pytorch/torch/csrc/jit/mobile/function.cpp

#include <ATen/core/dynamic_type.h>
#include <torch/csrc/jit/mobile/function.h>
#include <torch/csrc/jit/mobile/interpreter.h>
#include <torch/csrc/jit/mobile/parse_bytecode.h>
#include <torch/csrc/jit/mobile/parse_operators.h>
#include <torch/csrc/jit/mobile/prim_ops_registery.h>
#include <torch/csrc/jit/mobile/type_parser.h>
#include <torch/csrc/jit/runtime/instruction.h>
#include <torch/csrc/jit/runtime/operator.h>

namespace torch {
namespace jit {

char const* toString(OpCode op);
namespace mobile {
Function::Function(c10::QualifiedName name) : name_(std::move(name)) {}

Function::Function(
    c10::QualifiedName name,
    Code code,
    at::optional<c10::FunctionSchema> schema)
    : name_(std::move(name)),
      code_(std::move(code)),
      schema_(std::move(schema)) {}

const c10::QualifiedName& Function::qualname() const {
  return name_;
}

void Function::append_instruction(OpCode op, int X, int N, int64_t dbg_handle) {
  TORCH_CHECK(
      isOpSupportedInMobile(op),
      toString(op),
      " is not supported in mobile module.");
  code_.instructions_.emplace_back(op, X, N);
  code_.debug_handles_.emplace_back(dbg_handle);
}

void Function::append_instruction(OpCode op, int X, int N) {
  TORCH_CHECK(
      isOpSupportedInMobile(op),
      toString(op),
      " is not supported in mobile module.");
  code_.instructions_.emplace_back(op, X, N);
}

bool Function::append_operator(
    const std::string& name,
    const std::string& overload_name,
    const c10::optional<int>& num_specified_args) {
  // Keep the original opname in code_
  code_.op_names_.emplace_back(name, overload_name);
  code_.operator_input_sizes_.emplace_back(num_specified_args.value_or(-1));
  return true;
}

void print_unsupported_ops_and_throw(
    const std::unordered_set<std::string>& unsupported_ops) {}

std::string operator_str(const c10::OperatorName& opname) {
  std::string result = opname.name;
  if (!opname.overload_name.empty()) {
    result += "." + opname.overload_name;
  }
  return result;
}

bool Function::initialize_operators(bool should_check_operators) {
  if (code_.initialized) {
    return true;
  }
  std::unordered_set<std::string> unsupported_op_names;
  code_.operators_.clear();
  bool all_ops_supported = true;
  for (int i = 0; i < code_.op_names_.size(); i++) {
    const auto& opname = code_.op_names_[i];
    int num_args = code_.operator_input_sizes_[i];
    c10::optional<int> num_specified_args =
        num_args < 0 ? c10::nullopt : c10::optional<int>(num_args);
    auto func = makeOperatorFunction(opname, num_specified_args);
    if (!func.has_value()) {
      unsupported_op_names.insert(operator_str(opname));
      all_ops_supported = false;
    }
    code_.operators_.emplace_back(*func);
  }
  if (should_check_operators) {
    TORCH_CHECK(
        unsupported_op_names.empty(),
        "Following ops cannot be found. Please check if the operator library is included in the build. If built with selected ops, check if these ops are in the list. If you are a Meta employee, please see fburl.com/missing_ops for a fix. Or post it in https://discuss.pytorch.org/",
        c10::Join(", ", unsupported_op_names));
  }
  code_.initialized = all_ops_supported;
  return all_ops_supported;
}

void Function::append_constant(const c10::IValue& constant) {
  code_.constants_.push_back(constant);
}

void Function::append_type(const at::TypePtr& type) {
  code_.types_.push_back(type);
}

void Function::append_function(mobile::Function& function) {
  code_.functions_.push_back(&function);
}

void Function::set_register_size(size_t size) {
  code_.register_size_ = size;
}

int64_t Function::get_debug_handle(size_t pc) const {
  TORCH_CHECK(
      pc < code_.debug_handles_.size(),
      "Module debug info index out of boundary.");
  return code_.debug_handles_[pc];
}

torch::jit::Function& Function::setSchema(c10::FunctionSchema schema) {
  schema_ = std::move(schema);
  return *this;
}

bool Function::hasSchema() const {
  return schema_.has_value();
}

const c10::FunctionSchema& Function::getSchema() const {
  return *schema_;
}

void Function::run(Stack& stack) {
  initialize_operators(/* should_check_operators */ true);
  if (hasSchema()) { // if we have a schema then resolve optional args if any
    getSchema().checkAndNormalizeInputs<c10::DynamicType>(
        stack, std::unordered_map<std::string, IValue>{} /*kwargs*/);
  }
  InterpreterState interp_state(code_);
  interp_state.run(stack);
}

