376 lines
16 KiB
Python
376 lines
16 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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from argparse import Namespace
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from copy import deepcopy
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import networkx as nx
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from extensions.ops.parameter import Parameter
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from mo.front.common.partial_infer.utils import int64_array
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from mo.graph.graph import Node, Graph
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from mo.middle.pattern_match import all_edges_in_nodes
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from mo.ops.const import Const
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from mo.utils.error import Error
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def not_all_new(old_elements: list, new_elements: list):
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"""
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This function check whether at least one element from new_elements are in old_elements.
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"""
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return any([element in old_elements for element in new_elements])
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def check_and_update_ports(node, edges_data: list, in_port: bool = True):
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key = 'in' if in_port else 'out'
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key_in_edges = [key in edge_data for edge_data in edges_data]
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if all(key_in_edges):
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ports = [edge_data[key] for edge_data in edges_data]
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if len(ports) != len(set(ports)):
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raise Error("Please, provide unique {} ports for nodes".format(key))
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elif not any(key_in_edges):
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if node.has_valid('kind') and node.kind == 'data':
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return
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for i, edge_data in enumerate(edges_data):
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edge_data[key] = i
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else:
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raise Error("Please, provide all {} ports for nodes".format(key))
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def build_graph_with_attrs(nodes_with_attrs: list, edges_with_attrs: list, new_nodes_with_attrs: list = [],
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new_edges_with_attrs: list = [], update_edge_attrs: dict = None,
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update_nodes_attributes: dict = None, nodes_with_edges_only: bool = False,
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add_nodes_from_edges: bool = False):
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"""
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Build the Graph with specific nodes and edges. Also update of edge and node parameters is supported.
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:param nodes_with_attrs: list of tuples ('node_name', {node_attrs})
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:param edges_with_attrs: list of tuples like (start node, end node, (optional) {attrs of the edge}).
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:param new_nodes_with_attrs: analogically nodes_with_attrs
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:param new_edges_with_attrs: analogically new_edges
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:param update_edge_attrs: optional dictionary like {('from_node', 'to_node', key): {edge_attrs}}.
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:param update_nodes_attributes: optional dictionary which specifies nodes names and their attributes to be updated. The
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key is a node name to update attribute and the value is a dictionary with attribute name and its value.
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:param nodes_with_edges_only: add nodes which has at least one incoming or outcoming edge.
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:param add_nodes_from_edges: whether nodes that is not listed in all_nodes but are in all_edges is allowed.
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:return: generated graph.
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"""
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if not_all_new([node[0] for node in nodes_with_attrs], [node[0] for node in new_nodes_with_attrs]):
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raise Error('Some nodes from new_nodes_with_attrs are already in nodes.'
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' Please, add to new_nodes_with_attrs only NEW nodes.')
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if not_all_new([(edge[0], edge[1]) for edge in edges_with_attrs],
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[(edge[0], edge[1]) for edge in new_edges_with_attrs]):
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raise Error('Some edges from new_edges_with_attrs are already in edges.'
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' Please, add to new_edges_with_attrs only NEW edges.')
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# Check that all nodes from list of edges are in nodes
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all_nodes = nodes_with_attrs + new_nodes_with_attrs
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all_edges = edges_with_attrs + new_edges_with_attrs
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all_nodes_names = [node[0] for node in all_nodes]
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if not add_nodes_from_edges and not all_edges_in_nodes(nodes=all_nodes_names, edges=all_edges):
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raise Error("Some nodes from list of edges is not in nodes. Please, add all necessary nodes.")
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graph = Graph()
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# Create dict for nodes with attrs
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nodes_attrs = {}
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for node_name, attrs in all_nodes:
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nodes_attrs[node_name] = attrs
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if 'name' not in attrs:
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attrs['name'] = node_name
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if nodes_with_edges_only:
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# filter nodes to keep only ones with edges connected
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filtered_nodes = {}
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for edge in all_edges:
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node_1, node_2 = edge[0], edge[1]
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filtered_nodes[node_1] = nodes_attrs[node_1]
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filtered_nodes[node_2] = nodes_attrs[node_2]
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nodes_attrs = filtered_nodes
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# Create all nodes
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for node, attrs in nodes_attrs.items():
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graph.add_node(node, **deepcopy(attrs))
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# Connect nodes with edges (also unpack edge params)
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for edge in all_edges:
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node_1, node_2 = edge[0], edge[1]
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edge_attrs = edge[2] if len(edge) == 3 else {}
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graph.add_edge(node_1, node_2, **edge_attrs)
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# Update attributes of edges
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if update_edge_attrs:
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# it will work in 2.x networkx only
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for edge, attr in update_edge_attrs.items():
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for k, v in attr.items():
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nx.set_edge_attributes(G=graph, name=k, values={edge: v})
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# Update attributes of nodes
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if update_nodes_attributes is not None:
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for node_name, new_attrs in update_nodes_attributes:
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assert (node_name in graph.nodes())
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for attr, value in new_attrs.items():
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graph.node[node_name][attr] = value
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for node_id in graph.nodes():
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node = Node(graph, node_id)
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check_and_update_ports(node, [graph.get_edge_data(edge[0], node_id)[0] for edge in graph.in_edges(node_id)],
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True)
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check_and_update_ports(node, [graph.get_edge_data(node_id, edge[1])[0] for edge in graph.out_edges(node_id)],
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False)
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for node in graph.get_op_nodes():
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# Add in_ports attribute
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in_edges = node.in_edges()
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for i in range(len(in_edges)):
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node.add_input_port(idx=i)
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# Add out_ports attribute
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out_edges = node.out_edges()
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for i in range(len(out_edges)):
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node.add_output_port(idx=i)
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return graph
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def build_graph(nodes_attrs: dict, edges: list, update_attributes: dict = None, nodes_with_edges_only: bool = False,
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cli: Namespace = Namespace(static_shape=False, data_type='FP32')):
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"""
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Build the Graph with specific nodes and edges.
