Examples

The docs/source/user_guide/examples/ directory in this repository contains self-contained scripts demonstrating common Torch-Spyre use cases.

Available Examples

Script	Description
`tensor_allocate.py`	Creating and allocating tensors on the Spyre device
`softmax.py`	Computing softmax on Spyre
`gelu.py`	Computing GELU activation on Spyre
`mean.py`	Computing mean reduction on Spyre
`mul.py`	Element-wise multiplication on Spyre
`softplus.py`	Computing softplus activation on Spyre
`spyre_hints.py`	Using Spyre compiler hints to control tiling

Distributed Examples

Script	Description
`distributed/allgather.py`	AllGather collective on Spyre
`distributed/allreduce.py`	AllReduce collective on Spyre
`distributed/barrier.py`	Barrier synchronization on Spyre
`distributed/broadcast.py`	Broadcast collective on Spyre
`distributed/gather.py`	Gather collective on Spyre
`distributed/reduce.py`	Reduce collective on Spyre

Running an Example

python docs/source/user_guide/examples/tensor_allocate.py
python docs/source/user_guide/examples/softmax.py

Writing Your Own Example

A minimal Torch-Spyre script follows this pattern:

import torch

DEVICE = torch.device("spyre")

# Move data to device
x = torch.rand(512, 1024, dtype=torch.float16).to(DEVICE)

# Run computation (optionally with torch.compile)
output = torch.some_op(x)

# Move result back to CPU for inspection
print(output.cpu())

See Also