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routines.cc
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routines.cc
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#include "chainerx/python/routines.h"
#include <algorithm>
#include <cstdint>
#include <memory>
#include <string>
#include <tuple>
#include <utility>
#include <vector>
#include <absl/types/optional.h>
#include "chainerx/array.h"
#include "chainerx/axes.h"
#include "chainerx/constant.h"
#include "chainerx/context.h"
#include "chainerx/device.h"
#include "chainerx/dims.h"
#include "chainerx/dtype.h"
#include "chainerx/error.h"
#include "chainerx/macro.h"
#include "chainerx/routines/activation.h"
#include "chainerx/routines/arithmetic.h"
#include "chainerx/routines/binary.h"
#include "chainerx/routines/connection.h"
#include "chainerx/routines/creation.h"
#include "chainerx/routines/evaluation.h"
#include "chainerx/routines/explog.h"
#include "chainerx/routines/hyperbolic.h"
#include "chainerx/routines/indexing.h"
#include "chainerx/routines/linalg.h"
#include "chainerx/routines/logic.h"
#include "chainerx/routines/loss.h"
#include "chainerx/routines/manipulation.h"
#include "chainerx/routines/misc.h"
#include "chainerx/routines/normalization.h"
#include "chainerx/routines/pooling.h"
#include "chainerx/routines/reduction.h"
#include "chainerx/routines/rounding.h"
#include "chainerx/routines/sorting.h"
#include "chainerx/routines/statistics.h"
#include "chainerx/routines/n_step_rnn.h"
#include "chainerx/routines/trigonometric.h"
#include "chainerx/scalar.h"
#include "chainerx/python/array.h"
#include "chainerx/python/array_index.h"
#include "chainerx/python/axes.h"
#include "chainerx/python/common.h"
#include "chainerx/python/device.h"
#include "chainerx/python/dtype.h"
#include "chainerx/python/kwarg.h"
#include "chainerx/python/shape.h"
#include "chainerx/python/stack_vector.h"
#include "chainerx/python/strides.h"
namespace chainerx {
namespace python {
namespace python_internal {
namespace py = pybind11;
using py::literals::operator""_a;
namespace {
using internal::MoveArrayBodies;
using internal::MoveArrayBody;
ArrayBodyPtr MakeArrayFromBuffer(py::buffer buffer, py::handle dtype, int64_t count, int64_t offset, py::handle device) {
const py::buffer_info& info = buffer.request();
int64_t n_bytes = info.size * info.itemsize;
if (offset < 0 || offset > n_bytes) {
throw ChainerxError{"offset must be non-negative and no greater than buffer length (", n_bytes, ")"};
}
if (!internal::IsContiguous(
Shape{info.shape.begin(), info.shape.end()}, Strides{info.strides.begin(), info.strides.end()}, info.itemsize)) {
throw ChainerxError{"ndarray is not C-contiguous"};
}
n_bytes -= offset;
if (count < 0) {
if (n_bytes % info.itemsize != 0) {
throw ChainerxError{"buffer size must be a multiple of element size"};
}
count = n_bytes / info.itemsize;
} else if (n_bytes < count * info.itemsize) {
throw ChainerxError{"buffer is smaller than requested size"};
}
Shape shape{count};
std::shared_ptr<void> data{info.ptr, [](void*) {}};
return MoveArrayBody(chainerx::FromData(shape, GetDtype(dtype), data, absl::nullopt, offset, GetDevice(device)));
}
std::vector<Array> ArrayBodiesToArrays(std::vector<ArrayBodyPtr> array_bodies) {
std::vector<Array> arrays{};
arrays.reserve(array_bodies.size());
for (ArrayBodyPtr& array_body : array_bodies) {
arrays.emplace_back(std::move(array_body));
}
return arrays;
}
CastingMode ParseCastingMode(const std::string& casting) {
CastingMode mode{};
if (casting == "no") {
mode = CastingMode::kNo;
} else if (casting == "equiv") {
throw NotImplementedError{"'equiv' casting is not yet implemented."};
} else if (casting == "safe") {
throw NotImplementedError{"'safe' casting is not yet implemented."};
} else if (casting == "same_kind") {
throw NotImplementedError{"'same_kind' casting is not yet implemented."};
} else if (casting == "unsafe") {
throw NotImplementedError{"'unsafe' casting is not yet implemented."};
} else {
throw py::value_error{"Casting must be one of 'no', 'equiv', 'safe', 'same_kind', or 'unsafe'."};
}
return mode;
}
void InitChainerxCreation(pybind11::module& m) {
// creation routines
// TODO(niboshi): Accept CuPy ndarray in `array` and `asarray`. In principle it's CuPy's responsibility to provide some standard
// interface to allow this, but users may want to convert cupy.ndarray to ChainerX before CuPy's support will be implemented. In such
// case, ChainerX should provide the support for convenience.
