Chainer v7.0.0b3 をリリースしました

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Daisuke Nishino

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Aug 22, 2019, 4:39:44 AM8/22/19
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Chainer v7.0.0b3 をリリースしました！ リリースノートは以下の通りです。



This is the release note of v7.0.0b3. See here for the complete list of solved issues and merged PRs.

Dropping Support of Python 2

Due to the end-of-life (EOL) of Python 2 in January 2020, Python 2 support has been dropped in this release. Chainer v6.x continues to support Python 2. See the blog post for details.

Note on F.max_pooling_2d refactoring

Implementation of F.max_pooling_2d has been merged to F.max_pooling_nd. The behavior is unchanged, so ordinary users should not be affected by this change. However, the FunctionNode class recorded in the computational graph corresponding to F.max_pooling_2d has changed from MaxPooling2D to MaxPoolingND. The code explicitly depending on this class will need a fix.

New Features

  • Add an option to invoke extensions before training (#3511, thanks @wkentaro!)
  • Add automatic management of snapshots (deletion and load) (#6856)
  • Add chainerx.repeat (#7223, thanks @durswd!)
  • Support mixed indices in TabularDataset.slice (#7251)
  • Add chainer.dataset.tabular.DelegateDataset (#7276)
  • Add ObservationAggregator extension to ChainerMN (#7302)
  • Add strict mode to scatter_dataset as well as scatter_index (#7327)
  • Add chainer.dataset.tabular.from_data (#7361)
  • Add linalg.svd, linalg.pinv to ChainerX (#7411, thanks @IvanYashchuk!)
  • Add TabularDataset.convert/with_converter (#7428)
  • Add linalg.solve, linalg.inv to ChainerX (#7474, thanks @IvanYashchuk!)
  • Add base Converter class (#7489)
  • Add chainerx.sigmoid_cross_entropy (#7524, thanks @aksub99!)
  • Add chainerx.cumsum (#7558, thanks @aksub99!)
  • Add chainerx.nansum (#7719, thanks @aksub99!)
  • Add chainerx.nanargmax and chainerx.nanargmin (#7755, thanks @aksub99!)
  • LSTM, GRU and RNN implementation for ChainerX (#7764, thanks @dido1998!)
  • Add tri* routines to ChainerX (#7791, thanks @IvanYashchuk!)
  • Add finalize method to ChainerMN CommunicatorBase class (#7814)
  • Add numerical_grad_dtype to FunctionTestCase and LinkTestCase (#7817)
  • Support callable in tabular.from_data (#7847)
  • Add chainerx.count_nonzero (#7852, thanks @aksub99!)
  • Implement hooks for memory pool in ChainerX (#7898)
  • Add chainerx.flatten (#7901, thanks @aksub99!)
  • Add chainerx.ravel (#7904, thanks @aksub99!)

Enhancements

  • Use numbers for input check in roi_{average|max}_{pooling|align}_2d.py (#5636, thanks @knorth55!)
  • Warn Link.to_gpu unless compatible with to_device (#5762)
  • Change F.dropout to use cuDNN by default (#7185, thanks @crcrpar!)
  • Fix Adam FP16 overflow on GPU kernels (#7694)
  • Improve chainerx import check (#7738)
  • Make F.average as accurate as backend (#7758)
  • Improve NCCL availability error in PureNcclCommunicator (#7793)
  • Fix type_check error message on evaluating bool expression (#7795)
  • Fix module in msg of type_check (#7803)
  • Use scalar array in chx.leaky_relu/elu (#7816)
  • Allow None inputs to gradient check and generating None gradients in FunctionTestCase (#7831)
  • Display ChainerX availability in print_runtime_info (#7833)
  • Add support for input with different dtypes for 'linalg.solve' in ChainerX (#7840, thanks @IvanYashchuk!)
  • Fix F.clip for NumPy 1.17 (#7843)
  • Include rtol * abs(b) in allclose output (#7848)
  • Fix SLSTM for omitted upstream gradients (#7891)
  • Fix LSTM for omitted upstream gradients (#7896)
  • Insert missing spaces between concatenated string literals (#7930)
  • Fix a typo in a kernel name (#7962)

