peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/deepspeed
/runtime
/zero
/test.py
# Copyright (c) Microsoft Corporation. | |
# SPDX-License-Identifier: Apache-2.0 | |
# DeepSpeed Team | |
import torch | |
from deepspeed.runtime.zero.contiguous_memory_allocator import ContiguousMemoryAllocator | |
def test1(): | |
mem = ContiguousMemoryAllocator(1024, torch.half, 'cpu') | |
mem.print_allocation(resolution=100) | |
a1 = mem.allocate_tensor(64).mul_(0.0).add_(1.0) | |
mem.print_allocation(resolution=100) | |
mem.release_tensor(a1) | |
mem.print_allocation(resolution=100) | |
a2 = mem.allocate_tensor(64).mul_(0.0).add_(2.0) | |
a3 = mem.allocate_tensor(256).mul_(0.0).add_(3.0) | |
a4 = mem.allocate_tensor(128).mul_(0.0).add_(4.0) | |
mem.print_allocation(resolution=100) | |
mem.release_tensor(a3) | |
mem.print_allocation(resolution=100) | |
a5 = mem.allocate_tensor(64).mul_(0.0).add_(5.0) | |
a6 = mem.allocate_tensor(256).mul_(0.0).add_(6.0) | |
a7 = mem.allocate_tensor(128).mul_(0.0).add_(7.0) | |
mem.print_allocation(resolution=100) | |
a8 = mem.allocate_tensor(256).mul_(0.0).add_(8.0) | |
a9 = mem.allocate_tensor(128).mul_(0.0).add_(9.0) | |
mem.print_allocation(resolution=100) | |
mem.release_tensor(a9) | |
mem.release_tensor(a6) | |
mem.release_tensor(a2) | |
mem.release_tensor(a5) | |
a10 = mem.allocate_tensor(512).mul_(0.0).add_(10.0) | |
mem.print_allocation(resolution=100) | |
#print(f"a4:{a4}") | |
#print(f"a7:{a7}") | |
#print(f"a8:{a8}") | |
#print(f"a10:{a10}") | |
assert (a4.norm() + a7.norm() + a8.norm() + a10.norm()).item() == 474.50, "Test failed" | |
def test2(): | |
mem = ContiguousMemoryAllocator(512, torch.half, 'cpu') | |
a1 = mem.allocate_tensor(64).mul_(0.0).add_(1.0) | |
a2 = mem.allocate_tensor(64).mul_(0.0).add_(2.0) | |
a3 = mem.allocate_tensor(64).mul_(0.0).add_(3.0) | |
a4 = mem.allocate_tensor(64).mul_(0.0).add_(4.0) | |
a5 = mem.allocate_tensor(64).mul_(0.0).add_(5.0) | |
a6 = mem.allocate_tensor(64).mul_(0.0).add_(6.0) | |
a7 = mem.allocate_tensor(64).mul_(0.0).add_(7.0) | |
a8 = mem.allocate_tensor(64).mul_(0.0).add_(8.0) | |
mem.release_tensor(a2) | |
mem.release_tensor(a4) | |
mem.release_tensor(a6) | |
mem.release_tensor(a8) | |
mem.print_allocation(resolution=100) | |
a9 = mem.allocate_tensor(128).mul_(0.0).add_(9.0) | |
a10 = mem.allocate_tensor(64).mul_(0.0).add_(10.0) | |
a11 = mem.allocate_tensor(64).mul_(0.0).add_(11.0) | |
mem.release_tensor(a1) | |
mem.release_tensor(a5) | |
mem.print_allocation(resolution=100) | |
a12 = mem.allocate_tensor(128).mul_(0.0).add_(12.0) | |
mem.print_allocation(resolution=100) | |
print(f"a7:{a7}") | |
print(f"a9:{a9}") | |
print(f"a10:{a10}") | |
print(f"a11:{a11}") | |
print(f"a12:{a12}") | |
assert (a7.norm() + a9.norm() + a10.norm() + a11.norm() + a12.norm()) == 460.75, "TestFailed" | |
test1() | |
test2() | |