base

Base class for packaged Stained Glass Transforms.

Classes:

Name	Description
`StainedGlassTransform`	Base class for all packaged Stained Glass Transforms.

StainedGlassTransform ¶

Bases: Module, ABC, ModelHubMixin, Generic[NoisyModelT, NoiseLayerT]

Base class for all packaged Stained Glass Transforms.

This class provides a common, simple interface for performing inference with pretrained Stained Glass Transforms, as well as managing/loading/saving to the Hugging Face Hub and to disk. It also provides utilities for inferring the minimal parameters of the client and for optimizing the loading and saving of the Stained Glass Transform by only loading and saving the necessary submodules.

Methods:

Name	Description
`__getstate__`	Return a json-serializable dictionary representing the state of the Stained Glass Transform.
`__init__`	Initialize the Stained Glass Transform base client.
`__repr__`	Safe string representation of the Stained Glass Transform module.
`__setstate__`	Set the state of the Stained Glass Transform from a dictionary.
`forward`	Apply the Stained Glass Transform to an input.
`from_pretrained`	Load the client from the given path.
`generate_model_card`	Generate model card from instance model card metadata and class templates.
`infer_minimal_parameters`	Infer the minimal parameters of the client, excluding parameters not needed for the client.
`infer_minimal_submodules`	Infer the minimal set of submodules that are needed to apply the Stained Glass Transform.
`manual_seed`	Set seed to enable/disable reproducible behavior.
`override_runtime_config_during_load`	Override any attributes of the runtime config during loading of the Stained Glass Transform.
`push_to_hub`	Upload model checkpoint to the Hub.
`save_pretrained`	Save the client to the given path.
`state_dict`	Get the state dictionary of the client, excluding parameters not needed for the client.

Attributes:

Name	Type	Description
`noise_layer`	`NoiseLayerT`	Alias for the contained noise layer.
`noisy_model`	`NoisyModelT`	Alias for the contained `NoisyModel`.
`parameter_names_relative_to_client`	`list[str]`	Get the minimal parameters of the client, excluding parameters not needed for the client.
`parameter_names_to_remove_relative_to_client`	`list[str]`	Get the parameters to ignore when saving the client, excluding parameters not needed for the client.
`stainedglass_core_version`	`str \| None`	Get the version of Stained Glass Core used to save the Stained Glass Transform.

noise_layer `property` ¶

noise_layer: NoiseLayerT

Alias for the contained noise layer.

noisy_model `property` ¶

noisy_model: NoisyModelT

Alias for the contained NoisyModel.

Warning

A deserialized Stained Glass Transform may not include the complete base-model parameters. Calling the underlying noisy model referenced in this property can fail.

parameter_names_relative_to_client `property` ¶

parameter_names_relative_to_client: list[str]

Get the minimal parameters of the client, excluding parameters not needed for the client.

This property will first check if self.parameter_names_relative_to_base_model is set (this is usually set via the parameter_names argument in the __init__ method). If it is, then it will return the parameters defined there, but with the submodule names changed to be relative to the client.

If self.parameter_names_relative_to_base_model is not set, then it will return the parameters inferred by the infer_minimal_parameters method's most recent call. This requires that the infer_minimal_parameters method has been called at least once before accessing this property.

Note

self.parameter_names_relative_to_base_model, if specified, will override the inferred parameters in calculating this property.

Returns:

Type	Description
`list[str]`	The minimal parameters of the client, excluding parameters not needed for the client.

Raises:

Type	Description
`ValueError`	If the minimal parameters of the base model have not been specified manually or inferred automatically.

parameter_names_to_remove_relative_to_client `property` ¶

parameter_names_to_remove_relative_to_client: list[str]

Get the parameters to ignore when saving the client, excluding parameters not needed for the client.

This is effectively the set of all parameters in the client that are not in parameter_names_relative_to_client, considering duplicate parameters shared by multiple modules (and thus can be accessed by multiple names).

Returns:

Type	Description
`list[str]`	The parameters to ignore when saving the client, excluding parameters not needed for the client.

stainedglass_core_version `property` ¶

stainedglass_core_version: str | None

Get the version of Stained Glass Core used to save the Stained Glass Transform.

