exarl.candlelib.solr_keras
Module Contents
Classes
Capture Run level output and store/send for monitoring |
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This class implements timeout on model training. When the script reaches timeout, |
Functions
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Extract number of parameters from the given Keras model |
- exarl.candlelib.solr_keras.compute_trainable_params(model)
Extract number of parameters from the given Keras model
- Parameters
model (Keras model) –
- Returns
python dictionary that contains trainable_params, non_trainable_params and total_params
- class exarl.candlelib.solr_keras.CandleRemoteMonitor(params=None)
Bases:
tensorflow.keras.callbacks.CallbackCapture Run level output and store/send for monitoring
- on_train_begin(self, logs=None)
- on_epoch_begin(self, epoch, logs=None)
- on_epoch_end(self, epoch, logs=None)
- on_train_end(self, logs=None)
- submit(self, send)
Send json to solr
- Parameters
send (json object) – Object to send
- save(self)
Save log_messages to file
- class exarl.candlelib.solr_keras.TerminateOnTimeOut(timeout_in_sec=10)
Bases:
tensorflow.keras.callbacks.CallbackThis class implements timeout on model training. When the script reaches timeout, this class sets model.stop_training = True
Initialize TerminateOnTimeOut class.
- Parameters
timeout_in_sec (int) – seconds to timeout
- on_train_begin(self, logs={})
Start clock to calculate timeout
- on_epoch_end(self, epoch, logs={})
On every epoch end, check whether it exceeded timeout and terminate training if necessary