runtime/executor/method_meta.cpp

/*
 * Copyright (c) Meta Platforms, Inc. and affiliates.
 * All rights reserved.
 *
 * This source code is licensed under the BSD-style license found in the
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/runtime/core/error.h>
#include <executorch/runtime/core/exec_aten/exec_aten.h>
#include <executorch/runtime/core/exec_aten/util/scalar_type_util.h>
#include <executorch/runtime/core/result.h>
#include <executorch/runtime/core/span.h>
#include <executorch/runtime/core/tag.h>
#include <executorch/runtime/executor/method_meta.h>
#include <executorch/schema/program_generated.h>

namespace torch {
namespace executor {

namespace {
Result<Tag> get_tag(
    flatbuffers::Vector<flatbuffers::Offset<executorch_flatbuffer::EValue>>::
        return_type serialization_value,
    size_t index) {
  switch (serialization_value->val_type()) {
    case executorch_flatbuffer::KernelTypes::Null: {
      return Tag::None;
    } break;
    case executorch_flatbuffer::KernelTypes::Int: {
      return Tag::Int;
    } break;
    case executorch_flatbuffer::KernelTypes::Double: {
      return Tag::Double;
    } break;
    case executorch_flatbuffer::KernelTypes::Bool: {
      return Tag::Bool;
    } break;
    case executorch_flatbuffer::KernelTypes::String: {
      return Tag::String;
    } break;
    case executorch_flatbuffer::KernelTypes::Tensor: {
      return Tag::Tensor;
    } break;
    default:
      ET_LOG(
          Error,
          "Invalid tag: %zu input idx: %zu",
          (size_t)serialization_value->val_type(),
          index);
      return Error::Internal;
  }
}

size_t calculate_nbytes(
    Span<const int32_t> sizes,
    exec_aten::ScalarType scalar_type) {
  ssize_t n = 1;
  for (ssize_t i = 0; i < sizes.size(); i++) {
    n *= sizes[i];
  }
  return n * torch::executor::elementSize(scalar_type);
}

} // namespace

TensorInfo::TensorInfo(
    Span<const int32_t> sizes,
    Span<const uint8_t> dim_order,
    exec_aten::ScalarType scalar_type)
    : sizes_(sizes),
      dim_order_(dim_order),
      scalar_type_(scalar_type),
      nbytes_(calculate_nbytes(sizes_, scalar_type_)) {}

Span<const int32_t> TensorInfo::sizes() const {
  return sizes_;
}

Span<const uint8_t> TensorInfo::dim_order() const {
  return dim_order_;
}

exec_aten::ScalarType TensorInfo::scalar_type() const {
  return scalar_type_;
}

size_t TensorInfo::nbytes() const {
  return nbytes_;
}

MethodMeta::MethodMeta(const executorch_flatbuffer::ExecutionPlan* s_plan)
    : s_plan_(s_plan) {}

const char* MethodMeta::name() const {
  return s_plan_->name()->c_str();
}

size_t MethodMeta::num_inputs() const {
  return s_plan_->inputs()->size();
}

Result<Tag> MethodMeta::input_tag(size_t index) const {
  auto num_inputs = this->num_inputs();
  ET_CHECK_OR_RETURN_ERROR(
      index >= 0 && index < num_inputs,
      InvalidArgument,
      "index %zu out of range. num_inputs: %zu",
      index,
      num_inputs);
  auto input_index = s_plan_->inputs()->Get(index);
  auto serialization_value = s_plan_->values()->Get(input_index);
  return get_tag(serialization_value, index);
}

Result<TensorInfo> MethodMeta::input_tensor_meta(size_t index) const {
  auto tag = this->input_tag(index);
  if (!tag.ok()) {
    return tag.error();
  }
  ET_CHECK_OR_RETURN_ERROR(
      tag.get() == Tag::Tensor,
      InvalidArgument,
      "Tag: %zu input: %zu is not Tensor",
      (size_t)tag.get(),
      index);
  auto input_index = s_plan_->inputs()->Get(index);
  auto tensor_value = s_plan_->values()->Get(input_index)->val_as_Tensor();
  return TensorInfo(
      Span<const int32_t>(
          tensor_value->sizes()->data(), tensor_value->sizes()->size()),
      Span<const uint8_t>(
          tensor_value->dim_order()->data(), tensor_value->dim_order()->size()),
      static_cast<exec_aten::ScalarType>(tensor_value->scalar_type()));
}

size_t MethodMeta::num_outputs() const {
  return s_plan_->outputs()->size();
}

Result<Tag> MethodMeta::output_tag(size_t index) const {
  auto num_outputs = this->num_outputs();
  ET_CHECK_OR_RETURN_ERROR(
      index >= 0 && index < num_outputs,
      InvalidArgument,
      "index %zu out of range. num_outputs: %zu",
      index,
      num_outputs);
  auto input_index = s_plan_->outputs()->Get(index);
  auto serialization_value = s_plan_->values()->Get(input_index);
  return get_tag(serialization_value, index);
}

Result<TensorInfo> MethodMeta::output_tensor_meta(size_t index) const {
  auto tag = this->output_tag(index);
  if (!tag.ok()) {
    return tag.error();
  }
  ET_CHECK_OR_RETURN_ERROR(
      tag.get() == Tag::Tensor,
      InvalidArgument,
      "Tag: %zu output: %zu is not Tensor",
      (size_t)tag.get(),
      index);
  auto input_index = s_plan_->outputs()->Get(index);
  auto tensor_value = s_plan_->values()->Get(input_index)->val_as_Tensor();
  return TensorInfo(
      Span<const int32_t>(
          tensor_value->sizes()->data(), tensor_value->sizes()->size()),
      Span<const uint8_t>(
          tensor_value->dim_order()->data(), tensor_value->dim_order()->size()),
      static_cast<exec_aten::ScalarType>(tensor_value->scalar_type()));
}

size_t MethodMeta::num_memory_planned_buffers() const {
  // Index zero is reserved internally, and we hide it from users. The actual
  // number of buffers is one fewer than the actual size of this list in the
  // program.
  return s_plan_->non_const_buffer_sizes()->size() - 1;
}

Result<int64_t> MethodMeta::memory_planned_buffer_size(size_t index) const {
  auto num_buffers = this->num_memory_planned_buffers();
  ET_CHECK_OR_RETURN_ERROR(
      index >= 0 && index < num_buffers,
      InvalidArgument,
      "index %zu out of range. num_buffers: %zu",
      index,
      num_buffers);
  // Index zero is reserved internally, and we hide it from users. Adjust the
  // provided index to point to one of the actual buffers.
  return s_plan_->non_const_buffer_sizes()->Get(index + 1);
}

} // namespace executor
} // namespace torch