// TODO(niboshi): Add convenient function to convert to CuPy ndarray. Currently chainerx.ndarray exposes internal pointer
// (ndarray.data_ptr, etc.) to support this, but users may want more convenient method. In principle ChainerX should support some
// standard way (not depending on CuPy), but we might tentatively provide one which concretely depends on CuPy.
m.def("array",
[](py::handle object, py::handle dtype, bool copy, py::handle device) { return MakeArray(object, dtype, copy, device); },
"object"_a,
"dtype"_a = nullptr,
"copy"_a = true,
"device"_a = nullptr);
// TODO(niboshi): Rename `object` to `a` as per numpy.
m.def("asarray",
[](py::handle object, py::handle dtype, py::handle device) { return MakeArray(object, dtype, false, device); },
"object"_a,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("ascontiguousarray",
[](const ArrayBodyPtr& a, py::handle dtype) {
Array arr{a};
return MoveArrayBody(AsContiguousArray(arr, dtype.is_none() ? arr.dtype() : GetDtype(dtype)));
},
"a"_a,
"dtype"_a = nullptr);
m.def("empty",
[](py::handle shape, py::handle dtype, py::handle device) {
return MoveArrayBody(Empty(ToShape(shape), dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("full",
[](py::handle shape, Scalar fill_value, py::handle dtype, py::handle device) {
return MoveArrayBody(Full(ToShape(shape), fill_value, GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"fill_value"_a,
"dtype"_a,
"device"_a = nullptr);
m.def("full",
[](py::int_ dim, Scalar fill_value, py::handle dtype, py::handle device) {
return MoveArrayBody(Full(Shape{dim}, fill_value, GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"fill_value"_a,
"dtype"_a,
"device"_a = nullptr);
m.def("full",
[](py::handle shape, Scalar fill_value, py::handle device) {
return MoveArrayBody(Full(ToShape(shape), fill_value, GetDevice(device)));
},
"shape"_a,
"fill_value"_a,
"device"_a = nullptr);
m.def("full",
[](py::int_ dim, Scalar fill_value, py::handle device) { return MoveArrayBody(Full(Shape{dim}, fill_value, GetDevice(device))); },
"shape"_a,
"fill_value"_a,
"device"_a = nullptr);
m.def("zeros",
[](py::handle shape, py::handle dtype, py::kwargs kwargs) {
py::handle device;
std::tie(device) = GetKwargs(kwargs, "device");
return MoveArrayBody(Zeros(ToShape(shape), dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"dtype"_a = nullptr);
m.def("zeros",
[](py::int_ dim, py::handle dtype, py::kwargs kwargs) {
py::handle device;
std::tie(device) = GetKwargs(kwargs, "device");
return MoveArrayBody(Zeros(Shape{dim}, dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"dtype"_a = nullptr);
m.def("ones",
[](py::handle shape, py::handle dtype, py::handle device) {
return MoveArrayBody(Ones(ToShape(shape), dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("ones",
[](py::int_ dim, py::handle dtype, py::handle device) {
return MoveArrayBody(Ones(Shape{dim}, dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("arange",
[](Scalar start_or_stop,
const absl::optional<Scalar>& maybe_stop,
const absl::optional<Scalar>& maybe_step,
py::handle dtype,
py::handle device) {
DtypeKind start_or_stop_dtype_kind = start_or_stop.kind();
Scalar start{0, start_or_stop_dtype_kind};
Scalar stop{start_or_stop};
Scalar step = maybe_step.has_value() ? maybe_step.value() : Scalar{1, start_or_stop_dtype_kind};
if (maybe_stop.has_value()) {
start = start_or_stop;
stop = maybe_stop.value();
}
return dtype.is_none() ? MoveArrayBody(Arange(start, stop, step, GetDevice(device)))
: MoveArrayBody(Arange(start, stop, step, GetDtype(dtype), GetDevice(device)));
},
"start"_a,
"stop"_a = nullptr,
"step"_a = nullptr,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("empty_like",
[](const ArrayBodyPtr& a, py::handle device) { return MoveArrayBody(EmptyLike(Array{a}, GetDevice(device))); },
"a"_a,
"device"_a = nullptr);
m.def("full_like",
[](const ArrayBodyPtr& a, Scalar value, py::handle device) {
return MoveArrayBody(FullLike(Array{a}, value, GetDevice(device)));
},
"a"_a,
"fill_value"_a,
"device"_a = nullptr);
m.def("zeros_like",
[](const ArrayBodyPtr& a, py::handle device) { return MoveArrayBody(ZerosLike(Array{a}, GetDevice(device))); },
"a"_a,
"device"_a = nullptr);
m.def("ones_like",
[](const ArrayBodyPtr& a, py::handle device) { return MoveArrayBody(OnesLike(Array{a}, GetDevice(device))); },
"a"_a,
"device"_a = nullptr);
m.def("copy", [](const ArrayBodyPtr& a) { return MoveArrayBody(Copy(Array{a})); }, "a"_a);
m.def("frombuffer", &MakeArrayFromBuffer, "buffer"_a, "dtype"_a = "float32", "count"_a = -1, "offset"_a = 0, "device"_a = nullptr);
m.def("identity",
[](int64_t n, py::handle dtype, py::handle device) {
return MoveArrayBody(Identity(n, dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"n"_a,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("eye",
[](int64_t n, absl::optional<int64_t> m, int64_t k, py::handle dtype, py::handle device) {
if (!m.has_value()) {
m = n;
}
return MoveArrayBody(Eye(n, m.value(), k, GetDtype(dtype), GetDevice(device)));
