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
58 lines
1.9 KiB
Python
58 lines
1.9 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 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
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from mo.ops.lrn import LRN
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class LRN_normalization(BackReplacementPattern):
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"""
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Transforming LRN with `region` attribute to LRN with second `axis`-input
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"""
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enabled = True
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def pattern(self):
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return dict(
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nodes=[
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('lrn', dict(kind='op', op='AttributedLRN'))
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],
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edges=[]
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)
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def replace_pattern(self, graph: Graph, match: dict):
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node = match['lrn']
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name = node.soft_get('name', node.id)
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assert node.has_valid('region')
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assert node.region in ['across', 'same']
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input_shape = node.in_port(0).data.get_shape()
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assert input_shape is not None
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axis = [1] if node.region == 'across' else list(range(2, input_shape.size))
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new_lrn = create_op_node_with_second_input(graph, LRN, int64_array(axis), {
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'name': name,
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'alpha': node.alpha,
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'beta': node.beta,
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'size': node.local_size,
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'bias': node.bias,
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})
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node.out_port(0).get_connection().set_source(new_lrn.out_port(0))
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node.in_port(0).get_connection().set_destination(new_lrn.in_port(0))
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