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Revert "create a new torch.cuda.memory_usage_in_bytes api (#140719)"

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This reverts commit 9febc47637.

Reverted https://github.com/pytorch/pytorch/pull/140719 on behalf of https://github.com/huydhn due to Sorry for reverting your change, but the test is flaky on ROCm ([comment](https://github.com/pytorch/pytorch/pull/140719#issuecomment-2479832082))
This commit is contained in:
PyTorch MergeBot 2024-11-15 20:05:32 +00:00
parent 210de39872
commit 03b7ec9237
4 changed files with 0 additions and 46 deletions
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1
docs/source/cuda.rst
View File

@ -28,7 +28,6 @@ torch.cuda
is_available
is_initialized
memory_usage
memory_usage_in_bytes
set_device
set_stream
set_sync_debug_mode

14
test/test_cuda.py
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@ -3947,20 +3947,6 @@ class TestCudaMallocAsync(TestCase):
def test_temperature(self):
self.assertTrue(0 <= torch.cuda.temperature() <= 150)
@unittest.skipIf(TEST_PYNVML, "pynvml/amdsmi is not available")
def test_memory_usage_in_bytes(self):
"""
Verify memory usage in bytes
"""
torch.cuda.empty_cache()
a = torch.cuda.memory_usage_in_bytes()
num_bytes = 256 * 1024**2
_ = torch.empty(num_bytes, dtype=torch.int8, device="cuda")
torch.cuda.synchronize()
b = torch.cuda.memory_usage_in_bytes()
mem_bytes = b - a
self.assertTrue(mem_bytes > num_bytes // 2, mem_bytes < num_bytes * 8)
@unittest.skipIf(TEST_PYNVML, "pynvml/amdsmi is not available")
def test_power_draw(self):
self.assertTrue(torch.cuda.power_draw() >= 0)

1
torch/_dynamo/trace_rules.py
View File

@ -2540,7 +2540,6 @@ torch_non_c_binding_in_graph_functions = dict.fromkeys(
"torch.cuda.jiterator._create_jit_fn",
"torch.cuda.jiterator._create_multi_output_jit_fn",
"torch.cuda.memory_usage",
"torch.cuda.memory_usage_in_bytes",
"torch.cuda.memory._dump_snapshot",
"torch.cuda.memory._free_mutex",
"torch.cuda.memory._get_current_allocator",

30
torch/cuda/__init__.py
View File

@ -1110,17 +1110,6 @@ def _get_amdsmi_device_index(device: Optional[Union[int, Device]]) -> int:
return idx_map[idx]
def _get_amdsmi_memory_usage_in_bytes(
device: Optional[Union[Device, int]] = None
) -> int:
handle = _get_amdsmi_handler()
device = _get_amdsmi_device_index(device)
# amdsmi_get_gpu_vram_usage returns mem usage in megabytes
mem_mega_bytes = amdsmi.amdsmi_get_gpu_vram_usage(handle)["vram_used"]
mem_bytes = mem_mega_bytes * 1024 * 1024
return mem_bytes
def _get_amdsmi_memory_usage(device: Optional[Union[Device, int]] = None) -> int:
handle = _get_amdsmi_handler()
device = _get_amdsmi_device_index(device)
@ -1161,24 +1150,6 @@ def _get_amdsmi_clock_rate(device: Optional[Union[Device, int]] = None) -> int:
return clock_info["clk"]
def memory_usage_in_bytes(device: Optional[Union[Device, int]] = None) -> int:
r"""Return global (device) memory usage in bytes as given by `nvidia-smi` or `amd-smi`.
Args:
device (torch.device or int, optional): selected device. Returns
statistic for the current device, given by :func:`~torch.cuda.current_device`,
if :attr:`device` is ``None`` (default).
"""
if not torch.version.hip:
handle = _get_pynvml_handler()
device = _get_nvml_device_index(device)
handle = pynvml.nvmlDeviceGetHandleByIndex(device)
return pynvml.nvmlDeviceGetMemoryInfo(handle).used
else:
return _get_amdsmi_memory_usage_in_bytes(device)
def memory_usage(device: Optional[Union[Device, int]] = None) -> int:
r"""Return the percent of time over the past sample period during which global (device)
memory was being read or written as given by `nvidia-smi`.
@ -1681,7 +1652,6 @@ __all__ = [
"memory_stats_as_nested_dict",
"memory_summary",
"memory_usage",
"memory_usage_in_bytes",
"MemPool",
"MemPoolContext",
"use_mem_pool",