kernels/portable/cpu/op_add.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/kernels/portable/cpu/scalar_utils.h>
#include <executorch/kernels/portable/cpu/util/broadcast_util.h>
#include <executorch/kernels/portable/cpu/util/functional_util.h>
#include <executorch/kernels/portable/cpu/util/kernel_ops_util.h>
#include <executorch/runtime/kernel/kernel_includes.h>
#include <executorch/runtime/platform/assert.h>

namespace torch {
namespace executor {
namespace native {
namespace {

template <
    bool can_cast,
    typename CTYPE_A,
    typename CTYPE_B,
    typename CTYPE_IN,
    typename CTYPE_OUT>
struct AddInner;

template <
    typename CTYPE_A,
    typename CTYPE_B,
    typename CTYPE_IN,
    typename CTYPE_OUT>
struct AddInner<true, CTYPE_A, CTYPE_B, CTYPE_IN, CTYPE_OUT> {
  static void
  run(const Tensor& a, const Tensor& b, CTYPE_IN alpha_val, Tensor& out) {
    apply_binary_elementwise_fn<CTYPE_A, CTYPE_B, CTYPE_OUT>(
        // NOLINTNEXTLINE(facebook-hte-ConstantArgumentPassByValue)
        [alpha_val](const CTYPE_A val_a, const CTYPE_B val_b) {
          CTYPE_IN a_casted = static_cast<CTYPE_IN>(val_a);
          CTYPE_IN b_casted = static_cast<CTYPE_IN>(val_b);
          CTYPE_IN value = a_casted + alpha_val * b_casted;

          return static_cast<CTYPE_OUT>(value);
        },
        a,
        b,
        out);
  }
};

template <typename CTYPE_IN>
struct ReportCanCastBug {
  static void run(const Tensor&, const Tensor&, CTYPE_IN, Tensor&) {
    ET_DCHECK_MSG(false, "BUG: canCast should have been checked above");
  }
};

template <
    typename CTYPE_A,
    typename CTYPE_B,
    typename CTYPE_IN,
    typename CTYPE_OUT>
struct AddInner<false, CTYPE_A, CTYPE_B, CTYPE_IN, CTYPE_OUT>
    : public ReportCanCastBug<CTYPE_IN> {};

} // namespace

Tensor& add_out(
    RuntimeContext& ctx,
    const Tensor& a,
    const Tensor& b,
    const Scalar& alpha,
    Tensor& out) {
  ET_KERNEL_CHECK(
      ctx,
      resize_to_broadcast_target_size(a, b, out) == Error::Ok,
      InvalidArgument,
      out);

  ET_KERNEL_CHECK(
      ctx,
      executorch::runtime::tensor_is_realhbbf16_type(out),
      InvalidArgument,
      out);
  ET_KERNEL_CHECK(
      ctx, tensors_have_same_dim_order(a, b, out), InvalidArgument, out);

  ScalarType a_type = a.scalar_type();
  ScalarType b_type = b.scalar_type();
  ScalarType alpha_type = utils::get_scalar_dtype(alpha);
  ScalarType common_type = promoteTypes(a_type, b_type, /*half_to_float*/ true);
  ScalarType out_type = out.scalar_type();

  ET_KERNEL_CHECK(ctx, canCast(common_type, out_type), InvalidArgument, out);
  ET_KERNEL_CHECK(
      ctx, check_alpha_type(alpha_type, common_type), InvalidArgument, out);

  constexpr auto name = "add.out";

  ET_SWITCH_REALHBBF16_TYPES(a_type, ctx, name, CTYPE_A, [&]() {
    ET_SWITCH_REALHBBF16_TYPES(b_type, ctx, name, CTYPE_B, [&]() {
      using CTYPE_IN = typename torch::executor::
          promote_types<CTYPE_A, CTYPE_B, /*half_to_float*/ true>::type;
      ET_DCHECK(CppTypeToScalarType<CTYPE_IN>::value == common_type);
      CTYPE_IN alpha_val;
      utils::extract_scalar(alpha, &alpha_val);

      ET_SWITCH_REALHBBF16_TYPES(out_type, ctx, name, CTYPE_OUT, [&]() {
        AddInner<
            can_cast<CTYPE_IN, CTYPE_OUT>::value,
            CTYPE_A,
            CTYPE_B,
            CTYPE_IN,
            CTYPE_OUT>::run(a, b, alpha_val, out);
      });
    });
  });

  return out;
}

Tensor& add_scalar_out(
    RuntimeContext& ctx,
    const Tensor& a,
    const Scalar& b,
    const Scalar& alpha,
    Tensor& out) {
  (void)ctx;

  // Resize for dynamic shape
  ET_KERNEL_CHECK_MSG(
      ctx,
      resize_tensor(out, a.sizes()) == Error::Ok,
      InvalidArgument,
      out,
      "Failed to resize output tensor.");

  ET_KERNEL_CHECK(
      ctx,
      executorch::runtime::tensor_is_realhbbf16_type(out),
      InvalidArgument,
      out);
  ET_KERNEL_CHECK(
      ctx, tensors_have_same_dim_order(a, out), InvalidArgument, out);

  ScalarType a_type = a.scalar_type();
  ScalarType b_type = utils::get_scalar_dtype(b);
  ScalarType alpha_type = utils::get_scalar_dtype(alpha);
  ScalarType common_type =
      utils::promote_type_with_scalar(a_type, b, /*half_to_float*/ false);
  ScalarType out_type = out.scalar_type();

  ET_KERNEL_CHECK(ctx, common_type == out_type, InvalidArgument, out);
  ET_KERNEL_CHECK(
      ctx, check_alpha_type(alpha_type, common_type), InvalidArgument, out);

  if (common_type == ScalarType::Half) {
    common_type = ScalarType::Float;
  }

  constexpr auto name = "add.Scalar_out";

  ET_SWITCH_REALHBBF16_TYPES(a_type, ctx, name, CTYPE_A, [&]() {
    ET_SWITCH_SCALAR_OBJ_TYPES(b_type, ctx, name, CTYPE_B, [&]() {
      using CTYPE_IN = typename utils::promote_type_with_scalar_type<
          CTYPE_A,
          CTYPE_B,
          /*half_to_float*/ true>::type;
      ET_DCHECK(CppTypeToScalarType<CTYPE_IN>::value == common_type);

      CTYPE_B b_val;
      utils::extract_scalar(b, &b_val);
      CTYPE_IN b_casted = static_cast<CTYPE_IN>(b_val);

      CTYPE_IN alpha_val;
      utils::extract_scalar(alpha, &alpha_val);

      using CTYPE_OUT = typename std::conditional<
          std::is_same<CTYPE_A, internal::F2>::value,
          internal::F2,
          CTYPE_IN>::type;

      apply_unary_map_fn(
          [b_casted, alpha_val](const CTYPE_A val_a) {
            CTYPE_IN a_casted = static_cast<CTYPE_IN>(val_a);
            CTYPE_IN value = a_casted + alpha_val * b_casted;
            return static_cast<CTYPE_OUT>(value);
          },
          a.const_data_ptr<CTYPE_A>(),
          out.mutable_data_ptr<CTYPE_OUT>(),
          out.numel());
    });
  });

  return out;
}

} // namespace native
} // namespace executor
} // namespace torch