MinibatchSource: Minibatch Source
In Microsoft/CNTK-R: R Interface to the Microsoft Cognitive Toolkit (CNTK)

Source of minibatch data

MinibatchSource(deserializers, max_samples = IO_INFINITELY_REPEAT,
  max_sweeps = IO_INFINITELY_REPEAT,
  randomization_window_in_chunks = IO_DEFAULT_RANDOMIZATION_WINDOW_IN_CHUNKS,
  randomization_window_in_samples = 0, randomization_seed = 0,
  trace_level = get_logging_trace_level(),
  multithreaded_deserializer = NULL, frame_mode = FALSE,
  truncation_length = 0, randomize = TRUE)

`deserializers`	(deserializer or list) deserializers to be used in the composite reader
`max_samples`	(int, defaults to IO_INFINITELY_REPEAT) The maximum number of input samples (not ‘label samples’) the reader can produce. After this number has been reached, the reader returns empty minibatches on subsequent calls to next_minibatch(). max_samples and max_sweeps are mutually exclusive, an exception will be raised if both have non-default values.
`max_sweeps`	(int, defaults to IO_INFINITELY_REPEAT) The maximum number of of sweeps over the input dataset After this number has been reached, the reader returns empty minibatches on subsequent calls to func:next_minibatch. max_samples and max_sweeps are mutually exclusive, an exception will be raised if both have non-default values.
`randomization_window_in_chunks`	(int, defaults to IO_DEFAULT_RANDOMIZATION_WINDOW_IN_CHUNKS) size of the randomization window in chunks, non-zero value enables randomization. randomization_window_in_chunks and randomization_window_in_samples are mutually exclusive, an exception will be raised if both have non-zero values.
`randomization_window_in_samples`	(int, defaults to 0) size of the randomization window in samples, non-zero value enables randomization. randomization_window_in_chunks and randomization_window_in_samples are mutually exclusive, an exception will be raised if both have non-zero values.
`randomization_seed`	(int, defaults to 0) Initial randomization seed value (incremented every sweep when the input data is re-randomized).
`trace_level`	(TraceLevel) the output verbosity level, defaults to the current logging verbosity level given by get_trace_level().
`multithreaded_deserializer`	(bool) specifies if the deserialization should be done on a single or multiple threads. Defaults to None, which is effectively “auto” (multhithreading is disabled unless ImageDeserializer is present in the deserializers list). False and True faithfully turn the multithreading off/on.
`frame_mode`	(bool) switches the frame mode on and off. If the frame mode is enabled the input data will be processed as individual frames ignoring all sequence information (this option cannot be used for BPTT, an exception will be raised if frame mode is enabled and the truncation length is non-zero).
`truncation_length`	(int) truncation length in samples, non-zero value enables the truncation (only applicable for BPTT, cannot be used in frame mode, an exception will be raised if frame mode is enabled and the truncation length is non-zero).
`randomize`	(bool) Enables or disables randomization; use randomization_window_in_chunks or randomization_window_in_samples to specify the randomization range