From 04abcab823569b0a20904241fd92d9b2f09d50be Mon Sep 17 00:00:00 2001 From: mrcangye Date: Sat, 8 Oct 2022 14:35:57 +0800 Subject: [PATCH] fix some doc bug test=document_fix (#45488) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix some doc bug test=document_fix * fix some docs issues, test=document_fix * beta -> \beta in softplus * threshold -> \varepsilon in softplus * parameter name * delta -> \delta in smooth_l1_loss * fix some docs test=document_fix * fix docs test=document_fix * fix docs && 增加空行 test=document_fix * Update python/paddle/nn/functional/activation.py, test=document_fix * Update python/paddle/nn/layer/activation.py, test=document_fix Co-authored-by: SigureMo --- paddle/fluid/operators/activation_op.cc | 4 +- python/paddle/nn/functional/activation.py | 24 +++++------ python/paddle/nn/functional/loss.py | 23 +++++------ python/paddle/nn/layer/activation.py | 50 +++++++++++------------ python/paddle/nn/layer/loss.py | 25 +++++------- 5 files changed, 59 insertions(+), 67 deletions(-) diff --git a/paddle/fluid/operators/activation_op.cc b/paddle/fluid/operators/activation_op.cc index f921ad844b3..3ff75014e60 100644 --- a/paddle/fluid/operators/activation_op.cc +++ b/paddle/fluid/operators/activation_op.cc @@ -170,9 +170,9 @@ class ActivationOpGrad : public framework::OperatorWithKernel { }; UNUSED constexpr char SigmoidDoc[] = R"DOC( -Sigmoid Activation Operator +Sigmoid Activation -$$out = \\frac{1}{1 + e^{-x}}$$ +$$out = \frac{1}{1 + e^{-x}}$$ )DOC"; diff --git a/python/paddle/nn/functional/activation.py b/python/paddle/nn/functional/activation.py index b74471c9a18..9a32853542b 100644 --- a/python/paddle/nn/functional/activation.py +++ b/python/paddle/nn/functional/activation.py @@ -949,12 +949,14 @@ def silu(x, name=None): silu(x) = \frac{x}{1 + e^{-x}} + Where :math:`x` is the input Tensor. + Parameters: x (Tensor): The input Tensor with data type float32, float64. name (str, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None. Returns: - A Tensor with the same data type and shape as ``x`` . + A Tensor with the same data type and shape as :attr:`x`. Examples: .. code-block:: python @@ -1072,15 +1074,13 @@ def softmax(x, axis=-1, dtype=None, name=None): import paddle import paddle.nn.functional as F - import numpy as np - x = np.array([[[2.0, 3.0, 4.0, 5.0], + x = paddle.to_tensor([[[2.0, 3.0, 4.0, 5.0], [3.0, 4.0, 5.0, 6.0], [7.0, 8.0, 8.0, 9.0]], [[1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0], - [6.0, 7.0, 8.0, 9.0]]], 'float32') - x = paddle.to_tensor(x) + [6.0, 7.0, 8.0, 9.0]]],dtype='float32') out1 = F.softmax(x) out2 = F.softmax(x, dtype='float64') # out1's data type is float32; out2's data type is float64 @@ -1167,14 +1167,15 @@ def softplus(x, beta=1, threshold=20, name=None): softplus activation .. math:: - - softplus(x) = \frac{1}{beta} * \log(1 + e^{beta * x}) \\ - \text{For numerical stability, the implementation reverts to the linear function when: beta * x > threshold.} + softplus(x)=\begin{cases} + \frac{1}{\beta} * \log(1 + e^{\beta * x}),&x\leqslant\frac{\varepsilon}{\beta};\\ + x,&x>\frac{\varepsilon}{\beta}. + \end{cases} Parameters: x (Tensor): The input Tensor with data type float32, float64. - beta (float, optional): The value of beta for softplus. Default is 1 - threshold (float, optional): The value of threshold for softplus. Default is 20 + beta (float, optional): The value of :math:`\beta` for softplus. Default is 1 + threshold (float, optional): The value of :math:`\varepsilon` for softplus. Default is 20 name (str, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None. Returns: @@ -1185,9 +1186,8 @@ def softplus(x, beta=1, threshold=20, name=None): import paddle import paddle.nn.functional as F - import numpy as np - x = paddle.to_tensor(np.array([-0.4, -0.2, 0.1, 0.3])) + x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3], dtype='float32') out = F.softplus(x) # [0.513015, 0.598139, 0.744397, 0.854355] """ diff --git