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
75 lines
3.2 KiB
Python
75 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 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.graph.graph import Graph
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from mo.middle.passes.eliminate import merge_data_nodes
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from mo.middle.passes.fusing.helpers import get_next_operation
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from mo.utils.error import Error
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class FuseTransposesSequence(BackReplacementPattern):
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"""
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This pass finds sequence of Transpose operations and merge them to single Transpose operation
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In case if resulting Permutation do nothing, we just remove it
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"""
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enabled = True
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def find_and_replace_pattern(self, graph: Graph):
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for permute_node in graph.get_op_nodes(type='Transpose'):
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if permute_node.id not in graph.nodes():
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continue
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list_of_permutes = [permute_node]
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# Get sequence of permutations
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node = permute_node
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while True:
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next_ops = get_next_operation(node)
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if len(next_ops) != 1:
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break
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next_op = next_ops[0]
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if next_op.soft_get('type') == 'Transpose':
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list_of_permutes.append(next_op)
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node = next_op
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else:
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break
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final_permutation = int64_array([x for x in range(len(list_of_permutes[0].in_port(1).data.get_value()))])
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for permute in list_of_permutes:
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order = permute.in_port(1).data.get_value()
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if order is None:
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raise Error("Transpose node {} has wrong order for permute = None".format(permute.name))
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final_permutation = final_permutation[int64_array(order)]
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if np.array_equal(final_permutation, [x for x in range(len(list_of_permutes[0].in_port(1).data.get_value()))]):
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first_data_node, last_data_node = list_of_permutes[0].in_node(), list_of_permutes[-1].out_node()
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graph.remove_edge(first_data_node.id, list_of_permutes[0].id)
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else:
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if len(list_of_permutes) < 2:
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continue
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first_data_node, last_data_node = list_of_permutes[0].out_node(), list_of_permutes[-1].out_node()
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list_of_permutes[0].in_port(1).data.set_value(final_permutation)
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graph.remove_edge(first_data_node.id, first_data_node.out_node().id)
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graph.remove_edge(last_data_node.in_node().id, last_data_node.id)
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merge_data_nodes(graph, first_data_node, last_data_node)
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graph.remove_node(last_data_node.id)
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graph.clean_up()
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