Tutorial by Topics: generators

Generator functions (defined by the function* keyword) run as coroutines, generating a series of values as they're requested through an iterator. function* name(parameters) { yield value; return value } generator = name(arguments) { value, done } = generator.next(value) { value, done } = ge...

Generators are lazy iterators created by generator functions (using yield) or generator expressions (using (an_expression for x in an_iterator)). yield <expr> yield from <expr> <var> = yield <expr> next(<iter>)

Machine learning problems often require dealing with large quantities of training data with limited computing resources, particularly memory. It is not always possible to load an entire training set into memory. Fortunately, this can be dealt with through the use of Keras' fit_generator method, Pyth...