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Update v1 only training/gradient_descent_test with graph scope.

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PiperOrigin-RevId: 320497973
Change-Id: I222336a46900a79e0c224ebe3f9fd6585cdc4f89
This commit is contained in:
Pavithra Vijay 2020-07-09 16:27:50 -07:00 committed by TensorFlower Gardener
parent ad35731ffd
commit 9937a3c6c9
1 changed files with 18 additions and 19 deletions
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37
tensorflow/python/training/gradient_descent_test.py
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@ -24,7 +24,6 @@ from tensorflow.python.eager import function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import test_util
from tensorflow.python.ops import embedding_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
@ -36,10 +35,10 @@ from tensorflow.python.training import gradient_descent
class GradientDescentOptimizerTest(test.TestCase):
@test_util.run_deprecated_v1
def testBasic(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
var0 = variables.Variable([1.0, 2.0], dtype=dtype)
var1 = variables.Variable([3.0, 4.0], dtype=dtype)
grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@ -60,10 +59,10 @@ class GradientDescentOptimizerTest(test.TestCase):
self.evaluate(var1))
self.assertEqual(0, len(optimizer.variables()))
@test_util.run_deprecated_v1
def testBasicResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@ -86,10 +85,10 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
self.evaluate(var1))
@test_util.run_deprecated_v1
def testBasicCallableParams(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@ -113,10 +112,10 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
self.evaluate(var1))
@test_util.run_deprecated_v1
def testMinimizeResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype)
x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
@ -140,10 +139,10 @@ class GradientDescentOptimizerTest(test.TestCase):
[[1.0 - np_grad * 4.0, 2.0 - np_grad * 5.0]], self.evaluate(var0))
self.assertAllCloseAccordingToType([3.0 - np_grad], self.evaluate(var1))
@test_util.run_deprecated_v1
def testMinimizeSparseResourceVariable(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype)
x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
@ -168,10 +167,10 @@ class GradientDescentOptimizerTest(test.TestCase):
[[1.0 - np_grad * 4.0, 2.0 - np_grad * 5.0]], self.evaluate(var0))
self.assertAllCloseAccordingToType([3.0 - np_grad], self.evaluate(var1))
@test_util.run_deprecated_v1
def testTensorLearningRate(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
var0 = variables.Variable([1.0, 2.0], dtype=dtype)
var1 = variables.Variable([3.0, 4.0], dtype=dtype)
grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
@ -191,10 +190,10 @@ class GradientDescentOptimizerTest(test.TestCase):
self.assertAllCloseAccordingToType([3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
self.evaluate(var1))
@test_util.run_deprecated_v1
def testGradWrtRef(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
opt = gradient_descent.GradientDescentOptimizer(3.0)
values = [1.0, 3.0]
vars_ = [variables.Variable([v], dtype=dtype) for v in values]
@ -203,10 +202,10 @@ class GradientDescentOptimizerTest(test.TestCase):
for grad, _ in grads_and_vars:
self.assertAllCloseAccordingToType([1.0], self.evaluate(grad))
@test_util.run_deprecated_v1
def testWithGlobalStep(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
global_step = variables.Variable(0, trainable=False)
var0 = variables.Variable([1.0, 2.0], dtype=dtype)
var1 = variables.Variable([3.0, 4.0], dtype=dtype)
@ -227,10 +226,10 @@ class GradientDescentOptimizerTest(test.TestCase):
self.evaluate(var1))
self.assertAllCloseAccordingToType(1, self.evaluate(global_step))
@test_util.run_deprecated_v1
def testSparseBasic(self):
for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
with self.cached_session():
# train.GradientDescentOptimizer is V1 only API.
with ops.Graph().as_default(), self.cached_session():
var0 = variables.Variable([[1.0], [2.0]], dtype=dtype)
var1 = variables.Variable([[3.0], [4.0]], dtype=dtype)
grads0 = ops.IndexedSlices(