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[tensor] chunk manager monitor mem usage (#1076)

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ver217
2022-06-07 15:00:00 +08:00
committed by GitHub
parent 98cdbf49c6
commit 1b17859328
2 changed files with 35 additions and 1 deletions
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14
tests/test_tensor/test_chunk.py
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@@ -32,6 +32,8 @@ HAS_TENSORS = {
}
}
TOTAL_MEM = {True: {True: [8192, 8192], False: [16384, 16384]}, False: {True: [8192, 4096], False: [12288, 12288]}}
@parameterize('use_chunk', [False, True])
@parameterize('use_zero', [False, True])
@@ -42,15 +44,27 @@ def run_chunk_zero(use_chunk, use_zero):
params = [torch.rand(32, 32) for _ in range(3)]
chunk_size = 2048 if use_chunk else None
chunk_manager = ChunkManager(chunk_size, enable_distributed_storage=use_zero)
assert chunk_manager.total_mem['cpu'] == 0
assert chunk_manager.total_mem['cuda'] == 0
for p in params:
chunk_manager.append_tensor(p, 'param')
check_has_params(params, HAS_TENSORS[use_chunk][use_zero][rank])
assert chunk_manager.total_mem['cpu'] == 0
assert chunk_manager.total_mem['cuda'] == TOTAL_MEM[use_chunk][use_zero][rank]
for p in params:
chunk_manager.access_chunk(p)
check_has_params(params, [True, True, True])
assert chunk_manager.total_mem['cpu'] == 0
assert chunk_manager.total_mem['cuda'] == TOTAL_MEM[use_chunk][False][rank]
for p in params:
chunk_manager.release_chunk(p)
check_has_params(params, HAS_TENSORS[use_chunk][use_zero][rank])
assert chunk_manager.total_mem['cpu'] == 0
assert chunk_manager.total_mem['cuda'] == TOTAL_MEM[use_chunk][use_zero][rank], chunk_manager.total_mem['cuda']
for p in params:
chunk_manager.move_chunk(p, torch.device('cpu'))
assert chunk_manager.total_mem['cpu'] == TOTAL_MEM[use_chunk][use_zero][rank], chunk_manager.total_mem['cuda']
assert chunk_manager.total_mem['cuda'] == 0
def run_dist(rank, world_size, port):