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#pragma once
#include <torch/csrc/WindowsTorchApiMacro.h>
#include <torch/csrc/jit/ir/ir.h>
/*
* This file handles compilation and execution of a CudaFusionGroup;
*
* A CudaFusionGroup node comes with `attr::Subgraph` containing the computation
* graph. We compile the graph to generate CUDA function and cache them in a
* registry. We cache & reuse kernels across nodes sharing identical graph.
*
* After compilation, we assign the key to cached kernel as an integer attribute
* on the node `attr::cache_id`.
*/
namespace torch {
namespace jit {
namespace fuser {
namespace cuda {
// Get fusion_node ready for execution.
// find or compile `CudaKernel` for graph stored in `attr::Subgraph`
// this function assigns `attr::cache_id` to `fusion_node`
TORCH_CUDA_API void compileCudaFusionGroup(Node* fusion_node);
// Execute fusion_node.
// Current protocol is that the function allocates output tensor append them to
// `stack` after execution.
// TODO: support shape inferencing. Right now we only handles static shape
TORCH_CUDA_API void runCudaFusionGroup(const Node* fusion_node, Stack& stack);
TORCH_CUDA_API void CudaFuseGraph(std::shared_ptr<Graph>& graph);
} // namespace cuda
} // namespace fuser
} // namespace jit
} // namespace torch
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