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