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lrkkrlee30sonia
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Typo (lsils#578)
* [add] pre-commit typo [fix] typos * [fix] typos Co-authored-by: Siang-Yun (Sonia) Lee <[email protected]>
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.pre-commit-config.yaml

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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v2.2.1
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hooks:
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- id: end-of-file-fixer
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exclude: lib/
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- id: trailing-whitespace
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exclude: lib/
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v2.2.1
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hooks:
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- id: end-of-file-fixer
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exclude: lib/
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- id: trailing-whitespace
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exclude: lib/
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- repo: https://github.com/crate-ci/typos
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rev: v1.8.1
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hooks:
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- id: typos
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exclude: ^(lib/|experiments/|docs/|.github/|.ql/)

README.md

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@@ -36,10 +36,10 @@ aig.foreach_node( [&]( auto node ) {
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## Installation requirements
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A modern compiler is required to build *mockturtle*. We are continously
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A modern compiler is required to build *mockturtle*. We are continuously
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testing with Clang 12.0.1, GCC 9.3.0, and GCC 10.2.0. More information can be
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found in the [documentation](http://mockturtle.readthedocs.io/en/latest/installation.html).
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## EPFL logic sythesis libraries
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## EPFL logic synthesis libraries
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mockturtle is part of the [EPFL logic synthesis](https://lsi.epfl.ch/page-138455-en.html) libraries. The other libraries and several examples on how to use and integrate the libraries can be found in the [logic synthesis tool showcase](https://github.com/lsils/lstools-showcase).

_typos.toml

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[default.extend-words]
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fo = "fo"
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mis = "mis"
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lits = "lits"
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fot = "fot"
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CLAS = "CLAS"
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inouts = "inouts"
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"SEH" = "SEH"
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[type.po]
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extend-glob = ["*.aig", "catch.hpp"]
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check-file = false
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[files]
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extend-exclude = [".github/", ".ql/", "docs/", "examples/", "lib/", "experiments/"]

include/mockturtle/algorithms/aqfp/aqfp_node_resyn.hpp

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*/
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aqfp_node_resyn( aqfp_db<>& db, const aqfp_node_resyn_param& ps ) : params( ps ), db( db )
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{
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/*! must provid the cost of a simple buffer with one output */
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/*! must provide the cost of a simple buffer with one output */
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assert( ps.splitters.count( 1u ) > 0 );
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/*! must provid the cost of a splitter with the maximum capacity */
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/*! must provide the cost of a splitter with the maximum capacity */
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assert( ps.splitters.count( ps.assume.splitter_capacity ) > 0 );
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}
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aqfp_db<>& db;
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};
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} // namespace mockturtle
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} // namespace mockturtle

include/mockturtle/algorithms/aqfp/buffer_insertion.hpp

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#pragma endregion
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#pragma region Compute timeframe
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/*! \brief Compute the earilest and latest possible timeframe by eager ASAP and ALAP */
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/*! \brief Compute the earliest and latest possible timeframe by eager ASAP and ALAP */
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uint32_t compute_timeframe( uint32_t max_depth )
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{
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_timeframes.reset( std::make_pair( 0, 0 ) );
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uint32_t _start_id; // for chunked movement
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}; /* buffer_insertion */
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} // namespace mockturtle
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} // namespace mockturtle

include/mockturtle/algorithms/aqfp/detail/dag.hpp

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std::vector<std::vector<NodeT>> nodes; // fanins of nodes
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std::vector<NodeT> input_slots; // identifiers of the input slots (bundles of fanins where the inputs will be connected)
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NodeT zero_input = 0; // id of the input slot that is connected to contant 0
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NodeT zero_input = 0; // id of the input slot that is connected to constant 0
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aqfp_dag( const std::vector<std::vector<NodeT>>& nodes = {}, const std::vector<NodeT>& input_slots = {}, node_type zero_input = {} )
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: nodes( nodes ), input_slots( input_slots ), zero_input( zero_input ) {}
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}
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};
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} // namespace mockturtle
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} // namespace mockturtle

include/mockturtle/algorithms/cnf.hpp

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* In the default map, constants are mapped to variable `0` (literal `1` for
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* constant-1 and literal `0` for constant-0). Then each primary input is
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* mapped to variables `1, ..., n`. Then the next variables are assigned to
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* each gate in order, unless `gate_offset` is overriden which will be used for
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* each gate in order, unless `gate_offset` is overridden which will be used for
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* the next variable id. Therefore, this function can be used to create two
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* independent sets of node literals for two networks, but keep the same indexes
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* for the primary inputs.
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return impl.run();
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}
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} // namespace mockturtle
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} // namespace mockturtle

include/mockturtle/algorithms/cover_to_graph.hpp

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/*! \brief convert_node_to_graph
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* This helper function receives as input a node, storing the cover information.
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* This information corresponds to a vactor of cubes and to a boolean determining whether
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* This information corresponds to a vector of cubes and to a boolean determining whether
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* the cubes represent the ON set or the OFF set.
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* Each cube is mapped into a subgraph and the output signals are collected in a vector, corresponding to the
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* products/sums of the SOP/POS.
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return converter.get_network();
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}
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} /* namespace mockturtle */
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} /* namespace mockturtle */

include/mockturtle/algorithms/cut_enumeration.hpp

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* Unit cuts do not participate in the sorting and are always added to the end
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* of each cut set.
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*
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* The algorithm can be configured by speciying the template argument `CutData`
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* The algorithm can be configured by specifying the template argument `CutData`
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* which holds the application specific data assigned to each cut. Examples
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* on how to specify custom cost functions for sorting cuts based on the
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* application specific cut data can be found in the files contained in the
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* Unit cuts do not participate in the sorting and are always added to the end
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* of each cut set.
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*
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* The algorithm can be configured by speciying the template argument `CutData`
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* The algorithm can be configured by specifying the template argument `CutData`
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* which holds the application specific data assigned to each cut. Examples
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* on how to specify custom cost functions for sorting cuts based on the
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* application specific cut data can be found in the files contained in the
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}
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} /* namespace mockturtle */
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} /* namespace mockturtle */

include/mockturtle/algorithms/decomposition.hpp

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/*! \brief Shannon decomposition
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*
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* This function applies Shannon decomposition on an input truth table and
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* constructs a network based. The variabe ordering can be specified as
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* constructs a network based. The variable ordering can be specified as
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* an input. If not all variables are specified, the remaining co-factors
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* are synthesizes using the resynthesis function.
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*
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/*! \brief Positive Davio decomposition
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*
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* constructs a network based. The variabe ordering can be specified as
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* constructs a network based. The variable ordering can be specified as
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* an input. If not all variables are specified, the remaining co-factors
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* are synthesizes using the resynthesis function.
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*
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/*! \brief Negative Davio decomposition
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*
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* constructs a network based. The variabe ordering can be specified as
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* constructs a network based. The variable ordering can be specified as
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* an input. If not all variables are specified, the remaining co-factors
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* are synthesizes using the resynthesis function.
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*
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}
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} // namespace mockturtle
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} // namespace mockturtle

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