aten.minimum.default

backends/vulkan/partitioner/supported_ops.py

@@ -45,6 +45,7 @@ def __contains__(self, op):
 BINARY_OPS = [
     exir_ops.edge.aten.add.Tensor,
     exir_ops.edge.aten.sub.Tensor,
+    exir_ops.edge.aten.minimum.default,
     exir_ops.edge.aten.mul.Tensor,
     exir_ops.edge.aten.div.Tensor,
     exir_ops.edge.aten.div.Tensor_mode,

backends/vulkan/runtime/graph/ops/glsl/binary_op.yaml

@@ -28,3 +28,5 @@ binary_op:
       OPERATOR: pow(X, Y)
     - NAME: binary_floor_divide
       OPERATOR: floor(X / Y)
+    - NAME: binary_minimum
+      OPERATOR: min(X, Y)

backends/vulkan/runtime/graph/ops/impl/BinaryOp.cpp

@@ -118,6 +118,7 @@ DEFINE_BINARY_OP_WITH_ALPHA_FN(floor_divide);
 DEFINE_BINARY_OP_FN(mul);
 DEFINE_BINARY_OP_FN(div);
 DEFINE_BINARY_OP_FN(pow);
+DEFINE_BINARY_OP_FN(minimum);
 
 REGISTER_OPERATORS {
   VK_REGISTER_OP(aten.add.Tensor, add);
@@ -126,6 +127,7 @@ REGISTER_OPERATORS {
   VK_REGISTER_OP(aten.div.Tensor, div);
   VK_REGISTER_OP(aten.div.Tensor_mode, floor_divide);
   VK_REGISTER_OP(aten.pow.Tensor_Tensor, pow);
+  VK_REGISTER_OP(aten.minimum.default, minimum);
 }
 
 } // namespace vkcompute

backends/vulkan/test/op_tests/cases.py

@@ -1022,3 +1022,19 @@ def get_constant_pad_nd_inputs():
         ]
     )
     return test_suite
+
+
+@register_test_suite("aten.minimum.default")
+def get_minimum_inputs():
+    test_suite = VkTestSuite(
+        [
+            ((M1, M2), (M2)),
+            ((M1, M2), (M1, M2)),
+            ((M1, M2, M), (M2, M)),
+            ((M1, M1, S1, S2), (M1, M1, S1, S2)),
+            ((S1, S1, S2, S), (S1, S2, S)),
+            ((M1, S1, S2), (L, M1, S1, S2)),
+            ((S1, S2), (L, M1, S1, S2)),
+        ]
+    )
+    return test_suite

backends/vulkan/test/test_vulkan_delegate.py

@@ -1074,6 +1074,25 @@ def forward(self, x):
             memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
         )
 
+    def test_vulkan_backend_minimum(self):
+        class MinimumModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+
+            def forward(self, x, y):
+                return torch.minimum(x, y)
+
+        sample_inputs = (
+            torch.rand(size=(3, 5, 6, 4), dtype=torch.float32),
+            torch.rand(size=(6, 4), dtype=torch.float32),
+        )
+
+        self.lower_module_and_test_output(
+            MinimumModule(),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
     def test_vulkan_backend_reshape(self):
         class ReshapeModule(torch.nn.Module):
             def __init__(self):