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// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// The MIT License (MIT)
//
// Copyright (c) 2018-2021 www.open3d.org
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
// IN THE SOFTWARE.
// ----------------------------------------------------------------------------
#include "open3d/t/geometry/TensorMap.h"
#include "open3d/t/geometry/PointCloud.h"
#include "pybind/docstring.h"
#include "pybind/t/geometry/geometry.h"
namespace open3d {
namespace t {
namespace geometry {
// This is a copy of py::bind_map function, with `__delitem__` function
// removed. The same is defined in `pybind_tensormap` to use
// `TensorMap::Erase(key)`.
template <typename Map,
typename holder_type = std::unique_ptr<Map>,
typename... Args>
static py::class_<Map, holder_type> bind_tensor_map(py::handle scope,
const std::string &name,
Args &&... args) {
using KeyType = typename Map::key_type;
using MappedType = typename Map::mapped_type;
using Class_ = py::class_<Map, holder_type>;
// If either type is a non-module-local bound type then make the map binding
// non-local as well; otherwise (e.g. both types are either module-local or
// converting) the map will be module-local.
auto tinfo = py::detail::get_type_info(typeid(MappedType));
bool local = !tinfo || tinfo->module_local;
if (local) {
tinfo = py::detail::get_type_info(typeid(KeyType));
local = !tinfo || tinfo->module_local;
}
Class_ cl(scope, name.c_str(), pybind11::module_local(local),
std::forward<Args>(args)...);
cl.def(py::init<>());
// Register stream insertion operator (if possible)
py::detail::map_if_insertion_operator<Map, Class_>(cl, name);
cl.def(
"__bool__", [](const Map &m) -> bool { return !m.empty(); },
"Check whether the map is nonempty");
// Essential: keep list alive while iterator exists
cl.def(
"__iter__",
[](Map &m) { return py::make_key_iterator(m.begin(), m.end()); },
py::keep_alive<0, 1>()
);
// Essential: keep list alive while iterator exists
cl.def(
"items",
[](Map &m) { return py::make_iterator(m.begin(), m.end()); },
py::keep_alive<0, 1>());
cl.def(
"__getitem__",
[](Map &m, const KeyType &k) -> MappedType & {
auto it = m.find(k);
if (it == m.end())
throw py::key_error(
fmt::format("Key {} not found in TensorMap", k));
return it->second;
},
// py::return_value_policy::copy is used as the safest option.
// The goal is to make TensorMap works similarly as putting Tensors
// into a python dict, i.e., {"a": Tensor(xx), "b": Tensor(XX)}.
// Accessing a value in the map will return a shallow copy of the
// tensor that shares the same underlying memory.
//
// - automatic : works, different id
// - automatic_reference: works, different id
// - take_ownership : doesn't work, segfault
// - copy : works, different id
// - move : doesn't work, blob is null
// - reference : doesn't work, when a key is deleted, the
// alias becomes invalid
// - reference_internal : doesn't work, value in map overwritten
// when assigning to alias
py::return_value_policy::copy);
cl.def("__setitem__", [](Map &m, const KeyType &k, const MappedType &v) {
if (!TensorMap::GetReservedKeys().count(k)) {
m[k] = v;
} else {
throw py::key_error(
fmt::format("Cannot assign to reserved key \"{}\"", k));
}
});
cl.def("__contains__", [](Map &m, const KeyType &k) -> bool {
auto it = m.find(k);
if (it == m.end()) return false;
return true;
});
// Assignment provided only if the type is copyable
py::detail::map_assignment<Map, Class_>(cl);
// Deleted the "__delitem__" function.
// This will be implemented in `pybind_tensormap()`.
cl.def("__len__", [](const Map &m) -> size_t { return m.size(); });
return cl;
}
void pybind_tensormap(py::module &m) {
// Bind to the generic dictionary interface such that it works the same as a
// regular dictionary in Python, except that types are enforced. Supported
// functions include `__bool__`, `__iter__`, `items`, `__getitem__`,
// `__contains__`, `__len__` and map assignment.
// The `__delitem__` function is removed from bind_map, in bind_tensor_map,
// and defined in this function, to use TensorMap::Erase, in order to
// protect users from deleting the `private_key`.
auto tm = bind_tensor_map<TensorMap>(
m, "TensorMap", "Map of String to Tensor with a primary key.");
tm.def("__delitem__",
[](TensorMap &m, const std::string &k) { return m.Erase(k); });
tm.def("erase",
[](TensorMap &m, const std::string &k) { return m.Erase(k); });
// Constructors.
tm.def(py::init<const std::string &>(), "primary_key"_a);
tm.def(py::init<const std::string &,
const std::unordered_map<std::string, core::Tensor> &>(),
"primary_key"_a, "map_keys_to_tensors"_a);
// Member functions. Some C++ functions are ignored since the
// functionalities are already covered in the generic dictionary interface.
tm.def_property_readonly("primary_key", &TensorMap::GetPrimaryKey);
tm.def("is_size_synchronized", &TensorMap::IsSizeSynchronized);
tm.def("assert_size_synchronized", &TensorMap::AssertSizeSynchronized);
// Pickle support.
tm.def(py::pickle(
[](const TensorMap &m) {
// __getstate__
std::unordered_map<std::string, core::Tensor> map;
for (const auto &kv : m) {
map[kv.first] = kv.second;
}
return py::make_tuple(m.GetPrimaryKey(), map);
},
[](py::tuple t) {
// __setstate__
if (t.size() != 2) {
utility::LogError(
"Cannot unpickle TensorMap! Expecting a tuple of "
"size 2.");
}
return TensorMap(t[0].cast<std::string>(),
t[1].cast<std::unordered_map<std::string,
core::Tensor>>());
}));
tm.def("__setattr__",
[](TensorMap &m, const std::string &key, const core::Tensor &val) {
if (!TensorMap::GetReservedKeys().count(key)) {
m[key] = val;
} else {
throw py::key_error(fmt::format(
"Cannot assign to reserved key \"{}\"", key));
}
});
tm.def("__getattr__",
[](TensorMap &m, const std::string &key) -> core::Tensor {
auto it = m.find(key);
if (it == m.end()) {
throw py::key_error(
fmt::format("Key {} not found in TensorMap", key));
}
return it->second;
});
tm.def("__delattr__", [](TensorMap &m, const std::string &key) {
auto it = m.find(key);
if (it == m.end()) {
throw py::key_error(
fmt::format("Key {} not found in TensorMap", key));
}
return m.Erase(key);
});
tm.def("__str__", &TensorMap::ToString);
tm.def("__repr__", &TensorMap::ToString);
tm.def("__dir__", [](TensorMap &m) {
auto keys = py::list();
for (const auto &kv : m) {
keys.append(kv.first);
}
return keys;
});
}
} // namespace geometry
} // namespace t
} // namespace open3d
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