helper.py 文件源码

def conv_layer(x, filter_shape, stride, sigmoid, name):
    filter_width, num_inputs, num_outputs = filter_shape
    W = weight_variable(filter_shape, 0.1, name + "/W")
    b = bias_variable([num_outputs], 0.0, name + "/b")
    z = tf.nn.conv1d(x, W, stride = stride, padding = 'SAME') + b
    a = tf.nn.sigmoid(z) if sigmoid else tf.nn.tanh(z)
    return a