Returns:

Type	Description
`str \| None`	The version of Stained Glass Core used to save the Stained Glass Transform.

getstate `abstractmethod` ¶

__getstate__() -> dict[str, typing.Any]

Return a json-serializable dictionary representing the state of the Stained Glass Transform.

The output of this method should be able to be passed into __setstate__ to reconstruct the Stained Glass Transform.

init ¶

__init__(
    model: ~NoisyModelT,
    noise_layer_type: type[~NoiseLayerT],
    parameter_names: list[str] | None = None,
    include_all_base_model_params: bool = False,
    name: str | None = None,
    model_card_data: ModelCardData | None = None,
) -> None

Initialize the Stained Glass Transform base client.

Warning

The constructor will automatically infer the minimal base model parameters required to calculate the base model's input embeddings. This requires a forward pass and assumes the model has a static computational graph. If you want to manually specify the minimal parameters, you can pass in the parameter_names argument. Note, however, that you must specify all of the parameters necessary to calculate the base model's input embeddings.

Parameters:

Name	Type	Description	Default
`model` ¶	`~NoisyModelT`	The NoisyModel used to train Stained Glass Transform.	required
`noise_layer_type` ¶	`type[~NoiseLayerT]`	The type of the noise layer used in the Stained Glass Transform. This is primarily used for type safety.	required
`parameter_names` ¶	`list[str] \| None`	Parameters of the base model to be saved and loaded during serialization and deserialization. This should be the minimal list of parameters necessary to get the base model's input embeddings. If `None`, then the minimal parameters must be inferred by calling the `infer_minimal_parameters` method, before serialization. Parameter names specified here explicitly will override any inferred parameters.	`None`
`include_all_base_model_params` ¶	`bool`	Whether to include all base model parameters in the client. If `True`, then all parameters of the base model will be saved and loaded during serialization and deserialization, regardless of the `parameter_names`.	`False`
`name` ¶	`str \| None`	The name of the StainedGlassTransform. This is used to identify the transform when saving and loading.	`None`
`model_card_data` ¶	`ModelCardData \| None`	Optional model card data to associate with the Stained Glass Transform. Useful for providing metadata when sharing the transform on the Hugging Face Hub. Follow the documentation on Model Cards and `ModelCardData` for more information on how to fill out the model card data. Useful fields to consider setting include `base_model`, `datasets`, `eval_results`, and `metrics`.	`None`

repr ¶

__repr__() -> <class 'str'>

Safe string representation of the Stained Glass Transform module.

The Stained Glass Transform operates with None weight valued submodules which are not needed for the SGT computation. Standard nn.Module.__repr__ calls extra_repr on each submodule, which may attempt to access weight attributes and raise an AttributeError. This override temporarily patches nn.Module.__repr__ to gracefully handle those cases for the duration of the call.

Returns:

Type	Description
`<class 'str'>`	A string representation of the Stained Glass Transform module.

setstate `abstractmethod` ¶

__setstate__(state: dict[str, Any], **kwargs: Any) -> None

Set the state of the Stained Glass Transform from a dictionary.

The input dictionary should be in the format produced by __getstate__.

Parameters:

Name	Type	Description	Default
`state` ¶	`dict[str, Any]`	A dictionary representing the state of the Stained Glass Transform.	required
`**kwargs` ¶	`Any`	Additional keyword arguments that may be needed to set the state.	required

forward `abstractmethod` ¶

forward(*args: Any, **kwargs: Any) -> typing.Any

Apply the Stained Glass Transform to an input.

This method should be implemented by subclasses to define the forward pass of the Stained Glass Transform.

Parameters:

Name	Type	Description	Default
`*args` ¶	`Any`	Positional arguments for the forward pass.	required
`**kwargs` ¶	`Any`	Keyword arguments for the forward pass.	required

Returns:

Type	Description
`typing.Any`	The output of the forward pass.

from_pretrained `classmethod` ¶

from_pretrained(
    pretrained_model_name_or_path: str | Path,
    map_location: device | str | None = None,
    index_file_name: str | None = None,
    dtype: str | dtype | None = None,
    noise_layer_attention: (
        Literal[
            "sdpa",
            "flash_attention_2",
            "flex_attention",
            "transformers_default",
        ]
        | None
    ) = None,
    third_party_model_path: (
        str | PathLike[str] | None
    ) = None,
    *,
    force_download: bool = False,
    resume_download: bool | None = None,
    proxies: bool | dict[Any, Any] | None = None,
    token: str | bool | None = None,
    cache_dir: str | Path | None = None,
    local_files_only: bool = False,
    revision: str | None = None,
    trust_remote_code: bool = False,
    **model_kwargs: Any
) -> typing.Self

Load the client from the given path.

