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"""Tests for tensorflow.ops.math_ops."""
import math
import tensorflow.python.platform
import numpy as np
from tensorflow.python.framework import test_util
from tensorflow.python.ops import constant_op
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import googletest
exp = math.exp
log = math.log
class ReduceTest(test_util.TensorFlowTestCase):
def testReduceAllDims(self):
x = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32)
with self.test_session():
y_tf = math_ops.reduce_sum(x).eval()
self.assertEqual(y_tf, 21)
class RoundTest(test_util.TensorFlowTestCase):
def testRounding(self):
x = [0.49, 0.7, -0.3, -0.8]
for dtype in [np.float32, np.double]:
x_np = np.array(x, dtype=dtype)
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu):
x_tf = constant_op.constant(x_np, shape=x_np.shape)
y_tf = math_ops.round(x_tf)
y_tf_np = y_tf.eval()
y_np = np.round(x_np)
self.assertAllClose(y_tf_np, y_np, atol=1e-2)
class ModTest(test_util.TensorFlowTestCase):
def testFloat(self):
x = [0.5, 0.7, 0.3]
for dtype in [np.float32, np.double]:
# Test scalar and vector versions.
for denom in [x[0], [x[0]] * 3]:
x_np = np.array(x, dtype=dtype)
with self.test_session():
x_tf = constant_op.constant(x_np, shape=x_np.shape)
y_tf = math_ops.mod(x_tf, denom)
y_tf_np = y_tf.eval()
y_np = np.fmod(x_np, denom)
self.assertAllClose(y_tf_np, y_np, atol=1e-2)
def testFixed(self):
x = [5, 10, 23]
for dtype in [np.int32, np.int64]:
# Test scalar and vector versions.
for denom in [x[0], x]:
x_np = np.array(x, dtype=dtype)
with self.test_session():
x_tf = constant_op.constant(x_np, shape=x_np.shape)
y_tf = math_ops.mod(x_tf, denom)
y_tf_np = y_tf.eval()
y_np = np.mod(x_np, denom)
self.assertAllClose(y_tf_np, y_np)
if __name__ == "__main__":
googletest.main()
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