pretrained_word_embedding_TF_nn.py 文件源码

def conv1d_layer(inp, filter_shape):
    """This is a 1d conv, so filter_shape = [dim, input_channels, out_channels]"""
    W = tf.Variable(tf.truncated_normal(filter_shape, stddev=0.01))
    b = tf.Variable(tf.random_normal(shape=[filter_shape[2]]))
    # or you could initialize it as constant
    # b = tf.Variable(tf.constant(0.1, shape=[filter_shape[3]]))
    x = tf.nn.conv1d(inp,W,stride=1,padding="VALID")
    x = tf.nn.bias_add(x, b)
    x = tf.nn.relu(x)
    return x