mindspore.data_sink

mindspore.data_sink(fn, dataset, steps, sink_size=1, jit=False)[source]

A wrapper function to generate a function for the input function.

The generated function will be executed in data sinking mode.

Parameters

  • fn (Function) – The Python function that will be run with dataset.

  • dataset (Dataset) – The dataset iterator. The dataset can be generated by dataset generator API in mindspore.dataset, such as mindspore.dataset.ImageFolderDataset.

  • steps (int) – The total running steps. steps must be positive integer.

  • sink_size (int) – Control the amount of data in each sink. sink_size must be positive integer. Default: 1.

  • jit (bool) – Controls the execution mode(Graph mode/PyNative mode) of the generated function. Default: False, means running in PyNative mode.

Returns

Function, the generated function will be executed in data sinking mode.

Raises

ValueError – If steps or sink_size is not positive integer.

Supported Platforms:

Ascend GPU

Examples

>>> import numpy as np
>>> import mindspore as ms
>>> from mindspore import dataset as ds
>>>
>>> data = {"x": np.ones((1,), dtype=np.int32), "y": np.ones((1,), dtype=np.int32)}
>>> dataset = ds.NumpySlicesDataset(data=data)
>>>
>>> def func_net(x, y):
...     out = x + y
...     return out
>>>
>>> sink_process = ms.train.data_sink(func_net, dataset, steps=2, sink_size=1)
>>> for _ in range(2):
...     out = sink_process()
...     print(out)
2
2