Evgeny Lazarev
970b1301b5
* Removed back phase transformations related to IRv7 * Fixed setting value for the input port using the 'set_value' method * Removed front and middle phase transformations related to IRv7 * Cleanup the rest of the Model Optimizer transformations from IRv7 specific transformations * Final cleanup of the deprecated IR v7 related code * Removed 'blobs_as_input' usage in the Model Optimizer. * Removed function '_fuse_add' from the Model Optimizer since it is not used anymore. * Removed 'keep_in_IR' node attribute for FakeQuantize ops in the MO * Disabled failing gpu_engine.user_context test
73 lines
2.7 KiB
Python
73 lines
2.7 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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from extensions.back.Reshape0DToSqueeze import Reshape0DToSqueeze
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from extensions.back.ScalarConstNormalize import ScalarNormalize
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from mo.back.replacement import BackReplacementPattern
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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_node_with_second_input
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from mo.graph.graph import Graph, Node
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from mo.ops.reshape import Reshape
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from mo.ops.result import Result
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class TopKNormalizer(BackReplacementPattern):
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"""
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The transformation converts the second input to the TopK layer from 0D to 1D.
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Also the transformation adds the Result Op if there are no consumers of TopK outputs. However the Result for output
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with values is not added if the node has attribute 'remove_values_output' which is set to True for Caffe models
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where ArgMax does not have separate output with values.
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TODO this pass should be removed when IE supports 0D tensors.
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"""
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enabled = True
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def run_after(self):
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return [ScalarNormalize]
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def run_before(self):
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return [Reshape0DToSqueeze]
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@staticmethod
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def pattern():
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return dict(
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nodes=[('result', {'type': 'TopK'})],
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edges=[],
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)
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@staticmethod
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def replace_pattern(graph: Graph, match: dict):
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node = match['result']
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reshape = create_op_node_with_second_input(graph, Reshape, int64_array([]), {'override_output_shape': True})
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node.in_port(1).get_connection().insert_node(reshape)
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TopKNormalizer.normalize_outputs(node)
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@staticmethod
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def normalize_outputs(node: Node):
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"""
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This function adds missed outputs for TopK node.
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"""
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if node.out_port(0).disconnected():
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output = Result(node.graph, {'name': node.name + '/Result_port_0/',
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'remove_from_xml': node.has_and_set('remove_values_output')}).create_node()
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node.out_port(0).get_connection().set_destination(output.in_port(0))
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if node.out_port(1).disconnected():
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output = Result(node.graph, {'name': node.name + '/Result_port_1/'}).create_node()
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node.out_port(1).get_connection().set_destination(output.in_port(0))
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