From e56fd4388ef6e73e5c48d705f05c44794b3fffd5 Mon Sep 17 00:00:00 2001 From: dengkaipeng Date: Tue, 5 Mar 2019 13:48:02 +0800 Subject: [PATCH] fix statement. test=develop --- paddle/fluid/API.spec | 2 +- paddle/fluid/operators/kldiv_loss_op.cc | 24 +++++++++++++----------- 2 files changed, 14 insertions(+), 12 deletions(-) diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index 6b47666aa..7f7542b03 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -220,7 +220,7 @@ paddle.fluid.layers.py_func (ArgSpec(args=['func', 'x', 'out', 'backward_func', paddle.fluid.layers.psroi_pool (ArgSpec(args=['input', 'rois', 'output_channels', 'spatial_scale', 'pooled_height', 'pooled_width', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '1546136806fef5c08f6918544bd9151d')) paddle.fluid.layers.teacher_student_sigmoid_loss (ArgSpec(args=['input', 'label', 'soft_max_up_bound', 'soft_max_lower_bound'], varargs=None, keywords=None, defaults=(15.0, -15.0)), ('document', '2f6ff96864054a31aa4bb659c6722c99')) paddle.fluid.layers.huber_loss (ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None), ('document', '431a4301c35032166ec029f7432c80a7')) -paddle.fluid.layers.kldiv_loss (ArgSpec(args=['x', 'target', 'reduction', 'name'], varargs=None, keywords=None, defaults=('mean', None)), ('document', '74112f07e2329448f9f583cabd9d681e')) +paddle.fluid.layers.kldiv_loss (ArgSpec(args=['x', 'target', 'reduction', 'name'], varargs=None, keywords=None, defaults=('mean', None)), ('document', '776d536cac47c89073abc7ee524d5aec')) paddle.fluid.layers.tree_conv (ArgSpec(args=['nodes_vector', 'edge_set', 'output_size', 'num_filters', 'max_depth', 'act', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1, 2, 'tanh', None, None, None)), ('document', '34ea12ac9f10a65dccbc50100d12e607')) paddle.fluid.layers.data (ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True)), ('document', '33bbd42027d872b3818b3d64ec52e139')) paddle.fluid.layers.open_files (ArgSpec(args=['filenames', 'shapes', 'lod_levels', 'dtypes', 'thread_num', 'buffer_size', 'pass_num', 'is_test'], varargs=None, keywords=None, defaults=(None, None, 1, None)), ('document', 'b1ae2e1cc0750e58726374061ea90ecc')) diff --git a/paddle/fluid/operators/kldiv_loss_op.cc b/paddle/fluid/operators/kldiv_loss_op.cc index c120d7745..a43f22c04 100644 --- a/paddle/fluid/operators/kldiv_loss_op.cc +++ b/paddle/fluid/operators/kldiv_loss_op.cc @@ -65,11 +65,11 @@ class KLDivLossOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("X", - "The input tensor of KL divergence loss operator, " - "This is a tensor with shape of [N, *], where N is the" + "The input tensor of KL divergence loss operator. " + "This is a tensor with shape of [N, *], where N is the " "batch size, * means any number of additional dimensions."); AddInput("Target", - "The tensor of KL divergence loss operator, " + "The tensor of KL divergence loss operator. " "This is a tensor with shape of Input(X)."); AddOutput( "Loss", @@ -82,7 +82,7 @@ class KLDivLossOpMaker : public framework::OpProtoAndCheckerMaker { "The reduction type to apply to the output, available types " "are 'none' | 'batchmean' | 'mean' | 'sum', 'none' for no " "reduction, 'batchmean' for the sum of output divided by " - "batch size, 'mean' for the average valud of all output, " + "batch size, 'mean' for the average value of all output, " "'sum' for the sum of the output.") .SetDefault("mean"); @@ -90,21 +90,23 @@ class KLDivLossOpMaker : public framework::OpProtoAndCheckerMaker { This operator calculates the Kullback-Leibler divergence loss between Input(X) and Input(Target). - KL divergence loss calculates as follows: + KL divergence loss is calculated as follows: - $$l(x, y) = y * (\log y - x)$$ + $$l(x, y) = y * (\log(y) - x)$$ + + While :math:`x` is Input(X) and :math:`y` is Input(Target). While :attr:`reduction` is :attr:`none`, output loss is in - same shape with Input(X), loss in each point is calculated - seperately and no reduction applied. + the same shape as Input(X), loss in each point is calculated + seperately and no reduction is applied. - While :attr:`reduction` is :attr:`mean`, output loss in in + While :attr:`reduction` is :attr:`mean`, output loss is in shape of [1] and loss value is the mean value of all losses. - While :attr:`reduction` is :attr:`sum`, output loss in in + While :attr:`reduction` is :attr:`sum`, output loss is in shape of [1] and loss value is the sum value of all losses. - While :attr:`reduction` is :attr:`batchmean`, output loss in + While :attr:`reduction` is :attr:`batchmean`, output loss is in shape of [1] and loss value is the sum value of all losses divided by batch size. -- GitLab