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path: "tensorflow.keras.optimizers.Adagrad"
tf_class {
is_instance: "<class \'tensorflow.python.keras.optimizers.Adagrad\'>"
is_instance: "<class \'tensorflow.python.keras.optimizers.Optimizer\'>"
is_instance: "<type \'object\'>"
member_method {
name: "__init__"
argspec: "args=[\'self\', \'lr\', \'epsilon\', \'decay\'], varargs=None, keywords=kwargs, defaults=[\'0.01\', \'None\', \'0.0\'], "
}
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: "get_gradients"
argspec: "args=[\'self\', \'loss\', \'params\'], 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: "set_weights"
argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
}
}
|