a/python/paddle/nn/functional/loss.py b/python/paddle/nn/functional/loss.py index bc12bba94cc..b084b7db22a 100755 --- a/python/paddle/nn/functional/loss.py +++ b/python/paddle/nn/functional/loss.py @@ -993,17 +993,17 @@ def smooth_l1_loss(input, label, reduction='mean', delta=1.0, name=None): .. math:: - loss(x,y) = \frac{1}{n}\sum_{i}z_i + loss(x,y) = \frac{1}{n}\sum_{i}z_i - where z_i is given by: + where :math:`z_i` is given by: .. math:: \mathop{z_i} = \left\{\begin{array}{rcl} - 0.5(x_i - y_i)^2 & & {if |x_i - y_i| < delta} \\ - delta * |x_i - y_i| - 0.5 * delta^2 & & {otherwise} - \end{array} \right. + 0.5(x_i - y_i)^2 & & {if |x_i - y_i| < \delta} \\ + \delta * |x_i - y_i| - 0.5 * \delta^2 & & {otherwise} + \end{array} \right. Parameters: input (Tensor): Input tensor, the data type is float32 or float64. Shape is @@ -1017,12 +1017,11 @@ def smooth_l1_loss(input, label, reduction='mean', delta=1.0, name=None): If :attr:`reduction` is ``'sum'``, the reduced sum loss is returned. If :attr:`reduction` is ``'none'``, the unreduced loss is returned. Default is ``'mean'``. - delta (float, optional): Specifies the hyperparameter delta to be used. + delta (float, optional): Specifies the hyperparameter :math:`\delta` to be used. The value determines how large the errors need to be to use L1. Errors smaller than delta are minimized with L2. Parameter is ignored for negative/zero values. Default = 1.0 - name (str, optional): Name for the operation (optional, default is - None). For more information, please refer to :ref:`api_guide_Name`. + name (str, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None. Returns: Tensor, The tensor variable storing the smooth_l1_loss of input and label. @@ -1031,14 +1030,12 @@ def smooth_l1_loss(input, label, reduction='mean', delta=1.0, name=None): .. code-block:: python import paddle - import numpy as np - input_data = np.random.rand(3,3).astype("float32") - label_data = np.random.rand(3,3).astype("float32") - input = paddle.to_tensor(input_data) - label = paddle.to_tensor(label_data) + input = paddle.rand([3, 3]).astype('float32') + label = paddle.rand([3, 3]).astype('float32') output = paddle.nn.functional.smooth_l1_loss(input, label) print(output) + # [0.068004] """ check_variable_and_dtype(input, 'input', ['float32', 'float64'], 'smooth_l1_loss') diff --git a/python/paddle/nn/layer/activation.py b/python/paddle/nn/layer/activation.py index 0dbab2f64e4..e397f40c823 100644 --- a/python/paddle/nn/layer/activation.py +++ b/python/paddle/nn/layer/activation.py @@ -706,15 +706,15 @@ class LeakyReLU(Layer): class Sigmoid(Layer): - """ + r""" this interface is used to construct a callable object of the ``Sigmoid`` class. This layer calcluate the `sigmoid` of input x. .. math:: - Sigmoid(x) = \\frac{1}{1 + e^{-x}} + sigmoid(x) = \frac{1}{1 + e^{-x}} Parameters: - name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. + name (str, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None. Shape: x: N-D tensor, available dtype is float16, float32, float64. @@ -726,11 +726,11 @@ class Sigmoid(Layer): .. code-block:: python - import paddle + import paddle - m = paddle.nn.Sigmoid() - x = paddle.to_tensor([1.0, 2.0, 3.0, 4.0]) - out = m(x) # [0.7310586, 0.880797, 0.95257413, 0.98201376] + m = paddle.nn.Sigmoid() + x = paddle.to_tensor([1.0, 2.0, 3.0, 4.0]) + out = m(x) # [0.7310586, 0.880797, 0.95257413, 0.98201376] """ def __init__(self, name=None): @@ -801,15 +801,15 @@ class Softplus(Layer): Softplus Activation .. math:: - - Softplus(x) = \frac{1}{beta} * \log(1 + e^{beta * x}) \\ - \text{For numerical stability, the implementation reverts to the linear function when: beta * x > threshold.