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path: "tensorflow.keras.callbacks.TerminateOnNaN"
tf_class {
is_instance: "<class \'tensorflow.python.keras.callbacks.TerminateOnNaN\'>"
is_instance: "<class \'tensorflow.python.keras.callbacks.Callback\'>"
is_instance: "<type \'object\'>"
member_method {
name: "__init__"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "on_batch_begin"
argspec: "args=[\'self\', \'batch\', \'logs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "on_batch_end"
argspec: "args=[\'self\', \'batch\', \'logs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "on_epoch_begin"
argspec: "args=[\'self\', \'epoch\', \'logs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "on_epoch_end"
argspec: "args=[\'self\', \'epoch\', \'logs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "on_train_begin"
argspec: "args=[\'self\', \'logs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "on_train_end"
argspec: "args=[\'self\', \'logs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "set_model"
argspec: "args=[\'self\', \'model\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "set_params"
argspec: "args=[\'self\', \'params\'], varargs=None, keywords=None, defaults=None"
}
}
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