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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 <utility>
#include <vector>
#include <nonstd/optional.hpp>
#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/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/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/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/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, nonstd::nullopt, offset, GetDevice(device)));
}
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",
[](py::handle a, py::handle dtype, py::handle device) {
Array arr{MakeArray(a, dtype, false, device)};
return MoveArrayBody(AsContiguousArray(arr));
},
"a"_a,
"dtype"_a = nullptr,
"device"_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::handle device) {
return MoveArrayBody(Zeros(ToShape(shape), dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"dtype"_a = nullptr,
"device"_a = nullptr);
m.def("zeros",
[](py::int_ dim, py::handle dtype, py::handle device) {
return MoveArrayBody(Zeros(Shape{dim}, dtype.is_none() ? Dtype::kFloat32 : GetDtype(dtype), GetDevice(device)));
},
"shape"_a,
"dtype"_a = nullptr,
"device"_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 nonstd::optional<Scalar>& maybe_stop,
const nonstd::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, nonstd::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, py::handle device) { return MoveArrayBody(Diag(Array{v}, k, GetDevice(device))); },
"v"_a,
"k"_a = 0,
"device"_a = nullptr);
m.def("diagflat",
[](const ArrayBodyPtr& v, int64_t k, py::handle device) { return MoveArrayBody(Diagflat(Array{v}, k, GetDevice(device))); },
"v"_a,
"k"_a = 0,
"device"_a = nullptr);
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() ? nonstd::optional<Dtype>{nonstd::nullopt} : nonstd::optional<Dtype>{GetDtype(dtype)},
GetDevice(device)));
},
"start"_a,
"stop"_a,
"num"_a = 50,
"endpoint"_a = true,
"dtype"_a = nullptr,
"device"_a = nullptr);
}
void InitChainerxIndexing(pybind11::module& m) {
// indexing routines
m.def("take",
[](const ArrayBodyPtr& a, py::handle indices, const nonstd::optional<int8_t>& axis) {
if (!axis.has_value()) {
throw NotImplementedError{"axis=None is not yet supported for chainerx.take."};
}
if (py::isinstance<ArrayBody>(indices)) {
return MoveArrayBody(Take(Array{a}, Array{py::cast<ArrayBodyPtr>(indices)}, axis.value()));
}
if (py::isinstance<py::sequence>(indices)) {
nonstd::optional<Dtype> dtype = Dtype::kInt64;
return MoveArrayBody(Take(Array{a}, Array{MakeArray(indices, dtype, false, a->device())}, axis.value()));
}
if (py::isinstance<py::array>(indices)) {
return MoveArrayBody(
Take(Array{a}, Array{MakeArrayFromNumpyArray(py::cast<py::array>(indices), a->device())}, axis.value()));
}
throw py::type_error{"only integers, slices (`:`), sequence, numpy.ndarray and chainerx.newaxis (`None`) are valid indices"};
},
"a"_a,
"indices"_a,
"axis"_a);
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);
}
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);
}
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 nonstd::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 nonstd::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(Any(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
}
void InitChainerxManipulation(pybind11::module& m) {
// manipulation routines
m.def("transpose",
[](const ArrayBodyPtr& a, const nonstd::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 nonstd::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("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 nonstd::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("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, nonstd::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",
[](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.
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));
};
// 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))};
},
"ary"_a,
"indices_or_sections"_a,
"axis"_a = 0);
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);
}
void InitChainerxMath(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("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 nonstd::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("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);
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);
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);
m.def("logsumexp",
[](const ArrayBodyPtr& x, const nonstd::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(LogSumExp(Array{x}, ToAxes(axis), keepdims));
},
"x"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
m.def("log_softmax",
[](const ArrayBodyPtr& x, int8_t axis) { return MoveArrayBody(LogSoftmax(Array{x}, Axes{axis})); },
"x"_a,
"axis"_a);
m.def("log_softmax",
[](const ArrayBodyPtr& x, const nonstd::optional<std::vector<int8_t>>& axis) {
