Cache param/buffer/constant names in RemovePermutesAroundElementwiseTosaOps (#22164) - #22164
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…osaOps (pytorch#22164) Summary: `RemovePermutesAroundElementwiseTosaOps._is_constant` called `is_param_node()` for every node reached during recursive `visit()` walk. Each `is_param_node` rebuilds immutable dict over full input_specs via uncached graph_signature properties. This made pass O(nodes * inputs). Precompute union of param/buffer/lifted-constant placeholder names once in `__init__` and use O(1) set membership. Semantics unchanged. Differential Revision: D114224782
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…osaOps (pytorch#22164) Summary: `RemovePermutesAroundElementwiseTosaOps._is_constant` called `is_param_node()` for every node reached during recursive `visit()` walk. Each `is_param_node` rebuilds immutable dict over full input_specs via uncached graph_signature properties. This made pass O(nodes * inputs). Precompute union of param/buffer/lifted-constant placeholder names once in `__init__` and use O(1) set membership. Semantics unchanged. Differential Revision: D114224782
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…osaOps (pytorch#22164) Summary: `RemovePermutesAroundElementwiseTosaOps._is_constant` called `is_param_node()` for every node reached during recursive `visit()` walk. Each `is_param_node` rebuilds immutable dict over full input_specs via uncached graph_signature properties. This made pass O(nodes * inputs). Precompute the union of param/buffer/lifted-constant placeholder names once per pass invocation in `call()` and use O(1) set membership. Refreshing it at invocation time tracks the current `ExportedProgram` when a pass instance is reused. Semantics unchanged. Differential Revision: D114224782
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…osaOps (pytorch#22164) Summary: `RemovePermutesAroundElementwiseTosaOps._is_constant` called `is_param_node()` for every node reached during recursive `visit()` walk. Each `is_param_node` rebuilds immutable dict over full input_specs via uncached graph_signature properties. This made pass O(nodes * inputs). Precompute the union of param/buffer/lifted-constant placeholder names once per pass invocation in `call()` and use O(1) set membership. Refreshing it at invocation time tracks the current `ExportedProgram` when a pass instance is reused. Semantics unchanged. Differential Revision: D114224782
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…osaOps (pytorch#22164) Summary: `RemovePermutesAroundElementwiseTosaOps._is_constant` called `is_param_node()` for every node reached during recursive `visit()` walk. Each `is_param_node` rebuilds immutable dict over full input_specs via uncached graph_signature properties. This made pass O(nodes * inputs). Precompute the union of param/buffer/lifted-constant placeholder names once per pass invocation in `call()` and use O(1) set membership. Refreshing it at invocation time tracks the current `ExportedProgram` when a pass instance is reused. Semantics unchanged. Differential Revision: D114224782
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…osaOps (pytorch#22164) Summary: `RemovePermutesAroundElementwiseTosaOps._is_constant` called `is_param_node()` for every node reached during recursive `visit()` walk. Each `is_param_node` rebuilds immutable dict over full input_specs via uncached graph_signature properties. This made pass O(nodes * inputs). Precompute the union of param/buffer/lifted-constant placeholder names once per pass invocation in `call()` and use O(1) set membership. Refreshing it at invocation time tracks the current `ExportedProgram` when a pass instance is reused. Semantics unchanged. On an ensemble network of ~1M parameters, lowering produced identical output while running 10.5 seconds faster (2.7%). Differential Revision: D114224782
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Summary:
RemovePermutesAroundElementwiseTosaOps._is_constantcalledis_param_node()for every node reached during recursivevisit()walk. Eachis_param_noderebuilds immutable dict over full input_specs via uncached graph_signature properties. This made pass O(nodes * inputs). Precompute the union of param/buffer/lifted-constant placeholder names once per pass invocation incall()and use O(1) set membership. Refreshing it at invocation time tracks the currentExportedProgramwhen a pass instance is reused. Semantics unchanged.On an ensemble network of ~1M parameters, lowering produced identical output while running 10.5 seconds faster (2.7%).
Differential Revision: D114224782