path: "tensorflow.keras.optimizers.Adagrad" tf_class { is_instance: "" is_instance: "" is_instance: "" is_instance: "" member { name: "clipnorm" mtype: "" } member { name: "clipvalue" mtype: "" } member { name: "global_clipnorm" mtype: "" } member { name: "iterations" mtype: "" } member { name: "weights" mtype: "" } 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\', \'shape\'], varargs=None, keywords=None, defaults=[\'zeros\', \'None\'], " } 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\', \'experimental_aggregate_gradients\'], varargs=None, keywords=None, defaults=[\'None\', \'True\'], " } 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\', \'tape\'], varargs=None, keywords=None, defaults=[\'None\', \'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" } }