Provide GatherND with original layout for inputs and output (#3002)
* Provide GatherND with original layout for inputs and output Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com> * Fix code review #1 Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
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Roman Kazantsev
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@ -28,6 +28,7 @@ extensions/back/GroupedConvWeightsNormalize.py
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extensions/back/insert_compatibility_l2normalization.py
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extensions/back/insert_compatibility_l2normalization.py
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extensions/back/InterpolateReshape.py
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extensions/back/InterpolateReshape.py
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extensions/back/kaldi_remove_memory_output.py
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extensions/back/kaldi_remove_memory_output.py
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extensions/back/LayoutChangeForGatherND.py
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extensions/back/LeakyReLUMutation.py
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extensions/back/LeakyReLUMutation.py
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extensions/back/LRNToNorm.py
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extensions/back/LRNToNorm.py
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extensions/back/MatMulNormalizer.py
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extensions/back/MatMulNormalizer.py
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61
model-optimizer/extensions/back/LayoutChangeForGatherND.py
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61
model-optimizer/extensions/back/LayoutChangeForGatherND.py
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"""
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Copyright (C) 2018-2020 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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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import numpy as np
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from extensions.ops.transpose import Transpose
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from mo.front.common.partial_infer.utils import int64_array
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from mo.front.tf.graph_utils import create_op_with_const_inputs
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from mo.graph.graph import Graph, Port
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from mo.back.replacement import BackReplacementPattern
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class LayoutChangeForGatherND(BackReplacementPattern):
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"""
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Return original layout for inputs and output of GatherND operation
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since the operation is designed for NHWC layout.
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"""
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enabled = True
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force_shape_inference = True
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graph_condition = [lambda graph: graph.graph['fw'] == 'tf']
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@staticmethod
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def insert_transpose(graph: Graph, input_port: Port, before_input=True):
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input_rank = len(input_port.data.get_shape())
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if input_rank > 3:
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if before_input:
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axis_order = np.concatenate((int64_array([0]),
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int64_array(list(range(2, input_rank))),
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int64_array([1])))
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source_node = input_port.get_source().node
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transpose_name = source_node.soft_get('name', source_node.id) + '/TransposeToNHWC'
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else:
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axis_order = np.concatenate(
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(int64_array([0]),
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int64_array([input_rank - 1]),
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int64_array(list(range(1, input_rank - 1)))))
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transpose_name = input_port.node.soft_get('name', input_port.node.id) + '/TransposeToNCHW'
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input_port.node['need_shape_inference'] = True
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input_port.node['override_output_shape'] = True
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transpose = create_op_with_const_inputs(graph, Transpose, {1: axis_order}, {'name': transpose_name})
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input_port.get_connection().insert_node(transpose)
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transpose['need_shape_inference'] = True
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transpose['override_output_shape'] = True
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def find_and_replace_pattern(self, graph: Graph):
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for gathernd in graph.get_op_nodes(type='GatherND'):
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self.insert_transpose(graph, gathernd.in_port(0), before_input=True)
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self.insert_transpose(graph, gathernd.in_port(1), before_input=True)
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self.insert_transpose(graph, gathernd.out_port(0), before_input=False)
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139
model-optimizer/extensions/back/LayoutChangeForGatherND_test.py
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139
model-optimizer/extensions/back/LayoutChangeForGatherND_test.py
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"""
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Copyright (C) 2020 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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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import unittest
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import numpy as np
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from extensions.back.LayoutChangeForGatherND import LayoutChangeForGatherND
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from mo.front.common.partial_infer.utils import int64_array
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from mo.utils.ir_engine.compare_graphs import compare_graphs
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from mo.utils.unittest.graph import build_graph
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nodes_attributes = {
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'placeholder_1': {'shape': None, 'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
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'placeholder_1_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'placeholder_2': {'shape': None, 'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
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'placeholder_2_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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# GatherND
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'gathernd': {'type': 'GatherND', 'kind': 'op', 'op': 'GatherND'},
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'gathernd_data': {'value': None, 'shape': None, 'kind': 'data'},
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# Result layer
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'result': {'type': 'Result', 'kind': 'op', 'op': 'Result'},
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# Transpose layers
