Tensor names support in MO IR Reader (#4194)
* Added attributes save modes * Added tensor names to IR * Reformat code * Add support for tensor names in MO IR Reader * Unit tests and code refactoring * Fixed error * Code refactoring * Code refactoring * Code refactoring * Error fixed * Error fixed * Bug fixed * Bug fixed * Additional unit tests and comments * Small update * Update fake infer function * Update names restoring * optimize imports * Add support for old-style constants and for commas in reader * Added dest mode in Fuse Mul * Update default values * Fix missed debug info in some specific cases * Fix a lot of issues with missedand wrong names provoding * Resolve review comments * Update test IR's * Refactor and simplify code * More simplification * Remove unneccessary changes * model-optimizer/mo/utils/ir_reader/layer_to_class_test.py * Add separate tests for names restoring * Update copyright year * Apply review comments Co-authored-by: Anastasia Popova <anastasia.popova@intel.com>
This commit is contained in:
Anton Chetverikov
GitHub
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1bfe79cf48
commit
2c4afd8cd4
@ -1,5 +1,5 @@
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"""
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Copyright (C) 2018-2020 Intel Corporation
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Copyright (C) 2018-2021 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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@ -123,7 +123,7 @@ class IREngine(object):
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data_nodes = {}
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for port in self.graph.node[node]['ports']:
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data = self.graph.unique_id(prefix='data_')
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self.graph.add_node(data, **{'kind': 'data', 'shape': self.graph.node[node]['ports'][port],
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self.graph.add_node(data, **{'kind': 'data', 'shape': self.graph.node[node]['ports'][port][0],
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'value': None})
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self.graph.add_edges_from([(node, data, {'out': port})])
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data_nodes.update({port: data})
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@ -232,7 +232,11 @@ class IREngine(object):
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for dim in port:
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output_shape.append(int(dim.text))
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layer_attrs['ports'].update({port_id: output_shape})
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out_tensor_names = None
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if 'names' in port.attrib:
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out_tensor_names = port.attrib['names']
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layer_attrs['ports'].update({port_id: (output_shape, out_tensor_names)})
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elif attr.tag == 'blobs':
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in_port = inputs_counter
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for blob_attr in attr:
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@ -1,5 +1,5 @@
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"""
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Copyright (C) 2018-2020 Intel Corporation
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Copyright (C) 2018-2021 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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@ -51,5 +51,5 @@ class Extender(object):
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def const_shape_infer(node: Node):
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i = len(node.in_nodes())
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for num in node.out_nodes():
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node.out_node(num).shape = int64_array(node.ports[i])
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node.out_node(num).shape = int64_array(node.ports[i][0])
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i += 1
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@ -1,5 +1,5 @@
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"""
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Copyright (C) 2018-2020 Intel Corporation
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Copyright (C) 2018-2021 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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@ -281,6 +281,35 @@ postprocessing_op_nodes = {
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}
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def restore_tensor_names(op: Node):
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for out_port in op.ports:
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# op.ports is our internal attribute, dictionary, where keys are numbers of output ports
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# and values are tuples with shape and tensor name:
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# {out_port_idx_1: (out_port_idx_1_shape, out_port_idx_1_tensor_name),
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# out_port_idx_2: (out_port_idx_2_shape, out_port_idx_2_tensor_name)}
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out_tensor_names = op.ports[out_port][1]
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# handle Constant operations with old style output port numbering
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if op.soft_get('type') == 'Const':
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assert len(op.ports) == 1, 'Something wrong with Constant node: {}, wrong number ' \
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'of output ports: {}!'.format(op.soft_get('name'), len(op.ports))
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out_port = 0
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out_port = out_port - len(op.in_nodes())
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if out_tensor_names is not None:
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# handle tensor names with commas and add them to dictionary as separate items
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if out_tensor_names.find(',') >= 0:
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str_to_replace = '<comma_in_tensor_name>'
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out_tensor_names = (out_tensor_names.replace('\\,', str_to_replace)).split(',')
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op.out_node(out_port)['fw_tensor_debug_info'] = []
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for out_tensor_name in out_tensor_names:
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out_tensor_name = out_tensor_name.replace(str_to_replace, ',')
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op.out_node(out_port)['fw_tensor_debug_info'].append((out_tensor_name, out_port, out_tensor_name))
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else:
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op.out_node(out_port)['fw_tensor_debug_info'] = [(out_tensor_names, out_port, out_tensor_names)]
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def copy_graph_with_ops(graph: Graph) -> Graph:
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"""
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Function to copy graph and apply extenders to appropriate nodes
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@ -342,6 +371,9 @@ def copy_graph_with_ops(graph: Graph) -> Graph:
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# Nodes postprocessing stage in new graph
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for op in new_graph.get_op_nodes():
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restore_tensor_names(op)
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# operations postprocessing with some special types
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if op.soft_get('type') in postprocessing_op_nodes:
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postprocessing_op_nodes[op.type](op)
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@ -1,5 +1,5 @@
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"""
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Copyright (c) 2018-2020 Intel Corporation
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Copyright (c) 2018-2021 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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@ -21,7 +21,7 @@ from generator import generator, generate
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from mo.graph.graph import Node
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from mo.utils.ir_engine.compare_graphs import compare_graphs
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from mo.utils.ir_reader.layer_to_class import groupconv_to_conv
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from mo.utils.ir_reader.layer_to_class import groupconv_to_conv, restore_tensor_names
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from mo.utils.unittest.graph import build_graph
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@ -107,3 +107,39 @@ class TestFunction(unittest.TestCase):
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(flag, resp) = compare_graphs(graph, graph_ref, 'result', check_op_attrs=True)
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self.assertTrue(flag, resp)
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def test_restore_tensor_names(self):
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shape = [1, 3, 224, 224]
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nodes_attributes = {
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'input': {'kind': 'op', 'type': 'Parameter', 'ports': {0: (shape, 'abc,def')}},
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'input_data': {'shape': shape, 'kind': 'data'},
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'add': {'kind': 'op', 'type': 'Add', 'ports': {2: (shape, 'ghi\,jkl')}},
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'add_data': {'shape': shape, 'kind': 'data'},
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'add_const': {'kind': 'op', 'type': 'Const', 'ports': {0: (shape, 'mno,pqr\,stu')}},
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'add_const_data': {'shape': shape, 'kind': 'data'},
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'result': {'kind': 'op', 'type': 'Result', 'ports': {0: (shape, None)}}
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}
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edges = [('input', 'input_data'),
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('input_data', 'add'),
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('add_const', 'add_const_data'),
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('add_const_data', 'add'),
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('add', 'add_data'),
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('add_data', 'result'),
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]
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graph = build_graph(nodes_attributes, edges, nodes_with_edges_only=True)
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for op in graph.get_op_nodes():
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restore_tensor_names(op)
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node_1 = Node(graph, 'input_data')
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node_2 = Node(graph, 'add_data')
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node_3 = Node(graph, 'add_const_data')
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assert node_1['fw_tensor_debug_info'] == [('abc', 0, 'abc'), ('def', 0, 'def')], 'Restored debug info is wrong!'
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assert node_2['fw_tensor_debug_info'] == [('ghi,jkl', 0, 'ghi,jkl')], 'Restored debug info is wrong!'
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assert node_3['fw_tensor_debug_info'] == [('mno', 0, 'mno'), ('pqr,stu', 0, 'pqr,stu')],\
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'Restored debug info is wrong!'
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