ij \ddlZddlmZddlmZddlmZedGddeZy)N) keras_export)Callback)io_utilszkeras.callbacks.TerminateOnNaNc2eZdZdZddeffd ZddZxZS)TerminateOnNaNaCallback that terminates training when a NaN loss is encountered. This callback monitors the loss value during training and terminates training when a NaN or Inf loss is detected. By default, training is stopped gracefully by setting `model.stop_training = True`, which triggers all callback cleanup methods including `on_train_end()`. Alternatively, you can use `raise_error=True` to immediately raise a RuntimeError when NaN/Inf is detected. This raise_error termination prevents `on_train_end()` from being called on other callbacks, which is useful for preserving backup states or preventing unintended cleanup when training fails. Args: raise_error: Boolean, default False. If False, uses graceful stop via `model.stop_training = True`. If True, immediately raises RuntimeError on NaN/Inf loss, bypassing callback cleanup methods. Example: ``` # Graceful termination (default) callback = keras.callbacks.TerminateOnNaN() model.fit(x, y, callbacks=[callback]) # raise_error termination (strict failure) callback = keras.callbacks.TerminateOnNaN(raise_error=True) model.fit(x, y, callbacks=[callback]) ``` raise_errorc0t|||_yN)super__init__r)selfr __class__s y/var/www/html/emotional.easysim.app/public_html/venv/lib/python3.12/site-packages/keras/src/callbacks/terminate_on_nan.pyr zTerminateOnNaN.__init__*s &c|xsi}|jd}|ttj|stj|rI|jrt d|d|dt jd|dd|j_ yyy) a,Check for NaN/Inf loss at the end of each batch. Args: batch: Integer, index of batch within the current epoch. logs: Dict, contains the return value of `model.train_step()`. Raises: RuntimeError: If loss is NaN/Inf and raise_error=True. lossNz%NaN or Inf loss encountered at batch z. Loss value: z#. Terminating training immediately.zBatch z$: Invalid loss, terminating trainingT) getnpisnanisinfr RuntimeErrorr print_msgmodel stop_training)r batchlogsrs r on_batch_endzTerminateOnNaN.on_batch_end.szrxx  xx~$##&?wG''+f,OQ && 'KL04DJJ,"0 r)Fr )__name__ __module__ __qualname____doc__boolr r __classcell__)rs@rrrs@'D'4rr) numpyrkeras.src.api_exportrkeras.src.callbacks.callbackrkeras.src.utilsrrrrr)s2-1$./<4X<40<4r