Add warning about removed sm50 and sm60 arches (pytorch#158478)

Add warning about removed sm50 and sm60 arches (pytorch#158301)

Related to pytorch#157517

Detect when users are executing torch build with cuda 12.8/12.9 and running on Maxwell or Pascal architectures.
We would like to include reference to the issue: pytorch#157517 as well as ask people to install CUDA 12.6 builds if they are running on sm50 or sm60 architectures.

Test:
```
>>> torch.cuda.get_arch_list()
['sm_70', 'sm_75', 'sm_80', 'sm_86', 'sm_90', 'sm_100', 'sm_120', 'compute_120']
>>> torch.cuda.init()
/home/atalman/.conda/envs/py312/lib/python3.12/site-packages/torch/cuda/__init__.py:263: UserWarning:
    Found <GPU Name> which is of cuda capability 5.0.
    PyTorch no longer supports this GPU because it is too old.
    The minimum cuda capability supported by this library is 7.0.

  warnings.warn(
/home/atalman/.conda/envs/py312/lib/python3.12/site-packages/torch/cuda/__init__.py:268: UserWarning:
                        Support for Maxwell and Pascal architectures is removed for CUDA 12.8+ builds.
                        Please see pytorch#157517
                        Please install CUDA 12.6 builds if you require Maxwell or Pascal support.
```

Pull Request resolved: pytorch#158301
Approved by: https://github.com/nWEIdia, https://github.com/albanD

(cherry picked from commit fb731fe)

Co-authored-by: atalman <[email protected]>

Author: pytorchbot

torch/cuda/__init__.py

@@ -244,21 +244,25 @@ def _extract_arch_version(arch_string: str):
 
 
 def _check_capability():
-    incorrect_binary_warn = """
-    Found GPU%d %s which requires CUDA_VERSION >= %d to
-     work properly, but your PyTorch was compiled
-     with CUDA_VERSION %d. Please install the correct PyTorch binary
-     using instructions from https://pytorch.org
-    """  # noqa: F841
-
-    old_gpu_warn = """
+    incompatible_gpu_warn = """
     Found GPU%d %s which is of cuda capability %d.%d.
-    PyTorch no longer supports this GPU because it is too old.
-    The minimum cuda capability supported by this library is %d.%d.
+    Minimum and Maximum cuda capability supported by this version of PyTorch is
+    (%d.%d) - (%d.%d)
     """
+    matched_cuda_warn = """
+    Please install PyTorch with a following CUDA
+    configurations: {} following instructions at
+    https://pytorch.org/get-started/locally/
+    """
+
+    # Binary CUDA_ARCHES SUPPORTED by PyTorch
+    CUDA_ARCHES_SUPPORTED = {
+        "12.6": {"min": 50, "max": 90},
+        "12.8": {"min": 70, "max": 120},
+        "12.9": {"min": 70, "max": 120},
+    }
 
     if torch.version.cuda is not None:  # on ROCm we don't want this check
-        CUDA_VERSION = torch._C._cuda_getCompiledVersion()  # noqa: F841
         for d in range(device_count()):
             capability = get_device_capability(d)
             major = capability[0]
@@ -267,13 +271,35 @@ def _check_capability():
             current_arch = major * 10 + minor
             min_arch = min(
                 (_extract_arch_version(arch) for arch in torch.cuda.get_arch_list()),
-                default=35,
+                default=50,
             )
-            if current_arch < min_arch:
+            max_arch = max(
+                (_extract_arch_version(arch) for arch in torch.cuda.get_arch_list()),
+                default=50,
+            )
+            if current_arch < min_arch or current_arch > max_arch:
                 warnings.warn(
-                    old_gpu_warn
-                    % (d, name, major, minor, min_arch // 10, min_arch % 10)
+                    incompatible_gpu_warn
+                    % (
+                        d,
+                        name,
+                        major,
+                        minor,
+                        min_arch // 10,
+                        min_arch % 10,
+                        max_arch // 10,
+                        max_arch % 10,
+                    )
                 )
+                matched_arches = ""
+                for arch, arch_info in CUDA_ARCHES_SUPPORTED.items():
+                    if (
+                        current_arch >= arch_info["min"]
+                        and current_arch <= arch_info["max"]
+                    ):
+                        matched_arches += f" {arch}"
+                if matched_arches != "":
+                    warnings.warn(matched_cuda_warn.format(matched_arches))
 
 
 def _check_cubins():