Annotate tests only compatible with graph mode
PiperOrigin-RevId: 235952819
This commit is contained in:
Gaurav Jain
TensorFlower Gardener
parent
8951b7fb56
commit
d535cfc63d
@ -244,6 +244,7 @@ class TrtConvertTest(test_util.TensorFlowTestCase):
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"output:0",
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feed_dict={"input:0": [[[test_data]]]}))
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@test_util.deprecated_graph_mode_only
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def testTrtGraphConverter_BasicConversion(self):
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"""Test case for trt_convert.TrtGraphConverter()."""
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if not is_tensorrt_enabled():
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@ -276,6 +277,7 @@ class TrtConvertTest(test_util.TensorFlowTestCase):
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self.assertEqual(execute_native_segment_test_value,
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get_test_value("TRTEngineOp_0:ExecuteNativeSegment"))
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@test_util.deprecated_graph_mode_only
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def testTrtGraphConverter_MinimumSegmentSize(self):
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if not is_tensorrt_enabled():
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return
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@ -290,6 +292,7 @@ class TrtConvertTest(test_util.TensorFlowTestCase):
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"output": "Identity"
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}, node_name_to_op)
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@test_util.deprecated_graph_mode_only
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def testTrtGraphConverter_DynamicOp(self):
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if not is_tensorrt_enabled():
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return
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@ -329,6 +332,7 @@ class TrtConvertTest(test_util.TensorFlowTestCase):
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# the max, it should evict an old engine and create a new one.
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self._TestRun(sess, 3, True)
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@test_util.deprecated_graph_mode_only
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def testTrtGraphConverter_StaticOp(self):
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if not is_tensorrt_enabled():
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return
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@ -36,7 +36,7 @@ from tensorflow.python.util import compat as util_compat
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# TODO(b/117581999): add eager coverage when supported.
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class CopyToDeviceTest(test_base.DatasetTestBase):
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyToDevice(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -61,7 +61,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceInt32(self):
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host_dataset = dataset_ops.Dataset.from_tensors([0, 1, 2, 3])
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device_dataset = host_dataset.apply(
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@ -85,7 +85,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyToSameDevice(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -110,7 +110,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceWithPrefetch(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -135,7 +135,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyDictToDevice(self):
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host_dataset = dataset_ops.Dataset.range(10).map(lambda x: {"a": x})
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device_dataset = host_dataset.apply(
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@ -160,7 +160,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyDictToDeviceWithPrefetch(self):
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host_dataset = dataset_ops.Dataset.range(10).map(lambda x: {"a": x})
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device_dataset = host_dataset.apply(
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@ -185,7 +185,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopySparseTensorsToDevice(self):
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def make_tensor(i):
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@ -218,7 +218,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopySparseTensorsToDeviceWithPrefetch(self):
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def make_tensor(i):
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@ -251,6 +251,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpu(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -271,6 +272,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuWithPrefetch(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -291,6 +293,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuWithMap(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -328,6 +331,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuInt32(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -347,6 +351,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuInt32AndPrefetch(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -366,6 +371,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuStrings(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -385,6 +391,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuStringsAndPrefetch(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -404,6 +411,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDevicePingPongCPUGPU(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -427,7 +435,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceWithReInit(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -456,7 +464,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceWithReInitAndPrefetch(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -485,6 +493,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuWithReInit(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -508,6 +517,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testCopyToDeviceGpuWithReInitAndPrefetch(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -531,6 +541,7 @@ class CopyToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testIteratorGetNextAsOptionalOnGPU(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -32,7 +32,7 @@ from tensorflow.python.platform import test
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# TODO(b/117581999): add eager coverage when supported.
