mindspore.hal

Hal encapsulates interfaces for device, stream, event, and memory. MindSpore abstracts the corresponding modules from different backends, allowing users to schedule hardware resources at the Python layer.

Device

API Name	Description	Supported Platforms
`mindspore.hal.device_count`	Returns device count of specified backend.	`Ascend` `GPU` `CPU`
`mindspore.hal.get_arch_list`	Get the architecture list this MindSpore was compiled for.	`Ascend` `GPU` `CPU`
`mindspore.hal.get_device_capability`	Get specified device's capability.	`Ascend` `GPU` `CPU`
`mindspore.hal.get_device_name`	Get specified device's name.	`Ascend` `GPU` `CPU`
`mindspore.hal.get_device_properties`	Get specified device's properties.	`Ascend` `GPU` `CPU`
`mindspore.hal.is_available`	Returns whether specified backend is available.	`Ascend` `GPU` `CPU`
`mindspore.hal.is_initialized`	Returns whether specified backend is initialized.	`Ascend` `GPU` `CPU`

Stream

API Name	Description	Supported Platforms
`mindspore.hal.current_stream`	Return current stream used on this device.	`Ascend` `GPU` `CPU`
`mindspore.hal.default_stream`	Return default stream on this device.	`Ascend` `GPU` `CPU`
`mindspore.hal.set_cur_stream`	Sets the current stream.This is a wrapper API to set the stream.	`Ascend` `GPU` `CPU`
`mindspore.hal.synchronize`	Synchronize all streams on current device.(Each MindSpore process only occupies one device)	`Ascend` `GPU` `CPU`
`mindspore.hal.Stream`	Wrapper around a device stream.	`Ascend` `GPU` `CPU`
`mindspore.hal.StreamCtx`	Context-manager that selects a given stream.	`Ascend` `GPU` `CPU`

Event

API Name	Description	Supported Platforms
`mindspore.hal.Event`	Wrapper around a device event.	`Ascend` `GPU` `CPU`

Memory

API Name	Description	Supported Platforms
`mindspore.hal.max_memory_allocated`	Returns the peak memory size of the memory pool actually occupied by Tensor since the process was started.	`Ascend` `GPU` `CPU`
`mindspore.hal.max_memory_reserved`	Returns the peak value of the total memory managed by the memory pool since the process was started.	`Ascend` `GPU` `CPU`
`mindspore.hal.memory_allocated`	Returns the actual memory size currently occupied by Tensor.	`Ascend` `GPU` `CPU`
`mindspore.hal.memory_reserved`	Returns the total amount of memory currently managed by the memory pool.	`Ascend` `GPU` `CPU`
`mindspore.hal.memory_stats`	Returns status information queried from the memory pool.	`Ascend` `GPU` `CPU`
`mindspore.hal.memory_summary`	Returns readable memory pool status information.	`Ascend` `GPU` `CPU`
`mindspore.hal.reset_max_memory_reserved`	Reset the peak memory size managed by the memory pool.	`Ascend` `GPU` `CPU`
`mindspore.hal.reset_max_memory_allocated`	Reset the peak memory size of the memory pool actually occupied by Tensor.	`Ascend` `GPU` `CPU`
`mindspore.hal.reset_peak_memory_stats`	Reset the "peak" stats tracked by memory manager.	`Ascend` `GPU` `CPU`
`mindspore.hal.empty_cache`	Release all memory fragments in the memory pool, so that memory arrangement will be optimized.	`Ascend` `GPU` `CPU`