def _set_intersection(self, a, b):
# Validate that we get the same results with or without `validate_indices`,
# and with a & b swapped.
ops = (
sets.set_intersection(a, b, validate_indices=True),
sets.set_intersection(a, b, validate_indices=False),
sets.set_intersection(b, a, validate_indices=True),
sets.set_intersection(b, a, validate_indices=False),
)
for op in ops:
self._assert_static_shapes(a, op)
return self._run_equivalent_set_ops(ops)
def _set_intersection(self, a, b):
# Validate that we get the same results with or without `validate_indices`,
# and with a & b swapped.
ops = (
sets.set_intersection(
a, b, validate_indices=True),
sets.set_intersection(
a, b, validate_indices=False),
sets.set_intersection(
b, a, validate_indices=True),
sets.set_intersection(
b, a, validate_indices=False),)
for op in ops:
self._assert_static_shapes(a, op)
return self._run_equivalent_set_ops(ops)
def recall_at_k(labels, predictions, k):
'''
Compute recall at position k.
:param labels: shape=(num_examples,), dtype=tf.int64
:param predictions: logits of shape=(num_examples, num_classes)
:param k: recall position
:return: recall at position k
Example:
labels = tf.constant([0, 1, 1], dtype=tf.int64)
predictions = tf.constant([[0.1, 0.2, 0.3], [3, 5, 2], [0.3, 0.4, 0.7]])
recall_at_k(labels, predictions, 2)
# recall_at_k(labels, predictions, 2) = 0.6667
'''
labels = expand_dims(labels, axis=1)
_, predictions_idx = nn.top_k(predictions, k)
predictions_idx = math_ops.to_int64(predictions_idx)
tp = sets.set_size(sets.set_intersection(predictions_idx, labels))
tp = math_ops.to_double(tp)
tp = math_ops.reduce_sum(tp)
fn = sets.set_size(
sets.set_difference(predictions_idx, labels, aminusb=False))
fn = math_ops.to_double(fn)
fn = math_ops.reduce_sum(fn)
recall = math_ops.div(tp, math_ops.add(tp, fn), name='recall_at_k')
return recall
def _set_intersection(self, a, b):
# Validate that we get the same results with or without `validate_indices`,
# and with a & b swapped.
ops = (
sets.set_intersection(a, b, validate_indices=True),
sets.set_intersection(a, b, validate_indices=False),
sets.set_intersection(b, a, validate_indices=True),
sets.set_intersection(b, a, validate_indices=False),
)
for op in ops:
self._assert_shapes(a, op)
with self.test_session() as sess:
results = sess.run(ops)
for i in range(1, 4):
self.assertAllEqual(results[0].indices, results[i].indices)
self.assertAllEqual(results[0].values, results[i].values)
self.assertAllEqual(results[0].dense_shape, results[i].dense_shape)
return results[0]
def _set_intersection(self, a, b):
# Validate that we get the same results with or without `validate_indices`,
# and with a & b swapped.
ops = (
sets.set_intersection(
a, b, validate_indices=True),
sets.set_intersection(
a, b, validate_indices=False),
sets.set_intersection(
b, a, validate_indices=True),
sets.set_intersection(
b, a, validate_indices=False),)
for op in ops:
self._assert_shapes(a, op)
with self.test_session() as sess:
results = sess.run(ops)
for i in range(1, 4):
self.assertAllEqual(results[0].indices, results[i].indices)
self.assertAllEqual(results[0].values, results[i].values)
self.assertAllEqual(results[0].dense_shape, results[i].dense_shape)
return results[0]
def _set_intersection_count(self, a, b):
op = sets.set_size(sets.set_intersection(a, b))
with self.test_session() as sess:
return sess.run(op)
def _set_intersection_count(self, a, b):
op = sets.set_size(sets.set_intersection(a, b))
with self.cached_session() as sess:
return sess.run(op)
def _set_intersection_count(self, a, b):
op = sets.set_size(sets.set_intersection(a, b))
with self.cached_session() as sess:
return self.evaluate(op)
