[BE] wrap deprecated function/class with `typing_extensions.deprecate…

…d` (pytorch#127689) Use `typing_extensions.deprecated` for deprecation annotation if possible. Otherwise, add `category=FutureWarning` to `warnings.warn("message")` if the category is missing. Note that only warnings that their messages contain `[Dd]eprecat(ed|ion)` are updated in this PR. Resolves pytorch#126888 - pytorch#126888 This PR is split from PR pytorch#126898. - pytorch#126898 ------ Pull Request resolved: pytorch#127689 Approved by: https://github.com/Skylion007
weiyusheng · Jun 2, 2024 · 67ef268 · 67ef268
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diff --git a/.github/requirements/conda-env-Linux-X64.txt b/.github/requirements/conda-env-Linux-X64.txt
@@ -5,4 +5,4 @@ ninja=1.10.2
 numpy=1.23.3
 pyyaml=6.0
 setuptools=68.2.2
-typing-extensions=4.3.0
+typing-extensions=4.9.0
diff --git a/.github/requirements/conda-env-iOS.txt b/.github/requirements/conda-env-iOS.txt
@@ -4,4 +4,4 @@ ninja=1.10.2
 numpy=1.23.3
 pyyaml=6.0
 setuptools=68.2.2
-typing-extensions=4.3.0
+typing-extensions=4.9.0
diff --git a/.github/requirements/conda-env-macOS-ARM64 b/.github/requirements/conda-env-macOS-ARM64
@@ -2,7 +2,7 @@ numpy=1.22.3
 pyyaml=6.0
 setuptools=61.2.0
 cmake=3.22.*
-typing-extensions=4.3.0
+typing-extensions=4.9.0
 dataclasses=0.8
 pip=22.2.2
 pillow=10.0.1

diff --git a/.github/requirements/conda-env-macOS-X64 b/.github/requirements/conda-env-macOS-X64
@@ -4,7 +4,7 @@ numpy=1.21.2
 pyyaml=5.3
 setuptools=46.0.0
 cmake=3.22.*
-typing-extensions=4.3.0
+typing-extensions=4.9.0
 dataclasses=0.8
 pip=22.2.2
 pillow=10.0.1

diff --git a/test/distributed/_tensor/test_api.py b/test/distributed/_tensor/test_api.py
@@ -237,7 +237,7 @@ def output_fn(outputs, device_mesh):
             assert isinstance(outputs, DTensor)
             return outputs.to_local()
 
-        with self.assertWarnsRegex(UserWarning, "Deprecating"):
+        with self.assertWarnsRegex(FutureWarning, "Deprecating"):
             replica_module = distribute_module(
                 module_to_replicate,
                 device_mesh,

diff --git a/test/distributed/fsdp/test_fsdp_optim_state.py b/test/distributed/fsdp/test_fsdp_optim_state.py
@@ -1436,7 +1436,7 @@ def should_check_method(method_name: str):
         def get_warning_context():
             warning_regex = "`optim_input` argument is deprecated"
             return self.assertWarnsRegex(
-                expected_warning=UserWarning, expected_regex=warning_regex
+                expected_warning=FutureWarning, expected_regex=warning_regex
             )
 
         self._run_on_all_optim_state_apis(

diff --git a/test/functorch/test_eager_transforms.py b/test/functorch/test_eager_transforms.py
@@ -3258,7 +3258,7 @@ def test_deprecation_vmap(self, device):
         x = torch.randn(3, device=device)
 
         # functorch version of the API is deprecated
-        with self.assertWarnsRegex(UserWarning, "Please use torch.vmap"):
+        with self.assertWarnsRegex(FutureWarning, "Please use `torch.vmap`"):
             vmap(torch.sin)
 
         # the non-functorch version is not deprecated
@@ -3276,7 +3276,9 @@ def test_deprecation_transforms(self, device, transform):
         new_api = getattr(torch.func, transform)
 
         # functorch version of the API is deprecated
-        with self.assertWarnsRegex(UserWarning, f"Please use torch.func.{transform}"):
+        with self.assertWarnsRegex(
+            FutureWarning, f"Please use `torch.func.{transform}`"
+        ):
             api(torch.sin)
 
