(x, y)
return tf.concat(3, [x, y*tf.ones([x_shapes[0], x_shapes[1], x_shapes[2], y_shapes[3]])])
Concatenate conditioning vector on feature map axis.
Concatenate conditioning vector on feature map axis.
Concatenate conditioning vector on feature map axis .
def conv_cond_concat(x, y):
    """Concatenate conditioning vector on feature map axis."""
    x_shapes = x.get_shape()
    y_shapes = y.get_shape()
    return tf.concat(3, [x, y*tf.ones([x_shapes[0], x_shapes[1], x_shapes[2], y_shapes[3]])])
def conv_cond_concat ( x , y ) : x_shapes = x . get_shape ( ) y_shapes = y . get_shape ( ) return tf . concat ( 3 , [ x , y * tf . ones ( [ x_shapes [ 0 ] , x_shapes [ 1 ] , x_shapes [ 2 ] , y_shapes [ 3 ] ] ) ] )