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'transpose_1': {'type': 'Transpose', 'kind': 'op', 'op': 'Transpose', 'need_shape_inference': True},
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'transpose_1_data': {'value': None, 'shape': None, 'kind': 'data'},
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'axis_1_const': {'type': 'Const', 'kind': 'op', 'op': 'Const', 'value': None},
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'axis_1_const_data': {'kind': 'data', 'value': None, 'shape': None},
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'transpose_2': {'type': 'Transpose', 'kind': 'op', 'op': 'Transpose', 'need_shape_inference': True},
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'transpose_2_data': {'value': None, 'shape': None, 'kind': 'data'},
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'axis_2_const': {'type': 'Const', 'kind': 'op', 'op': 'Const', 'value': None},
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'axis_2_const_data': {'kind': 'data', 'value': None, 'shape': None},
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'transpose_3': {'type': 'Transpose', 'kind': 'op', 'op': 'Transpose', 'need_shape_inference': True},
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'transpose_3_data': {'value': None, 'shape': None, 'kind': 'data'},
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'axis_3_const': {'type': 'Const', 'kind': 'op', 'op': 'Const', 'value': None},
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'axis_3_const_data': {'kind': 'data', 'value': None, 'shape': None},
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}
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class LayoutChangeForGatherNDTests(unittest.TestCase):
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def test_tf_all_ports(self):
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graph = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_2', 'placeholder_2_data'),
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('placeholder_1_data', 'gathernd'),
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('placeholder_2_data', 'gathernd'),
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('gathernd', 'gathernd_data'),
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('gathernd_data', 'result'),
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],
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{'placeholder_1_data': {'shape': np.array([1, 3, 224, 224])},
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'placeholder_2_data': {'shape': np.array([1, 3, 224, 224])},
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'gathernd_data': {'shape': np.array([1, 3, 224, 224])},
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})
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graph.graph['fw'] = 'tf'
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graph_ref = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_2', 'placeholder_2_data'),
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('placeholder_1_data', 'transpose_1'),
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('axis_1_const', 'axis_1_const_data'),
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('axis_1_const_data', 'transpose_1'),
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('transpose_1', 'transpose_1_data'),
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('placeholder_2_data', 'transpose_2'),
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('axis_2_const', 'axis_2_const_data'),
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('axis_2_const_data', 'transpose_2'),
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('transpose_2', 'transpose_2_data'),
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('transpose_1_data', 'gathernd'),
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('transpose_2_data', 'gathernd'),
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('gathernd', 'gathernd_data'),
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('gathernd_data', 'transpose_3'),
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('axis_3_const', 'axis_3_const_data'),
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('axis_3_const_data', 'transpose_3'),
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('transpose_3', 'transpose_3_data'),
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('transpose_3_data', 'result'),
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],
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{'placeholder_1_data': {'shape': np.array([1, 3, 224, 224])},
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'placeholder_2_data': {'shape': np.array([1, 3, 224, 224])},
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'axis_1_const_data': {'value': int64_array([0, 2, 3, 1])},
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'axis_2_const_data': {'value': int64_array([0, 2, 3, 1])},
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'gathernd_data': {'shape': np.array([1, 3, 224, 224])},
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'axis_3_const_data': {'value': int64_array([0, 3, 1, 2])},
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})
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pattern = LayoutChangeForGatherND()
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pattern.find_and_replace_pattern(graph)
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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_tf_one_ports(self):
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graph = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_2', 'placeholder_2_data'),
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('placeholder_1_data', 'gathernd'),
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('placeholder_2_data', 'gathernd'),
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('gathernd', 'gathernd_data'),
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('gathernd_data', 'result'),
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],
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{'placeholder_1_data': {'shape': np.array([1, 3, 224, 224])},
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'placeholder_2_data': {'shape': np.array([1, 3])},
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'gathernd_data': {'shape': np.array([1, 3])},
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})
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graph.graph['fw'] = 'tf'
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graph_ref = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_2', 'placeholder_2_data'),
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('placeholder_1_data', 'transpose_1'),
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('axis_1_const', 'axis_1_const_data'),
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('axis_1_const_data', 'transpose_1'),
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('transpose_1', 'transpose_1_data'),
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('transpose_1_data', 'gathernd'),
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('placeholder_2_data', 'gathernd'),
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('gathernd', 'gathernd_data'),
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('gathernd_data', 'result'),
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],
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{'placeholder_1_data': {'shape': np.array([1, 3, 224, 224])},
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'placeholder_2_data': {'shape': np.array([1, 3])},
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'axis_1_const_data': {'value': int64_array([0, 2, 3, 1])},
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'gathernd_data': {'shape': np.array([1, 3])}
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})
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pattern = LayoutChangeForGatherND()
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pattern.find_and_replace_pattern(graph)
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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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