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feat(aten::Int): Adding a new pass to remove single use
0D Tensors Now we remove select more complex aten::Int cases found in models such as BERT, like the following: ``` graph(%0: int): %1: Tensor = prim::Constant[value={8}]() %2: int = prim::Constant[value=1]() %3: Tensor = prim::NumToTensor(%0) %4: Tensor = aten::add(%1, %3, %2) %5: int = aten::Int(%4) %6: int = aten::add(%5, %5) return (%6)"; graph(%0: int): %1: int = prim::Constant[value=8]() %4: int = aten::add(%1, %0) %6: int = aten::add(%4, %4) return (%6)"; ``` Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com>
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#include <stack> | ||
#include <unordered_set> | ||
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#include "torch/csrc/jit/passes/subgraph_rewrite.h" | ||
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#include "core/lowering/passes/passes.h" | ||
#include "core/util/prelude.h" | ||
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namespace torch_tensorrt { | ||
namespace core { | ||
namespace lowering { | ||
namespace passes { | ||
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void RemoveSetAttrs(const torch::jit::Module& mod, std::string method_name) { | ||
auto g = mod.get_method(method_name).graph(); | ||
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std::string set_attr_pattern = R"IR( | ||
graph(%self, %0): | ||
None = prim::SetAttr[name="_has_warned"](%self, %0) | ||
return ())IR"; | ||
std::string no_set_attr_pattern = R"IR( | ||
graph(%self, %0): | ||
return ())IR"; | ||
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// remove contiguous | ||
torch::jit::SubgraphRewriter remove_set_attr; | ||
remove_set_attr.RegisterRewritePattern(set_attr_pattern, no_set_attr_pattern); | ||
remove_set_attr.runOnGraph(g); | ||
LOG_GRAPH("Post remove contiguous: " << *g); | ||
} | ||
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} // namespace passes | ||
} // namespace lowering | ||
} // namespace core | ||
} // namespace torch_tensorrt |
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