path: "tensorflow.keras.callbacks.ModelCheckpoint" tf_class { is_instance: "" is_instance: "" is_instance: "" member_method { name: "__init__" argspec: "args=[\'self\', \'filepath\', \'monitor\', \'verbose\', \'save_best_only\', \'save_weights_only\', \'mode\', \'period\'], varargs=None, keywords=None, defaults=[\'val_loss\', \'0\', \'False\', \'False\', \'auto\', \'1\'], " } 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" } }