ccjoechou commented on pull request #9235:
URL: https://github.com/apache/tvm/pull/9235#issuecomment-943494906
Hi Wuwei, (or any other who can help?)
I have spent lots time on this pooling issue, which I believe it is a
fundamental-concept-related issue.
Similar to what we have implemented for the ConvInferCorrectLayout()
function in the tvm/src/relay/op/nn/convention.h file – for instance, it keeps
the conv op’s layouts, if they are provided.
Let me use the nn.max_pool2d op as an example.
If in a given (input) IR graph, it is “explicitly” described that a
nn.max_pool2d op needs to use the layout == “NHWC”.
* E.g.: y = relay.nn.max_pool2d(y, pool_size=(2, 2), layout="NHWC")
Plus, there is either:
* Either, “no” transforms.ConvertLayout() is given with a desired layout
for nn.max_pool2d op, or
* A transforms.ConvertLayout() is given with a desired layout for
"nn.max_pool2d": ["NHWC"] – i.e., to tell TVM.relay that the nn.max_pool2d op
must stick with its “NHWC” data layout format (for input and for output)
In the above conditions, shouldn’t TVM.relay keep the nn.max_pool2d op’s
input, data, output layouts as “NHWC”?
That is when nn.max_pool2d op’s param->layout != “” (assuming it is a legal
layout format), we should use:
* InferCorrectLayoutOutput({use the original, given params->layout},
{use the original, given params->layout}, Attrs(params))
If this fundamental concept stands, then, the PR-#9235’s change to
pooling.cc file should be (kind of) correct !
If you are in agreement with this fundamental concept, then, I can make
further changes to the following “test suites” …
*
Tvm/tests/python/contrib/test_vitis_ai/test_vitis_ai_runtime_cpu_part.py – by
change its golden result to have 18 tvm ops (instead of 7, originally)
* Performance Note: this can affect the visit ai team’s run-time
performance because, now, 11 more ops will not be executed on the visit ai
accelerator (based on their byoc comments)
* It is possible that we may need to provide an additional pool
param->layout == ?? so that it can force
* tests/python/relay/test_pass_alter_op_layout.py – by making similar
changes as I did to the tvm/tests/python/relay/test_pass_convert_op_layout.py
test suite.
… Please advice so that I can continue and then resolve this PR.
Thanks a lot !
* Joe
From: Joe Chou
Sent: Monday, October 11, 2021 12:05 PM
To: apache/tvm ***@***.***>; apache/tvm ***@***.***>
Cc: Author ***@***.***>
Subject: RE: [EXT] Re: [apache/tvm] [bug] pooling convert layout bug in
pooling.cc and in test_pass_conve… (see also issue #8848) (#9235)
Yes and I am trying to reproduce them locally in order to find resolutions.
* Joe
From: Wuwei Lin ***@***.******@***.***>>
Sent: Monday, October 11, 2021 12:00 PM
To: apache/tvm ***@***.******@***.***>>
Cc: Joe Chou ***@***.******@***.***>>; Author ***@***.******@***.***>>
Subject: [EXT] Re: [apache/tvm] [bug] pooling convert layout bug in
pooling.cc and in test_pass_conve… (see also issue #8848) (#9235)
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