},
"N"_a,
"M"_a = nullptr,
"k"_a = 0,
"dtype"_a = "float64",
"device"_a = nullptr);
m.def("diag", [](const ArrayBodyPtr& v, int64_t k) { return MoveArrayBody(Diag(Array{v}, k)); }, "v"_a, "k"_a = 0);
m.def("diagflat", [](const ArrayBodyPtr& v, int64_t k) { return MoveArrayBody(Diagflat(Array{v}, k)); }, "v"_a, "k"_a = 0);
m.def("linspace",
[](Scalar start, Scalar stop, int64_t num, bool endpoint, py::handle dtype, py::handle device) {
return MoveArrayBody(Linspace(
start,
stop,
num,
endpoint,
dtype.is_none() ? absl::optional<Dtype>{absl::nullopt} : absl::optional<Dtype>{GetDtype(dtype)},
GetDevice(device)));
},
"start"_a,
"stop"_a,
"num"_a = 50,
"endpoint"_a = true,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("tri",
[](int64_t n, absl::optional<int64_t> m, int64_t k, py::handle dtype, py::handle device) {
return MoveArrayBody(Tri(n, m, k, GetDtype(dtype), GetDevice(device)));
},
"N"_a,
"M"_a = nullptr,
"k"_a = 0,
"dtype"_a = "float32",
"device"_a = nullptr);
m.def("tril", [](const ArrayBodyPtr& m, int64_t k) { return MoveArrayBody(Tril(Array{m}, k)); }, "m"_a, "k"_a = 0);
m.def("triu", [](const ArrayBodyPtr& m, int64_t k) { return MoveArrayBody(Triu(Array{m}, k)); }, "m"_a, "k"_a = 0);
m.def("meshgrid", [](py::args xi, py::kwargs kwargs) {
std::vector<Array> xs;
MeshgridIndexingMode mode{MeshgridIndexingMode::kCartesian};
xs.reserve(xi.size());
std::transform(xi.begin(), xi.end(), std::back_inserter(xs), [](const auto& item) { return Array{py::cast<ArrayBodyPtr>(item)}; });
if (kwargs.size()) {
if (kwargs.size() != 1 || !kwargs.contains("indexing")) {
throw ChainerxError{"Only 'indexing' is a valid keyword argument"};
}
py::str index = kwargs["indexing"];
std::string indexing = index;
if (indexing == "xy") {
mode = MeshgridIndexingMode::kCartesian;
} else if (indexing == "ij") {
mode = MeshgridIndexingMode::kMatrix;
} else {
throw ChainerxError{"Indexing can only be 'xy' or 'ij'."};
}
}
return MoveArrayBodies(Meshgrid(xs, mode));
});
}
void InitChainerxEvaluation(pybind11::module& m) {
// evaluation routines
m.def("accuracy",
[](const ArrayBodyPtr& y, const ArrayBodyPtr& t, const absl::optional<int64_t>& ignore_label) {
return MoveArrayBody(Accuracy(Array{y}, Array{t}, ignore_label));
},
"y"_a,
"t"_a,
"ignore_label"_a = nullptr);
}
void InitChainerxIndexing(pybind11::module& m) {
// indexing routines
m.def("take",
[](const ArrayBodyPtr& a, py::handle indices, const absl::optional<int8_t>& axis, const absl::optional<std::string>& mode) {
if (!axis.has_value()) {
throw NotImplementedError{"axis=None is not yet supported for chainerx.take."};
}
IndexBoundsMode tmode{};
if (!mode.has_value()) {
tmode = IndexBoundsMode::kDefault;
} else {
const std::string& smode = mode.value();
if (smode == "raise") {
tmode = IndexBoundsMode::kRaise;
} else if (smode == "wrap") {
tmode = IndexBoundsMode::kWrap;
} else if (smode == "clip") {
tmode = IndexBoundsMode::kClip;
} else {
throw py::value_error{"mode must be 'raise', 'wrap', or 'clip'"};
}
}
if (py::isinstance<ArrayBody>(indices)) {
return MoveArrayBody(Take(Array{a}, Array{py::cast<ArrayBodyPtr>(indices)}, axis.value(), tmode));
}
if (py::isinstance<py::sequence>(indices)) {
absl::optional<Dtype> dtype = Dtype::kInt64;
return MoveArrayBody(Take(Array{a}, Array{MakeArray(indices, dtype, false, a->device())}, axis.value(), tmode));
}
if (py::isinstance<py::array>(indices)) {
return MoveArrayBody(
Take(Array{a}, Array{MakeArrayFromNumpyArray(py::cast<py::array>(indices), a->device())}, axis.value(), tmode));
}
throw py::type_error{"only integers, slices (`:`), sequence, numpy.ndarray and chainerx.newaxis (`None`) are valid indices"};
},
"a"_a,
"indices"_a,
"axis"_a,
"mode"_a = nullptr);
m.def("where",
[](const ArrayBodyPtr& condition, const ArrayBodyPtr& x, const ArrayBodyPtr& y) {
return MoveArrayBody(Where(Array{condition}, Array{x}, Array{y}));
},
"condition"_a,
"x"_a,
"y"_a);
m.def("where",
[](const ArrayBodyPtr& condition, const ArrayBodyPtr& x, Scalar y) {
return MoveArrayBody(Where(Array{condition}, Array{x}, y));
},
"condition"_a,
"x"_a,
"y"_a);
m.def("where",
[](const ArrayBodyPtr& condition, Scalar x, const ArrayBodyPtr& y) {
return MoveArrayBody(Where(Array{condition}, x, Array{y}));
},
"condition"_a,
"x"_a,
"y"_a);
m.def("where",
[](const ArrayBodyPtr& condition, Scalar x, Scalar y) { return MoveArrayBody(Where(Array{condition}, x, y)); },
"condition"_a,
"x"_a,
"y"_a);
m.def("nonzero", [](const ArrayBodyPtr& a) { return ToTuple(Nonzero(Array{a})); }, "a"_a);
}
void InitChainerxLinalg(pybind11::module& m) {
// linalg routines
m.def("dot", [](const ArrayBodyPtr& a, const ArrayBodyPtr& b) { return MoveArrayBody(Dot(Array{a}, Array{b})); }, "a"_a, "b"_a);
pybind11::module mlinalg = m.def_submodule("linalg");
#if CHAINERX_ENABLE_LAPACK
mlinalg.def("_is_lapack_available", []() -> bool { return true; });
#else
mlinalg.def("_is_lapack_available", []() -> bool { return false; });
#endif
mlinalg.def(