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class PrefetchToDeviceTest(test_base.DatasetTestBase):
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testPrefetchToDevice(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -57,7 +57,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testPrefetchToSameDevice(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -82,7 +82,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testPrefetchDictToDevice(self):
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host_dataset = dataset_ops.Dataset.range(10).map(lambda x: {"a": x})
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device_dataset = host_dataset.apply(
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@ -107,7 +107,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testPrefetchSparseTensorsToDevice(self):
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def make_tensor(i):
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return sparse_tensor.SparseTensorValue(
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@ -138,6 +138,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testPrefetchToDeviceGpu(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -157,7 +158,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testPrefetchToDeviceWithReInit(self):
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host_dataset = dataset_ops.Dataset.range(10)
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device_dataset = host_dataset.apply(
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@ -186,6 +187,7 @@ class PrefetchToDeviceTest(test_base.DatasetTestBase):
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with self.assertRaises(errors.OutOfRangeError):
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self.evaluate(next_element)
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@test_util.deprecated_graph_mode_only
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def testPrefetchToDeviceGpuWithReInit(self):
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if not test_util.is_gpu_available():
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self.skipTest("No GPU available")
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@ -55,7 +55,7 @@ from tensorflow.python.util import compat
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class IteratorTest(test.TestCase, parameterized.TestCase):
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testNoGradients(self):
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component = constant_op.constant([1.])
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side = constant_op.constant(0.)
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@ -66,7 +66,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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self.assertIsNone(gradients_impl.gradients(value, side)[0])
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self.assertIsNone(gradients_impl.gradients(value, [component, side])[0])
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testCapturingStateInOneShotRaisesException(self):
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var = variables.Variable(37.0, name="myvar")
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dataset = (
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@ -77,7 +77,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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"datasets that capture stateful objects.+myvar"):
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dataset_ops.make_one_shot_iterator(dataset)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testOneShotIterator(self):
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components = (np.arange(7),
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np.array([[1, 2, 3]]) * np.arange(7)[:, np.newaxis],
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@ -103,7 +103,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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with self.assertRaises(errors.OutOfRangeError):
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sess.run(get_next)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testOneShotIteratorCaptureByValue(self):
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components = (np.arange(7),
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np.array([[1, 2, 3]]) * np.arange(7)[:, np.newaxis],
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@ -166,7 +166,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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with self.assertRaises(errors.OutOfRangeError):
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sess.run(get_next)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testOneShotIteratorNonBlocking(self):
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dataset = dataset_ops.Dataset.from_tensors([1, 2, 3]).map(lambda x: x * x)
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iterator = dataset_ops.make_one_shot_iterator(dataset)
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@ -205,7 +205,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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len([None for r in results if r is None]))
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self.assertAllEqual([[1, 4, 9]], [r for r in results if r is not None])
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testOneShotIteratorInitializerFails(self):
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# Define a dataset whose initialization will always fail.
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dataset = dataset_ops.Dataset.from_tensors(
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@ -286,7 +286,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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with self.assertRaises(errors.OutOfRangeError):
