From 33910c7d76f855902d1a48c927675743fc467d5c Mon Sep 17 00:00:00 2001
From: Francois Chollet <fchollet@google.com>
Date: Thu, 7 Jan 2021 22:49:11 -0800
Subject: [PATCH] Graduate to core the following experimental learning rate
schedules: CosineDecay, CosineDecayRestarts.
Remove from the API the following experimental learning rate schedules: LinearCosineDecay, NoisyLinearCosineDecay.
PiperOrigin-RevId: 350704711
Change-Id: Iebe9bc0eff38f79684e8d2f030fd838d06176494
---
RELEASE.md | 3 +
.../optimizer_v2/learning_rate_schedule.py | 30 ++++----
.../learning_rate_schedule_test.py | 76 -------------------
.../v1/tensorflow.keras.experimental.pbtxt | 8 --
...rs.schedules.-cosine-decay-restarts.pbtxt} | 6 +-
....optimizers.schedules.-cosine-decay.pbtxt} | 6 +-
...ensorflow.keras.optimizers.schedules.pbtxt | 8 ++
.../v2/tensorflow.keras.experimental.pbtxt | 8 --
...ers.schedules.-cosine-decay-restarts.pbtxt | 18 +++++
....optimizers.schedules.-cosine-decay.pbtxt} | 6 +-
...ensorflow.keras.optimizers.schedules.pbtxt | 8 ++
...ers.schedules.-cosine-decay-restarts.pbtxt | 18 +++++
....optimizers.schedules.-cosine-decay.pbtxt} | 6 +-
.../v2/tensorflow.optimizers.schedules.pbtxt | 8 ++
14 files changed, 91 insertions(+), 118 deletions(-)
rename tensorflow/tools/api/golden/{v2/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt => v1/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt} (58%)
rename tensorflow/tools/api/golden/v1/{tensorflow.keras.experimental.-linear-cosine-decay.pbtxt => tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt} (70%)
create mode 100644 tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt
rename tensorflow/tools/api/golden/v2/{tensorflow.keras.experimental.-linear-cosine-decay.pbtxt => tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt} (70%)
create mode 100644 tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-cosine-decay-restarts.pbtxt
rename tensorflow/tools/api/golden/{v1/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt => v2/tensorflow.optimizers.schedules.-cosine-decay.pbtxt} (65%)
diff --git a/RELEASE.md b/RELEASE.md
index ff16b9b9606..a4a569938d5 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -36,6 +36,9 @@
* Improvements to model saving/loading:
* `model.load_weights` now accepts paths to saved models.
* Keras inputs can now be created directly from arbitrary `tf.TypeSpecs`.
+ * Two new learning rate schedules added:
+ `tf.keras.optimizers.schedules.CosineDecay` and
+ `tf.keras.optimizers.schedules.CosineDecayRestarts`.
* `tf.data`:
* Exposing `tf.data.experimental.ExternalStatePolicy`, which can be used
diff --git a/tensorflow/python/keras/optimizer_v2/learning_rate_schedule.py b/tensorflow/python/keras/optimizer_v2/learning_rate_schedule.py
index 30b4f2145bb..64fccc54521 100644
--- a/tensorflow/python/keras/optimizer_v2/learning_rate_schedule.py
+++ b/tensorflow/python/keras/optimizer_v2/learning_rate_schedule.py
@@ -65,7 +65,7 @@ class LearningRateSchedule(object):
class ExponentialDecay(LearningRateSchedule):
"""A LearningRateSchedule that uses an exponential decay schedule.
- When training a model, it is often recommended to lower the learning rate as
+ When training a model, it is often useful to lower the learning rate as
the training progresses. This schedule applies an exponential decay function
to an optimizer step, given a provided initial learning rate.
@@ -416,7 +416,7 @@ class PolynomialDecay(LearningRateSchedule):
class InverseTimeDecay(LearningRateSchedule):
"""A LearningRateSchedule that uses an inverse time decay schedule.