         # the non-functorch version is not deprecated

diff --git a/test/nn/test_init.py b/test/nn/test_init.py
@@ -521,7 +521,7 @@ def fn():
             init.normal(x)
 
         with self.assertWarnsRegex(
-            UserWarning,
+            FutureWarning,
             "deprecated",
             msg="methods not suffixed with underscore should be deprecated",
         ):

diff --git a/test/nn/test_module_hooks.py b/test/nn/test_module_hooks.py
@@ -1387,7 +1387,8 @@ def forward(self, l):
         m.register_backward_hook(noop)
 
         with self.assertWarnsRegex(
-            UserWarning, "does not take as input a single Tensor or a tuple of Tensors"
+            FutureWarning,
+            "does not take as input a single Tensor or a tuple of Tensors",
         ):
             m([a, b])
 
@@ -1400,7 +1401,7 @@ def forward(self, a, b):
         m.register_backward_hook(noop)
 
         with self.assertWarnsRegex(
-            UserWarning, "does not return a single Tensor or a tuple of Tensors"
+            FutureWarning, "does not return a single Tensor or a tuple of Tensors"
         ):
             m(a, b)
 
@@ -1413,7 +1414,7 @@ def forward(self, a, b):
         m.register_backward_hook(noop)
 
         with self.assertWarnsRegex(
-            UserWarning, "outputs are generated by different autograd Nodes"
+            FutureWarning, "outputs are generated by different autograd Nodes"
         ):
             m(a, b)
 
@@ -1426,7 +1427,7 @@ def forward(self, a):
         m.register_backward_hook(noop)
 
         with self.assertWarnsRegex(
-            UserWarning, "the forward contains multiple autograd Nodes"
+            FutureWarning, "the forward contains multiple autograd Nodes"
         ):
             m(a)
 

diff --git a/test/test_autocast.py b/test/test_autocast.py
@@ -255,8 +255,8 @@ def test_generic_autocast(self):
 
     def test_cpu_autocast_deprecated_warning(self):
         with self.assertWarnsRegex(
-            DeprecationWarning,
-            r"torch.cpu.amp.autocast\(args...\) is deprecated. Please use torch.amp.autocast\('cpu', args...\) instead.",
+            FutureWarning,
+            r"`torch.cpu.amp.autocast\(args...\)` is deprecated. Please use `torch.amp.autocast\('cpu', args...\)` instead.",
         ):
             with torch.cpu.amp.autocast():
                 _ = torch.ones(10)

diff --git a/test/test_autograd.py b/test/test_autograd.py
@@ -154,7 +154,7 @@ def hook(*args):
 
     def test_grad_mode_class_decoration(self):
         # Decorating class is deprecated and should not be used
-        with self.assertWarnsRegex(UserWarning, "Decorating classes is deprecated"):
+        with self.assertWarnsRegex(FutureWarning, "Decorating classes is deprecated"):
 
             @torch.no_grad()
             class Foo:
@@ -5937,13 +5937,13 @@ def fn(inputs):
         b = torch.rand(2, 2, requires_grad=True, dtype=torch.float64)
 
         with self.assertWarnsRegex(
-            UserWarning, "get_numerical_jacobian was part of PyTorch's private API"
+            FutureWarning, "`get_numerical_jacobian` was part of PyTorch's private API"
         ):
             jacobian = get_numerical_jacobian(fn, (a, b), target=a, eps=1e-6)
         self.assertEqual(jacobian[0], 2 * torch.eye(4, dtype=torch.double))
 
         with self.assertWarnsRegex(
-            UserWarning, "get_numerical_jacobian was part of PyTorch's private API"
+            FutureWarning, "`get_numerical_jacobian` was part of PyTorch's private API"
         ):
             jacobian = get_numerical_jacobian(fn, (a, b), eps=1e-6)
         self.assertEqual(jacobian[0], 2 * torch.eye(4, dtype=torch.double))
@@ -5963,7 +5963,7 @@ def fn(x, y):
 
         outputs = fn(a, b)
         with self.assertWarnsRegex(
-            UserWarning, "get_analytical_jacobian was part of PyTorch's private API"
+            FutureWarning, "`get_analytical_jacobian` was part of PyTorch's private API"
         ):
             (
                 jacobians,
@@ -5991,7 +5991,7 @@ def backward(ctx, grad_out):
 
         outputs = NonDetFunc.apply(a, 1e-6)
         with self.assertWarnsRegex(
-            UserWarning, "get_analytical_jacobian was part of PyTorch's private API"
+            FutureWarning, "`get_analytical_jacobian` was part of PyTorch's private API"
         ):
             (
                 jacobians,

diff --git a/test/test_cuda.py b/test/test_cuda.py
@@ -1820,10 +1820,10 @@ def backward(ctx, grad):
                     return grad, grad
 
