811d018ccb0cc49ce7c3b3b37849bff07c865761,tflearn/layers/core.py,,fully_connected,#,78

Before Change

    n_inputs = int(np.prod(input_shape[1:]))

    // Build variables and inference.
    with tf.name_scope(name) as scope:

        W_init = weights_init
        if isinstance(weights_init, str):
            W_init = initializations.get(weights_init)()
        W_regul = None
        if regularizer:
            W_regul = lambda x: losses.get(regularizer)(x, weight_decay)
        W = va.variable(scope + "W", shape=[n_inputs, n_units],
                        regularizer=W_regul, initializer=W_init,
                        trainable=trainable, restore=restore)
        tf.add_to_collection(tf.GraphKeys.LAYER_VARIABLES + "/" + scope, W)

        b = None
        if bias:
            b_init = initializations.get(bias_init)()
            b = va.variable(scope + "b", shape=[n_units],
                            initializer=b_init, trainable=trainable,
                            restore=restore)
            tf.add_to_collection(tf.GraphKeys.LAYER_VARIABLES + "/" + scope, b)

        inference = incoming
        // If input is not 2d, flatten it.
        if len(input_shape) > 2:
            inference = tf.reshape(inference, [-1, n_inputs])

        inference = tf.matmul(inference, W)
        if b: inference = tf.nn.bias_add(inference, b)

        if isinstance(activation, str):
            inference = activations.get(activation)(inference)
        elif hasattr(activation, "__call__"):
            inference = activation(inference)
        else:
            raise ValueError("Invalid Activation.")

        // Track activations.
        tf.add_to_collection(tf.GraphKeys.ACTIVATIONS, inference)

    // Add attributes to Tensor to easy access weights.
    inference.scope = scope
    inference.W = W
    inference.b = b

    return inference

After Change

    n_inputs = int(np.prod(input_shape[1:]))

    // Build variables and inference.
    with tf.variable_op_scope([incoming], scope, name, reuse=reuse) as scope:
        name = scope.name

        W_init = weights_init
        if isinstance(weights_init, str):
            W_init = initializations.get(weights_init)()

Instances