53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
#!/usr/bin/env python3
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# Copyright 2019 Mycroft AI Inc.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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from os.path import isfile
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from precise.scripts.calc_threshold import CalcThresholdScript
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from precise.scripts.eval import EvalScript
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from precise.scripts.graph import GraphScript
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def read_content(filename):
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with open(filename) as f:
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return f.read()
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def test_combined(train_folder, train_script):
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"""Test a "normal" development cycle, train, evaluate and calc threshold.
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"""
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train_script.run()
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params_file = train_folder.model + '.params'
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assert isfile(train_folder.model)
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assert isfile(params_file)
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EvalScript.create(folder=train_folder.root,
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models=[train_folder.model]).run()
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# Ensure that the graph script generates a numpy savez file
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out_file = train_folder.path('outputs.npz')
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graph_script = GraphScript.create(folder=train_folder.root,
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models=[train_folder.model],
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output_file=out_file)
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graph_script.run()
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assert isfile(out_file)
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# Esure the params are updated after threshold is calculated
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params_before = read_content(params_file)
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CalcThresholdScript.create(folder=train_folder.root,
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model=train_folder.model,
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input_file=out_file).run()
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assert params_before != read_content(params_file)
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