DNNWorkload Class Reference
Extends the ABC for workloads. More...
Inheritance diagram for DNNWorkload:
Collaboration diagram for DNNWorkload:
Public Member Functions | |
| def | __init__ (self, list[LayerNode] nodes, **Any attr) |
| "DNNWorkload" | get_copy_no_dummy (self) |
| Return a copy. More... | |
 Public Member Functions inherited from DiGraphWrapper | |
| list[tuple[T, T]] | in_edges (self, T node, Literal[False] data) |
| list[tuple[T, T, dict[str, Any]]] | in_edges (self, T node, Literal[True] data) |
| list[tuple[T, T]] | in_edges (self, T node) |
| list[tuple[T, T]]|list[tuple[T, T, dict[str, Any]]] | in_edges (self, T node, bool data=False) |
| list[tuple[T, T, dict[str, Any]]] | out_edges (self, T node, Literal[True] data) |
| list[tuple[T, T]] | out_edges (self, T node, Literal[False] data) |
| list[tuple[T, T]] | out_edges (self, T node) |
| list[tuple[T, T]]|list[tuple[T, T, dict[str, Any]]] | out_edges (self, T node, bool data=False) |
| Iterator[tuple[T, int]] | in_degree (self) |
| Iterator[tuple[T, int]] | out_degree (self, Literal[None] node) |
| Iterator[tuple[T, int]] | out_degree (self) |
| int | out_degree (self, T node) |
| int|Iterator[tuple[T, int]] | out_degree (self, T|None node=None) |
| Iterator[T] | successors (self, T node) |
| Iterator[T] | predecessors (self, T node) |
| Iterator[T] | topological_sort (self) |
| None | add_node (self, T node) |
| None | add_nodes_from (self, Sequence[T] node) |
| None | remove_nodes_from (self, Iterator[T] nodes) |
| None | add_edge (self, T edge_from, T edge_to) |
| None | add_edges_from (self, Sequence[tuple[T, T]|tuple[T, T, Any]] edges) |
| Iterator[list[T]] | all_simple_paths (self, T producer, T consumer) |
| list[T] | shortest_path (self, T producer, T consumer) |
| list[T] | node_list (self) |
| T | get_node_with_id (self, int node_id) |
| Public Member Functions inherited from LayerNode | |
| def | __init__ (self, int layer_id, str node_name, LayerNodeAttributes node_attr, MappingAttributes mapping_attr) |
| To construct each layer node, algorithm equation/dimension/indirect relation are parsed. More... | |
| LayerOperand | get_act_layer_op (self) |
Return the I LayerOperand: either the non-constant operand or one of the input operands if none are constant. More... | |
| LayerOperand | get_weight_layer_op (self) |
Return the W LayerOperand: either the constant operand or one of the input operands if none are constant. More... | |
| tuple[PrLoop, LoopList, PrScalingFactors] | build_pr_funcs (self) |
| def | __str__ (self) |
| def | __jsonrepr__ (self) |
| JSON representation used for saving this object to a json file. More... | |
| float | calc_tensor_size (self, LayerOperand layer_op, LayerDimSizes layer_dim_sizes) |
| Calculates the tensor size (nb of elements) for the given operand layer_op with the given loop dimension sizes layer_dim_sizes. More... | |
| def | calc_tensor_dim (self, LayerDim dim, LayerDimSizes layer_dim_sizes) |
| dict[LayerDim, UnrollFactor] | calc_tensor_dims (self, LayerOperand layer_op, LayerDimSizes layer_dim_sizes) |
| int | calc_pr_dimension_size_total (self, LayerDim dim) |
| Compute the total pr dimension size of this node, taking padding into account. More... | |
| def | extract_layer_info (self) |
| This function extract basic information for each layer node. More... | |
| list[LayerDim] | get_operand_irrelevant_layer_dims (self, LayerOperand layer_op) |
| Return the irrelevant dimensions of layer operand 'layer_op'. More... | |
| LayerNodeAttributes | extract_node_attr (self) |
| Pack this layer node's attributes in a LayerNodeAttributes instance. More... | |
| MappingAttributes | extract_mapping_attr (self) |
| Public Member Functions inherited from LayerNodeABC | |
| def | __init__ (self, int node_id, str node_name) |
| str | __repr__ (self) |
Public Attributes | |
| layer_node_list | |
| Public Attributes inherited from LayerNode | |
| type | |
| equation | |
| layer_dim_sizes | |
| operand_precision | |
| dimension_relations | |
| padding | |
| constant_operands | |
| input_operand_source | |
| spatial_mapping | |
| spatial_mapping_hint | |
| memory_operand_links | |
| temporal_ordering | |
| layer_operands | |
| output_operand | |
| input_operands | |
| layer_dims | |
| pr_scaling_factors | |
| pr_layer_dim_sizes | |
| loop_relevancy_info | |
| pr_decoupled_relevancy_info | |
| total_mac_count | |
| operand_size_bit | |
| operand_data_reuse | |
| Public Attributes inherited from LayerNodeABC | |
| id | |
| name | |
Additional Inherited Members | |
| Static Public Member Functions inherited from LayerNode | |
| def | calc_pr_dimension_size (int sa, int a, int sb, int b) |
| Calculates the number of unique indices c generated by iterating through the indices a in range(0,A,1) and b in range(0,B,1) according to the equation c = sa * a + sb * b. More... | |
Detailed Description
Extends the ABC for workloads.
For user-defined workloads (from yaml), the DummyNodes are not saved so this class only holds (non-dummy) LayerNodes
Constructor & Destructor Documentation
◆ __init__()
| def __init__ | ( | self, | |
| list[LayerNode] | nodes, | ||
| **Any | attr | ||
| ) |
- Returns
- (self): Directed Graph with nodes the layers and edges the connections between layers.
Member Function Documentation
◆ get_copy_no_dummy()
| "DNNWorkload" get_copy_no_dummy | ( | self | ) |
Return a copy.
DNNWorkloads don't contain DummyNodes in the first place.
Member Data Documentation
◆ layer_node_list
| layer_node_list |
The documentation for this class was generated from the following file:
- /home/runner/work/zigzag/zigzag/zigzag/workload/dnn_workload.py