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sess.run(get_next)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testNotInitializedError(self):
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components = (np.array(1), np.array([1, 2, 3]), np.array(37.0))
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iterator = dataset_ops.make_initializable_iterator(
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@ -298,7 +298,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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"iterator has not been initialized"):
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sess.run(get_next)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testReinitializableIterator(self):
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dataset_3 = dataset_ops.Dataset.from_tensors(
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constant_op.constant([1, 2, 3]))
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@ -339,7 +339,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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with self.assertRaises(errors.OutOfRangeError):
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sess.run(get_next)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testReinitializableIteratorWithFunctions(self):
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def g():
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@ -399,7 +399,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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(constant_op.constant([1, 2, 3], dtype=dtypes.int64),
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constant_op.constant([4., 5., 6., 7.], dtype=dtypes.float64))))
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testIteratorStringHandle(self):
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dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
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dataset_4 = dataset_ops.Dataset.from_tensor_slices([10, 20, 30, 40])
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@ -457,7 +457,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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sess.run(
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next_element, feed_dict={handle_placeholder: iterator_4_handle})
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testIteratorStringHandleFuture(self):
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with forward_compat.forward_compatibility_horizon(2018, 8, 4):
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dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
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@ -523,7 +523,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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sess.run(
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next_element, feed_dict={handle_placeholder: iterator_4_handle})
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testIteratorStringHandleReuseTensorObject(self):
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dataset = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
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one_shot_iterator = dataset_ops.make_one_shot_iterator(dataset)
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@ -552,7 +552,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
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self.assertEqual("foo_1", handle_with_same_name.op.name)
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self.assertIsNot(handle_with_name, handle_with_same_name)
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@test_util.run_deprecated_v1
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@test_util.deprecated_graph_mode_only
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def testIteratorStringHandleError(self):
|
||||
dataset_int_scalar = (
|
||||
dataset_ops.Dataset.from_tensor_slices([1, 2, 3]).repeat())
|
||||
@ -593,7 +593,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
|
||||
feedable_int_vector.get_next(),
|
||||
feed_dict={handle_placeholder: handle_float_vector}))
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testRemoteIteratorUsingRemoteCallOpDirectSession(self):
|
||||
worker_config = config_pb2.ConfigProto()
|
||||
worker_config.device_count["CPU"] = 3
|
||||
@ -651,7 +651,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
|
||||
target_placeholder: "/job:localhost/replica:0/task:0/cpu:1"
|
||||
})
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testRemoteIteratorUsingRemoteCallOpMultiWorkers(self):
|
||||
s1 = server_lib.Server.create_local_server()
|
||||
s2 = server_lib.Server.create_local_server()
|
||||
@ -705,6 +705,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
|
||||
with self.assertRaises(errors.OutOfRangeError):
|
||||
sess.run(n)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testRemoteIteratorUsingRemoteCallOpDirectSessionGPUCPU(self):
|
||||
if not test_util.is_gpu_available():
|
||||
self.skipTest("No GPU available")
|
||||
@ -761,7 +762,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
|
||||
target_placeholder: "/job:localhost/replica:0/task:0/cpu:0"
|
||||
})
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testIncorrectIteratorRestore(self):
|
||||
|
||||
def _path():
|
||||
@ -820,7 +821,7 @@ class IteratorTest(test.TestCase, parameterized.TestCase):
|
||||
with self.assertRaises(errors.InvalidArgumentError):
|
||||
sess.run(restore_op)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testRepeatedGetNextWarning(self):
|
||||
iterator = dataset_ops.make_one_shot_iterator(dataset_ops.Dataset.range(10))
|
||||
warnings.simplefilter("always")
|
||||
|
||||
