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Add MLX op handler for aten.bitwise_xor #18931

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Add MLX op handler for aten.bitwise_xor #18931

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8949a40
Add MLX op handler for aten.bitwise_xor (#18927)
nanookclaw Apr 16, 2026
83aa43f
fix: remove auto-generated files from PR
nanookclaw Apr 17, 2026
7091147
Remove auto-generated mlx_graph_schema.py per review feedback
nanookclaw Apr 17, 2026
6e6a7db
Add mlx_graph_schema.py to .gitignore
nanookclaw Apr 19, 2026
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3 changes: 3 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -79,3 +79,6 @@ xcuserdata/
# Agents
.claude/*.local.*
extension/pybindings/mlx.metallib

# Auto-generated flatbuffers
backends/mlx/serialization/mlx_graph_schema.py
7 changes: 7 additions & 0 deletions backends/mlx/ops.py
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Expand Up @@ -50,6 +50,7 @@
AsStridedNode,
AsTypeNode,
Atan2Node,
BitwiseXorNode,
BroadcastToNode,
CeilNode,
ClipNode,
Expand Down Expand Up @@ -490,6 +491,12 @@ def handler(P: MLXProgramBuilder, n: Node) -> Slot:
"aten.ne",
True,
),
(
[torch.ops.aten.bitwise_xor.Tensor, torch.ops.aten.bitwise_xor.Scalar],
BitwiseXorNode,
"aten.bitwise_xor",
True,
),
]


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9 changes: 8 additions & 1 deletion backends/mlx/serialization/schema.fbs
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Expand Up @@ -981,6 +981,12 @@ table MetalKernelNode {
init_value: float = null;
}

table BitwiseXorNode {
a: Tid;
b: Tid;
out: Tid;
}

// =============================================================================
// Union of all op types
// =============================================================================
Expand Down Expand Up @@ -1113,7 +1119,8 @@ union OpNode {
GatherMmNode,
GatherQmmNode,
ScanNode,
MetalKernelNode
MetalKernelNode,
BitwiseXorNode
// BC: Add new op nodes here (append only)
}

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3 changes: 3 additions & 0 deletions backends/mlx/test/test_ops.py
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Expand Up @@ -4205,6 +4205,9 @@ def create_model(self) -> nn.Module:
# logical
{"op_name": "logical_and", "op_fn": torch.logical_and, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn_a": _bool_input_fn(), "input_fn_b": _bool_input_fn()},
{"op_name": "logical_or", "op_fn": torch.logical_or, "shapes": [(2, 3, 4), (10,), (4, 8)], "dtypes": [torch.bool], "input_fn_a": _bool_input_fn(), "input_fn_b": _bool_input_fn()},
# bitwise
{"op_name": "bitwise_xor_bool", "op_fn": torch.bitwise_xor, "shapes": _SHAPES_3, "dtypes": [torch.bool], "input_fn_a": _bool_input_fn(), "input_fn_b": _bool_input_fn()},
{"op_name": "bitwise_xor_int", "op_fn": torch.bitwise_xor, "shapes": _SHAPES_3, "dtypes": [torch.int32, torch.int64], "input_fn_a": _int_input_fn(0, 256), "input_fn_b": _int_input_fn(0, 256)},
]
# fmt: on

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