- When training a model, it is often recommended to lower the learning rate as
+ When training a model, it is often useful to lower the learning rate as
the training progresses. This schedule applies the inverse decay function
to an optimizer step, given a provided initial learning rate.
It requires a `step` value to compute the decayed learning rate. You can
@@ -518,14 +518,15 @@ class InverseTimeDecay(LearningRateSchedule):
}
-@keras_export("keras.experimental.CosineDecay")
+@keras_export("keras.optimizers.schedules.CosineDecay",
+ "keras.experimental.CosineDecay")
class CosineDecay(LearningRateSchedule):
"""A LearningRateSchedule that uses a cosine decay schedule.
- See [Loshchilov & Hutter, ICLR2016], SGDR: Stochastic Gradient Descent
- with Warm Restarts. https://arxiv.org/abs/1608.03983
+ See [Loshchilov & Hutter, ICLR2016](https://arxiv.org/abs/1608.03983),
+ SGDR: Stochastic Gradient Descent with Warm Restarts.
- When training a model, it is often recommended to lower the learning rate as
+ When training a model, it is often useful to lower the learning rate as
the training progresses. This schedule applies a cosine decay function
to an optimizer step, given a provided initial learning rate.
It requires a `step` value to compute the decayed learning rate. You can
@@ -547,7 +548,7 @@ class CosineDecay(LearningRateSchedule):
Example usage:
```python
decay_steps = 1000
- lr_decayed_fn = tf.keras.experimental.CosineDecay(
+ lr_decayed_fn = tf.keras.optimizers.schedules.CosineDecay(
initial_learning_rate, decay_steps)
```
@@ -611,14 +612,15 @@ class CosineDecay(LearningRateSchedule):
}
-@keras_export("keras.experimental.CosineDecayRestarts")
+@keras_export("keras.optimizers.schedules.CosineDecayRestarts",
+ "keras.experimental.CosineDecayRestarts")
class CosineDecayRestarts(LearningRateSchedule):
"""A LearningRateSchedule that uses a cosine decay schedule with restarts.
- See [Loshchilov & Hutter, ICLR2016], SGDR: Stochastic Gradient Descent
- with Warm Restarts. https://arxiv.org/abs/1608.03983
+ See [Loshchilov & Hutter, ICLR2016](https://arxiv.org/abs/1608.03983),
+ SGDR: Stochastic Gradient Descent with Warm Restarts.
- When training a model, it is often recommended to lower the learning rate as
+ When training a model, it is often useful to lower the learning rate as
the training progresses. This schedule applies a cosine decay function with
restarts to an optimizer step, given a provided initial learning rate.
It requires a `step` value to compute the decayed learning rate. You can
@@ -637,7 +639,7 @@ class CosineDecayRestarts(LearningRateSchedule):
```python
first_decay_steps = 1000
lr_decayed_fn = (
- tf.keras.experimental.CosineDecayRestarts(
+ tf.keras.optimizers.schedules.CosineDecayRestarts(
initial_learning_rate,
first_decay_steps))
```
@@ -737,7 +739,7 @@ class CosineDecayRestarts(LearningRateSchedule):
}
-@keras_export("keras.experimental.LinearCosineDecay")
+# Note: this code is still used by V1 APIs.
class LinearCosineDecay(LearningRateSchedule):
"""A LearningRateSchedule that uses a linear cosine decay schedule.
@@ -855,7 +857,7 @@ class LinearCosineDecay(LearningRateSchedule):
}
-@keras_export("keras.experimental.NoisyLinearCosineDecay")
+# Note: this code is still used by V1 APIs.
class NoisyLinearCosineDecay(LearningRateSchedule):
"""A LearningRateSchedule that uses a noisy linear cosine decay schedule.
