experiments/STT-tensorflow
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remove v1 only decorator

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PiperOrigin-RevId: 323821989
Change-Id: Id0cb6221990644f70170891a6a9dbaa6b45e64a8
This commit is contained in:
Yanhua Sun 2020-07-29 10:54:22 -07:00 committed by TensorFlower Gardener
parent 50caa9d728
commit 6951872858
1 changed files with 47 additions and 43 deletions
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16
tensorflow/python/framework/tensor_spec_test.py
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@ -22,6 +22,7 @@ import pickle
import numpy as np
from tensorflow.python.eager import context
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
@ -51,8 +52,9 @@ class TensorSpecTest(test_util.TensorFlowTestCase):
desc = tensor_spec.TensorSpec(shape=None, dtype=dtypes.float32)
self.assertEqual(desc.shape, tensor_shape.TensorShape(None))
@test_util.run_deprecated_v1
def testShapeCompatibility(self):
# This test needs a placeholder which means we need to construct a graph.
with ops.Graph().as_default():
unknown = array_ops.placeholder(dtypes.int64)
partial = array_ops.placeholder(dtypes.int64, shape=[None, 1])
full = array_ops.placeholder(dtypes.int64, shape=[2, 3])
@ -82,10 +84,9 @@ class TensorSpecTest(test_util.TensorFlowTestCase):
self.assertFalse(desc_rank3.is_compatible_with(full))
self.assertTrue(desc_rank3.is_compatible_with(rank3))
@test_util.run_deprecated_v1
def testTypeCompatibility(self):
floats = array_ops.placeholder(dtypes.float32, shape=[10, 10])
ints = array_ops.placeholder(dtypes.int32, shape=[10, 10])
floats = constant_op.constant(1, dtype=dtypes.float32, shape=[10, 10])
ints = constant_op.constant(1, dtype=dtypes.int32, shape=[10, 10])
desc = tensor_spec.TensorSpec(shape=(10, 10), dtype=dtypes.float32)
self.assertTrue(desc.is_compatible_with(floats))
self.assertFalse(desc.is_compatible_with(ints))
@ -118,20 +119,23 @@ class TensorSpecTest(test_util.TensorFlowTestCase):
spec_2 = tensor_spec.TensorSpec.from_spec(spec_1)
self.assertEqual(spec_1, spec_2)
@test_util.run_deprecated_v1
def testFromTensor(self):
zero = constant_op.constant(0)
spec = tensor_spec.TensorSpec.from_tensor(zero)
self.assertEqual(spec.dtype, dtypes.int32)
self.assertEqual(spec.shape, [])
# Tensor.name is meaningless when eager execution is enabled.
if not context.executing_eagerly():
self.assertEqual(spec.name, "Const")
@test_util.run_deprecated_v1
def testFromPlaceholder(self):
# This test needs a placeholder which means we need to construct a graph.
with ops.Graph().as_default():
unknown = array_ops.placeholder(dtypes.int64, name="unknown")
partial = array_ops.placeholder(dtypes.float32,
shape=[None, 1],
name="partial")
spec_1 = tensor_spec.TensorSpec.from_tensor(unknown)
self.assertEqual(spec_1.dtype, dtypes.int64)
self.assertEqual(spec_1.shape, None)