Article directory
1. Local environment
D:\python2023>nvidia-smi
Thu Jul 27 23:27:45 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 497.29 Driver Version: 497.29 CUDA Version: 11.5 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... WDDM | 00000000:03:00.0 On | N/A |
| 27% 36C P8 8W / 120W | 397MiB / 3072MiB | 1% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 1288 C+G Insufficient Permissions N/A |
| 0 N/A N/A 3444 C+G ...y\ShellExperienceHost.exe N/A |
| 0 N/A N/A 7420 C+G ...nputApp\TextInputHost.exe N/A |
| 0 N/A N/A 7896 C+G C:\Windows\explorer.exe N/A |
| 0 N/A N/A 8392 C+G ...b3d8bbwe\WinStore.App.exe N/A |
| 0 N/A N/A 8872 C+G ...5n1h2txyewy\SearchApp.exe N/A |
| 0 N/A N/A 10860 C+G ...lPanel\SystemSettings.exe N/A |
| 0 N/A N/A 11536 C+G ...se6\Application\360se.exe N/A |
| 0 N/A N/A 14264 C+G ...\qbblinktrial\browser.exe N/A |
+-----------------------------------------------------------------------------+
D:\python2023>gcc --version
gcc (x86_64-posix-sjlj-rev0, Built by MinGW-W64 project) 8.1.0
Copyright (C) 2018 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
D:\python2023>python --version
Python 3.8.5
D:\python2023>
2.Anso pytorch (Windows GPU version book)
! Note Be sure to specify –index-url https://download.pytorch.org/whl/torch/ when installing, otherwise the cpu version will be installed. You can visit https://download.pytorch.org/whl/torch/ to find the version you need, such astorch-2.0.1+cu117-cp38-cp38-win_amd64.whl It is faster to download with Thunder
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
3. 官方quickstart
According to the code put together by the official quickstart, if there is a GPU and the installed GPU version pytorch will run on the GPU otherwise CPU (all CPUs). The local test of 20CPU and 1 geforce GPU takes almost 20s.
import torch
from torch import nn
from torch.utils.data import DataLoader
from torchvision import datasets
from torchvision.transforms import ToTensor
#####################
# Download training data from open datasets.
training_data = datasets.FashionMNIST(
root="data",
train=True,
download=True,
transform=ToTensor(),
)
# Download test data from open datasets.
test_data = datasets.FashionMNIST(
root="data",
train=False,
download=True,
transform=ToTensor(),
)
#####################
batch_size = 64
# Create data loaders.
train_dataloader = DataLoader(training_data, batch_size=batch_size)
test_dataloader = DataLoader(test_data, batch_size=batch_size)
for X, y in test_dataloader:
print(f"Shape of X [N, C, H, W]: {
X.shape}")
print(f"Shape of y: {
y.shape} {
y.dtype}")
break
#####################
# Get cpu, gpu or mps device for training.
device = (
"cuda"
if torch.cuda.is_available()
else "mps"
if torch.backends.mps.is_available()
else "cpu"
)
print(f"Using {
device} device")
# Define model
class NeuralNetwork(nn.Module):
def __init__(self):
super().__init__()
self.flatten = nn.Flatten()
self.linear_relu_stack = nn.Sequential(
nn.Linear(28 * 28, 512),
nn.ReLU(),
nn.Linear(512, 512),
nn.ReLU(),
nn.Linear(512, 10)
)
def forward(self, x):
x = self.flatten(x)
logits = self.linear_relu_stack(x)
return logits
model = NeuralNetwork().to(device)
print(model)
#######################################
loss_fn = nn.CrossEntropyLoss()
optimizer = torch.optim.SGD(model.parameters(), lr=1e-3)
########################################
def train(dataloader, model, loss_fn, optimizer):
size = len(dataloader.dataset)
model.train()
for batch, (X, y) in enumerate(dataloader):
X, y = X.to(device), y.to(device)
# Compute prediction error
pred = model(X)
loss = loss_fn(pred, y)
# Backpropagation
loss.backward()
optimizer.step()
optimizer.zero_grad()
if batch % 100 == 0:
loss, current = loss.item(), (batch + 1) * len(X)
print(f"loss: {
loss:>7f} [{
current:>5d}/{
size:>5d}]")
#######################################
def test(dataloader, model, loss_fn):
size = len(dataloader.dataset)
num_batches = len(dataloader)
model.eval()
test_loss, correct = 0, 0
with torch.no_grad():
for X, y in dataloader:
X, y = X.to(device), y.to(device)
pred = model(X)
test_loss += loss_fn(pred, y).item()
correct += (pred.argmax(1) == y).type(torch.float).sum().item()
test_loss /= num_batches
correct /= size
print(f"Test Error: \n Accuracy: {
(100 * correct):>0.1f}%, Avg loss: {
test_loss:>8f} \n")
if __name__ == '__main__':
epochs = 5
for t in range(epochs):
start = time.time()
print(f"Epoch {
t + 1}\n-------------------------------")
train(train_dataloader, model, loss_fn, optimizer)
test(test_dataloader, model, loss_fn)
end = time.time()
print(f"epoch Done:{
end-start}")
print("Done!")
D:\python2023>nvidia-smi
Fri Jul 28 00:42:59 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 497.29 Driver Version: 497.29 CUDA Version: 11.5 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... WDDM | 00000000:03:00.0 On | N/A |
| 27% 37C P5 9W / 120W | 1007MiB / 3072MiB | 9% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 11536 C+G ...se6\Application\360se.exe N/A |
| 0 N/A N/A 14264 C+G ...\qbblinktrial\browser.exe N/A |
| 0 N/A N/A 15648 C ...ython\Python38\python.exe N/A |
+-----------------------------------------------------------------------------+