Add module aliases for v2 optimizers tf.optimizers = tf.keras.optimizers

PiperOrigin-RevId: 233119697

tensorflow/api_template.__init__.py

@@ -115,5 +115,6 @@ except NameError:
 if hasattr(_current_module, 'keras'):
   losses = keras.losses
   metrics = keras.metrics
+  optimizers = keras.optimizers
 
 # pylint: enable=undefined-variable

tensorflow/compat_template.__init__.py

@@ -48,3 +48,4 @@ _current_module = _sys.modules[__name__]
 if hasattr(_current_module, 'keras'):
   losses = keras.losses
   metrics = keras.metrics
+  optimizers = keras.optimizers

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-adadelta.pbtxt

@@ -0,0 +1,71 @@
+path: "tensorflow.optimizers.Adadelta"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.adadelta.Adadelta\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'rho\', \'epsilon\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.95\', \'1e-07\', \'Adadelta\'], "
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-adagrad.pbtxt

@@ -0,0 +1,71 @@
+path: "tensorflow.optimizers.Adagrad"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.adagrad.Adagrad\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'initial_accumulator_value\', \'epsilon\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.1\', \'1e-07\', \'Adagrad\'], "
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-adam.pbtxt

@@ -0,0 +1,71 @@
+path: "tensorflow.optimizers.Adam"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.adam.Adam\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'amsgrad\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.9\', \'0.999\', \'1e-07\', \'False\', \'Adam\'], "
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-adamax.pbtxt

@@ -0,0 +1,71 @@
+path: "tensorflow.optimizers.Adamax"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.adamax.Adamax\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.9\', \'0.999\', \'1e-07\', \'Adamax\'], "
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-nadam.pbtxt

@@ -0,0 +1,71 @@
+path: "tensorflow.optimizers.Nadam"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.nadam.Nadam\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.9\', \'0.999\', \'1e-07\', \'Nadam\'], "
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-optimizer.pbtxt

@@ -0,0 +1,70 @@
+path: "tensorflow.optimizers.Optimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-r-m-sprop.pbtxt

@@ -0,0 +1,71 @@
+path: "tensorflow.optimizers.RMSprop"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.rmsprop.RMSprop\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'rho\', \'momentum\', \'epsilon\', \'centered\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.9\', \'0.0\', \'1e-07\', \'False\', \'RMSprop\'], "
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.-s-g-d.pbtxt

@@ -0,0 +1,71 @@
+path: "tensorflow.optimizers.SGD"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.gradient_descent.SGD\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.optimizer_v2.OptimizerV2\'>"
+  is_instance: "<class \'tensorflow.python.training.checkpointable.base.Checkpointable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "iterations"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "weights"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'momentum\', \'nesterov\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'0.001\', \'0.0\', \'False\', \'SGD\'], "
+  }
+  member_method {
+    name: "add_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\', \'initializer\'], varargs=None, keywords=None, defaults=[\'zeros\'], "
+  }
+  member_method {
+    name: "add_weight"
+    argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'trainable\', \'synchronization\', \'aggregation\'], varargs=None, keywords=None, defaults=[\'None\', \'zeros\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_config"
+    argspec: "args=[\'cls\', \'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_config"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_gradients"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'slot_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_updates"
+    argspec: "args=[\'self\', \'loss\', \'params\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_weights"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'grad_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "set_weights"
+    argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.pbtxt

@@ -0,0 +1,51 @@
+path: "tensorflow.optimizers"
+tf_module {
+  member {
+    name: "Adadelta"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Adagrad"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Adam"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Adamax"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Nadam"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Optimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "RMSprop"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SGD"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "schedules"
+    mtype: "<type \'module\'>"
+  }
+  member_method {
+    name: "deserialize"
+    argspec: "args=[\'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get"
+    argspec: "args=[\'identifier\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "serialize"
+    argspec: "args=[\'optimizer\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-exponential-decay.pbtxt

@@ -0,0 +1,18 @@
+path: "tensorflow.optimizers.schedules.ExponentialDecay"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.ExponentialDecay\'>"
+  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\', \'decay_rate\', \'staircase\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'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"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-inverse-time-decay.pbtxt

@@ -0,0 +1,18 @@
+path: "tensorflow.optimizers.schedules.InverseTimeDecay"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.InverseTimeDecay\'>"
+  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\', \'decay_rate\', \'staircase\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'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"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-learning-rate-schedule.pbtxt

@@ -0,0 +1,16 @@
+path: "tensorflow.optimizers.schedules.LearningRateSchedule"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+  }
+  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"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-piecewise-constant-decay.pbtxt

@@ -0,0 +1,18 @@
+path: "tensorflow.optimizers.schedules.PiecewiseConstantDecay"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.PiecewiseConstantDecay\'>"
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.LearningRateSchedule\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'boundaries\', \'values\', \'name\'], 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"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.-polynomial-decay.pbtxt

@@ -0,0 +1,18 @@
+path: "tensorflow.optimizers.schedules.PolynomialDecay"
+tf_class {
+  is_instance: "<class \'tensorflow.python.keras.optimizer_v2.learning_rate_schedule.PolynomialDecay\'>"
+  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\', \'end_learning_rate\', \'power\', \'cycle\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0001\', \'1.0\', \'False\', \'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"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.optimizers.schedules.pbtxt

@@ -0,0 +1,31 @@
+path: "tensorflow.optimizers.schedules"
+tf_module {
+  member {
+    name: "ExponentialDecay"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "InverseTimeDecay"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "LearningRateSchedule"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "PiecewiseConstantDecay"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "PolynomialDecay"
+    mtype: "<type \'type\'>"
+  }
+  member_method {
+    name: "deserialize"
+    argspec: "args=[\'config\', \'custom_objects\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize"
+    argspec: "args=[\'learning_rate_schedule\'], varargs=None, keywords=None, defaults=None"
+  }
+}

tensorflow/tools/api/golden/v2/tensorflow.pbtxt

@@ -232,6 +232,10 @@ tf_module {
     name: "ones_initializer"
     mtype: "<type \'type\'>"
   }
+  member {
+    name: "optimizers"
+    mtype: "<type \'module\'>"
+  }
   member {
     name: "qint16"
     mtype: "<class \'tensorflow.python.framework.dtypes.DType\'>"