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trimul-gpumode

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kernels-bot commited on 11 days ago

Commit

e0ebb61

verified ·

1 Parent(s): c740f75

Uploaded using `kernel-builder`.

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Files changed (4) hide show

build/torch-rocm/_ops.py +3 -6
build/torch-rocm/metadata.json +6 -5
build/torch-rocm/metadata.json.sigstore +1 -1
build/torch-rocm/symbols.json +97 -0

build/torch-rocm/_ops.py CHANGED Viewed

@@ -4,11 +4,8 @@ def get_backend() -> str:
     """Detect the backend by inspecting torch."""
     import torch
-    if hasattr(torch.backends, "tpu"):
-        # torch_tpu sets torch.backends.tpu when it is imported (via
-        # torch's device-backend autoload), regardless of whether TPU
-        # hardware is present — analogous to torch.version.cuda being
-        # set on CUDA builds without a GPU.
         return "tpu"
     elif hasattr(torch, "neuron"):
         # Needs to be sorted before specific Torch builds, since Neuron
@@ -28,7 +25,7 @@ def get_backend() -> str:
 def _find_ops_name() -> str:
     kernel_name = "trimul_gpumode"
-    unique_id = "89d4054"
     backend = get_backend()
     return f"_{kernel_name}_{backend}_{unique_id}"

     """Detect the backend by inspecting torch."""
     import torch
+    acc = torch.accelerator.current_accelerator() if hasattr(torch, "accelerator") else None
+    if acc is not None and acc.type == "tpu":
         return "tpu"
     elif hasattr(torch, "neuron"):
         # Needs to be sorted before specific Torch builds, since Neuron
 def _find_ops_name() -> str:
     kernel_name = "trimul_gpumode"
+    unique_id = "fe2bb66"
     backend = get_backend()
     return f"_{kernel_name}_{backend}_{unique_id}"

build/torch-rocm/metadata.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "name": "trimul-gpumode",
-  "id": "_trimul_gpumode_rocm_89d4054",
   "version": 1,
   "kernels-minver": "0.14.0",
   "license": "Apache-2.0",
@@ -13,7 +13,8 @@
     "algorithm": "sha256",
     "files": {
       "__init__.py": "faq/a7qAfoxACJHjm243zTsvPvOJEE/OWikCrh5pYiw=",
-      "_ops.py": "ewjD0P2jKBcGAxV2OtX5hN4xWylhySukyRU9k4T0eDs=",
       "task.py": "npDgsb+CyKHEyTsdQGXeEg+JqTbbSFzp2uWvGxJaeok=",
       "trimul_global.py": "2VteQYYwhlYAJ9N8vJO3gehLq/FM4PBOBDDRgKDe00k=",
       "trimul_mi300.py": "ciJH9BTi8g+6pDyFqJ8AYoxqAsPqJXLOZ0mpwKDiooY=",
@@ -24,12 +25,12 @@
   },
   "provenance": {
     "kernel-builder": {
-      "version": "0.17.0-dev0",
-      "commit": "a7f0afdb29a6a3372b1d47180cc0c182454c5e3b",
       "dirty": false
     },
     "kernel": {
-      "commit": "89d4054f3755039d5474cfed03f06de026ee2ce7",
       "dirty": false
     }
   }

 {
   "name": "trimul-gpumode",
+  "id": "_trimul_gpumode_rocm_fe2bb66",
   "version": 1,
   "kernels-minver": "0.14.0",
   "license": "Apache-2.0",
     "algorithm": "sha256",
     "files": {
       "__init__.py": "faq/a7qAfoxACJHjm243zTsvPvOJEE/OWikCrh5pYiw=",
+      "_ops.py": "2i/nvFFP4ZV7rh1W62IeIAWCl9m5y+n/sLaVRRfIBno=",
+      "symbols.json": "BSrmbC4zrscdGX9twmLe2Qcg08uKaTrnkXFWlCss0ns=",
       "task.py": "npDgsb+CyKHEyTsdQGXeEg+JqTbbSFzp2uWvGxJaeok=",
       "trimul_global.py": "2VteQYYwhlYAJ9N8vJO3gehLq/FM4PBOBDDRgKDe00k=",
       "trimul_mi300.py": "ciJH9BTi8g+6pDyFqJ8AYoxqAsPqJXLOZ0mpwKDiooY=",
   },
   "provenance": {
     "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
       "dirty": false
     },
     "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
       "dirty": false
     }
   }

build/torch-rocm/metadata.json.sigstore CHANGED Viewed

@@ -1 +1 @@

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build/torch-rocm/symbols.json ADDED Viewed

	@@ -0,0 +1,97 @@

+{
+  "schema_version": 1,
+  "module": "_trimul_gpumode_rocm_fe2bb66",
+  "functions": [
+    {
+      "name": "kernel_a100",
+      "qualname": "kernel_a100",
+      "module": "_trimul_gpumode_rocm_fe2bb66.triton_a100",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "data",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": null
+          }
+        ],
+        "return_annotation": null
+      }
+    },
+    {
+      "name": "kernel_h100",
+      "qualname": "kernel_h100",
+      "module": "_trimul_gpumode_rocm_fe2bb66.triton_h100",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "data",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": null
+          }
+        ],
+        "return_annotation": null
+      }
+    },
+    {
+      "name": "kernel_b200",
+      "qualname": "kernel_b200",
+      "module": "_trimul_gpumode_rocm_fe2bb66.triton_b200",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "data",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": null
+          }
+        ],
+        "return_annotation": null
+      }
+    },
+    {
+      "name": "kernel_mi300",
+      "qualname": "kernel_mi300",
+      "module": "_trimul_gpumode_rocm_fe2bb66.trimul_mi300",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "data",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": null
+          }
+        ],
+        "return_annotation": null
+      }
+    },
+    {
+      "name": "kernel_global",
+      "qualname": "kernel_global",
+      "module": "_trimul_gpumode_rocm_fe2bb66.trimul_global",
+      "kind": "function",
+      "doc": "Reference implementation of TriMul using PyTorch.\n\nArgs:\n    data: Tuple of (input: torch.Tensor, mask: torch.Tensor, weights: Dict[str, torch.Tensor], config: Dict)\n        - input: Input tensor of shape [batch_size, seq_len, seq_len, dim]\n        - mask: Mask tensor of shape [batch_size, seq_len, seq_len]\n        - weights: Dictionary containing model weights\n        - config: Dictionary containing model configuration parameters",
+      "signature": {
+        "parameters": [
+          {
+            "name": "data",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "Tuple[torch.Tensor, torch.Tensor, Dict[str, torch.Tensor], Dict[str, Any]]"
+          }
+        ],
+        "return_annotation": "torch.Tensor"
+      }
+    }
+  ],
+  "layers": []
+}