8df6b252447e160c2433f2f5e0f5343f7451876b,models/utils.py,,conv_layer,#,174

Before Change

    weight_decay = tf.multiply(tf.nn.l2_loss(W), wd, name="weight_loss")
    tf.add_to_collection(LOSSES_COLLECTION, weight_decay)

    result = tf.nn.bias_add(
        tf.nn.conv2d(input_x, W, [1, stride, stride, 1], padding), b)

    // apply nonlinearity
    out = activation(result)

After Change

    Rerturns the conv2d op

    W = weight("W", shape, wd=wd)
    result = tf.nn.conv2d(input_x, W, [1, stride, stride, 1], padding)
    if bias_term:
        b = bias("b", [shape[3]])
        result = tf.nn.bias_add(result, b)

Instances