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Add CFG to generate_scope in tutorials #1706

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38 changes: 19 additions & 19 deletions tutorials/codegen.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -480,66 +480,66 @@
" self.frame = frame_codegen\n",
" # Can be used to dispatch other code generators for allocation/nodes\n",
" self.dispatcher = frame_codegen.dispatcher\n",
" \n",
"\n",
" ################################################################\n",
" # Register handlers/hooks through dispatcher: Can be used for \n",
" # Register handlers/hooks through dispatcher: Can be used for\n",
" # nodes, memory copy/allocation, scopes, states, and more.\n",
" \n",
"\n",
" # In this case, register scopes\n",
" self.dispatcher.register_map_dispatcher(dace.ScheduleType.LoopyLoop, self)\n",
" \n",
"\n",
" # You can similarly use register_{array,copy,node,state}_dispatcher\n",
" \n",
" # A scope dispatcher will trigger a method called generate_scope whenever \n",
"\n",
" # A scope dispatcher will trigger a method called generate_scope whenever\n",
" # an SDFG has a scope with that schedule\n",
" def generate_scope(self, sdfg: dace.SDFG, scope: ScopeSubgraphView,\n",
" def generate_scope(self, sdfg: dace.SDFG, dfg, scope: ScopeSubgraphView,\n",
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" state_id: int, function_stream: CodeIOStream,\n",
" callsite_stream: CodeIOStream):\n",
" # The parameters here are:\n",
" # sdfg: The SDFG we are currently generating.\n",
" # scope: The subgraph of the state containing only the scope (map contents)\n",
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add tutorial documentation

" # we want to generate the code for.\n",
" # state_id: The state in the SDFG the subgraph is taken from (i.e., \n",
" # state_id: The state in the SDFG the subgraph is taken from (i.e.,\n",
" # `sdfg.node(state_id)` is the same as `scope.graph`)\n",
" # function_stream: A cursor to the global code (which can be used to define\n",
" # functions, hence the name).\n",
" # callsite_stream: A cursor to the current location in the code, most of\n",
" # the code is generated here.\n",
" \n",
"\n",
" # We can get the map entry node from the scope graph\n",
" entry_node = scope.source_nodes()[0]\n",
" \n",
"\n",
" # First, generate an opening brace (for instrumentation and dynamic map ranges)\n",
" callsite_stream.write('{', sdfg, state_id, entry_node)\n",
" \n",
"\n",
" ################################################################\n",
" # Generate specific code: We will generate a reversed loop with a \n",
" # Generate specific code: We will generate a reversed loop with a\n",
" # comment for each dimension of the map. For the sake of simplicity,\n",
" # dynamic map ranges are not supported.\n",
" \n",
"\n",
" for param, rng in zip(entry_node.map.params, entry_node.map.range):\n",
" # We use the sym2cpp function from the cpp support functions\n",
" # to convert symbolic expressions to proper C++\n",
" begin, end, stride = (sym2cpp(r) for r in rng)\n",
" \n",
"\n",
" # Every write is optionally (but recommended to be) tagged with\n",
" # 1-3 extra arguments, serving as line information to match\n",
" # SDFG, state, and graph nodes/edges to written code.\n",
" callsite_stream.write(f'''// Loopy-loop {param}\n",
" for (auto {param} = {end}; {param} >= {begin}; {param} -= {stride}) {{''',\n",
" sdfg, state_id, entry_node\n",
" )\n",
" \n",
"\n",
" # NOTE: CodeIOStream will automatically take care of indentation for us.\n",
" \n",
" \n",
"\n",
"\n",
" # Now that the loops have been defined, use the dispatcher to invoke any\n",
" # code generator (including this one) that is registered to deal with\n",
" # the internal nodes in the subgraph. We skip the MapEntry node.\n",
" self.dispatcher.dispatch_subgraph(sdfg, scope, state_id,\n",
" self.dispatcher.dispatch_subgraph(sdfg, dfg, scope, state_id,\n",
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" function_stream, callsite_stream,\n",
" skip_entry_node=True)\n",
" \n",
"\n",
" # NOTE: Since skip_exit_node above is set to False, closing braces will\n",
" # be automatically generated"
]
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