Revert "[AMP][Refactor] Autocast dtype handling to simplify device-specific c… (#165221)"

This reverts commit 4be1e3bf92.

Reverted https://github.com/pytorch/pytorch/pull/165221 on behalf of https://github.com/clee2000 due to I think this broke test_openreg [GH job link](https://github.com/pytorch/pytorch/actions/runs/18698271058/job/53322459496) [HUD commit link](4be1e3bf92) note to self: bad TD ([comment](https://github.com/pytorch/pytorch/pull/165221#issuecomment-3430012693))

test/cpp_extensions/open_registration_extension/torch_openreg/tests/test_autocast.py

@@ -8,8 +8,7 @@ class TestAutocast(TestCase):
     def test_autocast_with_unsupported_type(self):
         with self.assertWarnsRegex(
             UserWarning,
-            "In openreg autocast, but the target dtype is not supported."
-            "openreg Autocast only supports dtypes of torch.bfloat16, torch.float16 currently.",
+            "In openreg autocast, but the target dtype torch.float32 is not supported.",
         ):
             with torch.autocast(device_type="openreg", dtype=torch.float32):
                 _ = torch.ones(10)

test/test_autocast.py

@@ -346,7 +346,7 @@ class TestAutocastMPS(TestCase):
     def test_mps_autocast_error_message(self):
         with self.assertWarnsRegex(
             UserWarning,
-            "MPS Autocast only supports dtypes of torch.bfloat16, torch.float16 currently.",
+            "MPS Autocast only supports dtype of torch.bfloat16 and torch.float16 currently.",
         ):
             with torch.autocast(device_type="mps", dtype=torch.float32):
                 _ = torch.ones(10)

torch/amp/autocast_mode.py

@@ -230,9 +230,9 @@ class autocast:
             raise ValueError(
                 f"Expected `device_type` of type `str`, got: `{type(device_type)}`"
             )
-        self.fast_dtype = (
-            torch.get_autocast_dtype(device_type) if dtype is None else dtype
-        )
+        if dtype is None:
+            dtype = torch.get_autocast_dtype(device_type)
+        self.fast_dtype = dtype
         if torch._jit_internal.is_scripting():
             self._enabled = enabled
             self.device = device_type
@@ -243,9 +243,6 @@ class autocast:
             raise RuntimeError(
                 f"User specified an unsupported autocast device_type '{self.device}'"
             )
-
-        device_supported_dtypes = [torch.bfloat16, torch.float16]
-
         self.custom_backend_name = torch._C._get_privateuse1_backend_name()
         if self.device == self.custom_backend_name:
             necessary_funcs = [
@@ -262,55 +259,110 @@ class autocast:
                 assert hasattr(self.custom_device_mod, func), (
                     message + f"But the func `{func}` is missing. \n"
                 )
-            device_supported_dtypes = self.custom_device_mod.get_amp_supported_dtype()
 
-        self._cache_enabled = (
-            torch.is_autocast_cache_enabled()
-            if cache_enabled is None
-            else cache_enabled
-        )
+        self._cache_enabled = torch.is_autocast_cache_enabled()
+        if (
+            enabled
+            and self.device == "cuda"
+            and torch.cuda.amp.common.amp_definitely_not_available()
+        ):
+            warnings.warn(
+                "User provided device_type of 'cuda', but CUDA is not available. Disabling"
+            )
+            enabled = False
+        if cache_enabled is not None:
+            self._cache_enabled = cache_enabled
 
