Function fc_layer

3_Neural_Network/code/ops.py:32–48

Create a fully-connected layer :param x: input from previous layer :param num_units: number of hidden units in the fully-connected layer :param name: layer name :param use_relu: boolean to add ReLU non-linearity (or not) :return: The output array

(x, num_units, name, use_relu=True)

def fc_layer(x, num_units, name, use_relu=True):
    """
    Create a fully-connected layer
    :param x: input from previous layer
    :param num_units: number of hidden units in the fully-connected layer
    :param name: layer name
    :param use_relu: boolean to add ReLU non-linearity (or not)
    :return: The output array
    """
    in_dim = x.get_shape()[1]
    W = weight_variable(name, shape=[in_dim, num_units])
    b = bias_variable(name, [num_units])
    layer = tf.matmul(x, W)
    layer += b
    if use_relu:
        layer = tf.nn.relu(layer)
    return layer