def shortlist_insert():
larger_ids = array_ops.boolean_mask(
math_ops.to_int64(ids), larger_scores)
larger_score_values = array_ops.boolean_mask(scores, larger_scores)
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
self.sl_ids, self.sl_scores, larger_ids, larger_score_values)
u1 = state_ops.scatter_update(self.sl_ids, shortlist_ids, new_ids)
u2 = state_ops.scatter_update(self.sl_scores, shortlist_ids, new_scores)
return control_flow_ops.group(u1, u2)
def shortlist_insert():
larger_ids = tf.boolean_mask(tf.to_int64(ids), larger_scores)
larger_score_values = tf.boolean_mask(scores, larger_scores)
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
self.sl_ids, self.sl_scores, larger_ids, larger_score_values
)
u1 = tf.scatter_update(self.sl_ids, shortlist_ids, new_ids)
u2 = tf.scatter_update(self.sl_scores, shortlist_ids, new_scores)
return tf.group(u1, u2)
def shortlist_insert():
larger_ids = tf.boolean_mask(tf.to_int64(ids), larger_scores)
larger_score_values = tf.boolean_mask(scores, larger_scores)
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
self.sl_ids, self.sl_scores, larger_ids,
larger_score_values)
u1 = tf.scatter_update(self.sl_ids, shortlist_ids, new_ids)
u2 = tf.scatter_update(self.sl_scores, shortlist_ids,
new_scores)
return tf.group(u1, u2)
def testInsertOpIntoEmptyShortlist(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[0, -1, -1, -1, -1, -1], # sl_ids
[-999, -999, -999, -999, -999, -999], # sl_scores
[5],
[33.0] # new id and score
)
self.assertAllEqual([1, 0], shortlist_ids.eval())
self.assertAllEqual([5, 1], new_ids.eval())
self.assertAllEqual([33.0, -999], new_scores.eval())
def testInsertOpIntoEmptyShortlist(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[0, -1, -1, -1, -1, -1], # sl_ids
[-999, -999, -999, -999, -999, -999], # sl_scores
[5],
[33.0] # new id and score
)
self.assertAllEqual([1, 0], shortlist_ids.eval())
self.assertAllEqual([5, 1], new_ids.eval())
self.assertAllEqual([33.0, -999], new_scores.eval())
def testInsertOpIntoAlmostFullShortlist(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[4, 13, -1, 27, 99, 15], # sl_ids
[60.0, 87.0, -999, 65.0, 1000.0, 256.0], # sl_scores
[5],
[93.0] # new id and score
)
self.assertAllEqual([2, 0], shortlist_ids.eval())
self.assertAllEqual([5, 5], new_ids.eval())
# Shortlist still contains all known scores > 60.0
self.assertAllEqual([93.0, 60.0], new_scores.eval())
def testInsertOpIntoAlmostFullShortlist(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[4, 13, -1, 27, 99, 15], # sl_ids
[60.0, 87.0, -999, 65.0, 1000.0, 256.0], # sl_scores
[5],
[93.0] # new id and score
)
self.assertAllEqual([2, 0], shortlist_ids.eval())
self.assertAllEqual([5, 5], new_ids.eval())
# Shortlist still contains all known scores > 60.0
self.assertAllEqual([93.0, 60.0], new_scores.eval())
def shortlist_insert():
larger_ids = array_ops.boolean_mask(math_ops.to_int64(ids),
larger_scores)
larger_score_values = array_ops.boolean_mask(
scores, larger_scores)
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
self.sl_ids, self.sl_scores, larger_ids,
larger_score_values)
u1 = state_ops.scatter_update(self.sl_ids, shortlist_ids,
new_ids)
u2 = state_ops.scatter_update(self.sl_scores, shortlist_ids,
new_scores)
return control_flow_ops.group(u1, u2)
def testInsertOpHard(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[4, 13, -1, 27, 99, 15], # sl_ids
[60.0, 87.0, -999, 65.0, 1000.0, 256.0], # sl_scores
[5, 6, 7, 8, 9],
[61.0, 66.0, 90.0, 100.0, 2000.0] # new id and score
)
# Top 5 scores are: 2000.0, 1000.0, 256.0, 100.0, 90.0
self.assertAllEqual([2, 3, 1, 0], shortlist_ids.eval())
self.assertAllEqual([9, 8, 7, 5], new_ids.eval())
# 87.0 is the highest score we overwrote or didn't insert.
self.assertAllEqual([2000.0, 100.0, 90.0, 87.0], new_scores.eval())
def testInsertOpIntoFullShortlist(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[5, 13, 44, 27, 99, 15], # sl_ids
[60.0, 87.0, 111.0, 65.0, 1000.0, 256.0], # sl_scores
[5],
[93.0] # new id and score
)
self.assertAllEqual([3, 0], shortlist_ids.eval())
self.assertAllEqual([5, 5], new_ids.eval())
# We removed a 65.0 from the list, so now we can only claim that
# it holds all scores > 65.0.
self.assertAllEqual([93.0, 65.0], new_scores.eval())
def testInsertOpHard(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[4, 13, -1, 27, 99, 15], # sl_ids
[60.0, 87.0, -999, 65.0, 1000.0, 256.0], # sl_scores
[5, 6, 7, 8, 9],
[61.0, 66.0, 90.0, 100.0, 2000.0] # new id and score
)
# Top 5 scores are: 2000.0, 1000.0, 256.0, 100.0, 90.0
self.assertAllEqual([2, 3, 1, 0], shortlist_ids.eval())
self.assertAllEqual([9, 8, 7, 5], new_ids.eval())
# 87.0 is the highest score we overwrote or didn't insert.
self.assertAllEqual([2000.0, 100.0, 90.0, 87.0], new_scores.eval())
def testInsertOpIntoFullShortlist(self):
with self.test_session():
shortlist_ids, new_ids, new_scores = tensor_forest_ops.top_n_insert(
[5, 13, 44, 27, 99, 15], # sl_ids
[60.0, 87.0, 111.0, 65.0, 1000.0, 256.0], # sl_scores
[5],
[93.0] # new id and score
)
self.assertAllEqual([3, 0], shortlist_ids.eval())
self.assertAllEqual([5, 5], new_ids.eval())
# We removed a 65.0 from the list, so now we can only claim that
# it holds all scores > 65.0.
self.assertAllEqual([93.0, 65.0], new_scores.eval())
