#pragma once

// @generated by torchgen/gen.py from Function.h

#include <ATen/Context.h>
#include <ATen/DeviceGuard.h>
#include <ATen/TensorUtils.h>
#include <ATen/TracerMode.h>
#include <ATen/core/Generator.h>
#include <ATen/core/Reduction.h>
#include <ATen/core/Tensor.h>
#include <c10/core/Scalar.h>
#include <c10/core/Storage.h>
#include <c10/core/TensorOptions.h>
#include <c10/util/Deprecated.h>
#include <optional>



#include <ATen/ops/logspace_ops.h>

namespace at {


// aten::logspace(Scalar start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0, at::TensorOptions options={}) {
    return at::_ops::logspace::call(start, end, steps, base, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
}
// aten::logspace(Scalar start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
    return at::_ops::logspace::call(start, end, steps, base, dtype, layout, device, pin_memory);
}

// aten::logspace.Tensor_Tensor(Tensor start, Tensor end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base=10.0, at::TensorOptions options={}) {
    return at::_ops::logspace_Tensor_Tensor::call(start, end, steps, base, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
}
// aten::logspace.Tensor_Tensor(Tensor start, Tensor end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
    return at::_ops::logspace_Tensor_Tensor::call(start, end, steps, base, dtype, layout, device, pin_memory);
}

// aten::logspace.Tensor_Scalar(Tensor start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base=10.0, at::TensorOptions options={}) {
    return at::_ops::logspace_Tensor_Scalar::call(start, end, steps, base, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
}
// aten::logspace.Tensor_Scalar(Tensor start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
    return at::_ops::logspace_Tensor_Scalar::call(start, end, steps, base, dtype, layout, device, pin_memory);
}

// aten::logspace.Scalar_Tensor(Scalar start, Tensor end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base=10.0, at::TensorOptions options={}) {
    return at::_ops::logspace_Scalar_Tensor::call(start, end, steps, base, c10::optTypeMetaToScalarType(options.dtype_opt()), options.layout_opt(), options.device_opt(), options.pinned_memory_opt());
}
// aten::logspace.Scalar_Tensor(Scalar start, Tensor end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
inline at::Tensor logspace(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base, ::std::optional<at::ScalarType> dtype, ::std::optional<at::Layout> layout, ::std::optional<at::Device> device, ::std::optional<bool> pin_memory) {
    return at::_ops::logspace_Scalar_Tensor::call(start, end, steps, base, dtype, layout, device, pin_memory);
}

// aten::logspace.out(Scalar start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_out(at::Tensor & out, const at::Scalar & start, const at::Scalar & end, int64_t steps, double base=10.0) {
    return at::_ops::logspace_out::call(start, end, steps, base, out);
}
// aten::logspace.out(Scalar start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_outf(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out) {
    return at::_ops::logspace_out::call(start, end, steps, base, out);
}

// aten::logspace.Tensor_Tensor_out(Tensor start, Tensor end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_out(at::Tensor & out, const at::Tensor & start, const at::Tensor & end, int64_t steps, double base=10.0) {
    return at::_ops::logspace_Tensor_Tensor_out::call(start, end, steps, base, out);
}
// aten::logspace.Tensor_Tensor_out(Tensor start, Tensor end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_outf(const at::Tensor & start, const at::Tensor & end, int64_t steps, double base, at::Tensor & out) {
    return at::_ops::logspace_Tensor_Tensor_out::call(start, end, steps, base, out);
}

// aten::logspace.Tensor_Scalar_out(Tensor start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_out(at::Tensor & out, const at::Tensor & start, const at::Scalar & end, int64_t steps, double base=10.0) {
    return at::_ops::logspace_Tensor_Scalar_out::call(start, end, steps, base, out);
}
// aten::logspace.Tensor_Scalar_out(Tensor start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_outf(const at::Tensor & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out) {
    return at::_ops::logspace_Tensor_Scalar_out::call(start, end, steps, base, out);
}

// aten::logspace.Scalar_Tensor_out(Scalar start, Tensor end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_out(at::Tensor & out, const at::Scalar & start, const at::Tensor & end, int64_t steps, double base=10.0) {
    return at::_ops::logspace_Scalar_Tensor_out::call(start, end, steps, base, out);
}
// aten::logspace.Scalar_Tensor_out(Scalar start, Tensor end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)
inline at::Tensor & logspace_outf(const at::Scalar & start, const at::Tensor & end, int64_t steps, double base, at::Tensor & out) {
    return at::_ops::logspace_Scalar_Tensor_out::call(start, end, steps, base, out);
}

}