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:param nodes_attrs: dictionary where key is the node name and the value is the dictionary with node attributes.
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:param edges: list of pairs with start and end node names of the edge.
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:param update_attributes: optional dictionary which specifies nodes names and their attributes to be updated. The
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key is a node name to update attribute and the value is a dictionary with attribute name and its value.
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:param nodes_with_edges_only: add nodes which has at least one incoming or outcoming edge.
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:param cli: Namespace with cli keys to associate with the graph
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:return: generated graph.
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"""
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graph = Graph()
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for node_name, attrs in nodes_attrs.items():
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if 'name' not in attrs:
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attrs['name'] = node_name
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if nodes_with_edges_only:
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# filter nodes to keep only ones with edges connected
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filtered_nodes = {}
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for item in edges:
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if len(item) == 2: # TODO: is there any better way in python to do that?
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node1, node2 = item
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else:
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node1, node2, _ = item
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filtered_nodes[node1] = nodes_attrs[node1]
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filtered_nodes[node2] = nodes_attrs[node2]
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nodes_attrs = filtered_nodes
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# create all nodes first
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for node, attrs in nodes_attrs.items():
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assert node not in graph.nodes()
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graph.add_node(node, **deepcopy(attrs))
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# connect nodes with edges
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for item in edges:
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if len(item) == 2: # TODO: is there any better way in python to do that?
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node_1, node_2 = item
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edge_attrs = {}
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else:
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node_1, node_2, edge_attrs = item
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common_attrs = {'in': len(graph.in_edges(node_2)),
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'out': len(graph.out_edges(node_1)),
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'name': nodes_attrs[node_1]['name']}
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common_attrs.update(edge_attrs)
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graph.add_edge(node_1, node_2, **common_attrs)
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if update_attributes is not None:
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for node_name, new_attrs in update_attributes.items():
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assert (node_name in graph.nodes()), 'Node with name "{}" is not in the graph'.format(node_name)
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for attr, value in new_attrs.items():
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graph.node[node_name][attr] = value
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for node in graph.get_op_nodes():
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# Add in_ports attribute
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in_edges = node.in_edges()
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for attr in in_edges.values():
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node.add_input_port(idx=attr['in'])
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# Add out_ports attribute
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out_edges = node.out_edges()
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for attr in out_edges.values():
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node.add_output_port(idx=attr['out'])
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graph.graph['cmd_params'] = cli
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return graph
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def build_graph_with_edge_attrs(nodes_attrs: dict, edges: list, update_attributes: dict = None,
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cli: Namespace = Namespace(static_shape=False, data_type='FP32')):
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"""
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Build the Graph with specific nodes and edges.
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:param nodes_attrs: dictionary where key is the node name and the value is the dictionary with node attributes.
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:param edges: list of pairs with start and end node names of the edge.
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:param update_attributes: optional dictionary which specifies nodes names and their attributes to be updated. The
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key is a node name to update attribute and the value is a dictionary with attribute name and its value.
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:param cli: Namespace with cli keys to associate with the graph
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:return: generated graph.
