Fix of groupconv_to_conv() in MO IR reader (#17118)
* Fixed bug in groupconv_to_conv() method. * Small correction. * Test correction.
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Anastasiia Pnevskaia
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GitHub
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269ed1d9cc
@@ -8,7 +8,7 @@ import numpy as np
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from openvino.tools.mo.back.MaxPool import MaxPool
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from openvino.tools.mo.back.TopKNormalizer import TopKNormalizer
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from openvino.tools.mo.front.common.partial_infer.utils import int64_array
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from openvino.tools.mo.front.common.partial_infer.utils import int64_array, strict_compare_tensors
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from openvino.tools.mo.graph.graph import Graph, Node
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from openvino.tools.mo.ops.Cast import Cast
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from openvino.tools.mo.ops.GRU import GRU
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@@ -197,12 +197,13 @@ def groupconv_to_conv(op: Node):
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weights_node.value = np.reshape(weights_node.value, new_shape)
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elif weights_node.type == 'Reshape':
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# We remove reshape node added in ConvolutionWithGroupsResolver pass
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assert weights_node.in_port(0).get_source().data.get_shape() == new_shape, \
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assert strict_compare_tensors(weights_node.in_port(0).get_source().data.get_shape(), new_shape), \
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'Weight shape and calculated shape mismatch in GroupConv node {}.'.format(op.name)
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op.in_port(1).disconnect()
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# We use add_destination method here to support case with multiple destinations of source port
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weights_node.in_port(0).get_source().get_connection().add_destination(op.in_port(1))
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weights_node.in_port(0).disconnect()
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op.graph.remove_node(weights_node.id)
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elif weights_node.type == 'Convert' and weights_node.destination_type == 'f32'\
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and weights_node.in_port(0).get_source().node.type == 'Const':
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# Support new FP16 IRs
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@@ -212,7 +213,7 @@ def groupconv_to_conv(op: Node):
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const_node.value = np.reshape(const_node.value, new_shape)
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else:
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assert op.in_port(1).get_source().data.get_shape() == new_shape, \
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assert strict_compare_tensors(op.in_port(1).get_source().data.get_shape(), op.in_port(1).get_source().data.get_shape()), \
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'Weight shape and calculated shape mismatch in GroupConv node {}.'.format(op.name)
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# We need to set this attrs for correct shape infer as convolution
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op['group'] = group
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@@ -6,85 +6,63 @@ import unittest
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import numpy as np
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from generator import generator, generate
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import openvino.tools.mo.graph.graph
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from openvino.tools.mo.graph.graph import Node
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from openvino.tools.mo.utils.ir_engine.compare_graphs import compare_graphs
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from openvino.tools.mo.utils.ir_reader.internal_ops.squeeze import SqueezeInternal
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from openvino.tools.mo.utils.ir_reader.internal_ops.unsqueeze import UnsqueezeInternal
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from openvino.tools.mo.utils.ir_reader.layer_to_class import groupconv_to_conv, restore_tensor_names
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from unit_tests.utils.graph import build_graph
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from unit_tests.utils.graph import connect_data,shaped_parameter, regular_op_with_shaped_data, connect, valued_const_with_data, shaped_const_with_data, result
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from openvino.tools.mo.ops.op import Op
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@generator
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class TestFunction(unittest.TestCase):
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@generate(*[([1, 32, 112, 112], [32, 1, 1, 3], [32, 1, 1, 1, 3], 32),
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([1, 32, 112, 112], [32, 1, 1, 1, 3], None, 32),
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])
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def test_groupconv_to_conv(self, shape, weights_shape, reshape_shape, group):
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weights_const = np.random.randn(*weights_shape).astype(np.float32)
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nodes_attributes = {
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'input': {'kind': 'op', 'type': 'Parameter'},
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'input_data': {'shape': shape, 'kind': 'data'},
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'group_conv': {'kind': 'op', 'type': 'GroupConvolution'},
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'group_conv_data': {'shape': shape, 'kind': 'data'},
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'conv': {'kind': 'op', 'type': 'Convolution', 'group': group},
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'conv_data': {'shape': shape, 'kind': 'data'},