         self.assertRegex(
-            str(w[0].message), r"torch.cuda.amp.custom_fwd\(args...\) is deprecated."
+            str(w[0].message), r"`torch.cuda.amp.custom_fwd\(args...\)` is deprecated."
         )
         self.assertRegex(
-            str(w[1].message), r"torch.cuda.amp.custom_bwd\(args...\) is deprecated."
+            str(w[1].message), r"`torch.cuda.amp.custom_bwd\(args...\)` is deprecated."
         )
 
         mymm = MyMM.apply
@@ -2016,8 +2016,8 @@ def test_autocast_checkpointing(self):
 
     def test_cuda_autocast_deprecated_warning(self):
         with self.assertWarnsRegex(
-            DeprecationWarning,
-            r"torch.cuda.amp.autocast\(args...\) is deprecated. Please use torch.amp.autocast\('cuda', args...\) instead.",
+            FutureWarning,
+            r"`torch.cuda.amp.autocast\(args...\)` is deprecated. Please use `torch.amp.autocast\('cuda', args...\)` instead.",
         ):
             with torch.cuda.amp.autocast():
                 _ = torch.ones(10)

diff --git a/test/test_prims.py b/test/test_prims.py
@@ -338,7 +338,7 @@ def test_mul_complex(self):
         prims.mul(torch.randn(2), 1 + 1j)
 
     def test_check_deprecation_warning(self):
-        with self.assertWarnsRegex(DeprecationWarning, 'will be removed in the future'):
+        with self.assertWarnsRegex(FutureWarning, 'will be removed in the future'):
             torch._prims_common.check(True, lambda: 'message')
 
 

diff --git a/test/test_pytree.py b/test/test_pytree.py
@@ -723,7 +723,7 @@ def __init__(self, x, y):
                 self.y = y
 
         with self.assertWarnsRegex(
-            UserWarning, "torch.utils._pytree._register_pytree_node"
+            FutureWarning, "torch.utils._pytree._register_pytree_node"
         ):
             py_pytree._register_pytree_node(
                 DummyType,

diff --git a/test/test_stateless.py b/test/test_stateless.py
@@ -901,7 +901,7 @@ def test_stateless_functional_call_warns(self):
         m = torch.nn.Linear(1, 1)
         params = dict(m.named_parameters())
         x = torch.randn(3, 1)
-        with self.assertWarnsRegex(UserWarning, "Please use torch.func.functional_call"):
+        with self.assertWarnsRegex(FutureWarning, "Please use `torch.func.functional_call`"):
             stateless.functional_call(m, params, x)
 
 class TestPythonOptimizeMode(TestCase):

diff --git a/test/test_torch.py b/test/test_torch.py
@@ -6198,8 +6198,8 @@ def test_grad_scaler_deprecated_warning(self, device):
         GradScaler = torch.cuda.amp.GradScaler if "cuda" == device.type else torch.cpu.amp.GradScaler
 
         with self.assertWarnsRegex(
-            UserWarning,
-            rf"torch.{device.type}.amp.GradScaler\(args...\) is deprecated.",
+            FutureWarning,
+            rf"`torch.{device.type}.amp.GradScaler\(args...\)` is deprecated.",
         ):
             _ = GradScaler(init_scale=2.0)
 

diff --git a/torch/__init__.py b/torch/__init__.py
@@ -1996,17 +1996,6 @@ def _register_device_module(device_type, module):
 from torch.func import vmap
 
 
-# The function _sparse_coo_tensor_unsafe is removed from PyTorch
-# Python API (v. 1.13), here we temporarily provide its replacement
-# with a deprecation warning.
-# TODO: remove the function for PyTorch v 1.15.
-def _sparse_coo_tensor_unsafe(*args, **kwargs):
-    import warnings
-    warnings.warn('torch._sparse_coo_tensor_unsafe is deprecated, '
-                  'use torch.sparse_coo_tensor(..., check_invariants=False) instead.')
-    kwargs['check_invariants'] = False
-    return torch.sparse_coo_tensor(*args, **kwargs)
-
 # Register MPS specific decomps
 torch.backends.mps._init()
 

