Source code for torch._functorch.deprecated

import torch._functorch.vmap as _vmap_impl
import torch._functorch.eager_transforms as _impl
import torch._functorch.make_functional as _nn_impl
from torch._functorch.vmap import in_dims_t, out_dims_t
from torch._functorch.eager_transforms import argnums_t
import torch.nn as nn
import textwrap
from typing import Any, Callable, Optional, Tuple, Union
import warnings

The APIs in this file are exposed as `functorch.*`. They are thin wrappers
around the torch.func.* APIs that have deprecation warnings -- we're trying
to move people to the torch.func.* equivalents.

NB: We don't use *args, **kwargs in the signatures because that changes the

def get_warning(api, new_api=None, replace_newlines=False):
    if new_api is None:
        new_api = f'torch.func.{api}'
    warning = (
        f"We've integrated functorch into PyTorch. As the final step of the \n"
        f"integration, functorch.{api} is deprecated as of PyTorch \n"
        f"2.0 and will be deleted in a future version of PyTorch >= 2.3. \n"
        f"Please use {new_api} instead; see the PyTorch 2.0 release notes \n"
        f"and/or the torch.func migration guide for more details \n"
    if replace_newlines:
        warning = warning.replace("\n", "")
    return warning

def warn_deprecated(api, new_api=None):
    warning = get_warning(api, new_api, replace_newlines=True)
    warnings.warn(warning, stacklevel=2)

def setup_docs(functorch_api, torch_func_api=None, new_api_name=None):
    api_name = functorch_api.__name__
    if torch_func_api is None:
        torch_func_api = getattr(_impl, api_name)

    warning = get_warning(api_name, new_api_name)
    warning_note = "\n.. warning::\n\n" + textwrap.indent(warning, "    ")
    warning_note = textwrap.indent(warning_note, "    ")
    functorch_api.__doc__ = torch_func_api.__doc__ + warning_note

[docs]def vmap( func: Callable, in_dims: in_dims_t = 0, out_dims: out_dims_t = 0, randomness: str = 'error', *, chunk_size=None) -> Callable: warn_deprecated('vmap', 'torch.vmap') return _vmap_impl.vmap(func, in_dims, out_dims, randomness, chunk_size=chunk_size)
[docs]def grad(func: Callable, argnums: argnums_t = 0, has_aux: bool = False) -> Callable: warn_deprecated('grad') return _impl.grad(func, argnums, has_aux)
[docs]def grad_and_value(func: Callable, argnums: argnums_t = 0, has_aux: bool = False) -> Callable: warn_deprecated('grad_and_value') return _impl.grad_and_value(func, argnums, has_aux)
[docs]def vjp(func: Callable, *primals, has_aux: bool = False): warn_deprecated('vjp') return _impl.vjp(func, *primals, has_aux=has_aux)
[docs]def jvp(func: Callable, primals: Any, tangents: Any, *, strict: bool = False, has_aux: bool = False): warn_deprecated('jvp') return _impl.jvp(func, primals, tangents, strict=strict, has_aux=has_aux)
[docs]def jacrev(func: Callable, argnums: Union[int, Tuple[int]] = 0, *, has_aux=False, chunk_size: Optional[int] = None, _preallocate_and_copy=False): warn_deprecated('jacrev') return _impl.jacrev(func, argnums, has_aux=has_aux, chunk_size=chunk_size, _preallocate_and_copy=_preallocate_and_copy)
[docs]def jacfwd(func: Callable, argnums: argnums_t = 0, has_aux: bool = False, *, randomness: str = "error"): warn_deprecated('jacfwd') return _impl.jacfwd(func, argnums, has_aux, randomness=randomness)
[docs]def hessian(func, argnums=0): warn_deprecated('hessian') return _impl.hessian(func, argnums=argnums)
[docs]def functionalize(func: Callable, *, remove: str = 'mutations') -> Callable: warn_deprecated('functionalize') return _impl.functionalize(func, remove=remove)
[docs]def make_functional(model: nn.Module, disable_autograd_tracking: bool = False): warn_deprecated('make_functional', 'torch.func.functional_call') return _nn_impl.make_functional(model, disable_autograd_tracking)
[docs]def make_functional_with_buffers(model: nn.Module, disable_autograd_tracking: bool = False): warn_deprecated('make_functional_with_buffers', 'torch.func.functional_call') return _nn_impl.make_functional_with_buffers(model, disable_autograd_tracking)
[docs]def combine_state_for_ensemble(models): warn_deprecated('combine_state_for_ensemble', 'torch.func.stack_module_state') return _nn_impl.combine_state_for_ensemble(models)
setup_docs(vmap, _vmap_impl.vmap, 'torch.vmap') setup_docs(grad) setup_docs(grad_and_value) setup_docs(vjp) setup_docs(jvp) setup_docs(jacrev) setup_docs(jacfwd) setup_docs(hessian) setup_docs(functionalize) setup_docs(make_functional, _nn_impl.make_functional, 'torch.func.functional_call') setup_docs(make_functional_with_buffers, _nn_impl.make_functional, 'torch.func.functional_call') setup_docs(combine_state_for_ensemble, _nn_impl.combine_state_for_ensemble, 'torch.func.stack_module_state')


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