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"""Tests for tensorflow.ops.numerics."""
import tensorflow.python.platform
import numpy as np
import tensorflow as tf
from tensorflow.python.ops import control_flow_ops
class VerifyTensorAllFiniteTest(tf.test.TestCase):
def testVerifyTensorAllFiniteSucceeds(self):
x_shape = [5, 4]
x = np.random.random_sample(x_shape).astype(np.float32)
for use_gpu in [False, True]:
with self.test_session(use_gpu=use_gpu):
t = tf.constant(x, shape=x_shape, dtype=tf.float32)
t_verified = tf.verify_tensor_all_finite(t, "Input is not a number.")
self.assertAllClose(x, t_verified.eval())
def testVerifyTensorAllFiniteFails(self):
x_shape = [5, 4]
x = np.random.random_sample(x_shape).astype(np.float32)
my_msg = "Input is not a number."
# Test NaN.
x[0] = np.nan
for use_gpu in [False, True]:
with self.test_session(use_gpu=use_gpu):
with self.assertRaisesOpError(my_msg):
t = tf.constant(x, shape=x_shape, dtype=tf.float32)
t_verified = tf.verify_tensor_all_finite(t, my_msg)
t_verified.eval()
# Test Inf.
x[0] = np.inf
for use_gpu in [False, True]:
with self.test_session(use_gpu=use_gpu):
with self.assertRaisesOpError(my_msg):
t = tf.constant(x, shape=x_shape, dtype=tf.float32)
t_verified = tf.verify_tensor_all_finite(t, my_msg)
t_verified.eval()
class NumericsTest(tf.test.TestCase):
def testInf(self):
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
t1 = tf.constant(1.0)
t2 = tf.constant(0.0)
a = tf.div(t1, t2)
check = tf.add_check_numerics_ops()
a = control_flow_ops.with_dependencies([check], a)
with self.assertRaisesOpError("Inf"):
a.eval()
def testNaN(self):
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
t1 = tf.constant(0.0)
t2 = tf.constant(0.0)
a = tf.div(t1, t2)
check = tf.add_check_numerics_ops()
a = control_flow_ops.with_dependencies([check], a)
with self.assertRaisesOpError("NaN"):
a.eval()
def testBoth(self):
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
t1 = tf.constant([1.0, 0.0])
t2 = tf.constant([0.0, 0.0])
a = tf.div(t1, t2)
check = tf.add_check_numerics_ops()
a = control_flow_ops.with_dependencies([check], a)
with self.assertRaisesOpError("Inf and NaN"):
a.eval()
def testPassThrough(self):
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu, graph=tf.Graph()):
t1 = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3])
checked = tf.check_numerics(t1, message="pass through test")
value = checked.eval()
self.assertAllEqual(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]), value)
self.assertEqual([2, 3], checked.get_shape())
if __name__ == "__main__":
tf.test.main()
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