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| 1 | +# Copyright 2025 Arm Limited and/or its affiliates. |
| 2 | +# |
| 3 | +# This source code is licensed under the BSD-style license found in the |
| 4 | +# LICENSE file in the root directory of this source tree. |
| 5 | + |
| 6 | +# pyre-unsafe |
| 7 | + |
| 8 | + |
| 9 | +import logging |
| 10 | + |
| 11 | +import torch |
| 12 | +from executorch.backends.arm._passes.arm_pass_utils import create_node |
| 13 | +from executorch.exir.dialects._ops import ops as exir_ops |
| 14 | +from executorch.exir.pass_base import EdgeOpOverload, ExportPass, PassResult |
| 15 | +from torch._subclasses.fake_tensor import FakeTensor |
| 16 | + |
| 17 | + |
| 18 | +logger = logging.getLogger(__name__) |
| 19 | + |
| 20 | + |
| 21 | +class InsertInt32CastsAfterInt64PlaceholdersPass(ExportPass): |
| 22 | + """ |
| 23 | + Insert an int64->int32 cast after each int64 placeholder. |
| 24 | +
|
| 25 | + Note: Overflow checks are not applied in this pass. It is the user's responsibility to ensure that values fit within |
| 26 | + the int32 range. |
| 27 | + """ |
| 28 | + |
| 29 | + # Ops that require i64 inputs → positions of args to upcast. |
| 30 | + # Key: op overload; Value: zero-based indices of positional args that must be i64. |
| 31 | + I64_INPUT_ARG_POSITIONS = { |
| 32 | + torch.ops.aten.one_hot.default: (0,), |
| 33 | + } |
| 34 | + |
| 35 | + def _insert_callsite_i32_to_i64_casts(self, graph_module: torch.fx.GraphModule): |
| 36 | + """ |
| 37 | + If an operator requires int64 inputs but dtype propagation (via call_operator) |
| 38 | + produced int32, insert a local int32→int64 cast at the call site to satisfy |
| 39 | + PyTorch's operator input validation. |
| 40 | + """ |
| 41 | + modified = False |
| 42 | + graph = graph_module.graph |
| 43 | + for node in graph.nodes: |
| 44 | + if node.op != "call_function": |
| 45 | + continue |
| 46 | + if node.target not in self.I64_INPUT_ARG_POSITIONS: |
| 47 | + continue |
| 48 | + |
| 49 | + with graph.inserting_before(node): |
| 50 | + arg_positions = self.I64_INPUT_ARG_POSITIONS.get(node.target) |
| 51 | + args_list = list(node.args) |
| 52 | + for pos in arg_positions: # type: ignore[union-attr] |
| 53 | + input_arg = args_list[pos] |
| 54 | + to_copy_op = self._get_decomposition(graph) |
| 55 | + cast_node = graph_module.graph.create_node( |
| 56 | + "call_function", |
| 57 | + to_copy_op, |
| 58 | + (input_arg,), |
| 59 | + {"dtype": torch.int64}, |
| 60 | + ) |
| 61 | + cast_node.meta["val"] = node.meta["val"].to(torch.int64) |
| 62 | + args_list[pos] = cast_node |
| 63 | + node.args = tuple(args_list) |
| 64 | + modified = True |
| 65 | + return modified |
| 66 | + |
| 67 | + def _graph_uses_edge_ops(self, graph: torch.fx.Graph) -> bool: |
| 68 | + for n in graph.nodes: |
| 69 | + if n.op == "call_function": |
| 70 | + if isinstance(n.target, EdgeOpOverload): |
| 71 | + return True |
| 72 | + return False |
| 73 | + |
| 74 | + def _get_decomposition(self, graph: torch.fx.Graph): |
| 75 | + if self._graph_uses_edge_ops(graph): |
| 76 | + return exir_ops.edge.dim_order_ops._to_dim_order_copy.default |
| 77 | + else: |
| 78 | + return torch.ops.dim_order_ops._to_dim_order_copy.default |
| 79 | + |
| 80 | + def _is_tensor_of_dtype(self, node_val, dtype: torch.dtype) -> bool: |
| 81 | + return isinstance(node_val, FakeTensor) and node_val.dtype == dtype |
| 82 | + |
| 83 | + def _insert_placeholder_i64_to_i32_casts(self, graph_module: torch.fx.GraphModule): |
| 84 | + modified = False |
| 85 | + graph = graph_module.graph |
| 86 | + for node in graph.nodes: |
| 87 | + if node.op != "placeholder": |
| 88 | + continue |
| 89 | + node_val = node.meta["val"] |
| 90 | + if not self._is_tensor_of_dtype(node_val, torch.int64): |
| 91 | + continue |
| 92 | + |
| 93 | + to_copy_op = self._get_decomposition(graph) |
| 94 | + with graph.inserting_after(node): |
| 95 | + cast_after = create_node( |
| 96 | + graph, |
| 97 | + to_copy_op, |
| 98 | + args=(node,), |
| 99 | + kwargs={ |
| 100 | + "dtype": torch.int32, |
| 101 | + }, |
| 102 | + ) |
| 103 | + users = [user for user in node.users if user != cast_after] |
| 104 | + for user in users: |
| 105 | + user.replace_input_with(node, cast_after) |
| 106 | + logger.warning( |
| 107 | + f"Inserting a casting node {cast_after.name} after {node.name} to cast int64 placeholder" |
| 108 | + f" to int32 for {node.name} defined in {node.meta.get('stack_trace','[no stack trace found]')}" |
| 109 | + ) |
| 110 | + modified = True |
| 111 | + return modified |
| 112 | + |
| 113 | + def call(self, graph_module: torch.fx.GraphModule): |
| 114 | + modified = False |
| 115 | + modified |= self._insert_placeholder_i64_to_i32_casts(graph_module) |
| 116 | + modified |= self._insert_callsite_i32_to_i64_casts(graph_module) |
| 117 | + |
| 118 | + if modified: |
| 119 | + graph_module.graph.eliminate_dead_code() |
| 120 | + graph_module.recompile() |
| 121 | + graph_module = super().call(graph_module).graph_module |
| 122 | + return PassResult(graph_module, modified) |
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