candle.keras_utils.CandleRemoteMonitor

class candle.keras_utils.CandleRemoteMonitor(params=None)

Capture Run level output and store/send for monitoring.

__init__(params=None)

Methods

__init__([params])
on_batch_begin(batch[, logs])	A backwards compatibility alias for on_train_batch_begin.
on_batch_end(batch[, logs])	A backwards compatibility alias for on_train_batch_end.
on_epoch_begin(epoch[, logs])	Called at the start of an epoch.
on_epoch_end(epoch[, logs])	Called at the end of an epoch.
on_predict_batch_begin(batch[, logs])	Called at the beginning of a batch in predict methods.
on_predict_batch_end(batch[, logs])	Called at the end of a batch in predict methods.
on_predict_begin([logs])	Called at the beginning of prediction.
on_predict_end([logs])	Called at the end of prediction.
on_test_batch_begin(batch[, logs])	Called at the beginning of a batch in evaluate methods.
on_test_batch_end(batch[, logs])	Called at the end of a batch in evaluate methods.
on_test_begin([logs])	Called at the beginning of evaluation or validation.
on_test_end([logs])	Called at the end of evaluation or validation.
on_train_batch_begin(batch[, logs])	Called at the beginning of a training batch in fit methods.
on_train_batch_end(batch[, logs])	Called at the end of a training batch in fit methods.
on_train_begin([logs])	Called at the beginning of training.
on_train_end([logs])	Called at the end of training.
save()	Save log_messages to file.
set_model(model)
set_params(params)