Bug Fixes

  • Fix TypeError in max_pooling_2d (#6835, thanks @ishanrai05!)
  • Fix multi-device loss scaling (#7594)
  • Avoid unload module call in PureNcclCommunicator (#7600)
  • Fix decorrelated batch normalization when groups ≠ 1 (#7707)
  • Fix create_mnbn_model() bug (#7718)
  • Fix optimizer_hooks.GradientHardClipping for scalar array (#7760)
  • Fix "zero division" in resize image (#7769, thanks @meokz!)
  • Fix ChainerX non native deserialization (#7830)
  • Fix backends.copyto from chainerx to non-chainerx (#7835)
  • Fix backward of split_axis for intel64 when grad_ouputs contains None (#7836)
  • Support for CUDA async in batched copy (#7877)
  • Add scatter interface to CommunicatorBase (#7888)
  • Add DeprecationWarning to initializer of BuildingBlock (#7909)
  • Fix in-place update of arrays in Link.serialize and optimizers.Adam (#7918)
  • Fix precision in F.max_pooling_2d (#7922)

Code Fixes

  • Avoid using _fallback_workarounds in SpectralNormalization (#7539)
  • Create links.rnn and functions.rnn (#7725)
  • Add batched_copy to all Communicators (#7761)
  • Remove unused lambda capture of axis (#7799)
  • Remove unused argument from decorrelated batch norm (#7828)
  • Fix copies for linalg.svd python bindings layer in ChainerX (#7866, thanks @IvanYashchuk!)
  • Replace n_layer with n_layers for consistency (#7871)
  • Rename a variable in CUDA SVD kernel (#7921, thanks @IvanYashchuk!)
  • Refactor pooling_nd functions (#7938)
  • Merge implementation of F.max_pooling_2d into F.max_pooling_nd (#7939)
  • Fix typo in comment: unique -> deterministic (#7775)

Documentation

  • Fix static_graph docs code examples (#7875)
  • Add 1.17 to supported NumPy versions (#7883)
  • Add scatter to doc (#7897)
  • Update stable version in README (#7948)

Installation

  • Relax typing version requirement in Python 3 (#7811)
  • Remove mypy from requirements (#7812)
  • Add OpenMP option for cuSOLVER (#7839)
  • Fix Windows build of ChainerX (#7967, thanks @cloudhan!)

Examples

Tests

  • Add test to ensure no mutable default arguments (#4413)
  • Simplify F.max_pooling_2d test (#6836, thanks @ishanrai05!)
  • Simplify F.lstm test (#7808, thanks @dido1998!)
  • Simplify F.slstm test (#7805, thanks @dido1998!)
  • Simplify F.n_step_rnn test (#7804, thanks @dido1998!)
  • Simplify F.n_step_lstm test (#7807, thanks @dido1998!)
  • Simplify F.n_step_gru test (#7806, thanks @dido1998!)
  • Simplify F.embed_id test (#7903, thanks @dido1998!)
  • Add ChainerCV's tests to pfnCI (#7060)
  • Add mixed16 tests to multi-node chain list (#7630)
  • Add mixed16 tests to collective functions (#7633)
  • Add mixed16 tests to point_to_point communications (#7637)
  • Add mixed16 tests to pseudo_connect (#7638)
  • Skip flaky TestConv*TensorCore (#7710)
  • Fix test of chx.reshape (#7762)
  • Revert tentative workaround related to OpenSSL (#7790)
  • Switch current directory in Jenkins tests (#7834)
  • Fix flaky TestHuberLoss (#7837)
  • Configure tolerances of F.average_pooling_2d test (#7841)
  • Fix F.clipped_relu test for NumPy 1.17 (#7842)
  • Add test_accuracy.py to the list of slow test files (#7851)
  • Fix BatchNorm flaky of ChainerX (#7857)
  • Refactor convolution functions tests (#7863)
  • Relax tolerances in convolution function tests when using old cuDNN (#7864)
  • Fix test_TrilTriu (#7865)
  • Fix chainerx.logsumexp test tolerance (#7867)
  • Relax tolerances in convolution link tests when using old cuDNN (#7868)
  • Relax float16 tolerances in ChainerX binary math tests (#7874)
  • F.tree_lstm test for ChainerX (#7881, thanks @dido1998!)
  • Avoid ndarray.data access and fix wrong test (#7890)
  • Sample stable inputs in tests of group normalization (#7894)
  • Avoid unstable inputs in tests of decorrelated batch normalization (#7900)
  • Relax fp16 tolerance in TrueDiv test (#7917)
  • Avoid testing F.cast from negative floating-point to unsigned (#7920)
  • Fix tolerance in L.CRF1d test (#7926)
  • Refactor DecorrelatedBatchNormalizationTest and add stable input (#7932)
  • Relax tolerances in old cuDNN convolution tests (#7942)
  • Fix flaky chainerx.power test (#7950)
  • Increase CPU memory for test instance in PFN CI (#7951)
  • Relax fp16 tolerances in TestContrastive (#7953)
  • Relax float16 tolerances in F.batch_inv test (#7971)

Others

  • Drop support for Python 2.7 (#7826)
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