pytorch
e01324d0 - Port l1_loss to Aten (#26795)
Commit
4 years agoPort l1_loss to Aten (#26795)
Summary:
VitalyFedyunin, This PR is about port L1 lose to Aten:
**Test script:**
```
import torch
import torch.nn as nn
import time
torch.manual_seed(0)
def _time():
if torch.cuda.is_available():
torch.cuda.synchronize()
return time.time()
device = "cpu"
loss = nn.L1Loss(reduction = 'sum')
if torch.cuda.is_available():
device = "cuda"
loss = loss.cuda()
#warm up
for n in [100, 10000]:
input = torch.randn(128, n, requires_grad=True, device=device)
target = torch.randn(128, n, device=device)
for i in range(1000):
output = loss(input, target)
output.backward()
#get running time
for n in [100, 10000]:
fwd_t = 0
bwd_t = 0
input = torch.randn(128, n, requires_grad=True, device=device)
target = torch.randn(128, n, device=device)
for i in range(10000):
t1 = _time()
output = loss(input, target)
t2 = _time()
output.backward()
t3 = _time()
fwd_t = fwd_t + (t2 -t1)
bwd_t = bwd_t + (t3 - t2)
fwd_avg = fwd_t / 10000 * 1000
bwd_avg = bwd_t / 10000 * 1000
print("input size(128, %d) forward time is %.2f (ms); backwad avg time is %.2f (ms)."
% (n, fwd_avg, bwd_avg))
```
Test Device: CPU: skx-8180, GPU: Tesla P100.
**Perfromance:**
Before:
```
GPU:
reduction=’mean’
nput size(128, 100) forward time is 0.31 (ms); backwad avg time is 0.09 (ms).
input size(128, 10000) forward time is 0.33 (ms); backwad avg time is 0.14 (ms).
reduction=’sum’
input size(128, 100) forward time is 0.31 (ms); backwad avg time is 0.10 (ms).
input size(128, 10000) forward time is 0.34 (ms); backwad avg time is 0.14 (ms).
CPU:
reduction=’mean’
input size(128, 100) forward time is 0.06 (ms); backwad avg time is 0.10 (ms).
input size(128, 10000) forward time is 1.92 (ms); backwad avg time is 2.96 (ms).
reduction=’sum’
input size(128, 100) forward time is 0.04 (ms); backwad avg time is 0.09 (ms).
input size(128, 10000) forward time is 1.96 (ms); backwad avg time is 2.79 (ms).
nume_thread = 1:
reduction=’mean’
input size(128, 100) forward time is 0.03 (ms); backwad avg time is 0.05 (ms).
input size(128, 10000) forward time is 1.67 (ms); backwad avg time is 2.50 (ms).
reduction=’sum’:
input size(128, 100) forward time is 0.03 (ms); backwad avg time is 0.05 (ms).
input size(128, 10000) forward time is 1.67 (ms); backwad avg time is 2.51 (ms).
```
After:
```
GPU:
reduction=’mean’
input size(128, 100) forward time is 0.05 (ms); backwad avg time is 0.10 (ms).
input size(128, 10000) forward time is 0.11 (ms); backwad avg time is 0.17 (ms).
reduction=’sum’
input size(128, 100) forward time is 0.05 (ms); backwad avg time is 0.08 (ms).
input size(128, 10000) forward time is 0.11 (ms); backwad avg time is 0.16 (ms).
CPU:
reduction=’mean’
input size(128, 100) forward time is 0.03 (ms); backwad avg time is 0.05 (ms).
input size(128, 10000) forward time is 0.14 (ms); backwad avg time is 0.18 (ms).
reduction=’sum’
input size(128, 100) forward time is 0.03 (ms); backwad avg time is 0.05 (ms).
input size(128, 10000) forward time is 0.15 (ms); backwad avg time is 0.17 (ms).
nume_thread = 1:
reduction=’mean’:
input size(128, 100) forward time is 0.04 (ms); backwad avg time is 0.06 (ms).
input size(128, 10000) forward time is 1.05 (ms); backwad avg time is 1.72 (ms).
reduction=’sum’:
input size(128, 100) forward time is 0.03 (ms); backwad avg time is 0.05 (ms).
input size(128, 10000) forward time is 1.03 (ms); backwad avg time is 1.71 (ms).
```
How to set number thread? using following script:
```
num_threads=$1
script=$2
last_core=`expr $num_threads - 1`
echo "using $num_threads OMP threads"
echo "bind cores to 0~$last_core"
export OMP_NUM_THREADS=$num_threads
export KMP_AFFINITY=granularity=fine,compact,1,0
numactl --physcpubind=0-$last_core --membind=0 python $script
```
and run `./run.sh 1 L1loss.py`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26795
Differential Revision: D18140434
Pulled By: VitalyFedyunin
fbshipit-source-id: d0b976ec36797f2e6b4e58fbbac89688d29e736f
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