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#pragma once
#include <torch/csrc/jit/api/module.h>
#include <torch/csrc/jit/passes/quantization/quantization_type.h>
namespace std {
template <>
struct hash<torch::jit::Module> {
inline size_t operator()(const torch::jit::Module& arg) const {
return std::hash<c10::intrusive_ptr<c10::ivalue::Object>>()(arg._ivalue());
}
};
} // namespace std
namespace torch {
namespace jit {
using QConfig = std::tuple<Module, Module>;
using QConfigDict = std::unordered_map<std::string, c10::optional<QConfig>>;
/** \brief Insert observer module and observer function call for
* the Tensors that needs to be observed.
*
* For each Tensor that needs to be observed in the method, insert observer
* module to the input module and add forward calls of observer to the specified
* method.
*
* \param module the input module
* \param method_name the method we want to insert observers for
* \param qconfig_dict the qconfig dictionary that specifies how
* each module is going to be quantized
* \param inplace whether we want to do inplace modification to the input module
* or clone the module
* \param is_dynamic whether the dynamic quantization script is being used.
*/
TORCH_API Module InsertObservers(
Module& module,
const std::string& method_name,
const QConfigDict& qconfig_dict,
bool inplace,
QuantType quant_type = QuantType::STATIC);
} // namespace jit
} // namespace torch
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