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Python buffer objects can have negative strides.
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@ -41,8 +41,8 @@ completely avoid copy operations with Python expressions like
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py::format_descriptor<float>::format(), /* Python struct-style format descriptor */
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2, /* Number of dimensions */
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{ m.rows(), m.cols() }, /* Buffer dimensions */
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{ sizeof(float) * m.rows(), /* Strides (in bytes) for each index */
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sizeof(float) }
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{ (ssize_t)( sizeof(float) * m.rows() ),/* Strides (in bytes) for each index */
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(ssize_t)( sizeof(float) ) }
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);
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});
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@ -61,7 +61,7 @@ specification.
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std::string format;
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int ndim;
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std::vector<size_t> shape;
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std::vector<size_t> strides;
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std::vector<ssize_t> strides;
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};
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To create a C++ function that can take a Python buffer object as an argument,
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@ -121,8 +121,8 @@ as follows:
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{ (size_t) m.rows(),
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(size_t) m.cols() },
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/* Strides (in bytes) for each index */
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{ sizeof(Scalar) * (rowMajor ? m.cols() : 1),
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sizeof(Scalar) * (rowMajor ? 1 : m.rows()) }
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{ (ssize_t)( sizeof(Scalar) * (rowMajor ? m.cols() : 1) ),
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(ssize_t)( sizeof(Scalar) * (rowMajor ? 1 : m.rows()) ) }
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);
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})
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@ -265,14 +265,14 @@ protected:
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const unsigned char *data_;
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// Storing the shape & strides in local variables (i.e. these arrays) allows the compiler to
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// make large performance gains on big, nested loops, but requires compile-time dimensions
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conditional_t<Dynamic, const size_t *, std::array<size_t, (size_t) Dims>>
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shape_, strides_;
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conditional_t<Dynamic, const size_t *, std::array<size_t, (size_t) Dims>> shape_;
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conditional_t<Dynamic, const ssize_t *, std::array<ssize_t, (size_t) Dims>> strides_;
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const size_t dims_;
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friend class pybind11::array;
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// Constructor for compile-time dimensions:
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template <bool Dyn = Dynamic>
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unchecked_reference(const void *data, const size_t *shape, const size_t *strides, enable_if_t<!Dyn, size_t>)
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unchecked_reference(const void *data, const size_t *shape, const ssize_t *strides, enable_if_t<!Dyn, size_t>)
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: data_{reinterpret_cast<const unsigned char *>(data)}, dims_{Dims} {
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for (size_t i = 0; i < dims_; i++) {
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shape_[i] = shape[i];
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@ -281,7 +281,7 @@ protected:
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}
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// Constructor for runtime dimensions:
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template <bool Dyn = Dynamic>
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unchecked_reference(const void *data, const size_t *shape, const size_t *strides, enable_if_t<Dyn, size_t> dims)
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unchecked_reference(const void *data, const size_t *shape, const ssize_t *strides, enable_if_t<Dyn, size_t> dims)
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: data_{reinterpret_cast<const unsigned char *>(data)}, shape_{shape}, strides_{strides}, dims_{dims} {}
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public:
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@ -573,12 +573,12 @@ public:
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}
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/// Strides of the array
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const size_t* strides() const {
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return reinterpret_cast<const size_t *>(detail::array_proxy(m_ptr)->strides);
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const ssize_t* strides() const {
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return reinterpret_cast<const ssize_t *>(detail::array_proxy(m_ptr)->strides);
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}
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/// Stride along a given axis
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size_t strides(size_t dim) const {
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ssize_t strides(size_t dim) const {
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if (dim >= ndim())
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fail_dim_check(dim, "invalid axis");
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return strides()[dim];
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@ -702,9 +702,9 @@ protected:
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throw std::domain_error("array is not writeable");
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}
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static std::vector<Py_intptr_t> default_strides(const std::vector<Py_intptr_t>& shape, size_t itemsize) {
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static std::vector<ssize_t> default_strides(const std::vector<size_t>& shape, size_t itemsize) {
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auto ndim = shape.size();
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std::vector<Py_intptr_t> strides(ndim);
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std::vector<ssize_t> strides(ndim);
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if (ndim) {
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std::fill(strides.begin(), strides.end(), itemsize);
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for (size_t i = 0; i < ndim - 1; i++)
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@ -1133,7 +1133,7 @@ array_iterator<T> array_end(const buffer_info& buffer) {
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class common_iterator {
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public:
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using container_type = std::vector<size_t>;
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using container_type = std::vector<ssize_t>;
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using value_type = container_type::value_type;
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using size_type = container_type::size_type;
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@ -1175,7 +1175,7 @@ public:
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for (size_t i = 0; i < shape.size(); ++i)
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m_shape[i] = static_cast<container_type::value_type>(shape[i]);
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container_type strides(shape.size());
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std::vector<ssize_t> strides(shape.size());
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for (size_t i = 0; i < N; ++i)
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init_common_iterator(buffers[i], shape, m_common_iterator[i], strides);
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}
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@ -1203,7 +1203,7 @@ private:
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void init_common_iterator(const buffer_info &buffer,