Parameters:

Name	Type	Description	Default
`pretrained_model_name_or_path` ¶	`str \| Path`	The path to load the client from. This can be a path to a `.sgt` zipfile or a model name on the Hugging Face Hub (such as `Protopia/SGT-for-llama-3.1-8b-instruct-rare-rain-bfloat16`). Passing a local directory is not supported.	required
`map_location` ¶	`device \| str \| None`	The location to map the client to. See torch.device for more information.	`None`
`index_file_name` ¶	`str \| None`	The name of the index file to use within the zipfile. If None, the default index file name will be used.	`None`
`dtype` ¶	`str \| dtype \| None`	The dtype, either as a string or a `torch.dtype`, to use for the noise layer and embedding weights. If None, the default dtype will be used. When passed as a string, it should be formatted as "torch.", e.g. "torch.float32" or "torch.bfloat16".	`None`
`noise_layer_attention` ¶	`Literal['sdpa', 'flash_attention_2', 'flex_attention', 'transformers_default'] \| None`	The attention type to use for the noise layer. If None, the default attention type will be used.	`None`
`third_party_model_path` ¶	`str \| PathLike[str] \| None`	The path or huggingface reference to a third-party model to load. This is useful when loading SGTs whose internal structure depends on transformers which are not importable directly through transformers, but are present on the Hugging Face Hub.	`None`
`force_download` ¶	`bool`	Whether to force the download of the client. If False, the client will be downloaded if it is not already present in the cache.	`False`
`resume_download` ¶	`bool \| None`	Unused. Required for compatibility with the Hugging Face Hub API.	`None`
`proxies` ¶	`bool \| dict[Any, Any] \| None`	Unused. Required for compatibility with the Hugging Face Hub API.	`None`
`token` ¶	`str \| bool \| None`	The token to use for authentication with the Hugging Face Hub API.	`None`
`cache_dir` ¶	`str \| Path \| None`	The directory to use for caching the client. If None, the default cache directory will be used.	`None`
`local_files_only` ¶	`bool`	Whether to only use local files and not attempt to download the client. If True, an error will be raised if the client is not present in the cache.	`False`
`revision` ¶	`str \| None`	The revision of the client to use. This can be a branch name, tag name, or commit hash. If None, the default revision will be used.	`None`
`trust_remote_code` ¶	`bool`	Whether to trust remote code when loading from HuggingFace Hub.	`False`
`model_kwargs` ¶	`Any`	Unused. Required for compatibility with the Hugging Face Hub API.	required

Returns:

Type	Description
`typing.Self`	The loaded client.

Raises:

Type	Description
`ValueError`	If any `model_kwargs` are passed in, as they are not supported
`IsADirectoryError`	If the specified path is a directory, but a .sgt file path is required.

generate_model_card ¶

generate_model_card(*args: Any, **kwargs: Any) -> <class 'huggingface_hub.repocard.ModelCard'>

Generate model card from instance model card metadata and class templates.

Parameters:

Name	Type	Description	Default
`*args` ¶	`Any`	Positional arguments to huggingface_hub.ModelCard.from_template. Unused (because all arguments are passed by keyword).	required
`**kwargs` ¶	`Any`	Keyword arguments to the template_str passed to huggingface_hub.ModelCard.from_template.	required

Returns:

Type	Description
`<class 'huggingface_hub.repocard.ModelCard'>`	Generated ModelCard object.

Changed in version v2.8.0: Automatically generated model card files now respect instance model card metadata.

infer_minimal_parameters ¶

infer_minimal_parameters() -> None

Infer the minimal parameters of the client, excluding parameters not needed for the client.

