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Commit 19398e4a authored by Iryna de Albuquerque Silva's avatar Iryna de Albuquerque Silva
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Replaced local function for topological ordering by new GraphView's get_ordered_nodes() method

parent c6654d1e
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3 merge requests!279v0.4.0,!253v0.4.0,!211Add show_graphview funcionality.
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aidge_core/show_graphview.py
+ 15
− 77
View file @ 19398e4a
......@@ -4,73 +4,11 @@ import builtins
import aidge_core
import numpy as np
def dfs(graph : aidge_core.GraphView, node : aidge_core.Node, visited_nodes : list[aidge_core.Node], sorted_nodes : list[aidge_core.Node]) -> None:
"""
Performs the depth-first search algorithm for topological sorting.
:param graph: An unsorted GraphView of Aidge.
:type graph: aidge_core.GraphView
:param node: The GraphView's Node that is being treated.
:type node: aidge_core.Node
:param visited_nodes: List of nodes that have already been visited.
:type visited_nodes: list[aidge_core.Node]
:param sorted_nodes: List of nodes that have already been sorted.
:type sorted_nodes: list[aidge_core.Node]
"""
node_children = node.get_children()
visited_nodes.add(node)
for child in node_children:
if child not in visited_nodes:
dfs(graph, child, visited_nodes, sorted_nodes)
sorted_nodes.append(node)
# Make sure Producers are treated:
parents = []
for parent in node.get_parents():
try:
has_parents = parent.get_parents()
except AttributeError:
has_parents = False
if (not has_parents) and (parent not in sorted_nodes):
parents.append(parent)
parents.reverse()
sorted_nodes.extend(parents)
return None
def topological_sort(graph : aidge_core.GraphView) -> list[aidge_core.Node]:
"""
Performs topological sorting by applying depth-first search algorithm recursively.
:param graph: An unsorted GraphView of Aidge.
:type graph: aidge_core.GraphView
:return: A list with the GraphView's sorted nodes.
:rtype: list[aidge_core.Node]
"""
input_nodes = graph.get_input_nodes()
visited_nodes = set()
sorted_nodes = []
for input in input_nodes:
if input not in visited_nodes:
dfs(input_nodes, input, visited_nodes, sorted_nodes)
sorted_nodes.reverse()
return sorted_nodes
def retrieve_operator_attrs(node : aidge_core.Node) -> dict[str, int, float, bool, None]:
def _retrieve_operator_attrs(node : aidge_core.Node) -> dict[str, int, float, bool, None]:
"""
Returns the dictionary containing the attributes of a given Node.
:param graph: A Node in the list of sorted nodes.
:param graph: A Node in the list of ordered nodes.
:type graph: aidge_core.Node
:return: A dictionary with the Node's attributes.
:rtype: dict[str, int, float, bool, None]
......@@ -86,11 +24,11 @@ def retrieve_operator_attrs(node : aidge_core.Node) -> dict[str, int, float, boo
return node_attr_dict
def create_dict(sorted_nodes : list[aidge_core.Node], write_trainable_params_ext : bool, write_trainable_params_embed : bool, params_file_format : str, path_trainable_params : str) -> dict[str, int, float, bool, None]:
def _create_dict(ordered_nodes : list[aidge_core.Node], write_trainable_params_ext : bool, write_trainable_params_embed : bool, params_file_format : str, path_trainable_params : str) -> dict[str, int, float, bool, None]:
"""
Creates a dictionary to store the information of a given sorted GraphView.
Creates a dictionary to store the information of a given ordered GraphView.
:param sorted_nodes: A list with the GraphView's sorted nodes.
:param ordered_nodes: A list with the GraphView's ordered nodes.
:type graph: list
:param write_trainable_params_ext: Whether or not to write the eventual trainable parameters of the Nodes in an external file.