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'weights': {'kind': 'op', 'type': 'Const', 'value': weights_const},
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'weights_data': {'shape': weights_shape, 'kind': 'data'},
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'reshape': {'kind': 'op', 'type': 'Reshape'},
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'reshape_data': {'shape': reshape_shape, 'kind': 'data'},
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'reshape_const': {'kind': 'op', 'type': 'Const'},
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'reshape_const_data': {'shape': len(reshape_shape) if reshape_shape is not None else None, 'kind': 'data'},
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'add': {'kind': 'op', 'type': 'Add'},
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'add_data': {'shape': shape, 'kind': 'data'},
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'add_const': {'kind': 'op', 'type': 'Const'},
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'add_const_data': {'shape': [1, 32, 1, 1], 'kind': 'data'},
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'result': {'kind': 'op', 'type': 'Result'}
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**shaped_parameter('input', shape),
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**regular_op_with_shaped_data('group_conv', shape, {'type': 'GroupConvolution'}),
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**regular_op_with_shaped_data('conv', shape, {'type': 'Convolution'}),
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**valued_const_with_data('weights', weights_const, weights_shape, {'type': 'Const'}),
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**regular_op_with_shaped_data('reshape', reshape_shape, {'type': 'Reshape'}),
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**shaped_const_with_data('reshape_const', len(reshape_shape) if reshape_shape is not None else None, {'type': 'Const'}),
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**regular_op_with_shaped_data('add', shape, {'type': 'Add'}),
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**shaped_const_with_data('add_const', [1, 32, 1, 1], {'type': 'Const'}),
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**result("result")
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}
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edges = [('input', 'input_data'),
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('input_data', 'group_conv'),
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('weights', 'weights_data'),
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('group_conv', 'group_conv_data'),
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('group_conv_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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edges = [*connect('input:0', 'group_conv:0'),
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*connect('group_conv:0', 'add:0'),
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*connect('add_const:0', 'add:1'),
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*connect('add:0', 'result:0'),
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]
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if reshape_shape is not None:
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edges += [('weights_data', 'reshape'),
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('reshape_const', 'reshape_const_data'),
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('reshape_const_data', 'reshape'),
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('reshape', 'reshape_data'),
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('reshape_data', 'group_conv')]
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edges += [*connect('weights:0', 'reshape:0'),
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*connect('reshape_const:0', 'reshape:1'),
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*connect('reshape:0', 'group_conv:1')]
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else:
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edges.append(('weights_data', 'group_conv'))
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edges += [*connect('weights:0', 'group_conv:1')]
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graph = build_graph(nodes_attributes, edges, nodes_with_edges_only=True)
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graph = build_graph(nodes_attributes, edges)
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reshape_node = None
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if reshape_shape is None:
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reshape_node = Node(graph, 'reshape')
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graph_ref = build_graph(nodes_attributes,
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[('input', 'input_data'),
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('input_data', 'conv'),
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('weights', 'weights_data'),
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('weights_data', 'conv'),
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('conv', 'conv_data'),
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('conv_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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], nodes_with_edges_only=True)
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[*connect('input:0', 'conv:0'),
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*connect('weights:0', 'conv:1'),
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*connect('conv:0', 'add:0'),
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*connect('add_const:0', 'add:1'),
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*connect('add:0', 'result:0'),
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])
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for op in graph.get_op_nodes(type='GroupConvolution'):
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groupconv_to_conv(op)
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@@ -94,6 +72,8 @@ class TestFunction(unittest.TestCase):
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node = Node(graph_ref, 'weights')
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node.value = weights_const
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assert len(reshape_node.in_nodes()) == 0 and len(reshape_node.out_nodes()) == 0
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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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