Chainer v7.0.0b2 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 v7.0.0b2. See here for the complete list of solved issues and merged PRs.
ChainerX has several new backproppable ops such as ELU and softplus activation functions and loss functions including absolute error, squared error, Huber loss and Gaussian KL divergence. ChainerX is also supported in all OptimizerHooks when used through Chainer. TabularDataset has also been improved with new features.
Variable.grad getter now raises an error when it is called before calling cleargrad, zerograd, or setting the gradient directly. (#7146)BatchRenormalization (usage of epsilon) is fixed. It affects the inference behavior. (#7202)HierarchicalCommunicator, SingleNodeCommunicator and TwoDimensionalCommunicator and are no longer necessary as NCCL now supports inter-node communication. (#7697)WeightStandardization link hook (#6678, thanks @hitsgub!)chainerx.dsplit (#7031, thanks @ishanrai05!)chainerx.left_shift and chainerx.right_shift (#7339, thanks @sky58!)chainerx.elu (#7439, thanks @aksub99!)TabularDataset (#7493)TabluarDataset.__iter__ (#7601)Variable.mean (#7670)chainerx.softplus (#7679, thanks @aksub99!)top_data as -np.inf and argmax_data as -1 in F.roi_max_pooling_2d (#6237, thanks @knorth55!)cleargrad (#7146)chainerx.grad from chainer.grad (#7464)ImportError (#7518)device argument a keyword only argument. (#7537, thanks @kshitij12345!)Array::At and __getitem__ (#7561)chainerx.ndarray._is_chained (#7565)squared_difference and fix docs (#7582)allreduce_grad() and functions related with it (#7604)IndexError if the index __getitem__ takes is out of bounds (#7614)six.integer_types for axis check in F.concat (#7632, thanks @knorth55!)optimizer_hooks.GradientClipping for ChainerX (#7641)optimizer_hooks.GradientHardClipping for ChainerX (#7656, thanks @kshitij12345!)IntervalTrigger.__str__ (#7664, thanks @ktns!)GradientLARS optimizer hook working with ChainerX (#7669)absl::Span and related helpers instead of gsl::span (#7671)six.integer_types for axis checks (#7713)CHAINERX_BUILD_CUDA is set (#7752)None array in FunctionNode NaN check (#6283)CupyMemoryProfiler (#7003)running_var of F.batch_renormalization (#7202)MultiprocessIterator (#7486)initializers.Identity for ideep backend (#7548)chainermn.links.create_mnbn_model (#7603)PickleDataset crash when using multiprocessing (#7625, thanks @zaltoprofen!)AMSGrad with intel64 backend (#7661)chainer.grad for multiple devices (#7692)chainerx::Flip (#7727)Parameter.dtype for uninitialized parameter (#7735)UpdateRule.use_fp32_update for uninitialized parameter (#7736)backend.get_array_module not cuda.get_array_module (#7514, thanks @crcrpar!)squared_difference alias of squared_error (#7547)Optimizer and GradientMethod (#7585)chainerx.clipped_relu in F.clipped_relu (#7588)CMakeList.txt (#7647)Links (#6512)CHAINERX_CUDNN_USE_CUPY (#7574)ResNet prepare method (#7577)BackwardContext comment (#7595, thanks @crcrpar!)expand_dims.py (#7602)FunctionNode docs. (#7622)chainer/functions/math/average.py (#7653, thanks @ktns!)F.squeeze documentation (#7682)examples/vae/train_vae.py (#7578, thanks @m4saka!)F.polygamma test (#6970, thanks @ishanrai05!)F.cast test (#7034)y_shape not used in tests (#7610)optimizer_hooks.Lasso for ChainerX (#7657, thanks @kshitij12345!)GroupNormalization tests (#7684)optimizer_hooks.GradientNoise for ChainerX (#7709, thanks @kshitij12345!)protobuf (#7715)optimizer_hooks.WeightDecay for ChainerX (#7716, thanks @kshitij12345!)atol/rtol of chainerx.erf float16 test (#7721)TestHuberLoss (#7723)Contrastive.backward (#7745)TestContrastive (#7747)