@ -283,6 +283,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSplitWithNonConstAxis(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -318,6 +319,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_map_nhwc_to_nchw('split-0', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSplitVWithNonConstAxis(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -745,6 +747,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self.assertIn('concat-2-LayoutOptimizer', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFill(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -788,6 +791,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_trans_nchw_to_nhwc('Fill-0-0', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testTile(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -856,6 +860,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self.assertIn('ReverseV2-1-LayoutOptimizer', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testReverseWithNonConstDims(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -923,6 +928,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_trans_nchw_to_nhwc('Select-0-0', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSelectOpConditionUnknownShape(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -984,6 +990,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_trans_nchw_to_nhwc('Select-0-0', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testPadWithNonConstPaddings(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -1020,6 +1027,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_vec_nhwc_to_nchw('Pad-1', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testMaxPoolV2(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -1056,6 +1064,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self.assertIn('MaxPoolV2-1-LayoutOptimizer', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testMaxPoolGradV2(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -1093,6 +1102,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self.assertIn('MaxPoolGradV2-3-LayoutOptimizer', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSliceWithNonConstAxis(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -1129,6 +1139,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_vec_nhwc_to_nchw('Slice-2', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testStridedSliceWithNonConstAxis(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -1237,6 +1248,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self.assertIn('strided_slice-3-LayoutOptimizer', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testStridedSliceGradWithNonConstAxis(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
random_seed.set_random_seed(0)
|
||||
@ -1279,6 +1291,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self.assertIn('StridedSlice-2-LayoutOptimizer', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testShapeN(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
x = array_ops.placeholder(dtype='float32')
|
||||
@ -1310,6 +1323,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_vec_nchw_to_nhwc('ShapeN-0-0', nodes)
|
||||
self.assertAllEqual(output_val_ref, output_val)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testShapeNFollowedByNotConvertibleNodeReshape(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
x = array_ops.placeholder(dtype='float32')
|
||||
@ -1416,6 +1430,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_trans_nchw_to_nhwc('map/while/Add_1-0-2', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testBinaryOpSecondPort(self):
|
||||
if test.is_gpu_available(cuda_only=True):
|
||||
output = _model_with_second_port()
|
||||
@ -1440,7 +1455,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self._assert_trans_nchw_to_nhwc('Add-0-0', nodes)
|
||||
self.assertAllClose(output_val_ref, output_val, atol=1e-3)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testGradient(self):
|
||||
meta_graph = _simple_metagraph()
|
||||
config = config_pb2.ConfigProto()
|
||||
@ -1458,7 +1473,7 @@ class LayoutOptimizerTest(test.TestCase):
|
||||
self.assertEqual(node.attr['data_format'].s, b'NCHW')
|
||||
self.assertEqual(found, 5)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testDepthwise(self):
|
||||
meta_graph = _simple_metagraph(depthwise=True)
|
||||
config = config_pb2.ConfigProto()
|
||||
|
||||
@ -1161,6 +1161,7 @@ class Conv2DTest(test.TestCase):
|
||||
tf_logging.debug("actual = %s", value)
|
||||
self.assertArrayNear(value_2.flatten(), value.flatten(), err)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testConv2D2x2Depth3ValidBackpropFilterStride1x1Dilation2x1(self):
|
||||
if test.is_gpu_available(cuda_only=True) or test_util.IsMklEnabled():
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
@ -1175,6 +1176,7 @@ class Conv2DTest(test.TestCase):
|
||||
use_gpu=use_gpu,
|
||||
err=1e-5)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testConv2D2x2Depth1ValidBackpropFilterDilation1x2(self):
|
||||
if test.is_gpu_available(cuda_only=True) or test_util.IsMklEnabled():
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
@ -1203,6 +1205,7 @@ class Conv2DTest(test.TestCase):
|
||||
use_gpu=use_gpu,
|
||||
err=1e-5)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testConv2D2x2Depth3ValidBackpropFilterDilation2x2(self):
|
||||
if test.is_gpu_available(cuda_only=True) or test_util.IsMklEnabled():
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
@ -1231,6 +1234,7 @@ class Conv2DTest(test.TestCase):
|
||||
use_gpu=use_gpu,
|
||||
err=1e-5)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testConv2D2x2Depth3ValidBackpropInputStride1x1Dilation2x1(self):
|
||||
if test.is_gpu_available(cuda_only=True) or test_util.IsMklEnabled():
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
@ -1245,6 +1249,7 @@ class Conv2DTest(test.TestCase):
|
||||
use_gpu=use_gpu,
|
||||
err=1e-5)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testConv2D2x2Depth1ValidBackpropInputDilation1x2(self):
|
||||
if test.is_gpu_available(cuda_only=True) or test_util.IsMklEnabled():
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
@ -1273,6 +1278,7 @@ class Conv2DTest(test.TestCase):
|
||||
use_gpu=use_gpu,
|
||||
err=1e-5)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testConv2D2x2Depth3ValidBackpropInputDilation2x1(self):
