You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/02/11 17:23:26 UTC
[GitHub] [tvm] trevor-m opened a new pull request #7445: [Frontend][Tensorflow] Ignore some TF 2.x attributes
trevor-m opened a new pull request #7445:
URL: https://github.com/apache/tvm/pull/7445
Ignore "explicit_paddings" for pooling ops and "_cloned" for squeeze.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] FrozenGene merged pull request #7445: [Frontend][Tensorflow] Support explicit_paddings for TF 2.x
Posted by GitBox <gi...@apache.org>.
FrozenGene merged pull request #7445:
URL: https://github.com/apache/tvm/pull/7445
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] FrozenGene edited a comment on pull request #7445: [Frontend][Tensorflow] Ignore some TF 2.x attributes
Posted by GitBox <gi...@apache.org>.
FrozenGene edited a comment on pull request #7445:
URL: https://github.com/apache/tvm/pull/7445#issuecomment-781292049
I worry about we can not ignore it simply. According to doc: https://www.tensorflow.org/api_docs/python/tf/nn/conv2d
> Either the string "SAME" or "VALID" indicating the type of padding algorithm to use, or a list indicating the explicit paddings at the start and end of each dimension. When explicit padding is used and data_format is "NHWC", this should be in the form [[0, 0], [pad_top,pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used and data_format is "NCHW", this should be in the form [[0, 0], [0, 0],[pad_top, pad_bottom], [pad_left, pad_right]].
If `explicit_padding` is not None, we should apply its values. However, @trevor-m you could make a double check.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] FrozenGene commented on pull request #7445: [Frontend][Tensorflow] Support explicit_paddings for TF 2.x
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on pull request #7445:
URL: https://github.com/apache/tvm/pull/7445#issuecomment-782557714
Thanks @trevor-m Merged.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] FrozenGene commented on pull request #7445: [Frontend][Tensorflow] Ignore some TF 2.x attributes
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on pull request #7445:
URL: https://github.com/apache/tvm/pull/7445#issuecomment-781292049
I worry we can not ignore it simply. According to doc: https://www.tensorflow.org/api_docs/python/tf/nn/conv2d
> Either the string "SAME" or "VALID" indicating the type of padding algorithm to use, or a list indicating the explicit paddings at the start and end of each dimension. When explicit padding is used and data_format is "NHWC", this should be in the form [[0, 0], [pad_top,pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used and data_format is "NCHW", this should be in the form [[0, 0], [0, 0],[pad_top, pad_bottom], [pad_left, pad_right]].
If `explicit_padding` is not None, we should apply its values. However, @trevor-m you could make a double check.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] trevor-m commented on pull request #7445: [Frontend][Tensorflow] Ignore some TF 2.x attributes
Posted by GitBox <gi...@apache.org>.
trevor-m commented on pull request #7445:
URL: https://github.com/apache/tvm/pull/7445#issuecomment-781572571
> I worry about we can not ignore it simply. According to doc: https://www.tensorflow.org/api_docs/python/tf/nn/conv2d
>
> > Either the string "SAME" or "VALID" indicating the type of padding algorithm to use, or a list indicating the explicit paddings at the start and end of each dimension. When explicit padding is used and data_format is "NHWC", this should be in the form [[0, 0], [pad_top,pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used and data_format is "NCHW", this should be in the form [[0, 0], [0, 0],[pad_top, pad_bottom], [pad_left, pad_right]].
>
> If `explicit_padding` is not None, we should apply its values. However, @trevor-m you could make a double check.
Thanks for the review! That is true, I will update this PR to properly support explicit padding.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] FrozenGene commented on pull request #7445: [Frontend][Tensorflow] Ignore some TF 2.x attributes
Posted by GitBox <gi...@apache.org>.
FrozenGene commented on pull request #7445:
URL: https://github.com/apache/tvm/pull/7445#issuecomment-782072291
> > I worry about we can not ignore it simply. According to doc: https://www.tensorflow.org/api_docs/python/tf/nn/conv2d
> > > Either the string "SAME" or "VALID" indicating the type of padding algorithm to use, or a list indicating the explicit paddings at the start and end of each dimension. When explicit padding is used and data_format is "NHWC", this should be in the form [[0, 0], [pad_top,pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used and data_format is "NCHW", this should be in the form [[0, 0], [0, 0],[pad_top, pad_bottom], [pad_left, pad_right]].
> >
> >
> > If `explicit_padding` is not None, we should apply its values. However, @trevor-m you could make a double check.
>
> Thanks for the review! That is true, I will update this PR to properly support explicit padding.
Thanks @trevor-m Our convolution op ignore `explicit_padding` attribute simply is wrong too, not only just pooling op. You could correct it too.Thanks.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] FrozenGene edited a comment on pull request #7445: [Frontend][Tensorflow] Ignore some TF 2.x attributes
Posted by GitBox <gi...@apache.org>.
FrozenGene edited a comment on pull request #7445:
URL: https://github.com/apache/tvm/pull/7445#issuecomment-782072291
> > I worry about we can not ignore it simply. According to doc: https://www.tensorflow.org/api_docs/python/tf/nn/conv2d
> > > Either the string "SAME" or "VALID" indicating the type of padding algorithm to use, or a list indicating the explicit paddings at the start and end of each dimension. When explicit padding is used and data_format is "NHWC", this should be in the form [[0, 0], [pad_top,pad_bottom], [pad_left, pad_right], [0, 0]]. When explicit padding used and data_format is "NCHW", this should be in the form [[0, 0], [0, 0],[pad_top, pad_bottom], [pad_left, pad_right]].
> >
> >
> > If `explicit_padding` is not None, we should apply its values. However, @trevor-m you could make a double check.
>
> Thanks for the review! That is true, I will update this PR to properly support explicit padding.
Thanks @trevor-m Our convolution op ignore `explicit_padding` attribute simply is wrong too (Note: be careful of `conv2d_transpose`: https://www.tensorflow.org/api_docs/python/tf/nn/conv2d_transpose, its explicit padding is not the same as `conv2d`), not only just pooling op. You could correct it too.Thanks.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [tvm] trevor-m commented on pull request #7445: [Frontend][Tensorflow] Support explicit_paddings for TF 2.x
Posted by GitBox <gi...@apache.org>.
trevor-m commented on pull request #7445:
URL: https://github.com/apache/tvm/pull/7445#issuecomment-782329275
@FrozenGene I've updated the PR with explicit padding support. PTAL
I noticed that while many ops now have the "explicit_paddings" attribute, the ability to actually use explicit padding in the TF python API has only exposed it for a few ops.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org