} + softplus(x)=\begin{cases} + \frac{1}{\beta} * \log(1 + e^{\beta * x}),&x\leqslant\frac{\varepsilon}{\beta};\\ + x,&x>\frac{\varepsilon}{\beta}. + \end{cases} Parameters: - beta (float, optional): The value of beta for Softplus. Default is 1 - threshold (float, optional): The value of threshold for Softplus. Default is 20 - name (str, optional): Name for the operation (optional, default is None). - For more information, please refer to :ref:`api_guide_Name`. + beta (float, optional): The value of :math:`\beta` for Softplus. Default is 1 + threshold (float, optional): The value of :math:`\varepsilon` for Softplus. Default is 20 + name (str, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None. Shape: - input: Tensor with any shape. @@ -819,9 +819,8 @@ class Softplus(Layer): .. code-block:: python import paddle - import numpy as np - x = paddle.to_tensor(np.array([-0.4, -0.2, 0.1, 0.3])) + x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3], dtype='float32') m = paddle.nn.Softplus() out = m(x) # [0.513015, 0.598139, 0.744397, 0.854355] """ @@ -1101,16 +1100,17 @@ class ThresholdedReLU(Layer): class Silu(Layer): - """ - Silu Activation. + r""" + Silu Activation + .. math:: - Silu(x) = \frac{x}{1 + e^{-x}} + silu(x) = \frac{x}{1 + \mathrm{e}^{-x}} + + Where :math:`x` is the input Tensor. Parameters: - x (Tensor): The input Tensor with data type float32, or float64. - name (str, optional): Name for the operation (optional, default is None). - For more information, please refer to :ref:`api_guide_Name`. + name (str, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None. Shape: - input: Tensor with any shape. @@ -1271,15 +1271,13 @@ class Softmax(Layer): .. code-block:: python import paddle - import numpy as np - x = np.array([[[2.0, 3.0, 4.0, 5.0], + x = paddle.to_tensor([[[2.0, 3.0, 4.0, 5.0], [3.0, 4.0, 5.0, 6.0], [7.0, 8.0, 8.0, 9.0]], [[1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0], - [6.0, 7.0, 8.0, 9.0]]], 'float32') - x = paddle.to_tensor(x) + [6.0, 7.0, 8.0, 9.0]]], dtype='float32') m = paddle.nn.Softmax() out = m(x) # [[[0.0320586 , 0.08714432, 0.23688282, 0.64391426], diff --git a/python/paddle/nn/layer/loss.py b/python/paddle/nn/layer/loss.py index 711174c8a8c..8c80a82265f 100644 --- a/python/paddle/nn/layer/loss.py +++ b/python/paddle/nn/layer/loss.py @@ -1138,16 +1138,16 @@ class SmoothL1Loss(Layer): .. math:: - loss(x,y) = \frac{1}{n}\sum_{i}z_i + loss(x, y) = \frac{1}{n}\sum_{i}z_i - where z_i is given by: + where :math:`z_i` is given by: .. math:: \mathop{z_i} = \left\{\begin{array}{rcl} - 0.5(x_i - y_i)^2 & & {if |x_i - y_i| < delta} \\ - delta * |x_i - y_i| - 0.5 * delta^2 & & {otherwise} - \end{array} \right. + 0.5(x_i - y_i)^2 & & {if |x_i - y_i| < \delta} \\ + \delta * |x_i - y_i| - 0.5 * \delta^2 & & {otherwise} + \end{array} \right. Parameters: reduction (str, optional): Indicate how to average the loss by batch_size, @@ -1156,12 +1156,11 @@ class SmoothL1Loss(Layer): If :attr:`reduction` is ``'sum'``, the reduced sum loss is returned. If :attr:`reduction` is ``'none'``, the unreduced loss is returned. Default is ``'mean'``. - delta (float, optional): Specifies the hyperparameter delta to be used. + delta (float, optional): Specifies the hyperparameter :math:`\delta` to be used. The value determines how large the errors need to be to use L1. Errors smaller than delta are minimized with L2. Parameter is ignored for - negative/zero values. Default = 1.0 - name (str, optional): Name for the operation (optional, default is - None). For more information, please refer to :ref:`api_guide_Name`. + negative/zero values. Default value is :math:`1.0`. + name (str, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None. Call Parameters: @@ -1179,14 +1178,12 @@ class SmoothL1Loss(Layer): .. code-block:: python import paddle - import numpy as np - input_data = np.random.rand(3,3).astype("float32") - label_data = np.random.rand(3,3).astype("float32") - input = paddle.to_tensor(input_data) - label = paddle.to_tensor(label_data) + input = paddle.rand([3, 3]).astype("float32") + label = paddle.rand([3, 3]).astype("float32") loss = paddle.nn.SmoothL1Loss() output = loss(input, label) print(output) + # [0.049606] """ def __init__(self, reduction='mean', delta=1.0, name=None): -- GitLab