|
||||
if test.is_gpu_available(cuda_only=True) or test_util.IsMklEnabled():
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
@ -1703,7 +1709,7 @@ class Conv2DTest(test.TestCase):
|
||||
tf_logging.debug("conv_2d gradient error = %s", err)
|
||||
self.assertLess(err, max_err)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradientValidPaddingStrideOne(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1721,7 +1727,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientValidPaddingStrideOne(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1739,7 +1745,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradientValidPaddingStrideTwo(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1757,7 +1763,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientValidPaddingStrideTwo(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1775,7 +1781,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradientValidPaddingStrideThree(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1793,7 +1799,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientValidPaddingStrideThree(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1811,7 +1817,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradientSamePaddingStrideOne(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1829,7 +1835,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientSamePaddingStrideOne(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1847,7 +1853,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradientSamePaddingStrideTwo(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1865,7 +1871,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientSamePaddingStrideTwo(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1883,7 +1889,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradientSamePaddingStrideThree(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1901,7 +1907,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientSamePaddingStrideThree(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1919,7 +1925,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientSamePaddingStride2x1(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1937,7 +1943,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradientKernelSizeMatchesInputSize(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1955,7 +1961,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradientKernelSizeMatchesInputSize(self):
|
||||
for (data_format, use_gpu) in GetTestConfigs():
|
||||
self.ConstructAndTestGradient(
|
||||
@ -1973,6 +1979,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradient1x1PaddingStrideOne(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -1994,6 +2001,7 @@ class Conv2DTest(test.TestCase):
|
||||
use_gpu=use_gpu,
|
||||
max_err=0.0025)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradient1x1PaddingStrideOne(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2014,6 +2022,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradient1x1PaddingStrideTwo(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2034,6 +2043,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradient1x1PaddingStrideTwo(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2054,6 +2064,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradient2x2PaddingStrideOne(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2074,6 +2085,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradient2x2PaddingStrideOne(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2095,6 +2107,7 @@ class Conv2DTest(test.TestCase):
|
||||
use_gpu=use_gpu,
|
||||
max_err=0.003)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradient1_2_3_4PaddingStride3x2(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2115,6 +2128,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradient1_2_3_4PaddingStride3x2(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2135,6 +2149,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradient4_3_2_1PaddingStride2x1(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2155,6 +2170,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradient4_3_2_1PaddingStride2x1(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2175,6 +2191,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInputGradient0_0_0_5PaddingStride1x2(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2195,6 +2212,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testFilterGradient0_0_0_5PaddingStride1x2(self):
|
||||
if not test.is_gpu_available(cuda_only=True):
|
||||
return
|
||||
@ -2215,7 +2233,7 @@ class Conv2DTest(test.TestCase):
|
||||
data_format=data_format,
|
||||
use_gpu=use_gpu)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testShapeFunctionEdgeCases(self):
|
||||
# All shapes unknown.
|
||||
c1 = nn_ops.conv2d(
|
||||
@ -2302,7 +2320,7 @@ class Conv2DTest(test.TestCase):
|
||||
strides=[1, 1, 1, 1],
|
||||
padding=[0, 0, 0, 0])
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
@test_util.disable_xla("b/123337890") # Error messages differ
|
||||
def testOpEdgeCases(self):
|
||||
with self.cached_session() as sess:
|
||||
|
||||
@ -81,7 +81,7 @@ class SparseTensorDenseMatMulTest(test.TestCase):
|
||||
self.assertEqual(tf_value_ans.get_shape()[1], np_ans.shape[1])
|
||||
self.assertEqual(tf_tensor_ans.get_shape()[1], np_ans.shape[1])
|
||||
|
||||
for out in (tf_value_ans.eval(), self.evaluate(tf_tensor_ans)):
|
||||
for out in (self.evaluate(tf_value_ans), self.evaluate(tf_tensor_ans)):
|
||||
if x.dtype == np.float32:
|
||||
self.assertAllClose(np_ans, out, rtol=1e-4, atol=1e-4)
|
||||
elif x.dtype == np.float64:
|
||||
@ -134,6 +134,7 @@ class SparseTensorDenseMatMulTest(test.TestCase):
|
||||
with self.assertRaisesRegexp(ValueError, "Dimensions must be equal"):
|
||||
sparse_ops.sparse_tensor_dense_matmul(x_st_shape_inconsistent, y)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testInvalidIndicesForSparseTensorDenseMatmul(self):
