[ExecuTorch][WebGPU] Op-test for minimum

backends/webgpu/test/op_tests/cases.py

@@ -34,6 +34,7 @@
     CatModule,
     CONFIGS as _CAT_CONFIGS,
 )
+from executorch.backends.webgpu.test.ops.test_minimum import MinimumModule
 from executorch.backends.webgpu.test.ops.test_mul import (
     CONFIGS as _MUL_CONFIGS,
     MulModule,
@@ -184,6 +185,18 @@ def _fn_config_suite(module_cls, configs) -> WebGPUTestSuite:
     )
 
 
+@register_op_test("minimum")
+def _minimum_suite() -> WebGPUTestSuite:
+    # Same-shape numeric coverage (flat binary kernel; broadcast stays smoke).
+    return WebGPUTestSuite(
+        module_factory=lambda: MinimumModule(),
+        cases=[
+            Case(name="2d", inputs=((M1, M2), (M1, M2))),
+            Case(name="3d", inputs=((S, S1, S2), (S, S1, S2))),
+        ],
+    )
+
+
 @register_op_test("view_copy")
 def _view_copy_suite() -> WebGPUTestSuite:
     return _fn_config_suite(ViewModule, _VIEW_CONFIGS)

backends/webgpu/test/ops/test_minimum.py

@@ -0,0 +1,18 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""`aten.minimum.default` module for the WebGPU op-test framework.
+
+`MinimumModule` is imported by `cases.py`. minimum is a same-shape elementwise
+binary op mirroring the landed `add`/`mul` pattern (flat 2D-dispatch kernel).
+"""
+
+import torch
+
+
+class MinimumModule(torch.nn.Module):
+    def forward(self, a: torch.Tensor, b: torch.Tensor) -> torch.Tensor:
+        return torch.minimum(a, b)