google-coral
assert float(tf.__version__[:3]) >= 2.3 triggers because actual version is > 2.10
Description
In retrain_classification_ptq_tf2.ipynb, there is a check assert float(tf.__version__[:3]) >= 2.3 that should check whether the used tensorflow version is at least 2.3 or higher. Now colab uses 2.13 as its standard. That is higher than 2.3 but the assert triggers, because it makes 2.13 seem like 2.1. And also the float number 2.13 is smaller than 2.3. But as a version number it is higher.
Click to expand!
Issue Type
Bug
Operating System
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Coral Device
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Other Devices
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Programming Language
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Relevant Log Output
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-13-b98ebe4840c4> in <cell line: 1>()
----> 1 assert float(tf.__version__[:3]) >= 2.3
AssertionError:
Description
In retrain_classification_ptq_tf2.ipynb, there is a check
assert float(tf.__version__[:3]) >= 2.3that should check whether the used tensorflow version is at least 2.3 or higher. Now colab uses 2.13 as its standard. That is higher than 2.3 but the assert triggers, because it makes 2.13 seem like 2.1. And also the float number 2.13 is smaller than 2.3. But as a version number it is higher.Click to expand!
Issue Type
Bug
Operating System
No response
Coral Device
No response
Other Devices
No response
Programming Language
No response
Relevant Log Output
--------------------------------------------------------------------------- AssertionError Traceback (most recent call last) <ipython-input-13-b98ebe4840c4> in <cell line: 1>() ----> 1 assert float(tf.__version__[:3]) >= 2.3 AssertionError:
How to solve it for keep it running?
Version numbers as floats are always a bad idea. Something like this should fix it:
from packaging import version
assert version.parse(tf.__version__) >= version.parse("2.3"), "TensorFlow version is not >= 2.3"
Alternatively if you prefer less dependencies:
version_numbers = tuple(map(int, tf.__version__.split('.')))
assert version_numbers >= (2, 3, 0), "TensorFlow version is not >= 2.3"
Version numbers as floats are always a bad idea. Something like this should fix it:
from packaging import version assert version.parse(tf.__version__) >= version.parse("2.3"), "TensorFlow version is not >= 2.3"Alternatively if you prefer less dependencies:
version_numbers = tuple(map(int, tf.__version__.split('.'))) assert version_numbers >= (2, 3, 0), "TensorFlow version is not >= 2.3"
Hello, I have already managed to create a model. Now, how to run the model for live classification using web camera? I have following this tutorial https://coral.ai/docs/dev-board/camera/#view-with-a-streaming-server but the model cannot run. Thanks
This is the error message