This method will infer the minimal parameters of the client by tracing a forward pass through the model. This is useful when the minimal parameters are not known ahead of time.

Raises:

Type	Description
`ValueError`	If the minimal parameters of the client have been specified

infer_minimal_submodules `abstractmethod` ¶

infer_minimal_submodules() -> list[str]

Infer the minimal set of submodules that are needed to apply the Stained Glass Transform.

This method should return a list of submodule names that are needed to apply the Stained Glass Transform. This is used to optimize the loading and saving of the Stained Glass Transform by only loading and saving the necessary submodules.

Returns:

Type	Description
`list[str]`	A list of submodule names that are needed to apply the Stained Glass Transform.

manual_seed ¶

manual_seed(
    seed: int | None, rank_dependent: bool = True
) -> None

Set seed to enable/disable reproducible behavior.

Setting seed to None will disable reproducible behavior.

Parameters:

Name	Type	Description	Default
`seed` ¶	`int \| None`	Value to seed into the random number generator.	required
`rank_dependent` ¶	`bool`	Whether to add the distributed rank to the seed to ensure that each process samples different noise.	`True`

override_runtime_config_during_load `abstractmethod` `staticmethod` ¶

override_runtime_config_during_load(
    runtime_config: dict[str, Any], **kwargs: Any
) -> dict[str, typing.Any]

Override any attributes of the runtime config during loading of the Stained Glass Transform.

This is normally used to override add any backward compatibility fixes to the output of __getstate__ or for embedding any additional kwargs into the config passed to __setstate__ during loading.

This is used during from_pretrained after loading the SGT config from file, but before passing it to __setstate__ to construct the SGT.

Parameters:

Name	Type	Description	Default
`runtime_config` ¶	`dict[str, Any]`	The runtime config loaded from the SGT config file.	required
`**kwargs` ¶	`Any`	Additional keyword arguments that may be needed to override the runtime config.	required

Returns:

Type	Description
`dict[str, typing.Any]`	The overridden runtime config to be passed to `__setstate__` during loading.

push_to_hub ¶

push_to_hub(repo_id: str, *, config: dict | DataclassInstance | None = None, commit_message: str = 'Upload using stainedglass_core.', private: bool | None = None, token: str | None = None, branch: str | None = None, create_pr: bool | None = None, allow_patterns: list[str] | str | None = None, ignore_patterns: list[str] | str | None = None, delete_patterns: list[str] | str | None = None, model_card_kwargs: dict[str, Any] | None = None) -> <class 'str'>

Upload model checkpoint to the Hub.

Warning

This method is currently not supported on StainedGlassTransform. Instead use save_pretrained with push_to_hub=True.

Use allow_patterns and ignore_patterns to precisely filter which files should be pushed to the hub. Use delete_patterns to delete existing remote files in the same commit. See [upload_folder] reference for more details.

Parameters:

Name	Type	Description	Default
`repo_id` ¶	`str`	ID of the repository to push to (example: `"username/my-model"`).	required
`config` ¶	`dict \| DataclassInstance \| None`	Model configuration specified as a key/value dictionary or a dataclass instance.	`None`
`commit_message` ¶	`str`	Message to commit while pushing.	`'Upload using stainedglass_core.'`
`private` ¶	`bool \| None`	Whether the repository created should be private. If `None` (default), the repo will be public unless the organization's default is private.	`None`
`token` ¶	`str \| None`	The token to use as HTTP bearer authorization for remote files. By default, it will use the token cached when running `hf auth login`.	`None`
`branch` ¶	`str \| None`	The git branch on which to push the model. This defaults to `"main"`.	`None`
`create_pr` ¶	`bool \| None`	Whether or not to create a Pull Request from `branch` with that commit.	`None`
`allow_patterns` ¶	`list[str] \| str \| None`	If provided, only files matching at least one pattern are pushed.	`None`
`ignore_patterns` ¶	`list[str] \| str \| None`	If provided, files matching any of the patterns are not pushed.	`None`
`delete_patterns` ¶	`list[str] \| str \| None`	If provided, remote files matching any of the patterns will be deleted from the repo.	`None`
`model_card_kwargs` ¶	`dict[str, Any] \| None`	Additional arguments passed to the model card template to customize the model card.	`None`

Returns:

Type	Description
`<class 'str'>`	The url of the commit of your model in the given repository.

