kernels/portable/cpu/op_div.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/math_util.h>
#include <executorch/runtime/kernel/kernel_includes.h>
#include <executorch/runtime/platform/assert.h>
#include <cmath>

namespace torch {
namespace executor {
namespace native {

namespace {

ScalarType get_compute_type(ScalarType a_type, ScalarType b_type) {
  if (isFloatingType(a_type) && isFloatingType(b_type)) {
    return promoteTypes(a_type, b_type);
  } else if (isFloatingType(a_type)) {
    return a_type;
  } else if (isFloatingType(b_type)) {
    return b_type;
  }
  return ScalarType::Float;
}

} // namespace

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

  ScalarType a_type = a.scalar_type();
  ScalarType b_type = b.scalar_type();

  ET_KERNEL_CHECK(
      ctx,
      !isComplexType(a_type) && !isQIntType(a_type) && !isBitsType(a_type),
      InvalidArgument,
      out);
  ET_KERNEL_CHECK(
      ctx,
      !isComplexType(b_type) && !isQIntType(b_type) && !isBitsType(b_type),
      InvalidArgument,
      out);

  ET_KERNEL_CHECK(ctx, tensor_is_real_type(out), InvalidArgument, out);

  ScalarType common_type = get_compute_type(a_type, b_type);
  ScalarType out_type = out.scalar_type();

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

  ET_SWITCH_REAL_TYPES_AND(Bool, a_type, ctx, "div.out", CTYPE_A, [&]() {
    ET_SWITCH_REAL_TYPES_AND(Bool, b_type, ctx, "div.out", CTYPE_B, [&]() {
      ET_SWITCH_FLOAT_TYPES(common_type, ctx, "div.out", CTYPE_IN, [&]() {
        ET_SWITCH_FLOAT_TYPES(out_type, ctx, "div.out", CTYPE_OUT, [&]() {
          apply_binary_elementwise_fn<CTYPE_A, CTYPE_B, CTYPE_OUT>(
              [](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 / b_casted;

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

  return out;
}

Tensor& div_out_mode(
    RuntimeContext& ctx,
    const Tensor& a,
    const Tensor& b,
    exec_aten::optional<exec_aten::string_view> mode,
    Tensor& out) {
  ET_KERNEL_CHECK(
      ctx,
      resize_to_broadcast_target_size(a, b, out) == Error::Ok,
      InvalidArgument,
      out);

  ScalarType a_type = a.scalar_type();
  ScalarType b_type = b.scalar_type();
  ScalarType common_type = get_compute_type(a_type, b_type);
  ScalarType out_type = out.scalar_type();

  ET_KERNEL_CHECK(ctx, tensor_is_real_type(out), InvalidArgument, out);

  // Allow casting float -> integral here
  // non-bool -> bool is still disallowed
  ET_KERNEL_CHECK(
      ctx,
      !(common_type != ScalarType::Bool && out_type == ScalarType::Bool),
      InvalidArgument,
      out);

  ET_SWITCH_REAL_TYPES_AND(Bool, a_type, ctx, "div.out_mode", CTYPE_A, [&]() {
    ET_SWITCH_REAL_TYPES_AND(Bool, b_type, ctx, "div.out_mode", CTYPE_B, [&]() {
      ET_SWITCH_FLOAT_TYPES(common_type, ctx, "div.out_mode", CTYPE_IN, [&]() {
        ET_SWITCH_REAL_TYPES(out_type, ctx, "div.out_mode", CTYPE_OUT, [&]() {
          apply_binary_elementwise_fn<CTYPE_A, CTYPE_B, CTYPE_OUT>(
              [mode](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 / b_casted;
                if (mode.has_value() && mode.value() == "trunc") {
                  value = std::trunc(value);
                } else if (mode.has_value() && mode.value() == "floor") {
                  value = std::floor(value);
                }
                return static_cast<CTYPE_OUT>(value);
              },
              a,
              b,
              out);
        });
      });
    });
  });

  return out;
}

Tensor& div_scalar_out(
    RuntimeContext& ctx,
    const Tensor& a,
    const Scalar& b,
    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.");

  ScalarType a_type = a.scalar_type();
  ScalarType b_type = utils::get_scalar_dtype(b);
  ScalarType common_type = isFloatingType(a_type) ? a_type : ScalarType::Float;
  ScalarType out_type = out.scalar_type();

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

  ET_SWITCH_REAL_TYPES_AND(Bool, a_type, ctx, "div.Scalar_out", CTYPE_A, [&]() {
    ET_SWITCH_SCALAR_OBJ_TYPES(b_type, ctx, "div.Scalar_out", CTYPE_B, [&]() {
      ET_SWITCH_FLOAT_TYPES(
          common_type, ctx, "div.Scalar_out", CTYPE_IN, [&]() {
            ET_SWITCH_FLOAT_TYPES(
                out_type, ctx, "div.Scalar_out", CTYPE_OUT, [&]() {
                  CTYPE_B b_val;
                  utils::extract_scalar(b, &b_val);
                  CTYPE_IN b_casted = static_cast<CTYPE_IN>(b_val);

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

  return out;
}

Tensor& div_scalar_mode_out(
    RuntimeContext& ctx,
    const Tensor& a,
    const Scalar& b,
    exec_aten::optional<exec_aten::string_view> mode,
    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.");

  ScalarType a_type = a.scalar_type();
  ScalarType b_type = utils::get_scalar_dtype(b);
  ScalarType common_type = isFloatingType(a_type) ? a_type : ScalarType::Float;
  ScalarType out_type = out.scalar_type();

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

  constexpr auto name = "div.Scalar_mode_out";

  ET_SWITCH_REALB_TYPES(a_type, ctx, name, CTYPE_A, [&]() {
    ET_SWITCH_SCALAR_OBJ_TYPES(b_type, ctx, name, CTYPE_B, [&]() {
      ET_SWITCH_FLOAT_TYPES(common_type, ctx, name, CTYPE_IN, [&]() {
        ET_SWITCH_FLOAT_TYPES(out_type, ctx, name, CTYPE_OUT, [&]() {
          CTYPE_B b_val;
          utils::extract_scalar(b, &b_val);
          CTYPE_IN b_casted = static_cast<CTYPE_IN>(b_val);

          apply_unary_map_fn(
              [b_casted, mode](const CTYPE_A val_a) {
                CTYPE_IN a_casted = static_cast<CTYPE_IN>(val_a);
                CTYPE_IN value = a_casted / b_casted;
                if (mode.has_value() && mode.value() == "trunc") {
                  value = std::trunc(value);
                } else if (mode.has_value() && mode.value() == "floor") {
                  value = utils::floor_divide(a_casted, 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