54 lines
1.8 KiB
Python
54 lines
1.8 KiB
Python
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
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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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# A simple test to check whether the tflite_micro package works after it is
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# installed.
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# To test from the perspective of a package user, use import paths to locations
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# in the Python installation environment rather than to locations in the tflm
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# source tree.
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from tflite_micro import runtime
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import numpy as np
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import pkg_resources
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import sys
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def passed():
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# Create an interpreter with a sine model
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model = pkg_resources.resource_filename(__name__, "sine_float.tflite")
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interpreter = runtime.Interpreter.from_file(model)
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OUTPUT_INDEX = 0
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INPUT_INDEX = 0
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input_shape = interpreter.get_input_details(INPUT_INDEX).get("shape")
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# The interpreter infers sin(x)
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def infer(x):
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tensor = np.array(x, np.float32).reshape(input_shape)
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interpreter.set_input(tensor, INPUT_INDEX)
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interpreter.invoke()
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return interpreter.get_output(OUTPUT_INDEX).squeeze()
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# Check a few inferred values against a numerical computation
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PI = 3.14
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inputs = (0.0, PI / 2, PI, 3 * PI / 2, 2 * PI)
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outputs = [infer(x) for x in inputs]
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goldens = np.sin(inputs)
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return np.allclose(outputs, goldens, atol=0.05)
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if __name__ == "__main__":
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sys.exit(0 if passed() else 1)
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