"solve", [](const ArrayBodyPtr& a, const ArrayBodyPtr& b) { return MoveArrayBody(Solve(Array{a}, Array{b})); }, "a"_a, "b"_a);
mlinalg.def("inv", [](const ArrayBodyPtr& a) { return MoveArrayBody(Inverse(Array{a})); }, "a"_a);
mlinalg.def(
"svd",
[](const ArrayBodyPtr& a, bool full_matrices, bool compute_uv) -> py::object {
std::tuple<Array, Array, Array> usvt = Svd(Array{a}, full_matrices, compute_uv);
Array& u = std::get<0>(usvt);
Array& s = std::get<1>(usvt);
Array& vt = std::get<2>(usvt);
if (!compute_uv) {
return py::cast(MoveArrayBody(std::move(s)));
}
return py::make_tuple(MoveArrayBody(std::move(u)), MoveArrayBody(std::move(s)), MoveArrayBody(std::move(vt)));
},
"a"_a,
"full_matrices"_a = true,
"compute_uv"_a = true);
mlinalg.def(
"pinv",
[](const ArrayBodyPtr& a, float rcond) { return MoveArrayBody(PseudoInverse(Array{a}, rcond)); },
"a"_a,
"rcond"_a = 1e-15);
mlinalg.def(
"qr",
[](const ArrayBodyPtr& a, const std::string& mode) -> py::object {
Array a_array{a};
QrMode qrmode{};
if (mode == "reduced") {
qrmode = QrMode::kReduced;
} else if (mode == "complete") {
qrmode = QrMode::kComplete;
} else if (mode == "r") {
qrmode = QrMode::kR;
} else if (mode == "raw") {
qrmode = QrMode::kRaw;
} else {
throw py::value_error{"mode must be 'reduced', 'complete', 'r', or 'raw'"};
}
std::tuple<Array, Array> qr = Qr(a_array, qrmode);
Array& q = std::get<0>(qr);
Array& r = std::get<1>(qr);
if (mode == "r") {
return py::cast(MoveArrayBody(std::move(r)));
}
return py::make_tuple(MoveArrayBody(std::move(q)), MoveArrayBody(std::move(r)));
},
"a"_a,
"mode"_a = "reduced");
mlinalg.def("cholesky", [](const ArrayBodyPtr& a) { return MoveArrayBody(Cholesky(Array{a})); }, "a"_a);
mlinalg.def(
"eigh",
[](const ArrayBodyPtr& a, const std::string& UPLO) {
if (UPLO.length() != 1) {
throw py::value_error{"UPLO argument must be 'L' or 'U'."};
}
std::tuple<Array, Array> wv = Eigh(Array{a}, UPLO.c_str()[0]);
Array& w = std::get<0>(wv);
Array& v = std::get<1>(wv);
return std::make_tuple(MoveArrayBody(std::move(w)), MoveArrayBody(std::move(v)));
},
"a"_a,
"UPLO"_a = "L");
mlinalg.def(
"eigvalsh",
[](const ArrayBodyPtr& a, const std::string& UPLO) {
if (UPLO.length() != 1) {
throw py::value_error{"UPLO argument must be 'L' or 'U'."};
}
return MoveArrayBody(Eigvalsh(Array{a}, UPLO.c_str()[0]));
},
"a"_a,
"UPLO"_a = "L");
}
void InitChainerxLogic(pybind11::module& m) {
// logic routines
m.def("equal",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Equal(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("not_equal",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(NotEqual(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("greater",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Greater(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("greater_equal",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(GreaterEqual(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("less", [](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Less(Array{x1}, Array{x2})); }, "x1"_a, "x2"_a);
m.def("less_equal",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(LessEqual(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("logical_and",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(LogicalAnd(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("logical_or",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(LogicalOr(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("logical_not", [](const ArrayBodyPtr& x) { return MoveArrayBody(LogicalNot(Array{x})); }, "x"_a);
m.def("logical_xor",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(LogicalXor(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("all",
[](const ArrayBodyPtr& a, int8_t axis, bool keepdims) { return MoveArrayBody(All(Array{a}, Axes{axis}, keepdims)); },
"a"_a,
"axis"_a,
"keepdims"_a = false);
m.def("all",
[](const ArrayBodyPtr& a, const absl::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(All(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
m.def("any",
[](const ArrayBodyPtr& a, int8_t axis, bool keepdims) { return MoveArrayBody(Any(Array{a}, Axes{axis}, keepdims)); },
"a"_a,
"axis"_a,
"keepdims"_a = false);
m.def("any",
[](const ArrayBodyPtr& a, const absl::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(Any(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
m.def("isnan", [](const ArrayBodyPtr& x) { return MoveArrayBody(IsNan(Array{x})); }, "x"_a);
m.def("isinf", [](const ArrayBodyPtr& x) { return MoveArrayBody(IsInf(Array{x})); }, "x"_a);
m.def("isfinite", [](const ArrayBodyPtr& x) { return MoveArrayBody(IsFinite(Array{x})); }, "x"_a);
}
template <class T1, class T2>
std::vector<ArrayBodyPtr> SwitchBySplitArgs(
T1& split_sections, T2& split_indices, const ArrayBodyPtr& ary, py::handle indices_or_sections, int8_t axis) {
// TODO(niboshi): Perhaps we would want more general approach to handle multi-type arguments like indices_or_sections to
// provide more helpful error message for users.
