois, pooled_size, spatial_scale,
sample_ratio=-1, layout='N
Parameters
----------
data : relay.Expr
- 4-D tensor with shape [batch, channel, height, width]
+ 4-D tensor with shape [batch, channel, height, width] or [batch,
height, width, channel]
Review comment:
@kevinthesun and @anijain2305, In addition, I would like to add one more
point.
In our own target, this implementation method really affect our performance
for it add many layout_transpose operator(Our convolution only supports nhwc,
if roi_align only supports nchw, it means that many additional layout_transform
operators need to be inserted into the network), I also think really need nhwc
layout implementation for this op considering performance. And this submission
is needed for layout convert support whether nhwc layout realized or not. The
two mentioned function are not conflicting but complementary, I also hope the
nhwc layout topi implementation as soon as possible.
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