|
||||
# Note: use_gpu=False because nice errors are only returned from CPU kernel.
|
||||
with self.session(use_gpu=False):
|
||||
@ -147,23 +148,25 @@ class SparseTensorDenseMatMulTest(test.TestCase):
|
||||
dense_t = np.matrix([[1] * 5, [2] * 5], dtype=np.float32)
|
||||
with self.assertRaisesOpError(
|
||||
"k .10. from index.0,1. out of bounds .>=2."):
|
||||
sparse_ops.sparse_tensor_dense_matmul(sparse_t, dense_t).eval()
|
||||
self.evaluate(sparse_ops.sparse_tensor_dense_matmul(sparse_t, dense_t))
|
||||
dense_t = np.matrix([[1] * 500, [2] * 500], dtype=np.float32)
|
||||
with self.assertRaisesOpError(
|
||||
"k .10. from index.0,1. out of bounds .>=2."):
|
||||
sparse_ops.sparse_tensor_dense_matmul(sparse_t, dense_t).eval()
|
||||
self.evaluate(sparse_ops.sparse_tensor_dense_matmul(sparse_t, dense_t))
|
||||
|
||||
# Repeat with adjoint_a, to get a different error.
|
||||
dense_t = np.matrix([[1] * 5, [2] * 5, [3] * 5], dtype=np.float32)
|
||||
with self.assertRaisesOpError(
|
||||
"m .10. from index.0,1. out of bounds .>=2."):
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t, adjoint_a=True).eval()
|
||||
self.evaluate(
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t, adjoint_a=True))
|
||||
dense_t = np.matrix([[1] * 500, [2] * 500, [3] * 500], dtype=np.float32)
|
||||
with self.assertRaisesOpError(
|
||||
"m .10. from index.0,1. out of bounds .>=2."):
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t, adjoint_a=True).eval()
|
||||
self.evaluate(
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t, adjoint_a=True))
|
||||
|
||||
def testInvalidIndicesForSparseTensorDenseMatmulOnGPU(self):
|
||||
# Note: use_gpu=False because nice errors are only returned from CPU kerne
|
||||
@ -181,13 +184,13 @@ class SparseTensorDenseMatMulTest(test.TestCase):
|
||||
expected_t = np.array([[0] * 5, [np.nan] * 5, [0] * 5], dtype=np.float32)
|
||||
self.assertAllClose(expected_t,
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t).eval())
|
||||
sparse_t, dense_t))
|
||||
dense_t = np.matrix([[1] * 500, [2] * 500], dtype=np.float32)
|
||||
expected_t = np.array(
|
||||
[[0] * 500, [np.nan] * 500, [0] * 500], dtype=np.float32)
|
||||
self.assertAllClose(expected_t,
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t).eval())
|
||||
sparse_t, dense_t))
|
||||
|
||||
# Repeat with adjoint_a, now the error is that the sparse index
|
||||
# is OOO w.r.t. the output. The GPU kernel can't do much here,
|
||||
@ -197,13 +200,13 @@ class SparseTensorDenseMatMulTest(test.TestCase):
|
||||
expected_t = np.array([[0] * 5, [0] * 5], dtype=np.float32)
|
||||
self.assertAllClose(expected_t,
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t, adjoint_a=True).eval())
|
||||
sparse_t, dense_t, adjoint_a=True))
|
||||
|
||||
dense_t = np.matrix([[1] * 500, [2] * 500, [3] * 500], dtype=np.float32)
|
||||
expected_t = np.array([[0] * 500, [0] * 500], dtype=np.float32)
|
||||
self.assertAllClose(expected_t,
|
||||
sparse_ops.sparse_tensor_dense_matmul(
|
||||
sparse_t, dense_t, adjoint_a=True).eval())
|
||||
sparse_t, dense_t, adjoint_a=True))