// Converts an python float to sections (int64_t).
// Raises ValueError if the value has non-zero fraction.
auto pyfloat_to_sections_or_value_error = [](py::handle num) {
CHAINERX_ASSERT(py::isinstance<py::float_>(num));
double num_fp = py::cast<double>(num);
auto num_int = static_cast<int64_t>(num_fp);
if (static_cast<double>(num_int) != num_fp) {
throw py::value_error{"Sections must be an integer."};
}
return num_int;
};
// sections: int
if (py::isinstance<py::int_>(indices_or_sections)) {
int64_t sections = py::cast<int64_t>(indices_or_sections);
return split_sections(ary, sections, axis);
}
// sections: float
if (py::isinstance<py::float_>(indices_or_sections)) {
int64_t sections = pyfloat_to_sections_or_value_error(indices_or_sections);
return split_sections(ary, sections, axis);
}
// numpy.ndarray
if (py::isinstance<py::array>(indices_or_sections)) {
py::array np_ios = py::cast<py::array>(indices_or_sections);
if (np_ios.ndim() >= 2) {
throw py::value_error{std::string{"Too many dimensions of indices: "} + std::to_string(np_ios.ndim())};
}
// sections: scalar
if (np_ios.ndim() == 0) {
int64_t sections{};
py::object scalar_np = np_ios.attr("tolist")();
if (py::isinstance<py::int_>(scalar_np)) {
sections = py::cast<int64_t>(scalar_np);
} else if (py::isinstance<py::float_>(scalar_np)) {
sections = pyfloat_to_sections_or_value_error(scalar_np);
} else {
throw py::type_error{"Sections must be an integer."};
}
return split_sections(ary, sections, axis);
}
// indices: (0,)-shape
if (np_ios.size() == 0) {
return split_indices(ary, {}, axis);
}
if (np_ios.dtype().kind() != 'i') {
throw py::type_error{std::string{"Indices must be integers."}};
}
// indices: non-scalar
std::vector<int64_t> indices{};
py::list indices_pylist = np_ios.attr("tolist")();
for (py::handle item : indices_pylist) {
indices.emplace_back(py::cast<int64_t>(item));
}
return split_indices(ary, indices, axis);
}
// indices: sequence
if (py::isinstance<py::sequence>(indices_or_sections)) {
std::vector<int64_t> indices{};
try {
indices = py::cast<std::vector<int64_t>>(indices_or_sections);
} catch (const py::cast_error& e) {
throw py::type_error{std::string{"Indices not understood: "} + py::cast<std::string>(py::repr(indices_or_sections))};
}
return split_indices(ary, indices, axis);
}
throw py::type_error{std::string{"indices_or_sections not understood: "} + py::cast<std::string>(py::repr(indices_or_sections))};
}
std::vector<ArrayBodyPtr> SplitByIndicesOrSections(const ArrayBodyPtr& ary, py::handle indices_or_sections, int8_t axis) {
auto split_sections = [](const ArrayBodyPtr& ary, int64_t sections, int8_t axis) {
return MoveArrayBodies(Split(Array{ary}, sections, axis));
};
auto split_indices = [](const ArrayBodyPtr& ary, const std::vector<int64_t>& indices, int8_t axis) {
return MoveArrayBodies(Split(Array{ary}, indices, axis));
};
return SwitchBySplitArgs(split_sections, split_indices, ary, indices_or_sections, axis);
}
std::vector<ArrayBodyPtr> DSplitByIndicesOrSections(const ArrayBodyPtr& ary, py::handle indices_or_sections) {
auto split_sections = [](const ArrayBodyPtr& ary, int64_t sections, int8_t /*axis*/) {
return MoveArrayBodies(DSplit(Array{ary}, sections));
};
auto split_indices = [](const ArrayBodyPtr& ary, const std::vector<int64_t>& indices, int8_t /*axis*/) {
return MoveArrayBodies(DSplit(Array{ary}, indices));
};
return SwitchBySplitArgs(split_sections, split_indices, ary, indices_or_sections, 2);
}
std::vector<ArrayBodyPtr> VSplitByIndicesOrSections(const ArrayBodyPtr& ary, py::handle indices_or_sections) {
auto split_sections = [](const ArrayBodyPtr& ary, int64_t sections, int8_t /*axis*/) {
return MoveArrayBodies(VSplit(Array{ary}, sections));
};
auto split_indices = [](const ArrayBodyPtr& ary, const std::vector<int64_t>& indices, int8_t /*axis*/) {
return MoveArrayBodies(VSplit(Array{ary}, indices));
};
return SwitchBySplitArgs(split_sections, split_indices, ary, indices_or_sections, 0);
}
std::vector<ArrayBodyPtr> HSplitByIndicesOrSections(const ArrayBodyPtr& ary, py::handle indices_or_sections) {
auto split_sections = [](const ArrayBodyPtr& ary, int64_t sections, int8_t /*axis*/) {
return MoveArrayBodies(HSplit(Array{ary}, sections));
};
auto split_indices = [](const ArrayBodyPtr& ary, const std::vector<int64_t>& indices, int8_t /*axis*/) {
return MoveArrayBodies(HSplit(Array{ary}, indices));
};
return SwitchBySplitArgs(split_sections, split_indices, ary, indices_or_sections, 1);
}
void InitChainerxManipulation(pybind11::module& m) {
// manipulation routines
m.def("transpose",
[](const ArrayBodyPtr& a, const absl::optional<std::vector<int8_t>>& axes) {
return MoveArrayBody(Transpose(Array{a}, ToAxes(axes)));
},
"a"_a,
"axes"_a = nullptr);
m.def("transpose",
[](const ArrayBodyPtr& a, int8_t axes) { return MoveArrayBody(Transpose(Array{a}, {axes})); },
"a"_a,
"axes"_a = nullptr);
m.def("flip",
[](const ArrayBodyPtr& m, const absl::optional<std::vector<int8_t>>& axes) {
