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N | tdim | wdim | ch | is_channels_last | ms | |
---|---|---|---|---|---|---|
16 | 100 | 3 | 3 | 1 | 18.43367154942825 | |
16 | 100 | 3 | 3 | 0 | 18.246989184990525 | |
16 | 100 | 3 | 7 | 1 | 18.320465798024088 | |
16 | 100 | 3 | 7 | 0 | 18.22661985643208 | |
16 | 100 | 3 | 8 | 1 | 20.038793003186584 | |
16 | 100 | 3 | 8 | 0 | 18.317282549105585 | |
16 | 100 | 5 | 3 | 1 | 18.30171929905191 | |
16 | 100 | 5 | 3 | 0 | 18.09040275402367 | |
16 | 100 | 5 | 7 | 1 | 29.462874494493008 |
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. |
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============================= test session starts ============================== | |
platform linux -- Python 3.9.12, pytest-7.1.2, pluggy-1.0.0 -- /data/home/dberard/miniconda/envs/scratch39/bin/python | |
cachedir: .pytest_cache | |
hypothesis profile 'default' -> database=DirectoryBasedExampleDatabase('/scratch/dberard/local/vision/.hypothesis/examples') | |
rootdir: /scratch/dberard/local/vision, configfile: pytest.ini, testpaths: test | |
plugins: hypothesis-6.46.2 | |
collecting ... collected 29608 items | |
test/test_backbone_utils.py::test_resnet_fpn_backbone[resnet18] SKIPPED [ 0%] | |
test/test_backbone_utils.py::test_resnet_fpn_backbone[resnet50] SKIPPED [ 0%] |
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<GRAPH_EXPORT> | |
graph(%s.1 : Double(204, 204, 26, strides=[5304, 26, 1], requires_grad=0, device=cuda:0), | |
%t.1 : Double(204, 204, 26, strides=[5304, 26, 1], requires_grad=0, device=cuda:0), | |
%p.1 : Double(1, 1, 26, strides=[26, 26, 1], requires_grad=0, device=cuda:0)): | |
%3 : float = prim::Constant[value=2500.]() # /scratch/dberard/bench-june/benchmark/torchbenchmark/models/pyhpc_equation_of_state/eos_pytorch.py:236:10 | |
%4 : float = prim::Constant[value=5000.]() # /scratch/dberard/bench-june/benchmark/torchbenchmark/models/pyhpc_equation_of_state/eos_pytorch.py:197:10 | |
%5 : float = prim::Constant[value=3.028951243773433e-17]() | |
%6 : float = prim::Constant[value=1.2115804975093732e-16]() | |
%7 : float = prim::Constant[value=10000.]() # /scratch/dberard/bench-june/benchmark/torchbenchmark/models/pyhpc_equation_of_state/eos_pytorch.py:184:8 | |
%v31.1 : float = prim::Constant[value=-3.3033088713864211e-05]() # /scratch/dberard/bench-june/benchmark/torchbenchmark/models/pyhpc_equation_of_state |
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import argparse | |
from torch.utils.jit.log_extract import load_graph_and_inputs, run_nnc, run_nvfuser | |
ir = ["""graph(%maskT.1 : Double(204, 204, 26, strides=[5304, 26, 1], requires_grad=0, device=cuda:0), | |
%1 : Double(204, 204, 26, strides=[5304, 26, 1], requires_grad=0, device=cuda:0), | |
%2 : Double(204, 204, 26, strides=[15912, 78, 3], requires_grad=0, device=cuda:0), | |
%zt.1 : Double(26, strides=[1], requires_grad=0, device=cuda:0)): | |
%4 : float = prim::Constant[value=0.79871999999999999]() | |
%betaT.1 : float = prim::Constant[value=0.00016699999999999999]() # /scratch/dberard/bench-june/benchmark/torchbenchmark/models/pyhpc_isoneutral_mixing/isoneutral_pytorch.py:9:12 | |
%rho0.1 : float = prim::Constant[value=1024.]() # /scratch/dberard/bench-june/benchmark/torchbenchmark/models/pyhpc_isoneutral_mixing/isoneutral_pytorch.py:5:11 |
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====== resnext50_32x4d_forward_0 ====== | |
Generating testing data... | |
...Aten2aten called ... | |