:type write_trainable_params_ext: bool
......@@ -107,7 +45,7 @@ def create_dict(sorted_nodes : list[aidge_core.Node], write_trainable_params_ext
graphview_dict = {'graph': []}
for node in sorted_nodes:
for node in ordered_nodes:
if node is not None:
node_dict = {'name' : node.name(),
......@@ -171,12 +109,12 @@ def create_dict(sorted_nodes : list[aidge_core.Node], write_trainable_params_ext
micro_node_dict = {'name' : micro_node.name(),
'optype' : micro_node.type()}
micro_node_attr_dict = retrieve_operator_attrs(micro_node)
micro_node_attr_dict = _retrieve_operator_attrs(micro_node)
micro_node_dict['attributes'] = micro_node_attr_dict
attributes_dict['micro_graph'].append(micro_node_dict)
else:
node_attr_dict = retrieve_operator_attrs(node)
node_attr_dict = _retrieve_operator_attrs(node)
attributes_dict.update(node_attr_dict)
node_dict['attributes'] = attributes_dict
......@@ -215,7 +153,7 @@ def create_dict(sorted_nodes : list[aidge_core.Node], write_trainable_params_ext
return graphview_dict
def write_dict_json(graphview_dict : dict[str, int, float, bool, None], json_path : str) -> None:
def _write_dict_json(graphview_dict : dict[str, int, float, bool, None], json_path : str) -> None:
"""
Writes dictionary containing GraphView description to a JSON file.
......@@ -255,13 +193,13 @@ def gview_to_json(gview : aidge_core.GraphView, json_path : str, write_trainable
else:
path_trainable_params = ''
# Sort graphview
sorted_nodes = topological_sort(gview)
# Sort GraphView in topological order
ordered_nodes = gview.get_ordered_nodes()
# Create dict from graphview
graphview_dict = create_dict(sorted_nodes, write_trainable_params_ext, write_trainable_params_embed, params_file_format, path_trainable_params)
# Create dict from GraphView
graphview_dict = _create_dict(ordered_nodes, write_trainable_params_ext, write_trainable_params_embed, params_file_format, path_trainable_params)
# Write dict to json
write_dict_json(graphview_dict, json_path)
# Write dict to JSON
_write_dict_json(graphview_dict, json_path)
return None
\ No newline at end of file
aidge_core/unit_tests/test_show_graphview.py
+ 48
− 52
View file @ 19398e4a
......@@ -50,7 +50,7 @@ def create_gview():
return gview
class test_show_gview(unittest.TestCase):
"""Test aidge show GraphView
"""Test aidge functionality to show GraphView.
"""
def setUp(self):
......@@ -59,9 +59,8 @@ class test_show_gview(unittest.TestCase):
def tearDown(self):
pass
def test_model_to_json(self):
def test_gview_to_json(self):
gview = create_gview()
# Create temporary file to store JSON model description
......@@ -74,58 +73,55 @@ class test_show_gview(unittest.TestCase):
model_json = json.load(fp)
# Get list of nodes of Aidge graphview
gview_ranked_nodes = gview.get_ranked_nodes()[0]
# Iterate over ranked_nodes
gview_ordered_nodes = gview.get_ordered_nodes()
self.assertEqual(len(gview_ranked_nodes), len(model_json['graph']))
# Iterate over the list of ordered nodes and the corresponding JSON
self.assertEqual(len(gview_ordered_nodes), len(model_json['graph']))
for node_gview in gview_ranked_nodes:
for node_json in model_json['graph']:
if node_gview.name() == node_json['name']:
for node_gview, node_json in zip(gview_ordered_nodes, model_json['graph']):
self.assertEqual(node_gview.get_operator().type(), node_json['optype'])
self.assertEqual(node_gview.get_operator().nb_inputs(), node_json['nb_inputs'])
self.assertEqual(node_gview.get_operator().nb_outputs(), node_json['nb_outputs'])
self.assertEqual(node_gview.get_operator().nb_inputs(), len(node_json['inputs']))
for input_idx in range(node_gview.get_operator().nb_inputs()):
self.assertEqual(node_gview.get_operator().get_input(input_idx).dims(), node_json['inputs'][input_idx]['dims'])
self.assertEqual(str(node_gview.get_operator().get_input(input_idx).dtype()), node_json['inputs'][input_idx]['data_type'])
self.assertEqual(str(node_gview.get_operator().get_input(input_idx).dformat()), node_json['inputs'][input_idx]['data_format'])
self.assertEqual(node_gview.get_operator().nb_outputs(), len(node_json['outputs']))
for output_idx in range(node_gview.get_operator().nb_outputs()):
self.assertEqual(node_gview.get_operator().get_output(output_idx).dims(), node_json['outputs'][output_idx]['dims'])
self.assertEqual(str(node_gview.get_operator().get_output(output_idx).dtype()), node_json['outputs'][output_idx]['data_type'])
