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# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Test cases for Tensorflow functions."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.compiler.tests import xla_test
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import function
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import googletest
class FunctionTest(xla_test.XLATestCase):
def testFunction(self):
"""Executes a simple TensorFlow function."""
def APlus2B(a, b):
return a + b * 2
aval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
bval = np.array([5, 6, 7, 8]).reshape([2, 2]).astype(np.float32)
expected = APlus2B(aval, bval)
with self.cached_session() as sess:
@function.Defun(dtypes.float32, dtypes.float32)
def Foo(a, b):
return APlus2B(a, b)
a = constant_op.constant(aval, name="a")
b = constant_op.constant(bval, name="b")
with self.test_scope():
call_f = Foo(a, b)
result = sess.run(call_f)
self.assertAllClose(result, expected, rtol=1e-3)
def testNestedFunctions(self):
"""Executes two nested TensorFlow functions."""
def TimesTwo(x):
return x * 2
def APlus2B(a, b):
return a + TimesTwo(b)
aval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
bval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
expected = APlus2B(aval, bval)
with self.cached_session() as sess:
@function.Defun(dtypes.float32, dtypes.float32)
def Foo(a, b):
return APlus2B(a, b)
a = constant_op.constant(aval, name="a")
b = constant_op.constant(bval, name="b")
with self.test_scope():
call_g = Foo(a, b)
result = sess.run(call_g)
self.assertAllClose(result, expected, rtol=1e-3)
def testFunctionMultipleRetvals(self):
"""Executes a function with multiple return values."""
# This function will run on the XLA device
def Func(a, b):
return a + b, a - b
aval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
bval = np.array([5, 6, 7, 8]).reshape([2, 2]).astype(np.float32)
expected = Func(aval, bval)
with self.cached_session() as sess:
@function.Defun(dtypes.float32, dtypes.float32)
def Foo(a, b):
return Func(a, b)
a = constant_op.constant(aval, name="a")
b = constant_op.constant(bval, name="b")
with self.test_scope():
call_f = Foo(a, b)
result = sess.run(call_f)
self.assertAllClose(result, expected, rtol=1e-3)
def testCompileTimeConstantsInDefun(self):
"""Tests that XLA handles compile-time constants in defuns."""
with self.cached_session() as sess:
@function.Defun(dtypes.float32, dtypes.int32, dtypes.int32)
def Foo(a, c, d):
# c and d must be known at compile time
x = array_ops.slice(a, c, d)
return x
a = array_ops.placeholder(dtypes.float32)
c = array_ops.placeholder(dtypes.int32, shape=[4])
d = array_ops.placeholder(dtypes.int32, shape=[4])
with self.test_scope():
call_f = Foo(a, c, d)
result = sess.run(call_f, feed_dict={
a: np.ones([1, 4, 4, 1]),
c: [0, 0, 0, 0],
d: [1, 2, 2, 1]})
self.assertAllEqual(np.ones([1, 2, 2, 1]), result)
# TODO(b/36139787): Re-enable this test when noinline works again.
def DISABLED_testFunctionsNoInline(self):
@function.Defun(dtypes.float32, noinline=True)
def TimesTwo(x):
return x * 2
@function.Defun(dtypes.float32, dtypes.float32)
def APlus2B(a, b):
return a + TimesTwo(b)
aval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
bval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
expected = aval + bval * 2
with self.cached_session() as sess:
with self.test_scope():
a = array_ops.placeholder(dtypes.float32, name="a")
b = array_ops.placeholder(dtypes.float32, name="b")
call = APlus2B(a, b)
result = sess.run(call, {a: aval, b: bval})
self.assertAllClose(result, expected, rtol=1e-3)
if __name__ == "__main__":
googletest.main()
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