python - Tensorflow Update first matching element in each row -


building on question looking update values of 2-d tensor first time in row tf.where condition met. here sample code using simulate:

tf.reset_default_graph() graph = tf.graph() graph.as_default():     val = "hello"     new_val = "goodbye"     matrix = tf.constant([["word","hello","hello"],                           ["word", "other", "hello"],                           ["hello", "hello","hello"],                           ["word", "word", "word"]                          ])     matching_indices = tf.where(tf.equal(matrix, val))     first_matching_idx = tf.segment_min(data = matching_indices[:, 1],                                  segment_ids = matching_indices[:, 0])  sess = tf.interactivesession(graph=graph) print(sess.run(first_matching_idx))

this output [1, 2, 0] 1 placement of first hello in row 1, 2 placement of first hello in row 2, , 0 placement of first hello in row 3.

however, can't figure out way first matching index updated new value -- want first "hello" turned "goodbye". have tried using tf.scatter_update() not seem work on 2d tensors. there way modify 2-d tensor described?

one easy workaround use tf.py_func numpy array

def ch_val(array, val, new_val):     idx = np.array([[s, list(row).index(val)]                 s, row in enumerate(array) if val in row])     idx = tuple((idx[:, 0], idx[:, 1]))     array[idx] = new_val     return array  ... matrix = tf.variable([["word","hello","hello"],                       ["word", "other", "hello"],                       ["hello", "hello","hello"],                       ["word", "word", "word"]                      ]) matrix = tf.py_func(ch_val, [matrix, 'hello', 'goodbye'], tf.string)  tf.session() sess:     sess.run(tf.global_variables_initializer())     print(sess.run(matrix))     # results: [['word' 'goodbye' 'hello']       ['word' 'other' 'goodbye']       ['goodbye' 'hello' 'hello']       ['word' 'word' 'word']]

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