return MoveArrayBody(LogSoftmax(Array{x}, ToAxes(axis)));
},
"x"_a,
"axis"_a = nullptr);
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("softmax", [](const ArrayBodyPtr& x, int8_t axis) { return MoveArrayBody(Softmax(Array{x}, Axes{axis})); }, "x"_a, "axis"_a);
m.def("softmax",
[](const ArrayBodyPtr& x, const nonstd::optional<std::vector<int8_t>>& axis) {
return MoveArrayBody(Softmax(Array{x}, ToAxes(axis)));
},
"x"_a,
"axis"_a = nullptr);
m.def("square", [](const ArrayBodyPtr& x) { return MoveArrayBody(Square(Array{x})); }, "x"_a);
m.def("squared_difference",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(SquaredDifference(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
m.def("sqrt", [](const ArrayBodyPtr& x) { return MoveArrayBody(Sqrt(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("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);
m.def("sin", [](const ArrayBodyPtr& x) { return MoveArrayBody(Sin(Array{x})); }, "x"_a);
m.def("cos", [](const ArrayBodyPtr& x) { return MoveArrayBody(Cos(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("tan", [](const ArrayBodyPtr& x) { return MoveArrayBody(Tan(Array{x})); }, "x"_a);
m.def("arcsin", [](const ArrayBodyPtr& x) { return MoveArrayBody(Arcsin(Array{x})); }, "x"_a);
m.def("arccos", [](const ArrayBodyPtr& x) { return MoveArrayBody(Arccos(Array{x})); }, "x"_a);
m.def("arctan", [](const ArrayBodyPtr& x) { return MoveArrayBody(Arctan(Array{x})); }, "x"_a);
m.def("arctan2",
[](const ArrayBodyPtr& x1, const ArrayBodyPtr& x2) { return MoveArrayBody(Arctan2(Array{x1}, Array{x2})); },
"x1"_a,
"x2"_a);
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("ceil", [](const ArrayBodyPtr& x) { return MoveArrayBody(Ceil(Array{x})); }, "x"_a);
m.def("floor", [](const ArrayBodyPtr& x) { return MoveArrayBody(Floor(Array{x})); }, "x"_a);
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);
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 InitChainerxSorting(pybind11::module& m) {
// sorting routines
m.def("argmax",
[](const ArrayBodyPtr& a, const nonstd::optional<int8_t>& axis) { return MoveArrayBody(ArgMax(Array{a}, ToAxes(axis))); },
"a"_a,
"axis"_a = nullptr);
m.def("argmin",
[](const ArrayBodyPtr& a, const nonstd::optional<int8_t>& axis) { return MoveArrayBody(ArgMin(Array{a}, ToAxes(axis))); },
"a"_a,
"axis"_a = nullptr);
}
void InitChainerxStatistics(pybind11::module& m) {
// statistics routines
m.def("amax",
[](const ArrayBodyPtr& a, int8_t axis, bool keepdims) { return MoveArrayBody(AMax(Array{a}, Axes{axis}, keepdims)); },
"a"_a,
"axis"_a,
"keepdims"_a = false);
m.def("amax",
[](const ArrayBodyPtr& a, const nonstd::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(AMax(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
m.attr("max") = m.attr("amax");
m.def("amin",
[](const ArrayBodyPtr& a, int8_t axis, bool keepdims) { return MoveArrayBody(AMin(Array{a}, Axes{axis}, keepdims)); },
"a"_a,
"axis"_a,
"keepdims"_a = false);
m.def("amin",
[](const ArrayBodyPtr& a, const nonstd::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(AMin(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
m.attr("min") = m.attr("amin");
m.def("mean",
[](const ArrayBodyPtr& a, int8_t axis, bool keepdims) { return MoveArrayBody(Mean(Array{a}, Axes{axis}, keepdims)); },
"a"_a,
"axis"_a,
"keepdims"_a = false);
m.def("mean",
[](const ArrayBodyPtr& a, const nonstd::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(Mean(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
m.def("var",
[](const ArrayBodyPtr& a, int8_t axis, bool keepdims) { return MoveArrayBody(Var(Array{a}, Axes{axis}, keepdims)); },
"a"_a,
"axis"_a,
"keepdims"_a = false);
m.def("var",
[](const ArrayBodyPtr& a, const nonstd::optional<std::vector<int8_t>>& axis, bool keepdims) {
return MoveArrayBody(Var(Array{a}, ToAxes(axis), keepdims));
},
"a"_a,
"axis"_a = nullptr,
"keepdims"_a = false);
}
void InitChainerxConnection(pybind11::module& m) {
// connection routines
m.def("conv",
[](const ArrayBodyPtr& x,
const ArrayBodyPtr& w,
const nonstd::optional<ArrayBodyPtr>& b,
py::handle stride,
py::handle pad,
bool cover_all) {
// Create an Array from x to compute the image dimensions and the expected number of stride and padding elements.
Array x_array{x};
int8_t ndim = x_array.ndim() - 2;
return MoveArrayBody(
Conv(x_array,
Array{w},
b.has_value() ? nonstd::optional<Array>{Array{*b}} : nonstd::nullopt,
ToStackVector<int64_t>(stride, ndim),
ToStackVector<int64_t>(pad, ndim),
cover_all));
},
"x"_a,
"w"_a,
"b"_a = nullptr,
"stride"_a = 1,
"pad"_a = 0,
"cover_all"_a = false);
m.def("conv_transpose",
[](const ArrayBodyPtr& x,
const ArrayBodyPtr& w,
const nonstd::optional<ArrayBodyPtr>& b,
py::handle stride,
py::handle pad,
const nonstd::optional<py::tuple>& outsize) {
// Create an Array from x to compute the image dimensions and the expected number of stride and padding elements.
