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
83 lines
3.2 KiB
Python
83 lines
3.2 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.back.insert_compatibility_l2normalization import CompatibilityL2NormalizationPattern
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from extensions.ops.elementwise import Mul
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from extensions.ops.normalize_l2 import NormalizeL2Op
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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_with_const_inputs
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from mo.graph.graph import Graph, rename_node
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class NormalizeToNormalizeL2(BackReplacementPattern):
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enabled = True
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force_clean_up = True
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def run_after(self):
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return [CompatibilityL2NormalizationPattern]
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@staticmethod
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def pattern():
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return dict(
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nodes=[('normalize', {'type': 'Normalize'})],
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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['normalize']
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# rename normalize node since it will be no longer output node after the transformation
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output_name = node.soft_get('name', node.id)
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normalizel2_name = output_name + '/normalizel2'
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rename_node(node, normalizel2_name)
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assert node.in_port(0).data.get_shape().size in [2, 3, 4]
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assert node.has_valid('across_spatial')
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assert node.has_valid('channel_shared')
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assert node.has_valid('eps')
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if 'bin' in node.in_edge(1):
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del node.in_edge(1)['bin']
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weights = node.in_port(1).data.get_value()
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assert weights is not None
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# in the code below we intentionally use get_source() to get the out port. Because updating the out port will
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# update the Const node 'value' and 'shape' attributes
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if node.channel_shared or all(weights == weights[0]):
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node.in_port(1).get_source().data.set_value(np.array([weights[0]]))
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else:
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new_shape = np.ones((len(node.in_port(0).data.get_shape())), dtype=np.int64)
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new_shape[1] = -1
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node.in_port(1).get_source().data.set_value(np.array(weights).reshape(new_shape))
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mul = Mul(graph, {'name': output_name}).create_node()
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rename_node(mul, output_name)
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if not node.across_spatial:
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axes = int64_array([1])
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else:
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axes = int64_array(np.arange(start=1, stop=node.in_port(0).data.get_shape().size))
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normalizel2 = create_op_with_const_inputs(graph, NormalizeL2Op, {1: axes}, {'eps_mode': 'add', 'eps': node.eps})
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node.out_port(0).get_connection().set_source(mul.out_port(0))
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node.in_port(1).get_connection().get_source().connect(mul.in_port(1))
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normalizel2.out_port(0).connect(mul.in_port(0))
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node.in_port(0).get_connection().set_destination(normalizel2.in_port(0))
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