mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 12:54:11 +08:00
1fd119948e
Changes: - #95200 1. Recognize `.py.in` and `.pyi.in` files as Python in VS Code for a better development experience. 2. Fix deep setting merge in `tools/vscode_settings.py`. - #95267 3. Use `Namedtuple` rather than `namedtuple + __annotations__` for `torch.nn.utils.rnn.PackedSequence_`: `namedtuple + __annotations__`: ```python PackedSequence_ = namedtuple('PackedSequence_', ['data', 'batch_sizes', 'sorted_indices', 'unsorted_indices']) # type annotation for PackedSequence_ to make it compatible with TorchScript PackedSequence_.__annotations__ = {'data': torch.Tensor, 'batch_sizes': torch.Tensor, 'sorted_indices': Optional[torch.Tensor], 'unsorted_indices': Optional[torch.Tensor]} ``` `Namedtuple`: Python 3.6+ ```python class PackedSequence_(NamedTuple): data: torch.Tensor batch_sizes: torch.Tensor sorted_indices: Optional[torch.Tensor] unsorted_indices: Optional[torch.Tensor] ``` - => this PR: #95268 4. Sort import statements and remove unnecessary imports in `.pyi`, `.pyi.in` files. 5. Format `.pyi`, `.pyi.in` files and remove unnecessary ellipsis `...` in type stubs. Pull Request resolved: https://github.com/pytorch/pytorch/pull/95268 Approved by: https://github.com/huydhn
71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
from enum import Enum
|
|
from typing import Optional, Tuple
|
|
|
|
from torch import Tensor
|
|
|
|
# Defined in torch/csrc/functorch/init.cpp
|
|
|
|
def _set_dynamic_layer_keys_included(included: bool) -> None: ...
|
|
def get_unwrapped(tensor: Tensor) -> Tensor: ...
|
|
def is_batchedtensor(tensor: Tensor) -> bool: ...
|
|
def is_functionaltensor(tensor: Tensor) -> bool: ...
|
|
def is_functorch_wrapped_tensor(tensor: Tensor) -> bool: ...
|
|
def is_gradtrackingtensor(tensor: Tensor) -> bool: ...
|
|
def maybe_get_bdim(tensor: Tensor) -> int: ...
|
|
def maybe_get_level(tensor: Tensor) -> int: ...
|
|
def unwrap_if_dead(tensor: Tensor) -> Tensor: ...
|
|
def _unwrap_for_grad(tensor: Tensor, level: int) -> Tensor: ...
|
|
def _wrap_for_grad(tensor: Tensor, level: int) -> Tensor: ...
|
|
def _unwrap_batched(tensor: Tensor, level: int) -> Tuple[Tensor, Optional[int]]: ...
|
|
def current_level() -> int: ...
|
|
def _add_batch_dim(tensor: Tensor, bdim: int, level: int) -> Tensor: ...
|
|
def set_single_level_autograd_function_allowed(allowed: bool) -> None: ...
|
|
def get_single_level_autograd_function_allowed() -> bool: ...
|
|
|
|
# Defined in aten/src/ATen/functorch/Interpreter.h
|
|
class TransformType(Enum):
|
|
Torch: TransformType = ...
|
|
Vmap: TransformType = ...
|
|
Grad: TransformType = ...
|
|
Jvp: TransformType = ...
|
|
Functionalize: TransformType = ...
|
|
|
|
class RandomnessType(Enum):
|
|
Error: TransformType = ...
|
|
Same: TransformType = ...
|
|
Different: TransformType = ...
|
|
|
|
class CInterpreter:
|
|
def key(self) -> TransformType: ...
|
|
def level(self) -> int: ...
|
|
|
|
class CGradInterpreterPtr:
|
|
def __init__(self, interpreter: CInterpreter): ...
|
|
def lift(self, Tensor) -> Tensor: ...
|
|
def prevGradMode(self) -> bool: ...
|
|
|
|
class CJvpInterpreterPtr:
|
|
def __init__(self, interpreter: CInterpreter): ...
|
|
def lift(self, Tensor) -> Tensor: ...
|
|
def prevFwdGradMode(self) -> bool: ...
|
|
|
|
class CFunctionalizeInterpreterPtr:
|
|
def __init__(self, interpreter: CInterpreter): ...
|
|
def key(self) -> TransformType: ...
|
|
def level(self) -> int: ...
|
|
def functionalizeAddBackViews(self) -> bool: ...
|
|
|
|
class CVmapInterpreterPtr:
|
|
def __init__(self, interpreter: CInterpreter): ...
|
|
def key(self) -> TransformType: ...
|
|
def level(self) -> int: ...
|
|
def batchSize(self) -> int: ...
|
|
def randomness(self) -> RandomnessType: ...
|
|
|
|
class DynamicLayer:
|
|
pass
|
|
|
|
def peek_interpreter_stack() -> CInterpreter: ...
|
|
def pop_dynamic_layer_stack() -> DynamicLayer: ...
|
|
def push_dynamic_layer_stack(dl: DynamicLayer) -> int: ...
|