Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Respects torch.device(0) new behavior without breaking backward compatibility #509

Merged
merged 2 commits into from
Aug 1, 2024
Merged

Respects torch.device(0) new behavior without breaking backward compatibility #509

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
f665edb
Respects torch.device(0) new behavior without breaking backward
Narsil Jul 31, 2024
63a26d4
Fixing anonymous device type, apparently number string is not ok.
Narsil Aug 1, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
67 changes: 22 additions & 45 deletions bindings/python/src/lib.rs
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -267,6 +267,22 @@ enum Device {
Npu(usize),
Xpu(usize),
Xla(usize),
/// User didn't specify acceletor, torch
/// is responsible for choosing.
Anonymous(usize),
}

/// Parsing the device index.
fn parse_device(name: &str) -> PyResult<usize> {
let tokens: Vec<_> = name.split(':').collect();
if tokens.len() == 2 {
let device: usize = tokens[1].parse()?;
Ok(device)
} else {
Err(SafetensorError::new_err(format!(
"device {name} is invalid"
)))
}
}

impl<'source> FromPyObject<'source> for Device {
Expand All @@ -279,56 +295,16 @@ impl<'source> FromPyObject<'source> for Device {
"npu" => Ok(Device::Npu(0)),
"xpu" => Ok(Device::Xpu(0)),
"xla" => Ok(Device::Xla(0)),
name if name.starts_with("cuda:") => {
let tokens: Vec<_> = name.split(':').collect();
if tokens.len() == 2 {
let device: usize = tokens[1].parse()?;
Ok(Device::Cuda(device))
} else {
Err(SafetensorError::new_err(format!(
"device {name} is invalid"
)))
}
}
name if name.starts_with("npu:") => {
let tokens: Vec<_> = name.split(':').collect();
if tokens.len() == 2 {
let device: usize = tokens[1].parse()?;
Ok(Device::Npu(device))
} else {
Err(SafetensorError::new_err(format!(
"device {name} is invalid"
)))
}
}
name if name.starts_with("xpu:") => {
let tokens: Vec<_> = name.split(':').collect();
if tokens.len() == 2 {
let device: usize = tokens[1].parse()?;
Ok(Device::Xpu(device))
} else {
Err(SafetensorError::new_err(format!(
"device {name} is invalid"
)))
}
}
name if name.starts_with("xla:") => {
let tokens: Vec<_> = name.split(':').collect();
if tokens.len() == 2 {
let device: usize = tokens[1].parse()?;
Ok(Device::Xla(device))
} else {
Err(SafetensorError::new_err(format!(
"device {name} is invalid"
)))
}
}
name if name.starts_with("cuda:") => parse_device(name).map(Device::Cuda),
name if name.starts_with("npu:") => parse_device(name).map(Device::Npu),
name if name.starts_with("xpu:") => parse_device(name).map(Device::Xpu),
name if name.starts_with("xla:") => parse_device(name).map(Device::Xla),
name => Err(SafetensorError::new_err(format!(
"device {name} is invalid"
))),
}
} else if let Ok(number) = ob.extract::<usize>() {
Ok(Device::Cuda(number))
Ok(Device::Anonymous(number))
} else {
Err(SafetensorError::new_err(format!("device {ob} is invalid")))
}
Expand All @@ -344,6 +320,7 @@ impl IntoPy<PyObject> for Device {
Device::Npu(n) => format!("npu:{n}").into_py(py),
Device::Xpu(n) => format!("xpu:{n}").into_py(py),
Device::Xla(n) => format!("xla:{n}").into_py(py),
Device::Anonymous(n) => n.into_py(py),
}
}
}
Expand Down
13 changes: 13 additions & 0 deletions bindings/python/tests/test_pt_comparison.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -168,6 +168,19 @@ def test_npu(self):
for k, v in reloaded.items():
self.assertTrue(torch.allclose(data[k], reloaded[k]))

@unittest.skipIf(not torch.cuda.is_available(), "Cuda is not available")
def test_anonymous_accelerator(self):
data = {
"test1": torch.zeros((2, 2), dtype=torch.float32).to(device=0),
"test2": torch.zeros((2, 2), dtype=torch.float16).to(device=0),
}
local = "./tests/data/out_safe_pt_mmap_small_anonymous.safetensors"
save_file(data, local)

reloaded = load_file(local, device=0)
for k, v in reloaded.items():
self.assertTrue(torch.allclose(data[k], reloaded[k]))

def test_sparse(self):
data = {"test": torch.sparse_coo_tensor(size=(2, 3))}
local = "./tests/data/out_safe_pt_sparse.safetensors"
Expand Down
Loading