mindspore.dataset.DSCallback
- class mindspore.dataset.DSCallback(step_size=1)[source]
Abstract base class used to build dataset callback classes.
Users can obtain the dataset pipeline context through ds_run_context, including cur_epoch_num, cur_step_num_in_epoch and cur_step_num.
- Parameters
step_size (int, optional) – The number of steps between adjacent ds_step_begin/ds_step_end calls. Default: 1, will be called at each step.
Examples
>>> from mindspore.dataset import DSCallback >>> from mindspore.dataset.transforms import c_transforms >>> >>> class PrintInfo(DSCallback): ... def ds_epoch_end(self, ds_run_context): ... print(ds_run_context.cur_epoch_num) ... print(ds_run_context.cur_step_num) >>> >>> dataset = ds.MnistDataset(mnist_dataset_dir, num_samples=100) >>> op = c_transforms.OneHot(10) >>> dataset = dataset.map(operations=op, callbacks=PrintInfo())
- ds_begin(ds_run_context)[source]
Called before the data pipeline is started.
- Parameters
ds_run_context (RunContext) – Include some information of the data pipeline.
- ds_epoch_begin(ds_run_context)[source]
Called before a new epoch is started.
- Parameters
ds_run_context (RunContext) – Include some information of the data pipeline.
- ds_epoch_end(ds_run_context)[source]
Called after an epoch is finished.
- Parameters
ds_run_context (RunContext) – Include some information of the data pipeline.
- ds_step_begin(ds_run_context)[source]
Called before a step start.
- Parameters
ds_run_context (RunContext) – Include some information of the data pipeline.
- ds_step_end(ds_run_context)[source]
Called after a step finished.
- Parameters
ds_run_context (RunContext) – Include some information of the data pipeline.