as_numpy_iterator () for i in range ( n_devices )] validation_remaining =. derivative_parser ( example, n_params = n_params ))) ). glob ( 'tmp/validation_derivative_*.tfrecords' )), num_parallel_reads = 1 ).

as_numpy_iterator () for i in range ( n_devices )] validation_fiducial = validation_main =, tf. as_numpy_iterator () for i in range ( n_devices )] remaining =. glob ( 'tmp/derivative_*.tfrecords' )), num_parallel_reads = 1 ). We can then read these to a dataset using the parser from the TFRecordsĬlass mapping the format of the data to a 32-bit floatįiducial = main =, tf. write_record ( n_sims = n_d, get_simulation = lambda seed : get_simulation ( seed, directory = 'tmp', filename = 'validation_derivative' ), directory = 'tmp', filename = 'validation_derivative' ) write_record ( n_sims = n_s - n_d, get_simulation = lambda seed : get_simulation ( seed, directory = 'tmp', filename = 'validation_remaining' ), directory = 'tmp', filename = 'validation_remaining' ) writer. write_record ( n_sims = n_d, get_simulation = lambda seed : get_simulation ( seed, directory = 'tmp', filename = 'validation_fiducial' ), directory = 'tmp', filename = 'validation_fiducial' ) writer. write_record ( n_sims = n_d, get_simulation = lambda seed : get_simulation ( seed, directory = 'tmp', filename = 'derivative' ), directory = 'tmp', filename = 'derivative' ) writer. write_record ( n_sims = n_s - n_d, get_simulation = lambda seed : get_simulation ( seed, directory = 'tmp', filename = 'remaining' ), directory = 'tmp', filename = 'remaining' ) writer. write_record ( n_sims = n_d, get_simulation = lambda seed : get_simulation ( seed, directory = 'tmp', filename = 'fiducial' ), directory = 'tmp', filename = 'fiducial' ) writer.

Tf data generator