Array x_array{x};
int8_t ndim = x_array.ndim() - 2;
return MoveArrayBody(ConvTranspose(
x_array,
Array{w},
b.has_value() ? nonstd::optional<Array>{Array{*b}} : nonstd::nullopt,
ToStackVector<int64_t>(stride, ndim),
ToStackVector<int64_t>(pad, ndim),
outsize.has_value() ? nonstd::optional<Dims>{ToStackVector<int64_t>(*outsize, ndim)} : nonstd::nullopt));
},
"x"_a,
"w"_a,
"b"_a = nullptr,
"stride"_a = 1,
"pad"_a = 0,
"outsize"_a = nullptr);
m.def("linear",
[](const ArrayBodyPtr& x, const ArrayBodyPtr& w, const nonstd::optional<ArrayBodyPtr>& b, int8_t n_batch_axes) {
return MoveArrayBody(
Linear(Array{x}, Array{w}, b.has_value() ? nonstd::optional<Array>{Array{*b}} : nonstd::nullopt, n_batch_axes));
},
"x"_a,
"w"_a,
"b"_a = nullptr,
"n_batch_axes"_a = 1);
}
void InitChainerxNormalization(pybind11::module& m) {
// normalization routines
m.def("batch_norm",
[](const ArrayBodyPtr& x,
const ArrayBodyPtr& gamma,
const ArrayBodyPtr& beta,
const ArrayBodyPtr& running_mean,
const ArrayBodyPtr& running_var,
Scalar eps,
Scalar decay,
const nonstd::optional<std::vector<int8_t>>& axis) {
return MoveArrayBody(
BatchNorm(Array{x}, Array{gamma}, Array{beta}, Array{running_mean}, Array{running_var}, eps, decay, ToAxes(axis)));
},
"x"_a,
"gamma"_a,
"beta"_a,
"running_mean"_a,
"running_var"_a,
"eps"_a = 2e-5,
"decay"_a = 0.9,
"axis"_a = nullptr);
m.def("fixed_batch_norm",
[](const ArrayBodyPtr& x,
const ArrayBodyPtr& gamma,
const ArrayBodyPtr& beta,
const ArrayBodyPtr& mean,
const ArrayBodyPtr& var,
Scalar eps,
const nonstd::optional<std::vector<int8_t>>& axis) {
return MoveArrayBody(FixedBatchNorm(Array{x}, Array{gamma}, Array{beta}, Array{mean}, Array{var}, eps, ToAxes(axis)));
},
"x"_a,
"gamma"_a,
"beta"_a,
"mean"_a,
"var"_a,
"eps"_a = 2e-5,
"axis"_a = nullptr);
}
void InitChainerxPooling(pybind11::module& m) {
// pooling routines
// TODO(sonots): Support return_indicies option of chainer.functions.max_pooling_nd.
m.def("max_pool",
[](const ArrayBodyPtr& x, py::handle ksize, py::handle stride, py::handle pad, bool cover_all) {
Array x_array{x};
int8_t ndim = x_array.ndim() - 2;
return MoveArrayBody(
MaxPool(x_array,
ToStackVector<int64_t>(ksize, ndim),
stride.is_none() ? ToStackVector<int64_t>(ksize, ndim) : ToStackVector<int64_t>(stride, ndim),
ToStackVector<int64_t>(pad, ndim),
cover_all));
},
"x"_a,
"ksize"_a,
"stride"_a = py::none(),
"pad"_a = 0,
"cover_all"_a = false);
m.def("average_pool",
[](const ArrayBodyPtr& x, py::handle ksize, py::handle stride, py::handle pad, const std::string& pad_mode) {
Array x_array{x};
int8_t ndim = x_array.ndim() - 2;
AveragePoolPadMode mode{};
if (pad_mode == "zero") {
mode = AveragePoolPadMode::kZero;
} else if (pad_mode == "ignore") {
mode = AveragePoolPadMode::kIgnore;
} else {
throw py::value_error{"pad_mode must be either of 'zero' or 'ignore'"};
}
return MoveArrayBody(AveragePool(
x_array,
ToStackVector<int64_t>(ksize, ndim),
stride.is_none() ? ToStackVector<int64_t>(ksize, ndim) : ToStackVector<int64_t>(stride, ndim),
ToStackVector<int64_t>(pad, ndim),
mode));
},
"x"_a,
"ksize"_a,
"stride"_a = py::none(),
"pad"_a = 0,
"pad_mode"_a = "ignore");
}
void InitChainerxActivation(pybind11::module& m) {
m.def("leaky_relu",
[](const ArrayBodyPtr& x, Scalar slope) { return MoveArrayBody(LeakyRelu(Array{x}, slope)); },
py::arg("x"),
py::arg("slope") = 0.2);
}
} // namespace
void InitChainerxRoutines(pybind11::module& m) {
InitChainerxActivation(m);
InitChainerxCreation(m);
InitChainerxIndexing(m);
InitChainerxLinalg(m);
InitChainerxLogic(m);
InitChainerxManipulation(m);
InitChainerxMath(m);
InitChainerxSorting(m);
InitChainerxStatistics(m);