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| TensorMap (const std::string &primary_key) |
| Create empty TensorMap and set primary key. More...
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| TensorMap () |
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template<class InputIt > |
| TensorMap (const std::string &primary_key, InputIt first, InputIt last) |
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| TensorMap (const std::string &primary_key, const std::unordered_map< std::string, core::Tensor > &tensor_map) |
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| TensorMap (const std::string &primary_key, std::initializer_list< value_type > init) |
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| TensorMap (const TensorMap &other) |
| Copy constructor performs a "shallow" copy of the Tensors. More...
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| TensorMap (TensorMap &&other) |
| Move constructor performs a "shallow" copy of the Tensors. More...
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std::size_t | Erase (const std::string key) |
| Erase elements for the TensorMap by key value, if the key exists. If the key does not exists, a warning is thrown. Also primary_key cannot be deleted. It is based on size_type unordered_map::erase(const key_type& k); . More...
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std::pair< iterator, bool > | insert (const value_type &value) |
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template<class P > |
std::pair< iterator, bool > | insert (P &&value) |
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iterator | insert (const_iterator hint, const value_type &value) |
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template<class P > |
iterator | insert (const_iterator hint, P &&value) |
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template<class InputIt > |
void | insert (InputIt first, InputIt last) |
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void | insert (std::initializer_list< value_type > ilist) |
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TensorMap & | operator= (const TensorMap &)=default |
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TensorMap & | operator= (TensorMap &&)=default |
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std::string | GetPrimaryKey () const |
| Returns the primary key of the TensorMap. More...
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std::unordered_set< std::string > | GetKeySet () const |
| Returns a set with all keys. More...
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bool | IsSizeSynchronized () const |
| Returns true if all tensors in the map have the same size. More...
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void | AssertSizeSynchronized () const |
| Assert IsSizeSynchronized(). More...
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bool | IsContiguous () const |
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TensorMap | Contiguous () const |
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bool | Contains (const std::string &key) const |
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std::string | ToString () const |
| Print the TensorMap to string. More...
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TensorMap is a unordered_map<string, Tensor> with a primary key. It is typically used as a container for geometry attributes.
e.g. tensor_map.primary_key: "positions" tensor_map["positions"] : Tensor of shape {100, 3}. tensor_map["colors"] : Tensor of shape {100, 3}. tensor_map["normals"] : Tensor of shape {100, 3}.
Typically, tensors in the TensorMap should have the same length (the first dimension of shape) and device as the primary tensor.