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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/05/25 18:08:11 UTC
[GitHub] [tvm] tkonolige opened a new pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
tkonolige opened a new pull request #8128:
URL: https://github.com/apache/tvm/pull/8128
We handle lowering rank 0 tensors by lowering them to rank 1 buffers with a single element.
@junrushao1994 @Hzfengsy @vinx13 @MasterJH5574 @tqchen
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[GitHub] [tvm] junrushao1994 commented on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
junrushao1994 commented on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-848107931
@Hzfengsy would you like to take a look at this corner case? Basically it is due to the fact that 0-dimension tensor in Relay is lowered to a block with 0 IterVars, which causes ambiguity with the "opaque" block.
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[GitHub] [tvm] tqchen edited a comment on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
tqchen edited a comment on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-848218371
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[GitHub] [tvm] junrushao1994 commented on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
junrushao1994 commented on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-848192731
@tqchen The main problem is the ambiguity introduced by the definition of an opaque block. An alternative approach is that we just add a dummy iter-var in the block with unit extent. What do you think?
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[GitHub] [tvm] tqchen edited a comment on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
tqchen edited a comment on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-848190602
Perhaps we should think about proper rank 0 buffer support instead to change to rank 1.
We already support such rank-0 buffer through out the previous TE pipeline, and would be great to confirm and make things work through the current pipeline as well
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[GitHub] [tvm] tqchen commented on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
tqchen commented on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-848218371
I still think it would be great to have first-class 0-rank buffer and compute support, so we do not need to do special casing to handle the items. Such first-class support will bring a lot of benefit later, for example, in the cases such as adding a batching to the entire loop computations
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[GitHub] [tvm] tqchen commented on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
tqchen commented on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-848190602
Perhaps we should think about proper rank 0 buffer support instead to change to rank 1
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[GitHub] [tvm] junrushao1994 merged pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
junrushao1994 merged pull request #8128:
URL: https://github.com/apache/tvm/pull/8128
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[GitHub] [tvm] tqchen commented on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
tqchen commented on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-854711103
Suggest close this for now and instead move to a tracking issue that tracks the 0-rank support in various places of tensorIR.
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[GitHub] [tvm] junrushao1994 commented on pull request #8128: [TE/TIR] Fix create_prim_func to properly handle rank 0 tensors.
Posted by GitBox <gi...@apache.org>.
junrushao1994 commented on pull request #8128:
URL: https://github.com/apache/tvm/pull/8128#issuecomment-854831387
Given this PR does help some workloads (some subgraphs in BERT) temporarily, and doesn't introduce new problems, let's merge it in and start a tracking issue
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