A cross validation configuration for the training session.
CrossValidationConfig(minibatch_source = NULL, frequency = NULL, minibatch_size = 32, callback = NULL, max_samples = NULL, model_inputs_to_streams = NULL, criterion = NULL, source = NULL)
| minibatch_source | (MinibatchSource): minibatch source used for cross validation |
|---|---|
| frequency | (int): frequency in samples for cross validation If NULL or ``sys.maxsize``, a single cross validation is performed at the end of training. |
| callback | (func (index, average_error, cv_num_samples, cv_num_minibatches)): Callback that will be called with frequency which can implement custom cross validation logic, returns FALSE if training should be stopped. |
| max_samples | (int, default NULL): number of samples to perform cross-validation on. If NULL, all samples are taken. |
| model_inputs_to_streams | (dict): mapping between input variables and input streams If NULL, the mapping provided to the training session constructor is used. Don't specify this if `minibatch_source` is a tuple of numpy/scipy arrays. |
| criterion | (): criterion function): criterion function. Must be specified if `minibatch_source` is a tuple of numpy/scipy arrays. |
| source | (MinibatchSource): DEPRECATED, use minibatch_source instead |
| minibatch_size(int | or minibatch_size_schedule, defaults to 32): minibatch schedule for cross validation |