def test_reduce_batch_count_mean_and_var(self):
x = tf.constant([[[1], [2]], [[3], [4]]], dtype=tf.float32)
count, mean, var = tf_utils.reduce_batch_count_mean_and_var(
x, reduce_instance_dims=True)
with tf.compat.v1.Session():
self.assertAllEqual(count.eval(), 4)
self.assertAllEqual(mean.eval(), 2.5)
self.assertAllEqual(var.eval(), 1.25)
def test_reduce_batch_count_mean_and_var_elementwise(self):
x = tf.constant([[[1], [2]], [[3], [4]]], dtype=tf.float32)
count, mean, var = tf_utils.reduce_batch_count_mean_and_var(
x, reduce_instance_dims=False)
with tf.compat.v1.Session():
self.assertAllEqual(count.eval(), [[2.], [2.]])
self.assertAllEqual(mean.eval(), [[2.], [3.]])
self.assertAllEqual(var.eval(), [[1.], [1.]])
def test_reduce_batch_count_mean_and_var_sparse(self):
x = tf.SparseTensor(indices=[[0, 0], [0, 2], [1, 1], [1, 2]],
values=[1., 2., 3., 4.],
dense_shape=[2, 4])
count, mean, var = tf_utils.reduce_batch_count_mean_and_var(
x, reduce_instance_dims=True)
with tf.compat.v1.Session():
self.assertAllEqual(count.eval(), 4)
self.assertAllEqual(mean.eval(), 2.5)
self.assertAllEqual(var.eval(), 1.25)
def test_reduce_batch_count_mean_and_var_sparse_elementwise(self):
x = tf.SparseTensor(indices=[[0, 0], [0, 3], [1, 1], [1, 3]],
values=[1., 2., 3., 4.],
dense_shape=[2, 5])
count, mean, var = tf_utils.reduce_batch_count_mean_and_var(
x, reduce_instance_dims=False)
with tf.compat.v1.Session():
self.assertAllEqual(count.eval(), [1.0, 1.0, 0.0, 2.0, 0.0])
self.assertAllEqual(mean.eval(), [1.0, 3.0, 0.0, 3.0, 0.0])
self.assertAllEqual(var.eval(), [0.0, 0.0, 0.0, 1.0, 0.0])
def _reduce_batch_count_mean_and_var(x):
return tf_utils.reduce_batch_count_mean_and_var(
x, reduce_instance_dims=reduce_instance_dims)
