logsigmoid -> log_sigmoid (#2602)

doc/fluid/api/nn.rst

@@ -88,8 +88,8 @@ paddle.nn
     nn/Linear.rst
     nn/linear_lr_warmup.rst
     nn/log_loss.rst
+    nn/log_sigmoid.rst
     nn/log_softmax.rst
-    nn/logsigmoid.rst
     nn/loss.rst
     nn/lrn.rst
     nn/margin_rank_loss.rst

doc/fluid/api/nn/logsigmoid.rst → doc/fluid/api/nn/log_sigmoid.rst

-.. _api_nn_logsigmoid:
+.. _api_nn_log_sigmoid:
 
-logsigmoid
+log_sigmoid
 -------------------------------
 
-..  autofunction:: paddle.nn.functional.logsigmoid
+..  autofunction:: paddle.nn.functional.log_sigmoid
     :noindex:
 
 

doc/fluid/api_cn/layers_cn/logsigmoid_cn.rst

@@ -5,12 +5,6 @@ logsigmoid
 
 .. py:function:: paddle.fluid.layers.logsigmoid(x, name=None)
 
-:alias_main: paddle.nn.functional.logsigmoid
-:alias: paddle.nn.functional.logsigmoid,paddle.nn.functional.activation.logsigmoid
-:old_api: paddle.fluid.layers.logsigmoid
-
-
-
 Logsigmoid激活函数
 
 

doc/fluid/api_cn/nn_cn.rst

@@ -109,8 +109,8 @@ paddle.nn
     nn_cn/leaky_relu_cn.rst
     nn_cn/Linear_cn.rst
     nn_cn/linear_lr_warmup_cn.rst
-    nn_cn/logsigmoid_cn.rst
     nn_cn/log_loss_cn.rst
+    nn_cn/log_sigmoid_cn.rst
     nn_cn/log_softmax_cn.rst
     nn_cn/lrn_cn.rst
     nn_cn/margin_ranking_loss_cn.rst

doc/fluid/api_cn/nn_cn/logsigmoid_cn.rst → doc/fluid/api_cn/nn_cn/log_sigmoid_cn.rst

-.. _cn_api_nn_cn_logsigmoid:
+.. _cn_api_nn_cn_log_sigmoid:
 
-logsigmoid
+log_sigmoid
 -------------------------------
 
-.. py:function:: paddle.nn.functional.logsigmoid(x, name=None)
+.. py:function:: paddle.nn.functional.log_sigmoid(x, name=None)
 
-logsigmoid激活层。计算公式如下：
+log_sigmoid激活层。计算公式如下：
 
 .. math::
 
-    logsigmoid(x) = \log \frac{1}{1 + e^{-x}}
+    log\_sigmoid(x) = \log \frac{1}{1 + e^{-x}}
 
 其中，:math:`x` 为输入的 Tensor
 
@@ -29,9 +29,8 @@ logsigmoid激活层。计算公式如下：
 
     import paddle
     import paddle.nn.functional as F
-    import numpy as np
 
     paddle.disable_static()
 
-    x = paddle.to_tensor(np.array([1.0, 2.0, 3.0, 4.0]))
-    out = F.logsigmoid(x) # [-0.313262 -0.126928 -0.0485874 -0.0181499]
+    x = paddle.to_tensor([1.0, 2.0, 3.0, 4.0])
+    out = F.log_sigmoid(x) # [-0.313262 -0.126928 -0.0485874 -0.0181499]

doc/paddle/api/alias_api_mapping

@@ -5,7 +5,7 @@ paddle.nn.functional.loss.l1_loss	paddle.nn.functional.l1_loss
 paddle.nn.functional.loss.margin_ranking_loss	paddle.nn.functional.margin_ranking_loss
 paddle.nn.layer.pooling.AdaptiveAvgPool3d	paddle.nn.AdaptiveAvgPool3d,paddle.nn.layer.AdaptiveAvgPool3d
 paddle.nn.functional.common.alpha_dropout	paddle.nn.functional.alpha_dropout
-paddle.nn.functional.activation.logsigmoid	paddle.nn.functional.logsigmoid
+paddle.nn.functional.activation.log_sigmoid	paddle.nn.functional.log_sigmoid
 paddle.fluid.executor.Executor	paddle.static.Executor
 paddle.nn.functional.pooling.avg_pool2d	paddle.nn.functional.avg_pool2d
 paddle.fluid.dygraph.checkpoint.load_dygraph	paddle.load,paddle.framework.load

doc/paddle/api/api_label

@@ -398,7 +398,7 @@ Decoder	.. _api_paddle_fluid_layers_Decoder:
 array_read	.. _api_paddle_fluid_layers_array_read:
 floor_divide	.. _api_paddle_tensor_math_floor_divide:
 floor_mod	.. _api_paddle_tensor_math_floor_mod:
-logsigmoid	.. _api_paddle_nn_functional_logsigmoid:
+log_sigmoid	.. _api_paddle_nn_functional_log_sigmoid:
 generate_mask_labels	.. _api_paddle_fluid_layers_generate_mask_labels:
 square	.. _api_paddle_fluid_layers_square:
 reset_profiler	.. _api_paddle_fluid_profiler_reset_profiler:

doc/paddle/api/paddle/nn/functional/activation/logsigmoid_cn.rst → doc/paddle/api/paddle/nn/functional/activation/log_sigmoid_cn.rst

-.. _cn_api_nn_cn_logsigmoid:
+.. _cn_api_nn_cn_log_sigmoid:
 
-logsigmoid
+log_sigmoid
 -------------------------------
 
-.. py:function:: paddle.nn.functional.logsigmoid(x, name=None)
+.. py:function:: paddle.nn.functional.log_sigmoid(x, name=None)
 
-logsigmoid激活层。计算公式如下：
+log_sigmoid激活层。计算公式如下：
 
 .. math::
 
-    logsigmoid(x) = \log \frac{1}{1 + e^{-x}}
+    log\_sigmoid(x) = \log \frac{1}{1 + e^{-x}}
 
 其中，:math:`x` 为输入的 Tensor
 
@@ -29,9 +29,8 @@ logsigmoid激活层。计算公式如下：
 
     import paddle
     import paddle.nn.functional as F
-    import numpy as np
 
     paddle.disable_static()
 
-    x = paddle.to_tensor(np.array([1.0, 2.0, 3.0, 4.0]))
-    out = F.logsigmoid(x) # [-0.313262 -0.126928 -0.0485874 -0.0181499]
+    x = paddle.to_tensor([1.0, 2.0, 3.0, 4.0])
+    out = F.log_sigmoid(x) # [-0.313262 -0.126928 -0.0485874 -0.0181499]