Raises:

Type	Description
`NotImplementedError`	This method is not implemented.

save_pretrained ¶

save_pretrained(
    save_directory: str | Path,
    *,
    compression: int = 8,
    push_to_hub: bool = False,
    repo_id: str | None = None,
    private: bool = True,
    config: dict | DataclassInstance | None = None,
    model_card_kwargs: dict[str, Any] | None = None,
    **push_to_hub_kwargs: Any
) -> None

Save the client to the given path.

Parameters:

Name	Type	Description	Default
`save_directory` ¶	`str \| Path`	The path to save the client to. Although this is called `save_directory` for compatibility with `ModelHubMixin.save_pretrained`, passing in a directory name is not supported. A `.sgt` zipfile will be generated at the path provided (even if the path provided does not use the `.sgt` file extension)	required
`compression` ¶	`int`	The compression method to use for the ZIP file. Defaults to zipfile.ZIP_DEFLATED, but this can cause very slow serialization times. If serialization times are a problem, use zipfile.ZIP_STORED instead.	`8`
`push_to_hub` ¶	`bool`	Whether to push the client to the Hugging Face Hub.	`False`
`repo_id` ¶	`str \| None`	The repository ID to push the client to. This is required if `push_to_hub` is `True`.	`None`
`private` ¶	`bool`	Whether to make the repository private. This is only used if `push_to_hub` is `True`.	`True`
`config` ¶	`dict \| DataclassInstance \| None`	Unused. Required for compatibility with the Hugging Face Hub API.	`None`
`model_card_kwargs` ¶	`dict[str, Any] \| None`	The kwargs to pass to the model card generator. This is only used if `push_to_hub` is `True`.	`None`
`push_to_hub_kwargs` ¶	`Any`	The kwargs to pass to the `HfApi.upload_folder` method. This is only used if `push_to_hub` is `True`.	required

Raises:

Type	Description
`IsADirectoryError`	If a directory is passed in.
`ValueError`	If `push_to_hub` is `True` and `repo_id` is `None`.
`UserWarning`	If `push_to_hub` is `True` and `private` is `False`.
`compression`	The compression method to use for the ZIP file. Defaults to zipfile.ZIP_DEFLATED, but this can cause very slow serialization times. If serialization times are a problem, use zipfile.ZIP_STORED instead.

Examples:

Uploading a Stained Glass Transform zipfile to the Hugging Face Hub (note that this will also create a local copy of the SGT zipfile):

>>> from stainedglass_core.transform import text
>>> sgt = text.StainedGlassTransformForText.from_pretrained(
...     "path/to/sgt_file.sgt"
... )
>>> sgt.save_pretrained(
...     "new-sgt-zipfile.sgt",
...     push_to_hub=True,
...     repo_id="username/new-sgt-repo",
... )

Optionally, you can override any model card metadata before uploading to the Hub. This can be useful for specifying the base model and datasets used for training Stained Glass Transform. You can also specify additional metadata such as eval_results. See huggingface_hub.ModelCardData for more details on the available fields.

>>> sgt.model_card_data.base_model = (
...     "meta-llama/Llama-3.1-8B-Instruct"
... )
>>> sgt.model_card_data.__dict__["base_model_relation"] = (
...     "adapter"
... )
>>> sgt.model_card_data.datasets = ["Open-Orca/OpenOrca"]
>>> sgt.save_pretrained(
...     "new-sgt-zipfile.sgt",
...     push_to_hub=True,
...     repo_id="username/new-sgt-repo",
... )

Changed in version v2.8.0: Added ability to push Stained Glass Transform to the Hugging Face Hub. BREAKING CHANGE: Argument `path` was renamed `save_directory` for compatibility with ModelHubMixin.save_pretrained

Changed in version v2.20.3: The model safetensors filename was changed for better compatibility with the Hugging Face Hub. This has no practical effect on saving or loading.

state_dict ¶

state_dict(
    *, prefix: str = "", keep_vars: bool = False
) -> dict[str, typing.Any]

Get the state dictionary of the client, excluding parameters not needed for the client.

