Skip to content

v7.0.0b1

Pre-release
Pre-release

Choose a tag to compare

View all tags
@emcastillo emcastillo released this 21 Jun 06:31
· 3347 commits to master since this release
v7.0.0b1
89b9661
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
Verified
Learn about vigilant mode.

This is the release note of v7.0.0b1. See here for the complete list of solved issues and merged PRs.

Highlights

  • TabularDataset is added. This is a new dataset interface that supports rich manipulation in a tabular form (like pandas.DataFrame), e.g. loading only a specified subset of keys (columns), efficient slicing (with less transposition/concatenation), batch-wise preprocessing, etc. The API is still under development; we are adding more functionalities and widening its support in existing features where datasets are involved.

New Features

  • Add interface to backprop from multiple variables (#5952)
  • Option to show progress bar during evaluation (#6474, thanks @wkentaro!)
  • Elementwise Power for ChainerX (#6496, thanks @dido1998!)
  • Add chainerx.hstack, chainerx.vstack and chainerx.atleast_2d (#6886, thanks @kshitij12345!)
  • Add TabularDataset (#7115)
  • Add TabularDataset.concat/join (#7116)
  • Add chainerx.expm1 and chainerx.exp2 (#7126, thanks @aksub99!)
  • Add chainerx.log2 (#7139)
  • Add TabularDataset.{transform/transform_batch} (#7150)
  • Add chainerx.log1p (#7161, thanks @sky58!)
  • Expose chainerx::AsContiguous as a public C++ API (#7166)
  • Emit warning on chainerx import in debug mode (#7178)
  • Add chainer.as_array for consistency with chainer.as_variable (#7252, thanks @tkerola!)
  • Add chainerx.moveaxis (#7265, thanks @kshitij12345!)
  • Add chainerx.leaky_relu (#7351, thanks @aksub99!)
  • Add chainerx.dstack and chainerx.atleast_3d (#7353, thanks @kshitij12345!)
  • Add Python operator __abs__ with chainerx.ndarray (#7364)
  • Allow turning off the static subgraph optimizations using a config (#7369)
  • Add NumPy constants to ChainerX (#7384)
  • Add chainerx.erf (#7404, thanks @aksub99!)
  • Add align_corners option to resize_images (#7429)
  • Add nearest mode to resize_images (#7443)
  • Add input_device to StandardUpdater (#7472)
  • Add is_array_supported method on backend.Device (#7487)

Enhancements

  • Refactor roi_max_align_2d and roi_average_align_2d (#6405, thanks @knorth55!)
  • Support Tagged communication with MPI_Status. (#6696, thanks @y1r!)
  • Support ChainerX in F.copy (#6982)
  • Avoid unnecessary updates in F.batch_renormalization, and related fixes (#7104)
  • Support ChainerX in Variable.addgrad (#7132)
  • Fix cuda.DummyDevice inheritance (#7147)
  • Add Device.name property (#7149)
  • Link.serialize to support ChainerX (#7175)
  • Fix typo in Variable.backward (#7196)
  • Call require_grad() on ChainerX Variable.grad setter (#7198)
  • Clear outputs in FunctionNode.unchain and raise error in ChainerX fallback mode (#7216)
  • Support ChainerX in Variable.copydata (#7226)
  • Support ChainerX in MNIST data parallel example (#7227)
  • MultiprocessParallelUpdater to support new devices (#7245)
  • Alias StackVector<int64_t, kMaxNdim> to Dims (#7258)
  • Support bool dtypes in chainerx::{Max,Min}imum (#7261)
  • Fix integral negative powers (#7262)
  • Make chx.backward not cause error even if backprop is not required (#7287)
  • Support None arguments in chainerx.clip and chainerx.ndarray.clip (#7296)
  • Support scalar in chainerx::Where (#7325)
  • F.clip function with None parameter to min/max (#7333)
  • Support cudnn deterministic max pooling (#7390, thanks @anaruse!)
  • Avoid transferring from a native device to another in Array::ToNative() (#7394)
  • Add type hints to Variable (#7400)
  • Improve get_device error message when ChainerX is not available (#7401)
  • get_device to raise a more correct error types (#7421)
  • Make EXEPECT_ARRAY_* macros able to used outside ChainerX (#7434)
  • Add sequence support for ChainerX shape arguments (#7446)
  • Check positive dilation in F.convolution_2d (#7448)
  • Check positive dilation in F.deconvolution_2d (#7449)
  • Explicit check of chainerx arrays on fallback functions (#7452)
  • Support F.copy between non-ChainerX and ChainerX devices only if backprop is not required (#7473)

