This repository has been archived by the owner on Nov 17, 2023. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 6.8k
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
reminisce
approved these changes
Apr 5, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 5, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 5, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 5, 2019
reminisce
pushed a commit
that referenced
this pull request
Apr 6, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 10, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 11, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 12, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 13, 2019
reminisce
pushed a commit
to reminisce/mxnet
that referenced
this pull request
Apr 15, 2019
szha
pushed a commit
that referenced
this pull request
Apr 16, 2019
* [numpy] Shape support scalar tensor (#14315) * Support scalar and zero-size tensors with np.sum * Add sanity check when ndim is set * [Numpy] Change semantics of ndim for operators in `src/operator/contrib` (#14409) * Initial commit * Address comments * [WIP] Use new shape definition (#14453) * Init checkin * Fix ndarray alloc bug * Use TShape(0) as default empty tuple params * Fix bugs * Fix TShape init value * Fix infer shape pass shape type and reshape infer shape func * [numpy] Fix unit tests after introducing numpy compatible shapes (#14487) * Fix infer shape rnn * Fix boolean mask and custom op unit tests * Fix multi proposal * Fix diag * Add global switch for backward compatibility and fix infer shape bugs * Fix slice op infer shape * Fix rnn infer shape * Add util funcs for ndim_is_known and dim_size_is_known * Revert rnn_cell.py * Fix a bug to pass the test in test_contrib_rnn (#14520) * fix. * remove type conversion. * remove type cast. * [numpy] Fix test_dynamic_shape.test_dynamic_shape (#14538) * Initial commit * Address comments from Jun * [numpy] Fix numpy import in python2 (#14537) * Fix several test failures * Fix subgraph op infer shape * Fix sparse slice * Fix deconv infer shape * Fix numpy import compatibility problem in python2 * fix concat and slice (#14549) * fix R-package (#14536) * Fix cpp package build after using new shape definition (#14554) * Fix pooling_v1 and deformable_convolution param initialization (#14577) * Fix pooling_v1 param initialization * Fix deformable_convolution param initialization * [Numpy] Misc fix (#14612) * [Numpy] Misc Fix * fix build * !shape_is_none => shape_is_known * Address comments * Fix * [Numpy] fix test_operator_gpu.test_upsampling_bilinear_with_type (#14557) * Fix test_operator_gpu.test_upsampling_bilinear_with_type * Address comments * [Numpy] Java/Scala modification (#14625) * modify jni to support 0 dim/shape * fix transpose axes default value * fix shape index bug (#14630) * fix jni lint (#14634) * [numpy] Fix numpy branch failing tests in CI (#14639) * Remove numpy namespaces for operator registration * Fix bug when shape is compeltely unknown * Fix singed/unsigned compare warning * Fix CI * Fix pylint * Avoid launching gpu kernels for zero-size output tensors * Fix test_ndarray * Fix binary broadcast with zero-size tensors * Better error message for infer shape failure in imperative * Fix TShape constructor ambiguity on certain platforms * Fix mkldnn build failure * Fix build failure in gpu and cpp test * Fix gpu cpp test build with mkldnn * Fix mkldnn cpp test * Fix concatenating zero-size tensors * Avoid letting mkldnn handle zero-size tensors in concat * Fix quantized_concat infer shape * Try to fix perl c api * fix invalid ndarray dispose (#14657) * swig fixes for the changes in c_api.h (#14655) * Rename np_comp to np_compat for readability * Fix import error * Keep old c apis unchanged * Fix lint * Rebase and fix build * Fix R build failure * Fix Perl build failure * Rebase with master * Address cr comments * Use just one scope to represent numpy compatibility * Add code comment to NumpyScope object in Scala * Add use_np_compat decorator * Fix pylint
kedarbellare
pushed a commit
to kedarbellare/incubator-mxnet
that referenced
this pull request
Apr 20, 2019
* [numpy] Shape support scalar tensor (apache#14315) * Support scalar and zero-size tensors with np.sum * Add sanity check when ndim is set * [Numpy] Change semantics of ndim for operators in `src/operator/contrib` (apache#14409) * Initial commit * Address comments * [WIP] Use new shape definition (apache#14453) * Init checkin * Fix ndarray alloc bug * Use TShape(0) as default empty tuple params * Fix bugs * Fix TShape init value * Fix infer shape pass shape type and reshape infer shape func * [numpy] Fix unit tests after introducing numpy compatible shapes (apache#14487) * Fix infer shape rnn * Fix boolean mask and custom op unit tests * Fix multi proposal * Fix diag * Add global switch for backward compatibility and fix infer shape bugs * Fix slice op infer shape * Fix rnn infer shape * Add util funcs for ndim_is_known and dim_size_is_known * Revert rnn_cell.py * Fix a bug to pass the test in test_contrib_rnn (apache#14520) * fix. * remove type conversion. * remove type cast. * [numpy] Fix test_dynamic_shape.test_dynamic_shape (apache#14538) * Initial commit * Address comments from Jun * [numpy] Fix numpy import in python2 (apache#14537) * Fix several test failures * Fix subgraph op infer shape * Fix sparse slice * Fix deconv infer shape * Fix numpy import compatibility problem in python2 * fix concat and slice (apache#14549) * fix R-package (apache#14536) * Fix cpp package build after using new shape definition (apache#14554) * Fix pooling_v1 and deformable_convolution param initialization (apache#14577) * Fix pooling_v1 param initialization * Fix deformable_convolution param initialization * [Numpy] Misc fix (apache#14612) * [Numpy] Misc Fix * fix build * !shape_is_none => shape_is_known * Address comments * Fix * [Numpy] fix test_operator_gpu.test_upsampling_bilinear_with_type (apache#14557) * Fix test_operator_gpu.test_upsampling_bilinear_with_type * Address comments * [Numpy] Java/Scala modification (apache#14625) * modify jni to support 0 dim/shape * fix transpose axes default value * fix shape index bug (apache#14630) * fix jni lint (apache#14634) * [numpy] Fix numpy branch failing tests in CI (apache#14639) * Remove numpy namespaces for operator registration * Fix bug when shape is compeltely unknown * Fix singed/unsigned compare warning * Fix CI * Fix pylint * Avoid launching gpu kernels for zero-size output tensors * Fix test_ndarray * Fix binary broadcast with zero-size tensors * Better error message for infer shape failure in imperative * Fix TShape constructor ambiguity on certain platforms * Fix mkldnn build failure * Fix build failure in gpu and cpp test * Fix gpu cpp test build with mkldnn * Fix mkldnn cpp test * Fix concatenating zero-size tensors * Avoid letting mkldnn handle zero-size tensors in concat * Fix quantized_concat infer shape * Try to fix perl c api * fix invalid ndarray dispose (apache#14657) * swig fixes for the changes in c_api.h (apache#14655) * Rename np_comp to np_compat for readability * Fix import error * Keep old c apis unchanged * Fix lint * Rebase and fix build * Fix R build failure * Fix Perl build failure * Rebase with master * Address cr comments * Use just one scope to represent numpy compatibility * Add code comment to NumpyScope object in Scala * Add use_np_compat decorator * Fix pylint
haohuanw
pushed a commit
to haohuanw/incubator-mxnet
that referenced
this pull request
Jun 23, 2019
* [numpy] Shape support scalar tensor (apache#14315) * Support scalar and zero-size tensors with np.sum * Add sanity check when ndim is set * [Numpy] Change semantics of ndim for operators in `src/operator/contrib` (apache#14409) * Initial commit * Address comments * [WIP] Use new shape definition (apache#14453) * Init checkin * Fix ndarray alloc bug * Use TShape(0) as default empty tuple params * Fix bugs * Fix TShape init value * Fix infer shape pass shape type and reshape infer shape func * [numpy] Fix unit tests after introducing numpy compatible shapes (apache#14487) * Fix infer shape rnn * Fix boolean mask and custom op unit tests * Fix multi proposal * Fix diag * Add global switch for backward compatibility and fix infer shape bugs * Fix slice op infer shape * Fix rnn infer shape * Add util funcs for ndim_is_known and dim_size_is_known * Revert rnn_cell.py * Fix a bug to pass the test in test_contrib_rnn (apache#14520) * fix. * remove type conversion. * remove type cast. * [numpy] Fix test_dynamic_shape.test_dynamic_shape (apache#14538) * Initial commit * Address comments from Jun * [numpy] Fix numpy import in python2 (apache#14537) * Fix several test failures * Fix subgraph op infer shape * Fix sparse slice * Fix deconv infer shape * Fix numpy import compatibility problem in python2 * fix concat and slice (apache#14549) * fix R-package (apache#14536) * Fix cpp package build after using new shape definition (apache#14554) * Fix pooling_v1 and deformable_convolution param initialization (apache#14577) * Fix pooling_v1 param initialization * Fix deformable_convolution param initialization * [Numpy] Misc fix (apache#14612) * [Numpy] Misc Fix * fix build * !shape_is_none => shape_is_known * Address comments * Fix * [Numpy] fix test_operator_gpu.test_upsampling_bilinear_with_type (apache#14557) * Fix test_operator_gpu.test_upsampling_bilinear_with_type * Address comments * [Numpy] Java/Scala modification (apache#14625) * modify jni to support 0 dim/shape * fix transpose axes default value * fix shape index bug (apache#14630) * fix jni lint (apache#14634) * [numpy] Fix numpy branch failing tests in CI (apache#14639) * Remove numpy namespaces for operator registration * Fix bug when shape is compeltely unknown * Fix singed/unsigned compare warning * Fix CI * Fix pylint * Avoid launching gpu kernels for zero-size output tensors * Fix test_ndarray * Fix binary broadcast with zero-size tensors * Better error message for infer shape failure in imperative * Fix TShape constructor ambiguity on certain platforms * Fix mkldnn build failure * Fix build failure in gpu and cpp test * Fix gpu cpp test build with mkldnn * Fix mkldnn cpp test * Fix concatenating zero-size tensors * Avoid letting mkldnn handle zero-size tensors in concat * Fix quantized_concat infer shape * Try to fix perl c api * fix invalid ndarray dispose (apache#14657) * swig fixes for the changes in c_api.h (apache#14655) * Rename np_comp to np_compat for readability * Fix import error * Keep old c apis unchanged * Fix lint * Rebase and fix build * Fix R build failure * Fix Perl build failure * Rebase with master * Address cr comments * Use just one scope to represent numpy compatibility * Add code comment to NumpyScope object in Scala * Add use_np_compat decorator * Fix pylint
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description
@reminisce
Checklist
Essentials
Please feel free to remove inapplicable items for your PR.
Changes
Comments