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"""
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graph = Graph()
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for node_1, node_2, attr in edges:
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if node_1 not in graph.nodes():
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graph.add_node(node_1, **deepcopy(nodes_attrs[node_1]))
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if node_2 not in graph.nodes():
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graph.add_node(node_2, **deepcopy(nodes_attrs[node_2]))
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graph.add_edge(node_1, node_2, **attr)
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if update_attributes is not None:
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for node_name, new_attrs in update_attributes.items():
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assert (node_name in graph.nodes())
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for attr, value in new_attrs.items():
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graph.node[node_name][attr] = value
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for node in graph.get_op_nodes():
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# Add in_ports attribute
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in_edges = node.in_edges()
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for attr in in_edges.values():
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node.add_input_port(idx=attr['in'])
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# Add out_ports attribute
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out_edges = node.out_edges()
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for attr in out_edges.values():
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node.add_output_port(idx=attr['out'])
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graph.graph['cmd_params'] = cli
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return graph
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class FakeAttr:
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def __init__(self, **kwargs):
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self.__dict__.update(kwargs)
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def __setitem__(self, key, value):
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setattr(self, key, value)
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def __getitem__(self, item):
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return getattr(self, item)
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class FakeNode:
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def __init__(self, pl, ml):
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self.pb = pl
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self.model_pb = ml
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self.graph = FakeAttr()
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self.graph.graph = {}
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self.update_node = lambda: None
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def __setitem__(self, key, value):
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setattr(self, key, value)
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def __getitem__(self, item):
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return getattr(self, item)
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# regular units
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regular_op = lambda name, kwargs: {name: {'kind': 'op', 'type': 'NoType', **kwargs}}
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valued_data = lambda name, value: {name: {'kind': 'data', 'value': value,
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'shape': int64_array(value.shape) if value is not None else None}}
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shaped_data = lambda name, shape: {name: {'kind': 'data', 'value': None,
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'shape': int64_array(shape) if shape is not None else None}}
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empty_data = lambda name: valued_data(name, None)
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shaped_parameter = lambda name, shape, kwargs={}: {**regular_op(name, {'op': 'Parameter', 'type': 'Parameter',
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'shape': shape, 'infer': Parameter.infer,
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**kwargs}),
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**shaped_data(name + '_d', shape)}
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result = lambda name='output': {name: {'kind': 'op', 'type': 'Result', 'op': 'Result', 'infer': lambda x: 0}}
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regular_op_with_shaped_data = lambda name, shape, kwargs: {**regular_op(name, kwargs),
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**shaped_data(name + '_d', shape)}
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regular_op_with_empty_data = lambda name, kwargs: {**regular_op(name, kwargs), **empty_data(name + '_d')}
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# constants
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const = lambda name, value, kwargs={}: {name: {'kind': 'op', 'type': 'Const', 'op': 'Const',
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'value': value, 'shape': int64_array(value.shape),
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'infer': Const.infer, 'type_infer': Const.type_infer, **kwargs}}
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fake_const = lambda name, shape, kwargs={}: {name: {'kind': 'op', 'op': 'Const', 'type': 'Const',
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'value': None, 'infer': Const.infer, **kwargs,
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'shape': int64_array(shape) if shape is not None else None}}
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shaped_const_with_data = lambda name, shape, kwargs={}: {**fake_const(name, shape, kwargs),
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**shaped_data(name + '_d', shape)}
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valued_const_with_data = lambda name, value, kwargs={}: {**const(name, value, kwargs),
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**valued_data(name + '_d', value)}
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def extract_port_from_string(node_name: str):
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"""
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Extracts port and node name from string
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Raises if node name was not provided in the expected format:
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NODE:OUT_PORT
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or
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IN_PORT:NODE
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:param node_name: string value provided by user
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:return: node name, input port and output port
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"""
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parts = node_name.split(':')
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if len(parts) > 2:
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raise Error("Please provide only one port number for {}. Expected format is NODE:OUT_PORT or IN_PORT:NODE, "
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"where IN_PORT and OUTPUT_PORT are integers".format(node_name))
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if len(parts) == 1:
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return node_name, None, None
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else:
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in_port, out_port, name = None, None, None
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try:
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in_port, name = int(parts[0]), parts[1]
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except ValueError:
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try:
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out_port, name = int(parts[1]), parts[0]
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except ValueError:
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raise Error("Non integer port number in {}. Expected format is NODE:OUT_PORT or IN_PORT:NODE, where "
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"IN_PORT and OUTPUT_PORT are integers".format(node_name))
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return name, in_port, out_port
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def get_name_and_port(tensor_name):
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node_name, in_port, out_port = extract_port_from_string(tensor_name)
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assert in_port is None or out_port is None
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if in_port is not None:
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return node_name, in_port
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elif out_port is not None:
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return node_name, out_port
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else:
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return node_name, 0
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def connect(first_tensor_name, second_tensor_name, skip_data=False, front_phase=False):
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# ports could be skipped -- then zero in/out ports would be used
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# first_tensor_name = first_op_name:out_port
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# second_tensor_name = in_port:second_op_name
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# if skip_data is True connect directly from data node with postfix '_d' to second
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# if front_phase is True connect nodes directly without postfixes and data nodes
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first_op_name, out_port = get_name_and_port(first_tensor_name)
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second_op_name, in_port = get_name_and_port(second_tensor_name)
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if skip_data:
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return [(first_op_name + '_d', second_op_name, {'out': out_port, 'in': in_port})]
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if front_phase:
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return [(first_op_name, second_op_name, {'out': out_port, 'in': in_port})]
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return [
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(first_op_name, first_op_name + '_d', {'out': out_port}),
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(first_op_name + '_d', second_op_name, {'in': in_port}),
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]
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def connect_data(first_tensor_name, second_tensor_name):
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return connect(first_tensor_name, second_tensor_name, skip_data=True)
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def connect_front(first_tensor_name, second_tensor_name):
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return connect(first_tensor_name, second_tensor_name, skip_data=False, front_phase=True)
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