Performance Improvements

  • In FunctionNode ChainerX fallback, reuse ChainerxDevice taken from inputs to create outputs (#7397)

Bug Fixes

  • Fix type check of F.where (#6872)
  • Fix a bug in Bernoulli.log_prob (#7064, thanks @seiyab!)
  • Fix uncopyable MultiNodeBatchNormalization (#7106)
  • Bugfix: MultiNodeChainList should not assume float32 (#7165)
  • Fix initialization of L.Linear when called with n_batch_axes (#7167)
  • Fix float16 and Tensor Core related issue in ChainerX (#7189, thanks @anaruse!)
  • Fix recomputation of L.BatchRenormalization (#7256)
  • Fix F.absolute_error for ChainerX (#7281, thanks @crcrpar!)
  • Fix a bug that root is ignored in scatter_dataset and bcast (#7289)
  • Fix condition to invoke cuDNN dropout (#7293, thanks @crcrpar!)
  • Improve type check in _values_to_dicts so it works with unicode of python 2 too (#7316)
  • Fix DtypeError in chainerx.square (#7321)
  • Fix mypy errors (#7423)
  • Make WeightDecay aware of loss scale (#7491)
  • Fix GradientMethod ChainerX fallback for uninitialized parameters (#7492)
  • Bugfix for pytest 2x2 (#7509)
  • Fix AdamW update rule regression on CPU (#7512)

Code Fixes

  • Split binary functions from math.cc (#7128)
  • Avoid using cuda.DummyDevice and cuda.get_device_from_array (#7148)
  • Fix pointless comparison compiler warning in ChainerX (#7160)
  • Remove backslashes to continue lines of link targets (#7170)
  • Split trigonometric/hyperbolic routines from math.cc (#7171)
  • Remove duplicated code in logic.cc (#7176)
  • Consistent cases for Inplace (#7181)
  • Improve code in testing.backend.BackendConfig (#7212)
  • Split ChainerX statistics routines from math.cc (#7222)
  • Fix code style for long expressions (#7231)
  • Check device instance using xp when possible (#7234)
  • Move declaration of AMax and AMin to statistics routines (#7269)
  • Split reduction routines from math.cc (#7270)
  • Use _ for private classes under chainer.dataset.tabular (#7275)
  • Remove unused using declaration (#7284)
  • Split misc routines from math.cc (#7298)
  • Fix wrong comment in ChainerX backward implementation (#7311)
  • Split explog routines from math.cc (#7317)
  • Fix style on imports (#7338)
  • Split rounding routines (#7407)
  • Split arithmetic ops from routines/math.h (#7415)
  • Put comments in FindCuDNN.cmake (#7419)
  • DRY optimizer test parameterizations (#7437)
  • Split logic routines from math (#7444)
  • Qualify some arguments of pool kernels const& (#7453)
  • Include cuda_fp16.h instead of cuda_fp16.hpp (#7480)
  • Use py::arg literal in ChainerX python binding (#7490)
  • Remove rounding kernels from math (#7497)
  • Rename and move activation routines from math.h (#7501)
  • Remove ChainerX AsTypeKernel (#7522, thanks @kshitij12345!)
  • Split python binding math routines (#7527)
  • Use absolute namespace in macros (#7536)

Documentation

  • Improve contribution guide (#6140)
  • Fix dead sphinx links (#6450)
  • Fix F.normalize documentation (#7062, thanks @crcrpar!)
  • Document F.copy view behavior (#7135)
  • Improve device documentation (#7162)
  • Document backend.get_device_from_array (#7163)
  • Remove chainerx.md (#7179)
  • Add optimizers.MSVAG to documentation (#7183)
  • Fix grammatical errors in documentation (#7186)
  • Fix capitalization of F.relu in doc (#7188)
  • Add missing doc entry for CommunicatorBase.allgather (#7192)
  • Fix invalid escape sequences in ChainerX routine docstrings (#7214)
  • Fix typos in chainer.utils.type_check (#7249, thanks @ktns!)
  • Document observe_value and observe_lr trigger interval (#7266)
  • Fix robots.txt to allow indexing root (#7306)
  • Avoid installing ChainerX when building docs of other projects on ReadTheDocs (#7363, thanks @knorth55!)
  • Improve F.normalize documentation (#7371, thanks @crcrpar!)
  • Fix format of static_graph.rst (#7389)
  • Change Deformable Convolution 2D docs to match arguments (#7402, thanks @higumachan!)
  • Avoid setting test_iter.epoch manually in the tutorial of training loop (#7405)
  • Remove "Comparison with other frameworks" from docs (#7417)
  • Fix documentation for shape in generate_array (#7450)
  • Remove test coverage from ChainerX contribution guide (#7462)
  • Correct Embed ID documentation (#7484)
  • Fix typo in tabular_dataset.py (#7495, thanks @nai62!)