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const std::vector<size_t> &shape,
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common_iter &iterator, container_type &strides) {
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common_iter &iterator, std::vector<ssize_t> &strides) {
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auto buffer_shape_iter = buffer.shape.rbegin();
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auto buffer_strides_iter = buffer.strides.rbegin();
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auto shape_iter = shape.rbegin();
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@ -1211,7 +1211,7 @@ private:
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while (buffer_shape_iter != buffer.shape.rend()) {
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if (*shape_iter == *buffer_shape_iter)
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*strides_iter = static_cast<size_t>(*buffer_strides_iter);
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*strides_iter = *buffer_strides_iter;
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else
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*strides_iter = 0;
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@ -1283,10 +1283,11 @@ broadcast_trivial broadcast(const std::array<buffer_info, N> &buffers, size_t &n
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// Check for C contiguity (but only if previous inputs were also C contiguous)
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if (trivial_broadcast_c) {
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size_t expect_stride = buffers[i].itemsize;
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ssize_t expect_stride = static_cast<ssize_t>(buffers[i].itemsize);
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auto end = buffers[i].shape.crend();
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for (auto shape_iter = buffers[i].shape.crbegin(), stride_iter = buffers[i].strides.crbegin();
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trivial_broadcast_c && shape_iter != end; ++shape_iter, ++stride_iter) {
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auto shape_iter = buffers[i].shape.crbegin();
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auto stride_iter = buffers[i].strides.crbegin();
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for (; trivial_broadcast_c && shape_iter != end; ++shape_iter, ++stride_iter) {
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if (expect_stride == *stride_iter)
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expect_stride *= *shape_iter;
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else
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@ -1296,10 +1297,11 @@ broadcast_trivial broadcast(const std::array<buffer_info, N> &buffers, size_t &n
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// Check for Fortran contiguity (if previous inputs were also F contiguous)
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if (trivial_broadcast_f) {
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size_t expect_stride = buffers[i].itemsize;
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ssize_t expect_stride = static_cast<ssize_t>(buffers[i].itemsize);
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auto end = buffers[i].shape.cend();
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for (auto shape_iter = buffers[i].shape.cbegin(), stride_iter = buffers[i].strides.cbegin();
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trivial_broadcast_f && shape_iter != end; ++shape_iter, ++stride_iter) {
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auto shape_iter = buffers[i].shape.cbegin();
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auto stride_iter = buffers[i].strides.cbegin();
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for (; trivial_broadcast_f && shape_iter != end; ++shape_iter, ++stride_iter) {
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if (expect_stride == *stride_iter)
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expect_stride *= *shape_iter;
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else
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@ -1336,20 +1338,20 @@ struct vectorize_helper {
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auto trivial = broadcast(buffers, ndim, shape);
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size_t size = 1;
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std::vector<size_t> strides(ndim);
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std::vector<ssize_t> strides(ndim);
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if (ndim > 0) {
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if (trivial == broadcast_trivial::f_trivial) {
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strides[0] = sizeof(Return);
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strides[0] = static_cast<ssize_t>(sizeof(Return));
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for (size_t i = 1; i < ndim; ++i) {
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strides[i] = strides[i - 1] * shape[i - 1];
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strides[i] = strides[i - 1] * static_cast<ssize_t>(shape[i - 1]);
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size *= shape[i - 1];
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}
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size *= shape[ndim - 1];
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}
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else {
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strides[ndim-1] = sizeof(Return);
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strides[ndim-1] = static_cast<ssize_t>(sizeof(Return));
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for (size_t i = ndim - 1; i > 0; --i) {
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strides[i - 1] = strides[i] * shape[i];
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strides[i - 1] = strides[i] * static_cast<ssize_t>(shape[i]);
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size *= shape[i];
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}
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size *= shape[0];
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@ -109,8 +109,8 @@ test_initializer buffers([](py::module &m) {
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py::format_descriptor<float>::format(), /* Python struct-style format descriptor */
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2, /* Number of dimensions */
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{ m.rows(), m.cols() }, /* Buffer dimensions */
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{ sizeof(float) * m.rows(), /* Strides (in bytes) for each index */
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sizeof(float) }
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{ static_cast<ssize_t>(sizeof(float) * m.rows()), /* Strides (in bytes) for each index */
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static_cast<ssize_t>(sizeof(float)) }
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);
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})
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;
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@ -13,6 +13,7 @@
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#include <pybind11/stl.h>
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#include <cstdint>
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#include <vector>
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using arr = py::array;
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using arr_t = py::array_t<uint16_t, 0>;
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@ -203,6 +203,10 @@ def test_wrap():
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a2 = wrap(a1d)
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assert_references(a1d, a2, a1)
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a1m = a1[::-1, ::-1, ::-1]
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a2 = wrap(a1m)
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assert_references(a1m, a2, a1)
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def test_numpy_view(capture):
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from pybind11_tests.array import ArrayClass
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@ -226,7 +226,7 @@ py::array_t<int32_t, 0> test_array_ctors(int i) {
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std::vector<int32_t> data { 1, 2, 3, 4, 5, 6 };
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std::vector<size_t> shape { 3, 2 };
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std::vector<size_t> strides { 8, 4 };
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std::vector<ssize_t> strides { 8, 4 };
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auto ptr = data.data();
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auto vptr = (void *) ptr;
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