diff --git a/tensorflow/python/keras/optimizer_v2/learning_rate_schedule_test.py b/tensorflow/python/keras/optimizer_v2/learning_rate_schedule_test.py
index e7e89780f70..65f930822df 100644
--- a/tensorflow/python/keras/optimizer_v2/learning_rate_schedule_test.py
+++ b/tensorflow/python/keras/optimizer_v2/learning_rate_schedule_test.py
@@ -433,81 +433,5 @@ class CosineDecayRestartsTestV2(test_util.TensorFlowTestCase,
self.assertAllClose(self.evaluate(decayed_lr(step)), expected, 1e-6)
-@combinations.generate(combinations.combine(serialize=[False, True],
- mode=["graph", "eager"]))
-class LinearCosineDecayTestV2(test_util.TensorFlowTestCase,
- parameterized.TestCase):
-
- def np_linear_cosine_decay(self,
- step,
- decay_steps,
- alpha=0.0,
- beta=0.001,
- num_periods=0.5):
- step = min(step, decay_steps)
- linear_decayed = float(decay_steps - step) / decay_steps
- fraction = 2.0 * num_periods * step / float(decay_steps)
- cosine_decayed = 0.5 * (1.0 + math.cos(math.pi * fraction))
- return (alpha + linear_decayed) * cosine_decayed + beta
-
- def testDefaultDecay(self, serialize):
- num_training_steps = 1000
- initial_lr = 1.0
- for step in range(0, 1500, 250):
- decayed_lr = learning_rate_schedule.LinearCosineDecay(
- initial_lr, num_training_steps)
- decayed_lr = _maybe_serialized(decayed_lr, serialize)
- expected = self.np_linear_cosine_decay(step, num_training_steps)
- self.assertAllClose(self.evaluate(decayed_lr(step)), expected, 1e-6)
-
- def testNonDefaultDecay(self, serialize):
- num_training_steps = 1000
- initial_lr = 1.0
- for step in range(0, 1500, 250):
- decayed_lr = learning_rate_schedule.LinearCosineDecay(
- initial_lr,
- num_training_steps,
- alpha=0.1,
- beta=1e-4,
- num_periods=5)
- decayed_lr = _maybe_serialized(decayed_lr, serialize)
- expected = self.np_linear_cosine_decay(
- step, num_training_steps, alpha=0.1, beta=1e-4, num_periods=5)
- self.assertAllClose(self.evaluate(decayed_lr(step)), expected, 1e-6)
-
-
-@combinations.generate(combinations.combine(serialize=[False, True],
- mode=["graph", "eager"]))
-class NoisyLinearCosineDecayTestV2(test_util.TensorFlowTestCase,
- parameterized.TestCase):
-
- def testDefaultNoisyLinearCosine(self, serialize):
- num_training_steps = 1000
- initial_lr = 1.0
- for step in range(0, 1500, 250):
- # No numerical check because of noise
- decayed_lr = learning_rate_schedule.NoisyLinearCosineDecay(
- initial_lr, num_training_steps)
- decayed_lr = _maybe_serialized(decayed_lr, serialize)
- # Cannot be deterministically tested
- self.evaluate(decayed_lr(step))
-
- def testNonDefaultNoisyLinearCosine(self, serialize):
- num_training_steps = 1000
- initial_lr = 1.0
- for step in range(0, 1500, 250):
- # No numerical check because of noise
- decayed_lr = learning_rate_schedule.NoisyLinearCosineDecay(
- initial_lr,
- num_training_steps,
- initial_variance=0.5,
- variance_decay=0.1,
- alpha=0.1,
- beta=1e-4,
- num_periods=5)
- decayed_lr = _maybe_serialized(decayed_lr, serialize)
- # Cannot be deterministically tested
- self.evaluate(decayed_lr(step))
-
if __name__ == "__main__":
test.main()
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.pbtxt
index 340f2705b85..16759eb0bed 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.pbtxt
@@ -8,18 +8,10 @@ tf_module {
name: "CosineDecayRestarts"
mtype: "<type \'type\'>"
}
- member {
- name: "LinearCosineDecay"
- mtype: "<type \'type\'>"
- }
member {
name: "LinearModel"
mtype: "<type \'type\'>"
}
- member {
- name: "NoisyLinearCosineDecay"
- mtype: "<type \'type\'>"
- }
member {
name: "PeepholeLSTMCell"
mtype: "<type \'type\'>"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt
similarity index 58%
rename from tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt
rename to tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt
index 8ea3c6beb1c..41a5cbfe11c 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt
@@ -1,11 +1,11 @@
-path: "tensorflow.keras.experimental.NoisyLinearCosineDecay"
+path: "tensorflow.keras.optimizers.schedules.CosineDecayRestarts"
tf_class {
- is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.NoisyLinearCosineDecay\'>"