self.assertEqual(str(node_gview.get_operator().get_output(output_idx).dformat()), node_json['outputs'][output_idx]['data_format'])
self.assertEqual(len(node_gview.get_parents()), len(node_json['parents']))
self.assertEqual(len(node_gview.get_children()), len(node_json['children']))
if not hasattr(node_gview.get_operator(), 'get_micro_graph'):
try:
self.assertEqual(len(node_gview.get_operator().attr.dict()), len(node_json['attributes']))
self.assertDictEqual(node_gview.get_operator().attr.dict(), node_json['attributes'])
except AttributeError:
self.assertIsNone(node_gview.get_operator().attr) and self.assertFalse(node_json['attributes'])
elif hasattr(node_gview.get_operator(), 'get_micro_graph'):
self.assertEqual(len(node_gview.get_operator().get_micro_graph().get_nodes()), len(node_json['attributes']['micro_graph']))
for micro_node_gview in node_gview.get_operator().get_micro_graph().get_nodes():
for micro_node_json in node_json['attributes']['micro_graph']:
if micro_node_gview.get_operator().type() == micro_node_json['optype']:
for key, value in micro_node_gview.get_operator().attr.dict().items():
if not type(value).__name__ in dir(builtins):
# Replace original value by its name (str) because value is of a type that could not be written to the JSON
# Cannot update this dict inplace : micro_node_gview.get_operator().attr.dict().update({key : value.name})
temp_mnode_dict = micro_node_gview.get_operator().attr.dict()
temp_mnode_dict.update({key : value.name})
self.assertDictEqual(temp_mnode_dict, micro_node_json['attributes'])
self.assertEqual(node_gview.get_operator().type(), node_json['optype'])
self.assertEqual(node_gview.get_operator().nb_inputs(), node_json['nb_inputs'])
self.assertEqual(node_gview.get_operator().nb_outputs(), node_json['nb_outputs'])
self.assertEqual(node_gview.get_operator().nb_inputs(), len(node_json['inputs']))
for input_idx in range(node_gview.get_operator().nb_inputs()):
self.assertEqual(node_gview.get_operator().get_input(input_idx).dims(), node_json['inputs'][input_idx]['dims'])
self.assertEqual(str(node_gview.get_operator().get_input(input_idx).dtype()), node_json['inputs'][input_idx]['data_type'])
self.assertEqual(str(node_gview.get_operator().get_input(input_idx).dformat()), node_json['inputs'][input_idx]['data_format'])
self.assertEqual(node_gview.get_operator().nb_outputs(), len(node_json['outputs']))
for output_idx in range(node_gview.get_operator().nb_outputs()):
self.assertEqual(node_gview.get_operator().get_output(output_idx).dims(), node_json['outputs'][output_idx]['dims'])
self.assertEqual(str(node_gview.get_operator().get_output(output_idx).dtype()), node_json['outputs'][output_idx]['data_type'])
self.assertEqual(str(node_gview.get_operator().get_output(output_idx).dformat()), node_json['outputs'][output_idx]['data_format'])
self.assertEqual(len(node_gview.get_parents()), len(node_json['parents']))
self.assertEqual(len(node_gview.get_children()), len(node_json['children']))
if not hasattr(node_gview.get_operator(), 'get_micro_graph'):
try:
self.assertEqual(len(node_gview.get_operator().attr.dict()), len(node_json['attributes']))
self.assertDictEqual(node_gview.get_operator().attr.dict(), node_json['attributes'])
except AttributeError:
self.assertIsNone(node_gview.get_operator().attr) and self.assertFalse(node_json['attributes'])
elif hasattr(node_gview.get_operator(), 'get_micro_graph'):
self.assertEqual(len(node_gview.get_operator().get_micro_graph().get_nodes()), len(node_json['attributes']['micro_graph']))
for micro_node_gview in node_gview.get_operator().get_micro_graph().get_nodes():
for micro_node_json in node_json['attributes']['micro_graph']:
if micro_node_gview.get_operator().type() == micro_node_json['optype']:
for key, value in micro_node_gview.get_operator().attr.dict().items():
if not type(value).__name__ in dir(builtins):
# Replace original value by its name (str) because value is of a type that could not be written to the JSON
# Cannot update this dict inplace : micro_node_gview.get_operator().attr.dict().update({key : value.name})
temp_mnode_dict = micro_node_gview.get_operator().attr.dict()
temp_mnode_dict.update({key : value.name})
self.assertDictEqual(temp_mnode_dict, micro_node_json['attributes'])
if __name__ == '__main__':
unittest.main()
......
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