at::IValue Function::operator()(Stack& stack) {
  run(stack);
  return stack.front();
}

size_t Function::num_inputs() const {
  return schema_->arguments().size();
}

bool Function::call(Stack&, c10::function_ref<void(const mobile::Code&)> f) {
  f(code_);
  return true;
}

const Code& Function::get_code() const {
  return code_;
}

Code& Function::get_code() {
  return code_;
}

const std::vector<int64_t>& Function::getExceptionDebugHandles() const {
  return getInterpretersExceptionDebugHandles();
}

c10::optional<std::function<void(Stack&)>> makeOperatorFunction(
    c10::OperatorName opname,
    c10::optional<int> num_specified_args) {
  std::function<void(Stack&)> fn;
  const auto full_name = c10::toString(opname);
  const std::vector<c10::Argument>* pArgs = nullptr;
  bool promoted_op = mobile::hasPrimOpsFn(full_name);
  if (promoted_op) {
    fn = mobile::getPrimOpsFn(full_name);
  } else {
    std::shared_ptr<Operator> jit_op = findOperatorFor(opname);
    if (jit_op) {
      fn = [jit_op](Stack& stack) { jit_op->getOperation()(stack); };
      pArgs = &jit_op->schema().arguments();
    } else {
      auto op = c10::Dispatcher::singleton().findSchema(opname);
      if (op.has_value()) {
        fn = [op](Stack& stack) { op->callBoxed(&stack); };
        if (op->hasSchema()) {
          pArgs = &op->schema().arguments();
        } else {
          TORCH_CHECK(false, "arguments are missing for operator ", opname);
        }
      } else {
        return c10::nullopt;
      }
    }
  }

  if (!promoted_op) {
    TORCH_INTERNAL_ASSERT_DEBUG_ONLY(pArgs);
    const auto& args = *pArgs;
    // num_specified_args >= 0 indicates number of arguments are available
    // from model. We can use it to handle backward compatibility.
    if (num_specified_args &&
        num_specified_args.value() < static_cast<int64_t>(args.size())) {
      fn = [fn, num_specified_args, &args](Stack& stack) {
        std::vector<IValue> out_args;
        // The following logic pops and temporarily stores all out arguments
        // from the stack (which can be 0 or more, and always appended to the
        // schema), in order to push the necessary default values. Finally,
        // the out arguments are pushed back into the stack.
        for (size_t i = args.size() - 1; i > 0 && args.at(i).is_out(); i--) {
          out_args.push_back(stack.back());
          stack.pop_back();
        }
        size_t start_index = num_specified_args.value() - out_args.size();
        TORCH_CHECK(
            start_index >= 0,
            "The number of output arguments is: ",
            out_args.size(),
            ", which is more then the number of specified arguments: ",
            num_specified_args.value());
        for (size_t i = start_index; i < (args.size() - out_args.size()); ++i) {
          TORCH_CHECK(
              args[i].default_value().has_value(),
              "Error happened at preparing for default values for the argument. The ",
              i,
              "th argument ",
              args[i].name(),
              " does not have a specified value or default value. ");

          stack.push_back(args[i].default_value());
        }
        stack.insert(stack.end(), out_args.rbegin(), out_args.rend());
        fn(stack);
      };
    }
  }
  return fn;
}

Function& Function::registerFunc(
    const std::string& qualified_name,
    const std::vector<Instruction>& instructions,
    const std::vector<c10::IValue>& constants,
    const std::vector<c10::TypePtr>& types,
    const size_t register_size) {
  static std::unordered_map<c10::QualifiedName, Function>
      upgrader_function_holder;
  c10::QualifiedName name = c10::QualifiedName(qualified_name);
  auto found = upgrader_function_holder.find(name);
  // Register the function if it's not found in the map.
  if (found == upgrader_function_holder.end()) {
    auto name_function_pair =
        upgrader_function_holder.emplace(name, Function(name));
    auto& func = name_function_pair.first->second;
    for (auto const& inst : instructions) {
      func.append_instruction(inst.op, inst.X, inst.N);
    }
    for (auto const& constant : constants) {
      func.append_constant(constant);
    }
    for (auto const& type : types) {
      func.append_type(type);
    }
    func.set_register_size(register_size);
    return func;
  }
  auto& upgrader_function_in_holder = found->second;
  return upgrader_function_in_holder;
}

} // namespace mobile
} // namespace jit
} // namespace torch