return MoveArrayBody(Flip(Array{m}, ToAxes(axes)));
},
"m"_a,
"axes"_a = nullptr);
m.def("flip", [](const ArrayBodyPtr& m, int8_t axes) { return MoveArrayBody(Flip(Array{m}, {axes})); }, "m"_a, "axes"_a = nullptr);
m.def("fliplr", [](const ArrayBodyPtr& m) { return MoveArrayBody(Fliplr(Array{m})); }, "m"_a);
m.def("flipud", [](const ArrayBodyPtr& m) { return MoveArrayBody(Flipud(Array{m})); }, "m"_a);
m.def("ravel", [](const ArrayBodyPtr& a) { return MoveArrayBody(Ravel(Array{a})); }, "a"_a);
m.def("rollaxis",
[](const ArrayBodyPtr& a, int8_t axis, int8_t start) { return MoveArrayBody(RollAxis(Array{a}, axis, start)); },
"a"_a,
"axis"_a,
"start"_a = 0);
m.def("reshape",
[](const ArrayBodyPtr& a, py::handle newshape) { return MoveArrayBody(Reshape(Array{a}, ToShape(newshape))); },
"a"_a,
"newshape"_a);
m.def("reshape",
[](const ArrayBodyPtr& a, const std::vector<int64_t>& newshape) {
return MoveArrayBody(Reshape(Array{a}, {newshape.begin(), newshape.end()}));
},
"a"_a,
"newshape"_a);
m.def("reshape",
[](const ArrayBodyPtr& a, py::args args) {
if (args.size() == 0) {
throw ChainerxError{"Reshape is missing shape argument."};
}
return MoveArrayBody(Reshape(Array{a}, ToShape(args)));
},
"a"_a);
m.def("squeeze",
[](const ArrayBodyPtr& a, const absl::optional<std::vector<int8_t>>& axis) {
return MoveArrayBody(Squeeze(Array{a}, ToAxes(axis)));
},
"a"_a,
"axis"_a = nullptr);
m.def("squeeze", [](const ArrayBodyPtr& a, int8_t axis) { return MoveArrayBody(Squeeze(Array{a}, Axes{axis})); }, "a"_a, "axis"_a);
m.def("expand_dims", [](const ArrayBodyPtr& a, int8_t axis) { return MoveArrayBody(ExpandDims(Array{a}, axis)); }, "a"_a, "axis"_a);
m.def("swapaxes",
[](const ArrayBodyPtr& a, int8_t axis1, int8_t axis2) { return MoveArrayBody(Swapaxes(Array{a}, axis1, axis2)); },
"a"_a,
"axis1"_a,
"axis2"_a);
m.def("repeat",
[](const ArrayBodyPtr& a, int64_t repeats, absl::optional<int8_t> axis) {
return MoveArrayBody(Repeat(Array{a}, repeats, axis));
},
"a"_a,
"repeats"_a,
"axis"_a = nullptr);
m.def("repeat",
[](const ArrayBodyPtr& a, const std::vector<int64_t>& repeats, absl::optional<int8_t> axis) {
return MoveArrayBody(Repeat(Array{a}, repeats, axis));
},
"a"_a,
"repeats"_a,
"axis"_a = nullptr);
m.def("broadcast_to",
[](const ArrayBodyPtr& array, py::handle shape) { return MoveArrayBody(Array{array}.BroadcastTo(ToShape(shape))); },
"array"_a,
"shape"_a);
m.def("concatenate",
[](py::sequence arrays, absl::optional<int8_t> axis) {
std::vector<Array> xs;
xs.reserve(arrays.size());
std::transform(arrays.begin(), arrays.end(), std::back_inserter(xs), [](const auto& item) {
return Array{py::cast<ArrayBodyPtr>(item)};
});
return MoveArrayBody(Concatenate(xs, axis));
},
"arrays"_a,
"axis"_a = 0);
m.def("stack",
[](py::sequence arrays, int8_t axis) {
std::vector<Array> xs;
xs.reserve(arrays.size());
std::transform(arrays.begin(), arrays.end(), std::back_inserter(xs), [](const auto& item) {
return Array{py::cast<ArrayBodyPtr>(item)};
});
return MoveArrayBody(Stack(xs, axis));
},
"arrays"_a,
"axis"_a = 0);
m.def("atleast_2d", [](const ArrayBodyPtr& a) { return MoveArrayBody(AtLeast2D(Array{a})); }, "a"_a);
m.def("atleast_3d", [](const ArrayBodyPtr& a) { return MoveArrayBody(AtLeast3D(Array{a})); }, "a"_a);
m.def("hstack",
[](py::sequence arrays) {
std::vector<Array> xs;
xs.reserve(arrays.size());
std::transform(arrays.begin(), arrays.end(), std::back_inserter(xs), [](const auto& item) {
return Array{py::cast<ArrayBodyPtr>(item)};
});
return MoveArrayBody(HStack(xs));
},
"arrays"_a);
m.def("vstack",
[](py::sequence arrays) {
std::vector<Array> xs;
xs.reserve(arrays.size());
std::transform(arrays.begin(), arrays.end(), std::back_inserter(xs), [](const auto& item) {
return Array{py::cast<ArrayBodyPtr>(item)};
});
return MoveArrayBody(VStack(xs));
},
"arrays"_a);
m.def("dstack",
[](py::sequence arrays) {
std::vector<Array> xs;
xs.reserve(arrays.size());
std::transform(arrays.begin(), arrays.end(), std::back_inserter(xs), [](const auto& item) {
return Array{py::cast<ArrayBodyPtr>(item)};
});
return MoveArrayBody(DStack(xs));
},
"arrays"_a);
m.def("split", &SplitByIndicesOrSections, "ary"_a, "indices_or_sections"_a, "axis"_a = 0);
m.def("dsplit", &DSplitByIndicesOrSections, "ary"_a, "indices_or_sections"_a);
m.def("vsplit", &VSplitByIndicesOrSections, "ary"_a, "indices_or_sections"_a);
m.def("hsplit", &HSplitByIndicesOrSections, "ary"_a, "indices_or_sections"_a);
m.def("moveaxis",
[](const ArrayBodyPtr& a, const std::vector<int8_t>& source, const std::vector<int8_t>& destination) {
return MoveArrayBody(Moveaxis(Array{a}, Axes{source.begin(), source.end()}, Axes{destination.begin(), destination.end()}));
},
"a"_a,
"source"_a = nullptr,
"destination"_a = nullptr);
m.def("moveaxis",
[](const ArrayBodyPtr& a, py::tuple source, py::tuple destination) {
return MoveArrayBody(Moveaxis(Array{a}, ToAxes(source), ToAxes(destination)));
},
"a"_a,
"source"_a = nullptr,
