mirror of https://github.com/hpcaitech/ColossalAI
129 lines
7.5 KiB
Markdown
129 lines
7.5 KiB
Markdown
# Tensor Detector
|
|
|
|
This tool supports you to detect tensors on both CPU and GPU. However, there will always be some strange tensors on CPU, including the rng state of PyTorch.
|
|
|
|
## Example
|
|
|
|
An example is worth than a thousand words.
|
|
|
|
The code below defines a simple MLP module, with which we will show you how to use the tool.
|
|
|
|
```python
|
|
class MLP(nn.Module):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.mlp = nn.Sequential(nn.Linear(64, 8),
|
|
nn.ReLU(),
|
|
nn.Linear(8, 32))
|
|
def forward(self, x):
|
|
return self.mlp(x)
|
|
```
|
|
|
|
And here is how to use the tool.
|
|
|
|
```python
|
|
from colossalai.utils import TensorDetector
|
|
|
|
# create random data
|
|
data = torch.rand(64, requires_grad=True).cuda()
|
|
data.retain_grad()
|
|
# create the module
|
|
model = MLP().cuda()
|
|
# create the detector
|
|
# by passing the model to the detector, it can distinguish module parameters from common tensors
|
|
detector = TensorDetector(include_cpu=False, module=model)
|
|
detector.detect()
|
|
|
|
out = model(data)
|
|
|
|
detector.detect()
|
|
|
|
loss = out.sum()
|
|
loss.backward()
|
|
|
|
detector.detect()
|
|
```
|
|
|
|
I have made some comments on the right of the output for your understanding.
|
|
|
|
Note that the total `Mem` of all the tensors and parameters is not equal to `Total GPU Memery Allocated`. PyTorch's memory management is really complicated, and for models of a large scale, it's impossible to figure out clearly.
|
|
|
|
**The order of print is not equal to the order the tensor creates, but they are really close.**
|
|
|
|
```bash
|
|
------------------------------------------------------------------------------------------------------------
|
|
Tensor device shape grad dtype Mem
|
|
------------------------------------------------------------------------------------------------------------
|
|
+ Tensor cuda:0 (64,) True torch.float32 256 B # data
|
|
+ mlp.0.weight cuda:0 (8, 64) True torch.float32 2.0 KB
|
|
+ mlp.0.bias cuda:0 (8,) True torch.float32 32 B
|
|
+ mlp.2.weight cuda:0 (32, 8) True torch.float32 1.0 KB
|
|
+ mlp.2.bias cuda:0 (32,) True torch.float32 128 B
|
|
------------------------------------------------------------------------------------------------------------
|
|
Detect Location: "test_tensor_detector.py" line 27
|
|
Totle GPU Memery Allocated on cuda:0 is 4.5 KB
|
|
------------------------------------------------------------------------------------------------------------
|
|
|
|
|
|
------------------------------------------------------------------------------------------------------------
|
|
Tensor device shape grad dtype Mem
|
|
------------------------------------------------------------------------------------------------------------
|
|
+ Tensor cuda:0 (8,) True torch.float32 32 B # activation
|
|
+ Tensor cuda:0 (32,) True torch.float32 128 B # output
|
|
------------------------------------------------------------------------------------------------------------
|
|
Detect Location: "test_tensor_detector.py" line 30
|
|
Totle GPU Memery Allocated on cuda:0 is 5.5 KB
|
|
------------------------------------------------------------------------------------------------------------
|
|
|
|
|
|
------------------------------------------------------------------------------------------------------------
|
|
Tensor device shape grad dtype Mem
|
|
------------------------------------------------------------------------------------------------------------
|
|
+ Tensor cuda:0 () True torch.float32 4 B # loss
|
|
------------------------------------------------------------------------------------------------------------
|
|
Detect Location: "test_tensor_detector.py" line 32
|
|
Totle GPU Memery Allocated on cuda:0 is 6.0 KB
|
|
------------------------------------------------------------------------------------------------------------
|
|
|
|
|
|
------------------------------------------------------------------------------------------------------------
|
|
Tensor device shape grad dtype Mem
|
|
------------------------------------------------------------------------------------------------------------
|
|
+ Tensor (with grad) cuda:0 (64,) True torch.float32 512 B # data with grad
|
|
+ mlp.0.weight (with grad) cuda:0 (8, 64) True torch.float32 4.0 KB # for use data.retain_grad()
|
|
+ mlp.0.bias (with grad) cuda:0 (8,) True torch.float32 64 B
|
|
+ mlp.2.weight (with grad) cuda:0 (32, 8) True torch.float32 2.0 KB
|
|
+ mlp.2.bias (with grad) cuda:0 (32,) True torch.float32 256 B
|
|
|
|
- mlp.0.weight cuda:0 (8, 64) True torch.float32 2.0 KB
|
|
- mlp.0.bias cuda:0 (8,) True torch.float32 32 B
|
|
- mlp.2.weight cuda:0 (32, 8) True torch.float32 1.0 KB
|
|
- mlp.2.bias cuda:0 (32,) True torch.float32 128 B
|
|
- Tensor cuda:0 (64,) True torch.float32 256 B
|
|
- Tensor cuda:0 (8,) True torch.float32 32 B # deleted activation
|
|
------------------------------------------------------------------------------------------------------------
|
|
Detect Location: "test_tensor_detector.py" line 34
|
|
Totle GPU Memery Allocated on cuda:0 is 10.0 KB
|
|
------------------------------------------------------------------------------------------------------------
|
|
|
|
|
|
------------------------------------------------------------------------------------------------------------
|
|
Tensor device shape grad dtype Mem
|
|
------------------------------------------------------------------------------------------------------------
|
|
+ Tensor cuda:0 (64,) False torch.float32 256 B
|
|
+ Tensor cuda:0 (8, 64) False torch.float32 2.0 KB
|
|
+ Tensor cuda:0 (8,) False torch.float32 32 B
|
|
+ Tensor cuda:0 (32, 8) False torch.float32 1.0 KB
|
|
+ Tensor cuda:0 (32,) False torch.float32 128 B
|
|
------------------------------------------------------------------------------------------------------------
|
|
Detect Location: "test_tensor_detector.py" line 36
|
|
Totle GPU Memery Allocated on cuda:0 is 14.0 KB
|
|
------------------------------------------------------------------------------------------------------------
|
|
```
|
|
|
|
## Reference
|
|
|
|
This tool was inspired by https://github.com/Stonesjtu/pytorch_memlab/blob/master/pytorch_memlab/mem_reporter.py
|
|
and https://github.com/Oldpan/Pytorch-Memory-Utils
|
|
|