|
||||
|
||||
# Tests setting one dimension to be a high value.
|
||||
def _testLarge(self, np_dtype):
|
||||
|
||||
@ -162,7 +162,7 @@ class TensorArrayTest(test.TestCase):
|
||||
convert([[4.0, 5.0], [104.0, 105.0], [204.0, 205.0], [6.0, 7.0],
|
||||
[106.0, 107.0], [8.0, 9.0]]), c0)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testTensorArrayWriteConcat(self):
|
||||
self._testTensorArrayWriteConcat(dtypes.float32)
|
||||
self._testTensorArrayWriteConcat(dtypes.float64)
|
||||
@ -308,7 +308,7 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertAllEqual(convert([]).reshape(0, 2), d1)
|
||||
self.assertAllEqual(convert([[3.0, 301.0]]), d2)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testTensorArraySplitRead(self):
|
||||
self._testTensorArraySplitRead(dtypes.float32)
|
||||
self._testTensorArraySplitRead(dtypes.float64)
|
||||
@ -353,7 +353,7 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertAllEqual([[2.0]], g_d1)
|
||||
self.assertAllEqual(-2.0, g_d2)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayGradGrad(self):
|
||||
if not control_flow_util.ENABLE_CONTROL_FLOW_V2:
|
||||
self.skipTest("Legacy TensorArray does not support double derivatives.")
|
||||
@ -745,7 +745,7 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertAllEqual(c([[3.0, 2.0]]), grad_vals[0])
|
||||
self.assertAllEqual(c(-2.0), grad_vals[1])
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayGradientWriteRead(self):
|
||||
for dtype in (np.float32, np.float64, np.complex64, np.complex128):
|
||||
self._testTensorArrayGradientWriteReadType(dtype)
|
||||
@ -782,7 +782,7 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertAllClose([2.0 - 0.5 + 20.0, 3.0 + 1.5 + 30.0], grad_vals[0])
|
||||
self.assertAllEqual([4.0 + 40.0, 5.0 + 50.0], grad_vals[1])
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayGradientWritePackConcatAndRead(self):
|
||||
self._testTensorArrayGradientWritePackConcatAndRead()
|
||||
|
||||
@ -841,11 +841,11 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertEqual(len(grad_vals), 1)
|
||||
self.assertAllEqual([[2.0 - 1.5, 3.0 + 1.5], [4.0, 5.0]], grad_vals[0])
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayGradientUnpackRead(self):
|
||||
self._testTensorArrayGradientUnpackRead()
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayGradientSplitConcat(self):
|
||||
with self.session(use_gpu=True) as session:
|
||||
ta = tensor_array_ops.TensorArray(
|
||||
@ -891,7 +891,7 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertEqual(len(grad_vals), 1)
|
||||
self.assertAllEqual([[2.0, 3.0], [4.0, 5.0]], grad_vals[0])
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayGradientDynamicUnpackRead(self):
|
||||
self._testTensorArrayGradientDynamicUnpackRead()
|
||||
|
||||
@ -1056,7 +1056,7 @@ class TensorArrayTest(test.TestCase):
|
||||
grad = gradients_impl.gradients(loop(x), [x])[0]
|
||||
self.assertAllClose(31.0, self.evaluate(grad))
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerSumOfTwoReadVariablesWithoutRepeatGrad(self):
|
||||
with self.session(use_gpu=True) as session:
|
||||
a = array_ops.identity(
|
||||
@ -1092,7 +1092,7 @@ class TensorArrayTest(test.TestCase):
|
||||
def _grad_source_for_name(self, name):
|
||||
return tensor_array_grad._GetGradSource(constant_op.constant(0, name=name))
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerGetGradSource_Invalid(self):
|
||||
with self.assertRaises(ValueError):