['getattr', '_operator.getitem', 'torch.ops.aten.abs.default', 'torch.ops.aten.abs.out', 'torch.ops.aten.acos.default', 'torch.ops.aten.acos.out', 'torch.ops.aten.acos.int', 'torch.ops.aten.acos.float', 'torch.ops.aten.acos.complex', 'torch.ops.aten.acos.Scalar', 'torch.ops.aten.acosh.default', 'torch.ops.aten.acosh.out', 'torch.ops.aten.acosh.int', 'torch.ops.aten.acosh.float', 'torch.ops.aten.acosh.complex', 'torch.ops.aten.acosh.Scalar', 'torch.ops.aten.asin.default', 'torch.ops.aten.asin.out', 'torch.ops.aten.asin.int', 'torch.ops.aten.asin.float', 'torch.ops.aten.asin.complex', 'torch.ops.aten.asin.Scalar', 'torch.ops.aten.atan.default', 'torch.ops.aten.atan.out', 'torch.ops.aten.atan.int', 'torch.ops.aten.atan.float', 'torch.ops.aten.atan.complex', 'torch.ops.aten.atan.Scalar', 'torch.ops.aten.bitwise_not.default', 'torch.ops.aten.bitwise_not.out', 'torch.ops.aten.ceil.default', 'torch.ops.aten.ceil.out', 'torch.o |
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resnext50_32x4d_forward_0 | 54 | 218.74908078461885 | 4436.730502173305 | 57523.576692678034 | 4421.9345189630985 | None | |
---|---|---|---|---|---|---|---|
resnext50_32x4d_backward_0 | 50 | 285.865287296474 | 42.50716231763363 | None | None | None | |
nvidia_deeprecommender_backward_0 | 12 | 15.30700083822012 | 19.517005421221256 | None | None | None | |
nvidia_deeprecommender_forward_0 | 6 | 11.350277811288834 | 14.164607971906662 | 4775.836288928986 | 8.331834338605404 | True | |
moco_forward_4 | 0 | 0.40543172508478165 | 0.25066547095775604 | 0.2816496416926384 | 0.22500194609165192 | True | |
moco_backward_0 | 52 | 211.168865673244 | 46.68072052299976 | None | None | None | |
moco_backward_7 | 0 | 0.3038998693227768 | 0.578882172703743 | 0.03198999911546707 | 0.017229467630386353 | True | |
moco_forward_9 | 5 | 4.927339963614941 | 1.6684727743268013 | None | None | None | |
moco_forward_3 | 0 | 0.7490329444408417 | 0.4087546840310097 | 0.3969920799136162 | 0.3871563822031021 | True | |
moco_backward_10 | 0 | 0.23642834275960922 | 0.047839246690273285 | 0.027767382562160492 | 0.01574307680130005 | True |
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g++ counter.cpp -c -o counter.o | |
g++ x.cpp -c -o x.o | |
g++ x.cpp -c -o y.o | |
g++ main.cpp -c -o main.o | |
g++ counter.o x.o y.o main.o -o main |
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/data/home/dberard/miniconda/envs/bench-fast/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead. | |
warnings.warn( | |
/data/home/dberard/miniconda/envs/bench-fast/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=ResNet50_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet50_Weights.DEFAULT` to get the most up-to-date weights. | |
warnings.warn(msg) | |
WARNING:root:Using TorchDynamo with a context manager will be deprecated soon.Please read https://github.com/pytorch/torchdynamo#usage-example to use TorchDynamo using an annotation. | |
ERROR:root:Error while processing frame | |
Traceback (most recent call last): | |
File "/data/home/dberard/miniconda/envs/bench-fast/lib/python3.8/site-packages/torchd |
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submitit INFO (2022-09-15 00:31:04,046) - Starting with JobEnvironment(job_id=64923, hostname=a100-st-p4d24xlarge-15, local_rank=0(8), node=0(1), global_rank=0(8)) | |
submitit INFO (2022-09-15 00:31:04,047) - Loading pickle: /fsx/users/dberard/scratch-local/bench-fast/benchmark/logs/64923_submitted.pkl | |
Process group: 8 tasks, rank: 0 | |
a100-st-p4d24xlarge-15:26872:26872 [0] NCCL INFO NCCL_SOCKET_IFNAME set by environment to ens | |
a100-st-p4d24xlarge-15:26872:26872 [0] NCCL INFO NCCL_SOCKET_IFNAME set to ens | |
a100-st-p4d24xlarge-15:26872:26872 [0] NCCL INFO Bootstrap : Using ens32:10.200.83.149<0> | |
a100-st-p4d24xlarge-15:26872:26872 [0] NCCL INFO NET/Plugin: Failed to find ncclCollNetPlugin_v6 symbol. | |
a100-st-p4d24xlarge-15:26872:26872 [0] NCCL INFO NET/Plugin: Failed to find ncclCollNetPlugin symbol (v4 or v5). | |
a100-st-p4d24xlarge-15:26872:26872 [0] NCCL INFO cudaDriverVersion 11060 | |
NCCL version 2.13.4+cuda11.6 |