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Make tranpose_op_test.py use subTest for clearer test debugging.

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PiperOrigin-RevId: 309961979
Change-Id: I5d48a37fcdc5ba6a582be0648fd77742377c66a5
This commit is contained in:
Andrew Selle 2020-05-05 09:35:08 -07:00 committed by TensorFlower Gardener
parent 30bdba67cc
commit d0f2e69e27
1 changed files with 86 additions and 70 deletions
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156
tensorflow/python/kernel_tests/transpose_op_test.py
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@ -164,15 +164,18 @@ class TransposeTest(test.TestCase):
datatypes = [np.int8, np.float16, np.float32, np.float64, np.complex128]
for datatype in datatypes:
for input_shape, perm in zip(large_shapes, perms):
total_size = np.prod(input_shape)
inp = np.arange(1, total_size + 1, dtype=datatype).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
with self.subTest(
datatype=datatype, input_shape=input_shape, perm=perm):
total_size = np.prod(input_shape)
inp = np.arange(
1, total_size + 1, dtype=datatype).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
def test4DGPU(self):
# If no GPU available, skip the test
@ -185,15 +188,17 @@ class TransposeTest(test.TestCase):
]] * 3 + [[2, 3, 0, 1]] * 3
for input_shape, perm in zip(large_shapes, perms):
total_size = np.prod(input_shape)
inp = np.arange(1, total_size + 1, dtype=np.float32).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
with self.subTest(input_shape=input_shape, perm=perm):
total_size = np.prod(input_shape)
inp = np.arange(
1, total_size + 1, dtype=np.float32).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
# shapes related to Inception (taken from conv_ops_test.py)
inception_shapes = [[4, 5, 5, 124], [4, 8, 8, 38], [4, 8, 8, 38], [
@ -219,16 +224,18 @@ class TransposeTest(test.TestCase):
[4, 35, 35, 19], [4, 73, 73, 6], [4, 73, 73,
6], [4, 147, 147, 2]]
for input_shape in inception_shapes:
perm = [0, 3, 1, 2]
total_size = np.prod(input_shape)
inp = np.arange(1, total_size + 1, dtype=np.float32).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
with self.subTest(input_shape=input_shape):
perm = [0, 3, 1, 2]
total_size = np.prod(input_shape)
inp = np.arange(
1, total_size + 1, dtype=np.float32).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
def test3DGPU(self):
# If no GPU available, skip the test
@ -242,15 +249,18 @@ class TransposeTest(test.TestCase):
] * 3
for datatype in datatypes:
for input_shape, perm in zip(large_shapes, perms):
total_size = np.prod(input_shape)
inp = np.arange(1, total_size + 1, dtype=datatype).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
with self.subTest(
datatype=datatype, input_shape=input_shape, perm=perm):
total_size = np.prod(input_shape)
inp = np.arange(
1, total_size + 1, dtype=datatype).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
def testLargeSizeGPU(self):
# If no GPU available, skip the test
@ -263,15 +273,17 @@ class TransposeTest(test.TestCase):
perms = [[0, 2, 1]] * 9
for input_shape, perm in zip(large_shapes, perms):
total_size = np.prod(input_shape)
inp = np.arange(1, total_size + 1, dtype=np.float32).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
with self.subTest(input_shape=input_shape, perm=perm):
total_size = np.prod(input_shape)
inp = np.arange(
1, total_size + 1, dtype=np.float32).reshape(input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
def testRandomizedSmallDimLargeSizeGPU(self):
# If no GPU available, skip the test
@ -316,15 +328,16 @@ class TransposeTest(test.TestCase):
for input_shape, perm in zip(input_shapes, perms):
# generate input data with random ints from 0 to 9.
inp = np.random.randint(10, size=input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
self._ClearCachedSession()
with self.subTest(input_shape=input_shape, perm=perm):
inp = np.random.randint(10, size=input_shape)
np_ans = self._np_transpose(inp, perm)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(inp)
y = array_ops.transpose(inx, perm)
tf_ans = self.evaluate(y)
self.assertAllEqual(np_ans, tf_ans)
self.assertShapeEqual(np_ans, y)
self._ClearCachedSession()
@test_util.run_v1_only("b/120545219")
def testNop(self):
@ -338,16 +351,17 @@ class TransposeTest(test.TestCase):
def testPermType(self):
for perm_dtype in [np.int64, np.int32]:
x = np.arange(0, 8).reshape([2, 4]).astype(np.float32)
p = np.array([1, 0]).astype(perm_dtype)
np_ans = np.copy(x).transpose(p)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(x)
inp = constant_op.constant(p)
y = array_ops.transpose(inx, inp)
tf_ans = self.evaluate(y)
self.assertShapeEqual(np_ans, y)
self.assertAllEqual(np_ans, tf_ans)
with self.subTest(perm_dtype=perm_dtype):
x = np.arange(0, 8).reshape([2, 4]).astype(np.float32)
p = np.array([1, 0]).astype(perm_dtype)
np_ans = np.copy(x).transpose(p)
with self.cached_session(use_gpu=True):
inx = ops.convert_to_tensor(x)
inp = constant_op.constant(p)
y = array_ops.transpose(inx, inp)
tf_ans = self.evaluate(y)
self.assertShapeEqual(np_ans, y)
self.assertAllEqual(np_ans, tf_ans)
def testHalf(self):
self._compare(np.arange(0, 21).reshape([3, 7]).astype(np.float16))
@ -423,9 +437,10 @@ class TransposeTest(test.TestCase):
def testTranspose2DAuto(self):
x_np = [[1, 2, 3], [4, 5, 6]]
for use_gpu in [False, True]:
with self.cached_session(use_gpu=use_gpu):
x_tf = array_ops.transpose(x_np).eval()
self.assertAllEqual(x_tf, [[1, 4], [2, 5], [3, 6]])
with self.subTest(use_gpu=use_gpu):
with self.cached_session(use_gpu=use_gpu):
x_tf = array_ops.transpose(x_np).eval()
self.assertAllEqual(x_tf, [[1, 4], [2, 5], [3, 6]])
@test_util.run_v1_only("b/120545219")
def testSingletonDims(self):
@ -439,8 +454,9 @@ class TransposeTest(test.TestCase):
# copy here.
for shape in [[2, 1, 2], [2, 1, 2, 1, 1, 2], [1, 2, 2, 1, 1, 1],
[1, 1, 1, 2, 2, 2], [2, 2, 1, 1, 1]]:
self._compare_cpu_gpu(
np.arange(np.prod(shape)).reshape(shape).astype(np.float32))
with self.subTest(shape=shape):
self._compare_cpu_gpu(
np.arange(np.prod(shape)).reshape(shape).astype(np.float32))
@test_util.run_v1_only("b/120545219")
def testTransposeShapes(self):