"destination"_a = nullptr);
m.def("moveaxis",
[](const ArrayBodyPtr& a, int8_t source, int8_t destination) {
return MoveArrayBody(Moveaxis(Array{a}, {source}, {destination}));
},
"a"_a,
"source"_a = nullptr,
"destination"_a = nullptr);
m.def("copyto",
[](const ArrayBodyPtr& dst, const ArrayBodyPtr& src, const std::string& casting, Scalar where) {
CopyTo(Array{dst}, Array{src}, ParseCastingMode(casting), Full({}, where, Dtype::kBool));
},
"dst"_a,
"src"_a,
"casting"_a = "no",
"where"_a = true);
m.def("copyto",
[](const ArrayBodyPtr& dst, const ArrayBodyPtr& src, const std::string& casting, const ArrayBodyPtr& where) {
CopyTo(Array{dst}, Array{src}, ParseCastingMode(casting), Array{where});
},
"dst"_a,
"src"_a,
"casting"_a = "no",
"where"_a);
}
void InitChainerxActivation(pybind11::module& m) {
m.def("clipped_relu", [](const ArrayBodyPtr& x, Scalar z) { return MoveArrayBody(ClippedRelu(Array{x}, z)); }, "x"_a, "z"_a = 20.0);
m.def("crelu", [](const ArrayBodyPtr& x, int8_t axis) { return MoveArrayBody(CRelu(Array{x}, axis)); }, "x"_a, "axis"_a = 1);
m.def("elu", [](const ArrayBodyPtr& x, double alpha) { return MoveArrayBody(Elu(Array{x}, alpha)); }, "x"_a, "alpha"_a = 1.0);
m.def("sigmoid", [](const ArrayBodyPtr& x) { return MoveArrayBody(Sigmoid(Array{x})); }, "x"_a);
m.def("relu", [](const ArrayBodyPtr& x) { return MoveArrayBody(Relu(Array{x})); }, "x"_a);
m.def("leaky_relu",
[](const ArrayBodyPtr& x, Scalar slope) { return MoveArrayBody(LeakyRelu(Array{x}, slope)); },
"x"_a,
"slope"_a = 0.2);
m.def("tree_lstm", [](py::args args) {
std::vector<ArrayBodyPtr> arrays = py::cast<std::vector<ArrayBodyPtr>>(args);
std::vector<Array> input = ArrayBodiesToArrays(std::move(arrays));
return ToTuple(TreeLstm(input));
});
m.def("slstm", [](const ArrayBodyPtr& c1, const ArrayBodyPtr& c2, const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) {
return ToTuple(SLstm(Array{c1}, Array{c2}, Array{x1}, Array{x2}));
});
m.def("softplus", [](const ArrayBodyPtr& x, double beta) { return MoveArrayBody(Softplus(Array{x}, beta)); }, "x"_a, "beta"_a = 1.0);
}
void InitChainerxArithmetic(pybind11::module& m) {
// math routines
m.def("negative", [](const ArrayBodyPtr& x) { return MoveArrayBody(Negative(Array{x})); }, "x"_a);
m.def("add", [](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Array{x1} + Array{x2}); }, "x1"_a, "x2"_a);
m.def("add", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Add(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("add", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Add(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("subtract", [](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Array{x1} - Array{x2}); }, "x1"_a, "x2"_a);
m.def("subtract", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Subtract(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("subtract", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Subtract(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("multiply", [](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Array{x1} * Array{x2}); }, "x1"_a, "x2"_a);
m.def("multiply", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Multiply(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("multiply", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Multiply(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("divide", [](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Array{x1} / Array{x2}); }, "x1"_a, "x2"_a);
m.def("divide", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Divide(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("divide", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Divide(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("floor_divide",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(FloorDivide(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("floor_divide", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(FloorDivide(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("floor_divide", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(FloorDivide(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("true_divide",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(TrueDivide(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("true_divide", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(TrueDivide(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("true_divide", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(TrueDivide(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("reciprocal", [](const ArrayBodyPtr& x) { return MoveArrayBody(Reciprocal(Array{x})); }, "x"_a);
