Roman Kazantsev
e3b879ad3b
* 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>
62 lines
2.8 KiB
Python
62 lines
2.8 KiB
Python
"""
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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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