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.CosineDecayRestarts\'>"
is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
is_instance: "<type \'object\'>"
member_method {
name: "__init__"
- argspec: "args=[\'self\', \'initial_learning_rate\', \'decay_steps\', \'initial_variance\', \'variance_decay\', \'num_periods\', \'alpha\', \'beta\', \'name\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0.55\', \'0.5\', \'0.0\', \'0.001\', \'None\'], "
+ argspec: "args=[\'self\', \'initial_learning_rate\', \'first_decay_steps\', \'t_mul\', \'m_mul\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'2.0\', \'1.0\', \'0.0\', \'None\'], "
}
member_method {
name: "from_config"
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-linear-cosine-decay.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt
similarity index 70%
rename from tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-linear-cosine-decay.pbtxt
rename to tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt
index f083120b52c..299ff85e813 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-linear-cosine-decay.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt
@@ -1,11 +1,11 @@
-path: "tensorflow.keras.experimental.LinearCosineDecay"
+path: "tensorflow.keras.optimizers.schedules.CosineDecay"
tf_class {
- is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LinearCosineDecay\'>"
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.CosineDecay\'>"
is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
is_instance: "<type \'object\'>"
member_method {
name: "__init__"
- argspec: "args=[\'self\', \'initial_learning_rate\', \'decay_steps\', \'num_periods\', \'alpha\', \'beta\', \'name\'], varargs=None, keywords=None, defaults=[\'0.5\', \'0.0\', \'0.001\', \'None\'], "
+ argspec: "args=[\'self\', \'initial_learning_rate\', \'decay_steps\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\'], "
}
member_method {
name: "from_config"
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.pbtxt
index 024e472a734..3ecc437199f 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.keras.optimizers.schedules.pbtxt
@@ -1,5 +1,13 @@
path: "tensorflow.keras.optimizers.schedules"
tf_module {
+ member {
+ name: "CosineDecay"
+ mtype: "<type \'type\'>"
+ }
+ member {
+ name: "CosineDecayRestarts"
+ mtype: "<type \'type\'>"
+ }
member {
name: "ExponentialDecay"
mtype: "<type \'type\'>"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.pbtxt
index 2a0f0c780f1..26b8df6600e 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.pbtxt
@@ -8,18 +8,10 @@ tf_module {
name: "CosineDecayRestarts"
mtype: "<type \'type\'>"
}
- member {
- name: "LinearCosineDecay"
- mtype: "<type \'type\'>"
- }
member {
name: "LinearModel"
mtype: "<type \'type\'>"
}
- member {
- name: "NoisyLinearCosineDecay"
- mtype: "<type \'type\'>"
- }
member {
name: "PeepholeLSTMCell"
mtype: "<type \'type\'>"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt
new file mode 100644
index 00000000000..41a5cbfe11c
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.-cosine-decay-restarts.pbtxt
@@ -0,0 +1,18 @@
+path: "tensorflow.keras.optimizers.schedules.CosineDecayRestarts"
+tf_class {
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.CosineDecayRestarts\'>"
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
+ is_instance: "<type \'object\'>"
+ member_method {
+ name: "__init__"
+ argspec: "args=[\'self\', \'initial_learning_rate\', \'first_decay_steps\', \'t_mul\', \'m_mul\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'2.0\', \'1.0\', \'0.0\', \'None\'], "
+ }
+ member_method {
+ name: "from_config"
+ argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_config"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-linear-cosine-decay.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt
similarity index 70%
rename from tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-linear-cosine-decay.pbtxt
rename to tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt
index f083120b52c..299ff85e813 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.keras.experimental.-linear-cosine-decay.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.-cosine-decay.pbtxt
@@ -1,11 +1,11 @@
-path: "tensorflow.keras.experimental.LinearCosineDecay"
+path: "tensorflow.keras.optimizers.schedules.CosineDecay"
tf_class {
- is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LinearCosineDecay\'>"
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.CosineDecay\'>"
is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
is_instance: "<type \'object\'>"
member_method {
name: "__init__"
- argspec: "args=[\'self\', \'initial_learning_rate\', \'decay_steps\', \'num_periods\', \'alpha\', \'beta\', \'name\'], varargs=None, keywords=None, defaults=[\'0.5\', \'0.0\', \'0.001\', \'None\'], "
+ argspec: "args=[\'self\', \'initial_learning_rate\', \'decay_steps\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\'], "
}
member_method {
name: "from_config"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.pbtxt
index 024e472a734..3ecc437199f 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.keras.optimizers.schedules.pbtxt
@@ -1,5 +1,13 @@
path: "tensorflow.keras.optimizers.schedules"
tf_module {
+ member {
+ name: "CosineDecay"
+ mtype: "<type \'type\'>"
+ }
+ member {
+ name: "CosineDecayRestarts"
+ mtype: "<type \'type\'>"
+ }
member {
name: "ExponentialDecay"
mtype: "<type \'type\'>"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-cosine-decay-restarts.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-cosine-decay-restarts.pbtxt
new file mode 100644
index 00000000000..1bc5e3fc105
--- /dev/null
+++ b/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-cosine-decay-restarts.pbtxt
@@ -0,0 +1,18 @@
+path: "tensorflow.optimizers.schedules.CosineDecayRestarts"
+tf_class {
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.CosineDecayRestarts\'>"
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
+ is_instance: "<type \'object\'>"
+ member_method {
+ name: "__init__"
+ argspec: "args=[\'self\', \'initial_learning_rate\', \'first_decay_steps\', \'t_mul\', \'m_mul\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'2.0\', \'1.0\', \'0.0\', \'None\'], "
+ }
+ member_method {
+ name: "from_config"
+ argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
+ }
+ member_method {
+ name: "get_config"
+ argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+ }
+}
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-cosine-decay.pbtxt
similarity index 65%
rename from tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt
rename to tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-cosine-decay.pbtxt
index 8ea3c6beb1c..6d21f4bb8b9 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.keras.experimental.-noisy-linear-cosine-decay.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-cosine-decay.pbtxt
@@ -1,11 +1,11 @@
-path: "tensorflow.keras.experimental.NoisyLinearCosineDecay"
+path: "tensorflow.optimizers.schedules.CosineDecay"
tf_class {
- is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.NoisyLinearCosineDecay\'>"
+ is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.CosineDecay\'>"
is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
is_instance: "<type \'object\'>"
member_method {
name: "__init__"
- argspec: "args=[\'self\', \'initial_learning_rate\', \'decay_steps\', \'initial_variance\', \'variance_decay\', \'num_periods\', \'alpha\', \'beta\', \'name\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0.55\', \'0.5\', \'0.0\', \'0.001\', \'None\'], "
+ argspec: "args=[\'self\', \'initial_learning_rate\', \'decay_steps\', \'alpha\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'None\'], "
}
member_method {
name: "from_config"
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.pbtxt
index 8e1e61b7662..775b2cafd4f 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.pbtxt
@@ -1,5 +1,13 @@
path: "tensorflow.optimizers.schedules"
tf_module {
+ member {
+ name: "CosineDecay"
+ mtype: "<type \'type\'>"
+ }
+ member {
+ name: "CosineDecayRestarts"
+ mtype: "<type \'type\'>"
+ }
member {
name: "ExponentialDecay"
mtype: "<type \'type\'>"