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Export Ftrl optimizer.

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PiperOrigin-RevId: 433338123
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Chen Qian 2022-03-08 16:20:53 -08:00 committed by TensorFlower Gardener
parent a341b0eb2c
commit 9577fa87b7
5 changed files with 107 additions and 0 deletions
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1
keras/api/BUILD
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@ -95,6 +95,7 @@ keras_packages = [
"keras.optimizers.optimizer_experimental.adagrad",
"keras.optimizers.optimizer_experimental.adam",
"keras.optimizers.optimizer_experimental.adamax",
"keras.optimizers.optimizer_experimental.ftrl",
"keras.optimizers.optimizer_experimental.sgd",
"keras.optimizers.optimizer_experimental.optimizer",
"keras.optimizers.optimizer_experimental.rmsprop",

98
keras/api/golden/v2/tensorflow.keras.optimizers.experimental.-ftrl.pbtxt Normal file
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@ -0,0 +1,98 @@
path: "tensorflow.keras.optimizers.experimental.Ftrl"
tf_class {
is_instance: "<class \'keras.optimizers.optimizer_experimental.ftrl.Ftrl\'>"
is_instance: "<class \'keras.optimizers.optimizer_experimental.optimizer.Optimizer\'>"
is_instance: "<class \'keras.optimizers.optimizer_experimental.optimizer._BaseOptimizer\'>"
is_instance: "<class \'tensorflow.python.module.module.Module\'>"
is_instance: "<class \'tensorflow.python.training.tracking.autotrackable.AutoTrackable\'>"
is_instance: "<class \'tensorflow.python.training.tracking.base.Trackable\'>"
is_instance: "<type \'object\'>"
member {
name: "iterations"
mtype: "<type \'property\'>"
}
member {
name: "learning_rate"
mtype: "<type \'property\'>"
}
member {
name: "lr"
mtype: "<type \'property\'>"
}
member {
name: "name"
mtype: "<type \'property\'>"
}
member {
name: "name_scope"
mtype: "<type \'property\'>"
}
member {
name: "non_trainable_variables"
mtype: "<type \'property\'>"
}
member {
name: "submodules"
mtype: "<type \'property\'>"
}
member {
name: "trainable_variables"
mtype: "<type \'property\'>"
}
member {
name: "variables"
mtype: "<type \'property\'>"
}
member_method {
name: "__init__"
argspec: "args=[\'self\', \'learning_rate\', \'learning_rate_power\', \'initial_accumulator_value\', \'l1_regularization_strength\', \'l2_regularization_strength\', \'l2_shrinkage_regularization_strength\', \'beta\', \'clipnorm\', \'clipvalue\', \'global_clipnorm\', \'use_ema\', \'ema_momentum\', \'ema_overwrite_frequency\', \'jit_compile\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'-0.5\', \'0.1\', \'0.0\', \'0.0\', \'0.0\', \'0.0\', \'None\', \'None\', \'None\', \'False\', \'0.99\', \'None\', \'False\', \'Ftrl\'], "
}
member_method {
name: "add_variable"
argspec: "args=[\'self\', \'shape\', \'dtype\', \'initializer\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\'], "
}
member_method {
name: "add_variable_from_reference"
argspec: "args=[\'self\', \'model_variable\', \'variable_name\', \'initial_value\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "aggregate_gradients"
argspec: "args=[\'self\', \'grads_and_vars\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "apply_gradients"
argspec: "args=[\'self\', \'grads_and_vars\', \'skip_gradients_aggregation\'], varargs=None, keywords=None, defaults=[\'False\'], "
}
member_method {
name: "build"
argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "compute_gradients"
argspec: "args=[\'self\', \'loss\', \'var_list\', \'tape\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "finalize_variable_values"
argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=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"
}
member_method {
name: "minimize"
argspec: "args=[\'self\', \'loss\', \'var_list\', \'tape\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "update_step"
argspec: "args=[\'self\', \'gradient\', \'variable\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "with_name_scope"
argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"
}
}

4
keras/api/golden/v2/tensorflow.keras.optimizers.experimental.pbtxt
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@ -20,6 +20,10 @@ tf_module {
name: "Adamax"
mtype: "<type \'type\'>"
}
member {
name: "Ftrl"
mtype: "<type \'type\'>"
}
member {
name: "Optimizer"
mtype: "<type \'type\'>"

1
keras/optimizers/__init__.py
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@ -27,6 +27,7 @@ from keras.optimizers.optimizer_experimental import adagrad as adagrad_experimen
from keras.optimizers.optimizer_experimental import adam as adam_experimental
from keras.optimizers.optimizer_experimental import adamax as adamax_experimental
from keras.optimizers.optimizer_experimental import adamw as adamw_experimental
from keras.optimizers.optimizer_experimental import ftrl as ftrl_experimental
from keras.optimizers.optimizer_experimental import rmsprop as rmsprop_experimental
from keras.optimizers.optimizer_experimental import sgd as sgd_experimental
from keras.optimizers.optimizer_v1 import Optimizer

3
keras/optimizers/optimizer_experimental/ftrl.py
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@ -17,10 +17,13 @@
from keras.optimizers.optimizer_experimental import optimizer
from keras.utils import generic_utils
import tensorflow.compat.v2 as tf
# pylint: disable=g-direct-tensorflow-import
from tensorflow.python.util.tf_export import keras_export
# pylint: disable=g-classes-have-attributes
@generic_utils.register_keras_serializable()
@keras_export('keras.optimizers.experimental.Ftrl', v1=[])
class Ftrl(optimizer.Optimizer):
r"""Optimizer that implements the FTRL algorithm.