-        device_name = (
-            self.device
-            if self.device == self.custom_backend_name
-            else self.device.upper()
-        )
-        if enabled:
-            # Special case for CUDA AMP and bfloat16 support
-            if self.device == "cuda":
-                if torch.cuda.amp.common.amp_definitely_not_available():
-                    warnings.warn(
-                        "CUDA is not available or torch_xla is imported. Disabling autocast."
-                    )
-                    enabled = False
-                elif (
-                    self.fast_dtype == torch.bfloat16
-                    and not torch.cuda.is_bf16_supported()
-                ):
-                    raise RuntimeError(
-                        "Current CUDA Device does not support bfloat16. Please switch dtype to float16."
-                    )
-            elif self.fast_dtype not in device_supported_dtypes:
-                error_message = (
-                    f"In {device_name} autocast, but the target dtype is not supported. Disabling autocast.\n"
-                    f"{device_name} Autocast only supports dtypes of "
-                    + ", ".join(map(str, device_supported_dtypes))
-                    + " currently."
+        if self.device == "cpu":
+            supported_dtype = [torch.bfloat16, torch.float16]
+            if self.fast_dtype not in supported_dtype and enabled:
+                error_message = "In CPU autocast, but the target dtype is not supported. Disabling autocast.\n"
+                error_message += "CPU Autocast only supports dtype of "
+                error_message += (
+                    ", ".join(str(dtype) for dtype in supported_dtype) + " currently."
                 )
                 warnings.warn(error_message)
                 enabled = False
-                # Special case for MPS bfloat16 support on macOS < 14
-                if (
-                    self.device == "mps"
-                    and self.fast_dtype == torch.bfloat16
-                    and not torch.backends.mps.is_macos_or_newer(14, 0)
-                ):
+        elif self.device == "mtia":
+            supported_dtype = [torch.bfloat16, torch.float16]
+            if self.fast_dtype not in supported_dtype:
+                error_message = "In MTIA autocast, but the target dtype is not supported. Disabling autocast.\n"
+                error_message += "MTIA Autocast only supports dtypes of torch.bfloat16 and torch.float16 currently."
+                warnings.warn(error_message)
+                enabled = False
+        elif self.device == "maia":
+            supported_dtype = [torch.bfloat16, torch.float16]
+            if self.fast_dtype not in supported_dtype:
+                error_message = "In MAIA autocast, but the target dtype is not supported. Disabling autocast.\n"
+                error_message += "MAIA Autocast only supports dtypes of torch.bfloat16 and torch.float16 currently."
+                warnings.warn(error_message)
+                enabled = False
+        elif self.device == "xpu":
+            supported_dtype = [torch.bfloat16, torch.float16]
+            if self.fast_dtype not in supported_dtype:
+                error_message = "In XPU autocast, but the target dtype is not supported. Disabling autocast.\n"
+                error_message += "XPU Autocast only supports dtypes of torch.bfloat16 and torch.float16 currently."
+                warnings.warn(error_message)
+                enabled = False
+        elif self.device == "ipu":
+            supported_dtypes = [torch.bfloat16, torch.float16]
+            if self.fast_dtype not in supported_dtypes:
+                error_message = "In IPU autocast, but the target dtype is not supported. Disabling autocast.\n"
+                error_message += "IPU Autocast only supports dtypes of torch.bfloat16 and torch.float16 currently."
+                warnings.warn(error_message)
+                enabled = False
+        elif self.device == "hpu":
+            supported_dtype = [torch.bfloat16, torch.float16]
+            if self.fast_dtype not in supported_dtype:
+                error_message = "In HPU autocast, but the target dtype is not supported. Disabling autocast.\n"
+                error_message += "HPU Autocast only supports dtypes of torch.bfloat16 and torch.float16 currently."
+                warnings.warn(error_message)
+                enabled = False
+        elif self.device == self.custom_backend_name:
+            supported_dtype = self.custom_device_mod.get_amp_supported_dtype()
+            if self.fast_dtype not in supported_dtype:
+                error_message = f"In {self.custom_backend_name} autocast, but the target dtype {self.fast_dtype} is not supported. "
+                error_message += f"Disabling autocast.\n {self.custom_backend_name} Autocast only supports dtypes of "
+                error_message += (
+                    ", ".join(str(dtype) for dtype in supported_dtype) + " currently."
+                )
+                warnings.warn(error_message)
+                enabled = False
+        elif self.device == "cuda":
+            if (
+                enabled
+                and self.fast_dtype == torch.bfloat16
+                and not torch.cuda.is_bf16_supported()
+            ):
+                raise RuntimeError(
+                    "Current CUDA Device does not support bfloat16. Please switch dtype to float16."
+                )
+        elif self.device == "mps":
+            supported_dtype = [torch.bfloat16, torch.float16]
+            if self.fast_dtype not in supported_dtype:
+                error_message = (
+                    "In MPS autocast, but the target dtype is not supported. Disabling autocast.\n"
+                    "MPS Autocast only supports dtype of torch.bfloat16 and torch.float16 currently."
+                )
+                warnings.warn(error_message)
+                enabled = False
+            elif self.fast_dtype == torch.bfloat16:
+                if not torch.backends.mps.is_macos_or_newer(14, 0):
                     error_message = (
                         "In MPS autocast, but the target dtype torch.bfloat16 is not supported "
                         "on macOS versions below 14. Disabling autocast."
                     )
                     warnings.warn(error_message)
                     enabled = False
+        elif self.device == "xla":
+            supported_dtype = [torch.float16, torch.bfloat16]
+            if self.fast_dtype not in supported_dtype:
+                error_message = "In XLA autocast, but the target dtype is not supported. Disabling autocast.\n"
+                error_message += (
+                    "XLA Autocast only supports dtype of torch.bfloat16 currently."
+                )
+                warnings.warn(error_message)
+                enabled = False
         self._enabled = enabled
 
     def __enter__(self):