内积层和全连接层是一样的

http://caffe.berkeleyvision.org/tutorial/layers.html#data-layers

The InnerProduct layer (also usually referred to as the fully connected layer) treats the input as a simple vector and produces an output in the form of a single vector (with the blob’s height and width set to 1).

就是定义输出的个数，然后就全部连接所有的滤波器的所有通道（特征子图）的所有元素。

使用方法：（可以看出它的计算方法）

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Parameters (InnerProductParameter inner_product_param)
Required
num_output (c_o): the number of filters
Strongly recommended
weight_filler [default type: 'constant' value: 0]

Optional
bias_filler [default type: 'constant' value: 0]
bias_term [default true]: specifies whether to learn and apply a set of additive biases to the filter outputs

Input
n * c_i * h_i * w_i

Output
n * c_o * 1 * 1