/usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/jit
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jit_log.h50340644editdlrm
jit_opt_limit.h14190644editdlrm
resource_guard.h4760644editdlrm
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/jit/jit_opt_limit.h (1419B)
#pragma once #include #include #include // `TorchScript` offers a simple optimization limit checker // that can be configured through environment variable `PYTORCH_JIT_OPT_LIMIT`. // The purpose is to limit how many optimization you can make per pass. // This is useful for debugging any passes. // Opt limit checker is enabled on a per file basis (hence per pass). For // example, in `constant_propagation.cpp`, `PYTORCH_JIT_OPT_LIMIT` should be set // to `constant_propagation=` or, simply, to // `constant_propagation=` where is the number of // optimizations you want to make for the pass. (i.e. // `PYTORCH_JIT_OPT_LIMIT="constant_propagation="`). // Multiple files can be configured by separating each file name with a colon // `:` as in the following example, // `PYTORCH_JIT_OPT_LIMIT="constant_propagation=:dead_code_elimination="` // You can call opt limiter by calling JIT_OPT_ALLOWED. It will return true if // we haven't reached the optimization limit yet. Otherwise, it will return // false. Typical usage: // if (!JIT_OPT_ALLOWED) { // GRAPH_DUMP(...); //supplied from jit_log // return; // } namespace torch { namespace jit { TORCH_API bool opt_limit(const char* pass_name); #define JIT_OPT_ALLOWED opt_limit(__FILE__) } // namespace jit } // namespace torch