ModelEvaluator

Handles calculation of word error rate using an LMDB dataset. For more information on the calculation, see Evaluator.

ModelEvaluator:__init(datasetPath, mapper, testBatchSize, nbOfTestIterations, logsPath)

datasetPath the path to the LMDB test dataset to use in evaluation.

mapper Maps predicted numeric values to characters, see Mapper for more details.

testBatchSize The size of the batches (usually should be kept to 1, we test one sample at a time).

nbOfTestIterations Number of iterations of the dataset we test.

logsPath File path to put the details of evaluations into.

ModelEvaluator:getEvaluation(gpu, model, verbose, epoch)

Calculates the word error rate and character error rate averaged over the test iterations. Uses the same threading as the training process does to load batches from the dataset.

gpu Set to true to use CUDA.

model The Torch model to evaluate.

verbose If set to true, will store details of WER calculations into the log files.

epoch Determines the epoch number that is written in the log files for this calculation.

ModelEvaluator:tokens2text(tokens)

Using the mapper converts the tokens into readable text.

tokens A set of numeric tokens to convert into readable text.