Comments (1)
Note that calling size twice in the same trace but on different tensors works fine:
import torch
import thunder
def func(a, b):
c = a.size()
d = b.size() # works
return a, b
a = torch.randn(100, 100, device='cuda')
b = torch.randn(100, 100, device='cuda')
jfunc = thunder.jit(func)
jfunc(a, b)
Additionally, calling size once in the same trace but invoking the trace twice is also fine:
import torch
import thunder
def func(a):
b = a.size()
return a
a = torch.randn(100, 100, device='cuda')
jfunc = thunder.jit(func)
jfunc(a)
jfunc(a) # works
from lightning-thunder.
Related Issues (20)
- disabling implicit NumberProxy to Number translation.
- Broken CI tests for distributed HOT 5
- `CUDAGraphExecutor` - limited to static graphs only
- `use_cuda` deprecated, switch to `use_device = cuda` instead
- Support for Stable Diffusion models HOT 1
- Add nvfuser to requirements.txt
- benchmark_litgpt.py + Llama-3-8B + FSDP hits OOM since 5/4/24 on H100 HOT 2
- Add the benchmark for ResNet50 HOT 1
- have a method to compare speed of different parts of training between compilation backends
- Use nvFuser executor decisions to pass on op execution to a different backend and retire hybrid `torch_compile_cat_ex` executor. HOT 1
- Expose parameters with overrides in ThunderModule .
- Quantization as a tranform
- Unexpected keyword arg 'inplace' for torch.nn.SiLU HOT 1
- Implement torch.Tensor.masked_fill_ HOT 1
- TypeError with torch.finfo() HOT 1
- TypeError with torch.nn.functional.pad HOT 1
- 'NoneType' object error using thunder.jit with NeMo Stable Diffusion HOT 1
- Recursion error in transformer module with NeMo Stable Diffusion
- Hang using thunder.jit with tokenizer in NeMo Stable Diffusion
- Constraints to insert static numbers
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from lightning-thunder.