I'm trying to do a tf.scatter_nd_add inside a tf.while loop. It gives me an error message though.
TypeError: 'ScatterNdAdd' Op requires that input 'ref' be a mutable tensor (e.g.: a tf.Variable) It seems like the way that while loops work is that it changes the input variable from being of type tf.Variable to having some other type. Is it possible to do a scatter_nd_add op inside a while loop?
Here's a code excerpt:
self.hough = tf.Variable(tf.zeros((num_points, num_points), dtype=tf.float32), name='hough') self.i = tf.constant(0) c = lambda i, hough: tf.less(i, tf.squeeze(tf.shape(self.img_x))) b = lambda i, hough: self.ProcessPixel(i, hough) self.r = tf.while_loop(c, b, [self.i, self.hough], back_prop=False) This is the body of the loop:
def ProcessPixel(self, i, hough): pixel_x, pixel_y = self.img_x[self.i], self.img_y[self.i] result = self.GetLinesThroughPixel(pixel_x, pixel_y) idx = tf.stack([tf.range(num_points, dtype=tf.int64), result]) pixel_val = self.img[tf.to_int32(pixel_x), tf.to_int32(pixel_y)] print type(hough) updated_hough = tf.scatter_nd_add(hough, tf.transpose(idx), updates=pixel_val * tf.ones(num_points)) return tf.add(i, 1), updated_hough 
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