diff options
-rw-r--r-- | tensorflow/compiler/tests/reduce_ops_test.py | 62 |
1 files changed, 40 insertions, 22 deletions
diff --git a/tensorflow/compiler/tests/reduce_ops_test.py b/tensorflow/compiler/tests/reduce_ops_test.py index 965fdf684b..2c084b04fa 100644 --- a/tensorflow/compiler/tests/reduce_ops_test.py +++ b/tensorflow/compiler/tests/reduce_ops_test.py @@ -18,6 +18,7 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function +import functools import numpy as np from tensorflow.compiler.tests.xla_test import XLATestCase @@ -30,8 +31,13 @@ from tensorflow.python.platform import googletest class ReduceOpsTest(XLATestCase): - def _testReduction(self, tf_reduce_fn, np_reduce_fn, dtype, test_inputs, - rtol=1e-4, atol=1e-4): + def _testReduction(self, + tf_reduce_fn, + np_reduce_fn, + dtype, + test_inputs, + rtol=1e-4, + atol=1e-4): """Tests that the output of 'tf_reduce_fn' matches numpy's output.""" for test_input in test_inputs: @@ -41,16 +47,16 @@ class ReduceOpsTest(XLATestCase): index = array_ops.placeholder(dtypes.int32) out = tf_reduce_fn(a, index) result = sess.run(out, {a: test_input, index: [0]}) - self.assertAllClose(result, np_reduce_fn(test_input, axis=0), - rtol=rtol, atol=atol) + self.assertAllClose( + result, np_reduce_fn(test_input, axis=0), rtol=rtol, atol=atol) result = sess.run(out, {a: test_input, index: [1]}) - self.assertAllClose(result, np_reduce_fn(test_input, axis=1), - rtol=rtol, atol=atol) + self.assertAllClose( + result, np_reduce_fn(test_input, axis=1), rtol=rtol, atol=atol) result = sess.run(out, {a: test_input, index: [-1]}) - self.assertAllClose(result, np_reduce_fn(test_input, axis=1), - rtol=rtol, atol=atol) + self.assertAllClose( + result, np_reduce_fn(test_input, axis=1), rtol=rtol, atol=atol) with self.assertRaisesWithPredicateMatch( errors_impl.InvalidArgumentError, 'Invalid reduction dim'): @@ -60,7 +66,7 @@ class ReduceOpsTest(XLATestCase): errors_impl.InvalidArgumentError, 'Invalid reduction dim'): sess.run(out, {a: test_input, index: [2]}) - FLOAT_DATA = [ + REAL_DATA = [ np.zeros(shape=(2, 0)), np.zeros(shape=(0, 30)), np.arange(1, 7).reshape(2, 3), @@ -74,7 +80,7 @@ class ReduceOpsTest(XLATestCase): np.arange(-14, -2, dtype=np.float32).view(np.complex64).reshape(2, 3), np.arange(-4, 8, dtype=np.float32).view(np.complex64).reshape(2, 3), ] - NONEMPTY_FLOAT_DATA = [x for x in FLOAT_DATA if np.size(x) > 0] + NONEMPTY_REAL_DATA = [x for x in REAL_DATA if np.size(x) > 0] NONEMPTY_COMPLEX_DATA = [x for x in COMPLEX_DATA if np.size(x) > 0] BOOL_DATA = [ np.array([], dtype=np.bool).reshape(2, 0), @@ -83,8 +89,7 @@ class ReduceOpsTest(XLATestCase): ] def testReduceSumF32(self): - self._testReduction(math_ops.reduce_sum, np.sum, np.float32, - self.FLOAT_DATA) + self._testReduction(math_ops.reduce_sum, np.sum, np.float32, self.REAL_DATA) def testReduceSumC64(self): self._testReduction(math_ops.reduce_sum, np.sum, np.complex64, @@ -92,7 +97,7 @@ class ReduceOpsTest(XLATestCase): def testReduceProdF32(self): self._testReduction(math_ops.reduce_prod, np.prod, np.float32, - self.FLOAT_DATA) + self.REAL_DATA) def testReduceProdC64(self): self._testReduction(math_ops.reduce_prod, np.prod, np.complex64, @@ -100,31 +105,44 @@ class ReduceOpsTest(XLATestCase): def testReduceMin(self): - def reference_min(inp, axis): + def reference_min(dtype, inp, axis): """Wrapper around np.amin that returns +infinity for an empty input.""" if inp.shape[axis] == 0: - return np.full(inp.shape[0:axis] + inp.shape[axis + 1:], float('inf')) + if np.issubdtype(dtype, np.floating): + return np.full(inp.shape[0:axis] + inp.shape[axis + 1:], float('inf')) + return np.full(inp.shape[0:axis] + inp.shape[axis + 1:], + np.iinfo(dtype).max) return np.amin(inp, axis) - self._testReduction(math_ops.reduce_min, reference_min, np.float32, - self.FLOAT_DATA) + for dtype in set(self.all_types).intersection( + [np.float32, np.int32, np.int64]): + self._testReduction(math_ops.reduce_min, + functools.partial(reference_min, dtype), dtype, + self.REAL_DATA) def testReduceMax(self): - def reference_max(inp, axis): + def reference_max(dtype, inp, axis): """Wrapper around np.amax that returns -infinity for an empty input.""" if inp.shape[axis] == 0: - return np.full(inp.shape[0:axis] + inp.shape[axis + 1:], float('-inf')) + if np.issubdtype(dtype, np.floating): + return np.full(inp.shape[0:axis] + inp.shape[axis + 1:], + float('-inf')) + return np.full(inp.shape[0:axis] + inp.shape[axis + 1:], + np.iinfo(dtype).min) return np.amax(inp, axis) - self._testReduction(math_ops.reduce_max, reference_max, np.float32, - self.FLOAT_DATA) + for dtype in set(self.all_types).intersection( + [np.float32, np.int32, np.int64]): + self._testReduction(math_ops.reduce_max, + functools.partial(reference_max, dtype), dtype, + self.REAL_DATA) def testReduceMeanF32(self): # TODO(phawkins): mean on XLA currently returns 0 instead of NaN when # reducing across zero inputs. self._testReduction(math_ops.reduce_mean, np.mean, np.float32, - self.NONEMPTY_FLOAT_DATA) + self.NONEMPTY_REAL_DATA) def testReduceMeanC64(self): self._testReduction(math_ops.reduce_mean, np.mean, np.complex64, |