diff --git a/torch/_dynamo/eval_frame.py b/torch/_dynamo/eval_frame.py
@@ -798,7 +798,9 @@ def guard_export_print(guards):
         warnings.warn(
             "explain(f, *args, **kwargs) is deprecated, use explain(f)(*args, **kwargs) instead.  "
             "If you don't migrate, we may break your explain call in the future if your user defined kwargs "
-            "conflict with future kwargs added to explain(f)."
+            "conflict with future kwargs added to explain(f).",
+            FutureWarning,
+            stacklevel=2,
         )
         return inner(*extra_args, **extra_kwargs)
     else:
@@ -941,7 +943,7 @@ def check_signature_rewritable(graph):
             tb = "".join(traceback.format_list(stack))
             extra = ""
             if len(user_stacks) > 1:
-                extra = f"(elided {len(user_stacks)-1} more accesses)"
+                extra = f"(elided {len(user_stacks) - 1} more accesses)"
             msg = f"{source.name()}, accessed at:\n{tb}{extra}"
         # TODO: option to print ALL of the stack traces at once
         input_errors.append(msg)
@@ -1476,7 +1478,9 @@ def graph_with_interpreter(*args):
         warnings.warn(
             "export(f, *args, **kwargs) is deprecated, use export(f)(*args, **kwargs) instead.  "
             "If you don't migrate, we may break your export call in the future if your user defined kwargs "
-            "conflict with future kwargs added to export(f)."
+            "conflict with future kwargs added to export(f).",
+            FutureWarning,
+            stacklevel=2,
         )
         return inner(*extra_args, **extra_kwargs)
     else:

diff --git a/torch/_functorch/deprecated.py b/torch/_functorch/deprecated.py
@@ -1,3 +1,12 @@
+"""
+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
+documentation.
+"""
+
 import textwrap
 import warnings
 from typing import Any, Callable, Optional, Tuple, Union
@@ -9,25 +18,16 @@
 from torch._functorch.eager_transforms import argnums_t
 from torch._functorch.vmap import in_dims_t, out_dims_t
 
-"""
-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
-documentation.
-"""
-
 
 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"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"
+        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"
         f"https://pytorch.org/docs/main/func.migrating.html"
     )
     if replace_newlines:
@@ -37,7 +37,7 @@ def get_warning(api, new_api=None, replace_newlines=False):
 
 def warn_deprecated(api, new_api=None):
     warning = get_warning(api, new_api, replace_newlines=True)
-    warnings.warn(warning, stacklevel=2)
+    warnings.warn(warning, FutureWarning, stacklevel=3)
 
 
 def setup_docs(functorch_api, torch_func_api=None, new_api_name=None):

diff --git a/torch/_functorch/pytree_hacks.py b/torch/_functorch/pytree_hacks.py
@@ -16,7 +16,8 @@
 with warnings.catch_warnings():
     warnings.simplefilter("always")
     warnings.warn(
-        "torch._functorch.pytree_hacks is deprecated and will be removed in a future release. "
-        "Please use torch.utils._pytree instead.",
+        "`torch._functorch.pytree_hacks` is deprecated and will be removed in a future release. "
+        "Please `use torch.utils._pytree` instead.",
         DeprecationWarning,
+        stacklevel=2,
     )
diff --git a/torch/_inductor/ir.py b/torch/_inductor/ir.py
@@ -2750,7 +2750,8 @@ def make_indexer(self):
         """A closure containing math to read a given element"""
 
         def indexer(index):
-            assert len(index) == len(self.stride) == len(self.size)
+            assert len(index) == len(self.stride)
+            assert len(index) == len(self.size)
             result = self.offset
             for idx, stride, sz in zip(index, self.stride, self.size):
                 if sz != 1:

diff --git a/torch/_library/abstract_impl.py b/torch/_library/abstract_impl.py
@@ -1,7 +1,7 @@
 import contextlib
 import functools
-import warnings
 from typing import Callable, Optional
+from typing_extensions import deprecated
 
 import torch
 from torch._library.utils import Kernel, RegistrationHandle
@@ -124,10 +124,11 @@ def __init__(self, _fake_mode, _op):
         self._shape_env = _fake_mode.shape_env
         self._op = _op
 
+    @deprecated(
+        "`create_unbacked_symint` is deprecated, please use `new_dynamic_size` instead",
+        category=FutureWarning,
+    )
     def create_unbacked_symint(self, *, min=2, max=None) -> torch.SymInt:
-        warnings.warn(
-            "create_unbacked_symint is deprecated, please use new_dynamic_size instead"
-        )
         return self.new_dynamic_size(min=min, max=max)
 
     def new_dynamic_size(self, *, min=0, max=None) -> torch.SymInt: