Function _squeeze_cpp

imperative/python/src/tensor_utils.cpp:1575–1619

}

py::object _squeeze_cpp(py::handle inp_hdl, py::handle axis_hdl) {
    std::vector<int32_t> axis;
    size_t ndim;
    if (axis_hdl.ptr() != Py_None) {
        axis = list2vector(axis_hdl);
    }
    if (auto p = TensorWrapper::try_cast(inp_hdl.ptr())) {
        auto&& shape = p->m_tensor->shape();
        if (shape) {
            ndim = shape->ndim;
            if (axis_hdl.ptr() == Py_None) {
                for (size_t i = 0; i < shape->ndim; ++i) {
                    if (shape->shape[i] == 1) {
                        axis.push_back(i);
                    }
                }
            }
        }
    } else {
        py::tuple shape =
                py::reinterpret_borrow<py::tuple>(getattr(inp_hdl, "_tuple_shape"));
        ndim = shape.size();
        if (axis_hdl.ptr() == Py_None) {
            for (size_t i = 0; i < shape.size(); ++i) {
                if (shape[i].cast<size_t>() == 1) {
                    axis.push_back(i);
                }
            }
        }
    }
    for (size_t i = 0; i < axis.size(); ++i) {
        if (axis[i] < 0) {
            axis[i] += static_cast<int32_t>(ndim);
        }
    }
    std::sort(axis.begin(), axis.end());
    for (size_t i = 0; i < axis.size(); ++i) {
        axis[i] -= static_cast<int32_t>(i);
    }
    std::shared_ptr<OpDef> op = RemoveAxis::make(axis = axis);
    py::object Op = py::cast(op);
    PyObject* p[2] = {Op.ptr(), inp_hdl.ptr()};
    py::tuple ret = py::reinterpret_steal<py::object>(py_apply(NULL, p, 2));
    return ret[0];
}

py::object _transpose_cpp(py::handle inp_hdl, py::handle args) {
    py::object obj = _expand_args(args);