|
||||
self._grad_source_for_name("")
|
||||
@ -1101,7 +1101,7 @@ class TensorArrayTest(test.TestCase):
|
||||
with self.assertRaises(ValueError):
|
||||
self._grad_source_for_name("foo/bar")
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerGetGradSource_NoEnclosingScope(self):
|
||||
self.assertEqual("gradients:0", self._grad_source_for_name("gradients"))
|
||||
self.assertEqual("gradients_0:0", self._grad_source_for_name("gradients_0"))
|
||||
@ -1113,7 +1113,7 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertEqual("gradients_0",
|
||||
self._grad_source_for_name("gradients_0/foo/bar"))
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerGetGradSource_EnclosingScope(self):
|
||||
self.assertEqual("foo/gradients:0",
|
||||
self._grad_source_for_name("foo/gradients"))
|
||||
@ -1128,13 +1128,13 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertEqual("foo/bar/gradients_0",
|
||||
self._grad_source_for_name("foo/bar/gradients_0/baz"))
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerGetGradSource_NestedUsesInnermost(self):
|
||||
self.assertEqual(
|
||||
"foo/gradients/bar/gradients_0",
|
||||
self._grad_source_for_name("foo/gradients/bar/gradients_0/baz"))
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerWriteShape(self):
|
||||
with self.session(use_gpu=True):
|
||||
ta = tensor_array_ops.TensorArray(
|
||||
@ -1159,7 +1159,7 @@ class TensorArrayTest(test.TestCase):
|
||||
with self.assertRaises(ValueError):
|
||||
w0.write(0, c2)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerPartlyUnknownShape(self):
|
||||
with self.session(use_gpu=True):
|
||||
ta = tensor_array_ops.TensorArray(
|
||||
@ -1237,7 +1237,7 @@ class TensorArrayTest(test.TestCase):
|
||||
def testUnpackShape(self):
|
||||
self._testUnpackShape()
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSplitShape(self):
|
||||
with self.session(use_gpu=True):
|
||||
ta = tensor_array_ops.TensorArray(
|
||||
@ -1269,7 +1269,7 @@ class TensorArrayTest(test.TestCase):
|
||||
tensor_shape.TensorShape(
|
||||
ta1.handle.op.get_attr("element_shape")).ndims, None)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerWriteUnknownShape(self):
|
||||
with self.session(use_gpu=True):
|
||||
ta = tensor_array_ops.TensorArray(
|
||||
@ -1293,11 +1293,11 @@ class TensorArrayTest(test.TestCase):
|
||||
grad_r0_vals = session.run(grad_r0)[0]
|
||||
self.assertAllEqual(grad_r0_vals, [1.0, 0.0])
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerGradientWhenNotAllComponentsRead(self):
|
||||
self._testGradientWhenNotAllComponentsRead()
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerWriteButNotAllComponentsReadGrad(self):
|
||||
with self.cached_session(use_gpu=True) as session:
|
||||
x0 = constant_op.constant(5.0)
|
||||
@ -1645,7 +1645,7 @@ class TensorArrayTest(test.TestCase):
|
||||
self.assertEqual(size0_v, 2)
|
||||
self.assertEqual(size1_v, 4)
|
||||
|
||||
@test_util.run_deprecated_v1
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayGradYsInCorrectScope(self):
|
||||
n_time = 1
|
||||
n_dim = 1
|
||||
@ -1664,6 +1664,7 @@ class TensorArrayTest(test.TestCase):
|
||||
vdx, vdy = self.evaluate([dx, dy])
|
||||
self.assertAllClose(vdx, vdy)
|
||||
|
||||
@test_util.deprecated_graph_mode_only
|
||||
def testSkipEagerTensorArrayInt64GPU(self):
|
||||
if not test.is_gpu_available():
|
||||
return
|
||||
|
||||
Loading…
Reference in New Issue
Block a user