From 1d936f1dfaa884c830723d1eb4a77ef6c1171294 Mon Sep 17 00:00:00 2001 From: chengduoZH Date: Sat, 23 Dec 2017 17:01:30 +0800 Subject: [PATCH] refine --- python/paddle/v2/fluid/layers/nn.py | 31 +++++++++++++++++++---------- 1 file changed, 20 insertions(+), 11 deletions(-) diff --git a/python/paddle/v2/fluid/layers/nn.py b/python/paddle/v2/fluid/layers/nn.py index f49a958a0f..1240b2576f 100644 --- a/python/paddle/v2/fluid/layers/nn.py +++ b/python/paddle/v2/fluid/layers/nn.py @@ -489,34 +489,40 @@ def conv2d(input, of the feature, and W is the width of the feature. The details of convolution layer, please refer UFLDL's `convolution, `_ . - If bias_attr and activation type are provided, bias is added to the output of the convolution, + If bias attribution and activation type are provided, bias is added to the output of the convolution, and the corresponding activation function is applied to the final result. For each input :math:`X`, the equation is: + .. math:: - Out = \sigma (W\ast X + b) + Out = \sigma (W \\ast X + b) - In the above equation: + In the above equation: * :math:`X`: Input value, a tensor with NCHW format. * :math:`W`: Filter value, a tensor with MCHW format. - * :math:`b`: Bias, . - * :math:\sigma : Activation function. + * :math: \\ast : Convolution operation. + * :math:`b`: Bias value, a 2-D tensor with shape [M, 1]. + * :math: \\sigma : Activation function. * :math:`Out`: Output value, the shape of :math:`Out` and :math:`X` may be different. Example: - Input: + - Input: Input shape: $(N, C_{in}, H_{in}, W_{in})$ + Filter shape: $(C_{out}, C_{in}, H_f, W_f)$ - Output: + + - Output: Output shape: $(N, C_{out}, H_{out}, W_{out})$ Where - $$ - H_{out}= \\frac{(H_{in} + 2 * paddings[0] - (dilations[0] * (H_f - 1) + 1))}{strides[0]}+ 1 \\ + .. math:: + + H_{out}= \\frac{(H_{in} + 2 * paddings[0] - (dilations[0] * (H_f - 1) + 1))}{strides[0]}+ 1 + W_{out}= \\frac{(W_{in} + 2 * paddings[1] - (dilations[1] * (W_f - 1) + 1))}{strides[1]}+ 1 - $$ + All the input variables are passed in as local variables to the LayerHelper constructor. @@ -537,10 +543,13 @@ def conv2d(input, Variable: The tensor variable storing the convolution and \ non-linearity activation result. + Raises: + ValueError: If the shapes of input, filter_size, stride, padding and groups mismatch. + Examples: .. code-block:: python - data = fluid.layers.data(name='data', shape=[3,32, 32], dtype='float32') + data = fluid.layers.data(name='data', shape=[3, 32, 32], dtype='float32') conv2d = fluid.layers.conv2d(input=data, num_filters=2, filter_size=3, act="relu") """ -- GitLab