Installation

  • Fix ChainerX compilation with MSVC (#7108, thanks @durswd!)
  • Allow CUDNN_LIBNAME to be specified by environment variable (#7243)
  • Use external $MAKEFLAGS instead if set in Travis CI script (#7331)
  • In FindCuDNN.cmake, prioritize explicit variables over environment variables (#7441)
  • Add ChainerX build option to use cuDNN from CuPy installation (#7442)
  • Pin typing == 3.6.6 (#7562)
  • Fix typing requirements (#7564)

Examples

  • Add CIFAR example to ChainerMN (#6839, thanks @ai-kase!)
  • Support device specifiers in MNIST data parallel example (#6857)
  • Support device specifiers in PTB example (#7055)
  • Support device specifiers in pix2pix example (#7076)
  • Support device specifiers in static graph example (#7153)
  • Support device specifiers in ImageNet data parallel example (#7164)
  • Support ChainerX in MNIST inference example (#7169)
  • Support device specifier in image captioning example (#7204)
  • Support device specifier in image captioning example (predict.py) (#7206)
  • Remove PlotReport.available() check in glance example (#7209)
  • Minor fix in DCGAN example README (#7210)
  • Fix sentiment example test (#7215)
  • Support device specifiers in MNIST model parallel example (#7225)
  • Use Agg backend in examples with plot functionality (#7247)
  • Support ChainerX in PTB gentxt example (#7314)
  • Support ChainerX in MNIST model parallel example (#7330)
  • Warn NaN in FP16 mode in dcgan example (#7344)
  • Warn NaN in FP16 mode in memnn example (#7345)
  • Warn NaN in FP16 mode in pix2pix example (#7346)
  • Warn NaN in FP16 mode in pos example (#7354)
  • Warn NaN in FP16 mode in reinforcement learning examples (#7355)
  • Warn NaN in FP16 mode in sentiment example (#7356)
  • Warn NaN in FP16 mode in static_graph_optimizations/cifar example (#7357)
  • Warn NaN in FP16 mode in static_graph_optimizations/mnist example (#7358)
  • Warn NaN in FP16 mode in vae example (#7362)
  • Warn NaN in FP16 mode in word2vec example (#7366)
  • Fix typo in wavenet example requirements (#7367)
  • Warn NaN in FP16 mode in wavenet example (#7372)
  • Support ChainerX in static subgraph optimization examples (#7431)
  • Implement reset method in the PTB example (#7533)

Tests

  • Add FP16 test to multi_node_chain_list (#6575)
  • [chainerx] Fix skipped_backward tests to return as PASS (#6815, thanks @kshitij12345!)
  • Add configuration of new CI system (#6843)
  • Simplify F.tensordot test (#6968, thanks @ishanrai05!)
  • Simplify F.cumprod test (#6978, thanks @hikjik!)
  • Simplify F.average test (#6995, thanks @hikjik!)
  • Move test_cuda.py to backends_tests (#7144)
  • Fix missing cuda in chainerx.swapaxes test (#7184, thanks @kshitij12345!)
  • Split Variable.grad and Variable.grad_var tests (#7191)
  • Refactor Variable.zerograd test (#7199)
  • Add Tensor Core test for chainerx.conv and chainerx.conv_transpose (#7203)
  • Move TestTanh from test_math.py to test_trigonometric_hyperbolic.py (#7207)
  • Refactor Variable.copydata test (#7224)
  • Add a test to reproduce the bcast deadlock problem (#7257)
  • Add float16 comparison test (#7260)
  • Use CUDA_VISIBLE_DEVICES in ChainerX tests (#7290)
  • Add chainer.as_array test (#7318)
  • Rewrite StandardUpdater tests with pytest style assertion (#7326)
  • Change 0 to 0.0 for python2 (#7373)
  • Add missing parameter dstack to invalid_shape test (#7457, thanks @kshitij12345!)
  • Use pytest.mark.xfail instead of unittest.expectedFailure (#7488)

Others

  • Remove "Research projects using Chainer" from README (#7416)
Assets 2
Loading