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
74 lines
2.6 KiB
Python
74 lines
2.6 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.middle.LeakyReluPattern import LeakyReLU
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from extensions.middle.pass_separator import PostMiddleStart
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from mo.graph.graph import Graph
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from mo.middle.passes.mean_scale_values import move_scaleshift_to_preprocess
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from mo.middle.replacement import MiddleReplacementPattern
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from mo.utils.error import Error
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from mo.utils.find_inputs import find_inputs
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from mo.utils.utils import refer_to_faq_msg
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class Preprocessing(MiddleReplacementPattern):
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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 [LeakyReLU]
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def run_before(self):
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return [PostMiddleStart]
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def find_and_replace_pattern(self, graph: Graph):
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argv = graph.graph['cmd_params']
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if argv.move_to_preprocess:
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move_scaleshift_to_preprocess(graph)
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class CaffeMeanFileProcessing(MiddleReplacementPattern):
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enabled = True
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force_clean_up = True
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graph_condition = [lambda graph: graph.graph['fw'] == 'caffe']
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def run_after(self):
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return [Preprocessing]
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def run_before(self):
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return [PostMiddleStart]
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def find_and_replace_pattern(self, graph: Graph):
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from mo.front.caffe import loader
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argv = graph.graph['cmd_params']
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original_shapes = graph.graph['original_shapes']
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caffe_pb2 = graph.graph['caffe_pb2']
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del graph.graph['caffe_pb2']
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input_names = find_inputs(graph)
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mf = []
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try:
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if argv.mean_file and len(original_shapes) == 1:
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mf = loader.parse_mean(argv.mean_file, original_shapes[input_names[0]],
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argv.mean_file_offsets, caffe_pb2)
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elif argv.mean_file:
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raise Error('Mean file for topologies with multiple inputs is not supported. ' +
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refer_to_faq_msg(9))
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except ValueError as e:
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raise Error('Cannot load or process mean file: value error {}. ' +
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refer_to_faq_msg(10), str(e)) from e
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graph.graph['mf'] = mf
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graph.graph['input_names'] = input_names
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