The parameters considered necessary for the client are those passed into the constructor as parameter_names.

Parameters:

Name	Type	Description	Default
`prefix` ¶	`str`	A prefix added to parameter and buffer names to compose the keys in state_dict.	`''`
`keep_vars` ¶	`bool`	By default the `torch.Tensor`s returned in the state dict are detached from autograd. If it's set to `True`, detaching will not be performed.	`False`

Returns:

Type	Description
`dict[str, typing.Any]`	The state dictionary of the client, excluding parameters not needed for the client.

base

StainedGlassTransform ¶

noise_layer property ¶

noisy_model property ¶

parameter_names_relative_to_client property ¶

parameter_names_to_remove_relative_to_client property ¶

stainedglass_core_version property ¶

__getstate__ abstractmethod ¶

__init__ ¶

model ¶

noise_layer_type ¶

parameter_names ¶

include_all_base_model_params ¶

name ¶

model_card_data ¶

__repr__ ¶

__setstate__ abstractmethod ¶

state ¶

**kwargs ¶

forward abstractmethod ¶

*args ¶

**kwargs ¶

from_pretrained classmethod ¶

pretrained_model_name_or_path ¶

map_location ¶

index_file_name ¶

dtype ¶

noise_layer_attention ¶

third_party_model_path ¶

force_download ¶

resume_download ¶

proxies ¶

token ¶

cache_dir ¶

local_files_only ¶

revision ¶

trust_remote_code ¶

model_kwargs ¶

generate_model_card ¶

*args ¶

**kwargs ¶

infer_minimal_parameters ¶

infer_minimal_submodules abstractmethod ¶

manual_seed ¶

seed ¶

rank_dependent ¶

override_runtime_config_during_load abstractmethod staticmethod ¶

runtime_config ¶

**kwargs ¶

push_to_hub ¶

repo_id ¶

config ¶

commit_message ¶

private ¶

token ¶

branch ¶

create_pr ¶

allow_patterns ¶

ignore_patterns ¶

delete_patterns ¶

model_card_kwargs ¶

save_pretrained ¶

save_directory ¶

compression ¶

push_to_hub ¶

repo_id ¶

private ¶

config ¶

model_card_kwargs ¶

push_to_hub_kwargs ¶

state_dict ¶

prefix ¶

keep_vars ¶

noise_layer `property` ¶

noisy_model `property` ¶

parameter_names_relative_to_client `property` ¶

parameter_names_to_remove_relative_to_client `property` ¶

stainedglass_core_version `property` ¶

getstate `abstractmethod` ¶

init ¶

`model` ¶

`noise_layer_type` ¶

`parameter_names` ¶

`include_all_base_model_params` ¶

`name` ¶

`model_card_data` ¶

repr ¶

setstate `abstractmethod` ¶

`state` ¶

`**kwargs` ¶

forward `abstractmethod` ¶

`*args` ¶

`**kwargs` ¶

from_pretrained `classmethod` ¶

`pretrained_model_name_or_path` ¶

`map_location` ¶

`index_file_name` ¶

`dtype` ¶

`noise_layer_attention` ¶

`third_party_model_path` ¶

`force_download` ¶

`resume_download` ¶

`proxies` ¶

`token` ¶

`cache_dir` ¶

`local_files_only` ¶

`revision` ¶

`trust_remote_code` ¶

`model_kwargs` ¶

`*args` ¶

`**kwargs` ¶

infer_minimal_submodules `abstractmethod` ¶

`seed` ¶

`rank_dependent` ¶

override_runtime_config_during_load `abstractmethod` `staticmethod` ¶

`runtime_config` ¶

`**kwargs` ¶

`repo_id` ¶

`config` ¶

`commit_message` ¶

`private` ¶

`token` ¶

`branch` ¶

`create_pr` ¶

`allow_patterns` ¶

`ignore_patterns` ¶

`delete_patterns` ¶

`model_card_kwargs` ¶

`save_directory` ¶

`compression` ¶

`push_to_hub` ¶

`repo_id` ¶

`private` ¶

`config` ¶

`model_card_kwargs` ¶

`push_to_hub_kwargs` ¶

`prefix` ¶

`keep_vars` ¶