m.def("power",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Power(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("power", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Power(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("power", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Power(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("remainder",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Mod(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("remainder", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Mod(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("remainder", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Mod(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.attr("mod") = m.attr("remainder");
m.def("fmod", [](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Fmod(Array{x1}, Array{x2})); }, "x1"_a, "x2"_a);
}
void InitChainerxBinary(pybind11::module& m) {
m.def("bitwise_and",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(BitwiseAnd(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("bitwise_and", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(BitwiseAnd(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("bitwise_and", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(BitwiseAnd(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("bitwise_or",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(BitwiseOr(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("bitwise_or", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(BitwiseOr(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("bitwise_or", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(BitwiseOr(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("bitwise_xor",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(BitwiseXor(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("bitwise_xor", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(BitwiseXor(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("bitwise_xor", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(BitwiseXor(x1, Array{x2})); }, "x1"_a, "x2"_a);
}
void InitChainerxExpLog(pybind11::module& m) {
m.def("erf", [](const ArrayBodyPtr& x) { return MoveArrayBody(Erf(Array{x})); }, "x"_a);
m.def("exp", [](const ArrayBodyPtr& x) { return MoveArrayBody(Exp(Array{x})); }, "x"_a);
m.def("expm1", [](const ArrayBodyPtr& x) { return MoveArrayBody(Expm1(Array{x})); }, "x"_a);
m.def("exp2", [](const ArrayBodyPtr& x) { return MoveArrayBody(Exp2(Array{x})); }, "x"_a);
m.def("log", [](const ArrayBodyPtr& x) { return MoveArrayBody(Log(Array{x})); }, "x"_a);
m.def("log10", [](const ArrayBodyPtr& x) { return MoveArrayBody(Log10(Array{x})); }, "x"_a);
m.def("log2", [](const ArrayBodyPtr& x) { return MoveArrayBody(Log2(Array{x})); }, "x"_a);
m.def("log1p", [](const ArrayBodyPtr& x) { return MoveArrayBody(Log1p(Array{x})); }, "x"_a);
}
void InitChainerxHyperbolic(pybind11::module& m) {
m.def("sinh", [](const ArrayBodyPtr& x) { return MoveArrayBody(Sinh(Array{x})); }, "x"_a);
m.def("cosh", [](const ArrayBodyPtr& x) { return MoveArrayBody(Cosh(Array{x})); }, "x"_a);
m.def("tanh", [](const ArrayBodyPtr& x) { return MoveArrayBody(Tanh(Array{x})); }, "x"_a);
m.def("arcsinh", [](const ArrayBodyPtr& x) { return MoveArrayBody(Arcsinh(Array{x})); }, "x"_a);
m.def("arccosh", [](const ArrayBodyPtr& x) { return MoveArrayBody(Arccosh(Array{x})); }, "x"_a);
}
void InitChainerxMisc(pybind11::module& m) {
m.def("square", [](const ArrayBodyPtr& x) { return MoveArrayBody(Square(Array{x})); }, "x"_a);
m.def("sqrt", [](const ArrayBodyPtr& x) { return MoveArrayBody(Sqrt(Array{x})); }, "x"_a);
m.def("abs", [](const ArrayBodyPtr& x) { return MoveArrayBody(Absolute(Array{x})); }, "x"_a);
m.attr("absolute") = m.attr("abs");
m.def("fabs", [](const ArrayBodyPtr& x) { return MoveArrayBody(Fabs(Array{x})); }, "x"_a);
m.def("sign", [](const ArrayBodyPtr& x) { return MoveArrayBody(Sign(Array{x})); }, "x"_a);
m.def("maximum", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Maximum(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("maximum", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Maximum(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("maximum",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Maximum(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("minimum", [](const ArrayBodyPtr& x1, Scalar x2) { return MoveArrayBody(Minimum(Array{x1}, x2)); }, "x1"_a, "x2"_a);
m.def("minimum", [](Scalar x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Minimum(x1, Array{x2})); }, "x1"_a, "x2"_a);
m.def("minimum",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Minimum(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
}
void InitChainerxReduction(pybind11::module& m) {
m.def("sum",
[](const ArrayBodyPtr& a, int8_t axis, bool keepdims) { return MoveArrayBody(Sum(Array{a}, Axes{axis}, keepdims)); },
"a"_a,
"axis"_a,
"keepdims"_a = false);
m.def("sum",
[](const ArrayBodyPtr& a, const absl::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(Sum(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
m.def("logsumexp",
[](const ArrayBodyPtr& x, int8_t axis, bool keepdims) { return MoveArrayBody(LogSumExp(Array{x}, Axes{axis}, keepdims)); },
"x"_a,
"axis"_a,
"keepdims"_a = false);