#pragma once
#include <torch/csrc/WindowsTorchApiMacro.h>
#include <torch/csrc/jit/function_schema.h>
#include <torch/csrc/jit/named_value.h>
#include <torch/csrc/jit/type.h>

namespace torch {
namespace jit {
namespace script {

// try to match a list if inputs and keyword 'attributes' to this schema,
// if it works return the flat list of positional inputs to the call
// if it returns nullopt, then failure_messages contains a good error report
// set convert_tensor_to_num to true if ImplicitTensorToNums should be inserted
// to match the schema

struct MatchedSchema {
  std::vector<Value*> inputs;
  std::vector<TypePtr> return_types;
};

TORCH_API c10::optional<MatchedSchema> tryMatchSchema(
    const FunctionSchema& schema,
    const SourceRange& loc,
    Graph& graph,
    c10::optional<NamedValue> self,
    at::ArrayRef<NamedValue> inputs,
    at::ArrayRef<NamedValue> attributes,
    std::ostream& failure_messages,
    bool allow_conversions);

TORCH_API Value* emitBuiltinCall(
    const SourceRange& loc,
    Graph& graph,
    Symbol name,
    const c10::optional<NamedValue>& self,
    at::ArrayRef<NamedValue> inputs,
    at::ArrayRef<NamedValue> attributes,
    // if true, emitBuiltinCall will throw an exception if this builtin does not
    // exist, otherwise it will return nullptr if the builtin is not found.
    bool required);

TORCH_API c10::optional<size_t> findInputWithName(
    const std::string& name,
    at::ArrayRef<NamedValue> kwargs);

// applies implict conversion from value trying to turn it into type
// concrete_type it succeeds if the return_value->isSubclassOf(concrete_type)
TORCH_API Value* tryConvertToType(
    const SourceRange& loc,
    Graph& graph,
    const TypePtr& concrete_type,
    Value* value,
    bool allow_conversions);

} // namespace script
} // namespace jit
} // namespace torch
