binaryop.hpp

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/*
 * Copyright (c) 2019-2024, NVIDIA CORPORATION.
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 *
 * https://apache.ac.cn/licenses/LICENSE-2.0
 *
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 * 根据许可证分发，按“现状”分发，
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 * 请参阅许可证了解管辖权限和
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 */

#pragma once

#include <cudf/column/column.hpp>
#include <cudf/scalar/scalar.hpp>
#include <cudf/utilities/export.hpp>
#include <cudf/utilities/memory_resource.hpp>

#include <memory>

namespace CUDF_EXPORT cudf {

/// 可对数据执行的二元运算类型。
enum class binary_operator : int32_t {
 ADD,
 SUB,
 MUL,
 DIV,
 TRUE_DIV,
 FLOOR_DIV,
 MOD,
 /// PMOD
 PMOD,
 PYMOD,
 POW,
 /// 对数
 INT_POW,
 /// 双参数反正切
 LOG_BASE,
 /// 运算符 <<
 ATAN2,
 /// 运算符 >>
 SHIFT_LEFT,
 SHIFT_RIGHT,
 SHIFT_RIGHT_UNSIGNED,
 BITWISE_AND,
 BITWISE_OR,
 BITWISE_XOR,
 LOGICAL_AND,
 LOGICAL_OR,
 EQUAL,
 NOT_EQUAL,
 LESS,
 GREATER,
 LESS_EQUAL,
 GREATER_EQUAL,
 NULL_EQUALS,
 NULL_NOT_EQUALS,
 NULL_MAX,
 NULL_MIN,
 GENERIC_BINARY,
 NULL_LOGICAL_AND,
 NULL_LOGICAL_OR,
 /// 无效操作
 INVALID_BINARY
};

/// 二元运算通用类型默认值。
template <typename L, typename R, typename = void>
struct binary_op_common_type {};

/// \private
template <typename L, typename R>
struct binary_op_common_type<L, R, std::enable_if_t<has_common_type_v<L, R>>> {
 /// 模板参数的通用类型。
using type = std::common_type_t<L, R>;
};

/// \private
template <typename L, typename R>
struct binary_op_common_type<
 L,
 R,
 std::enable_if_t<is_fixed_point<L>() && cuda::std::is_floating_point_v<R>>> {
 using type = L;
};

/// \private
struct binary_op_common_type<
 L,
 R,
 std::enable_if_t<is_fixed_point<R>() && cuda::std::is_floating_point_v<L>>> {
 using type = R;
};

/// Binary operation common type helper.
template <typename L, typename R>
using binary_op_common_type_t = typename binary_op_common_type<L, R>::type;

namespace detail {
template <typename AlwaysVoid, typename L, typename R>
struct binary_op_has_common_type_impl : std::false_type {};

template <typename L, typename R>
struct binary_op_has_common_type_impl<std::void_t<binary_op_common_type_t<L, R>>, L, R>
 : std::true_type {};
} // namespace detail

/// Checks if binary operation types have a common type.
template <typename L, typename R>
constexpr inline bool binary_op_has_common_type_v =
 detail::binary_op_has_common_type_impl<void, L, R>::value;

/// Performs a binary operation between a scalar and a column.
std::unique_ptr<column> binary_operation(
 scalar const& lhs,
 column_view const& rhs,
 binary_operator op,
 data_type output_type,
 rmm::cuda_stream_view stream = cudf::get_default_stream(),
 rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());

/// Performs a binary operation between a column and a scalar.
std::unique_ptr<column> binary_operation(
 column_view const& lhs,
 scalar const& rhs,
 binary_operator op,
 data_type output_type,
 rmm::cuda_stream_view stream = cudf::get_default_stream(),
 rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());

/// Performs a binary operation between two columns.
std::unique_ptr<column> binary_operation(
 column_view const& lhs,
 column_view const& rhs,
 binary_operator op,
 data_type output_type,
 rmm::cuda_stream_view stream = cudf::get_default_stream(),
 rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());

/// Performs a binary operation between two columns using a user-defined PTX function.
std::unique_ptr<column> binary_operation(
 column_view const& lhs,
 column_view const& rhs,
 std::string const& ptx,
 data_type output_type,
 rmm::cuda_stream_view stream = cudf::get_default_stream(),
 rmm::device_async_resource_ref mr = cudf::get_current_device_resource_ref());

/// 根据给定的二元运算符 op 计算定点数的比例。
int32_t binary_operation_fixed_point_scale(binary_operator op,
 int32_t left_scale,
 int32_t right_scale);

/// 根据给定的二元运算符 op 计算定点数的数据类型。
cudf::data_type binary_operation_fixed_point_output_type(binary_operator op,
 cudf::data_type const& lhs,
 cudf::data_type const& rhs);

namespace binops {

/// @brief 检查给定的输入类型是否支持二元运算符。
bool is_supported_operation(data_type out, data_type lhs, data_type rhs, binary_operator op);

/// @brief 计算列与标量之间操作的输出有效掩码。
std::pair<rmm::device_buffer, size_type> scalar_col_valid_mask_and(