torch.xpu.memory_stats — PyTorch 2.7 documentation (original) (raw)
torch.xpu.memory_stats(device=None)[source][source]¶
Return a dictionary of XPU memory allocator statistics for a given device.
The return value of this function is a dictionary of statistics, each of which is a non-negative integer.
Core statistics:
"allocated_bytes.{all,large_pool,small_pool}.{current,peak,allocated,freed}": amount of allocated memory."reserved_bytes.{all,large_pool,small_pool}.{current,peak,allocated,freed}": amount of reserved memory."active_bytes.{all,large_pool,small_pool}.{current,peak,allocated,freed}": amount of active memory."requested_bytes.{all,large_pool,small_pool}.{current,peak,allocated,freed}": memory requested by client code, compare this with allocated_bytes to check if allocation rounding adds too much overhead.
For these core statistics, values are broken down as follows.
Pool type:
all: combined statistics across all memory pools.large_pool: statistics for the large allocation pool (for size >= 1MB allocations).small_pool: statistics for the small allocation pool (for size < 1MB allocations).
Metric type:
current: current value of this metric.peak: maximum value of this metric.allocated: historical total increase in this metric.freed: historical total decrease in this metric.
Parameters
device (torch.device or int or str, optional) – selected device. Returns statistics for the current device, given by current_device(), if device is None (default).
Return type