mirror of
https://github.com/huggingface/candle.git
synced 2025-06-18 11:37:11 +00:00
Refactor the pth tensor exctraction. (#1109)
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@ -193,6 +193,50 @@ impl Object {
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_ => Err(self),
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}
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}
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pub fn into_tensor_info(
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self,
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name: Self,
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dir_name: &std::path::Path,
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) -> Result<Option<TensorInfo>> {
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let name = match name.unicode() {
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Ok(name) => name,
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Err(_) => return Ok(None),
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};
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let (callable, args) = match self.reduce() {
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Ok(callable_args) => callable_args,
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_ => return Ok(None),
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};
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let (callable, args) = match callable {
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Object::Class {
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module_name,
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class_name,
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} if module_name == "torch._tensor" && class_name == "_rebuild_from_type_v2" => {
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let mut args = args.tuple()?;
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let callable = args.remove(0);
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let args = args.remove(1);
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(callable, args)
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}
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_ => (callable, args),
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};
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match callable {
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Object::Class {
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module_name,
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class_name,
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} if module_name == "torch._utils" && class_name == "_rebuild_tensor_v2" => {}
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_ => return Ok(None),
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};
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let (layout, dtype, file_path, storage_size) = rebuild_args(args)?;
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let mut path = dir_name.to_path_buf();
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path.push(file_path);
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Ok(Some(TensorInfo {
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name,
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dtype,
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layout,
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path: path.to_string_lossy().into_owned(),
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storage_size,
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}))
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}
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}
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impl TryFrom<Object> for String {
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@ -623,50 +667,10 @@ pub fn read_pth_tensor_info<P: AsRef<std::path::Path>>(
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};
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if let Object::Dict(key_values) = obj {
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for (name, value) in key_values.into_iter() {
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let name = match name.unicode() {
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Ok(name) => name,
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Err(_) => continue,
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};
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let (callable, args) = match value.reduce() {
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Ok(callable_args) => callable_args,
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_ => continue,
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};
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let (callable, args) = match callable {
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Object::Class {
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module_name,
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class_name,
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} if module_name == "torch._tensor"
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&& class_name == "_rebuild_from_type_v2" =>
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{
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let mut args = args.tuple()?;
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let callable = args.remove(0);
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let args = args.remove(1);
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(callable, args)
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}
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_ => (callable, args),
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};
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match callable {
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Object::Class {
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module_name,
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class_name,
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} if module_name == "torch._utils" && class_name == "_rebuild_tensor_v2" => {}
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_ => continue,
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};
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match rebuild_args(args) {
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Ok((layout, dtype, file_path, storage_size)) => {
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let mut path = dir_name.clone();
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path.push(file_path);
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tensor_infos.push(TensorInfo {
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name,
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dtype,
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layout,
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path: path.to_string_lossy().into_owned(),
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storage_size,
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})
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}
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Err(err) => {
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eprintln!("skipping {name}: {err:?}")
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}
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match value.into_tensor_info(name, &dir_name) {
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Ok(Some(tensor_info)) => tensor_infos.push(tensor_info),
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Ok(None) => {}
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Err(err) => eprintln!("skipping: {err:?}"),
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}
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}
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}
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