Comments (3)
drasmuss
commented on June 16, 2024
1
This is due to an update in the progressbar2 package. You can either downgrade the progressbar2 version (pip install progressbar2<3.37.0), or, as you noticed, the development version of nengo-dl is updated to work with the latest progressbar2 version. We'll try to get a release out this week that includes that fix.
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drasmuss
commented on June 16, 2024
Just released v0.6.2 which should resolve this. Let me know if it doesn't for some reason, and I'll reopen the issue!
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arkhodamoradi
commented on June 16, 2024
Great! Thank you.
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Related Issues (20)
- AssertionError running custom neuron with TensorFlow 2.3.0 HOT 3
- Empty probes are Python lists instead of ndarrays
- Creating a simulator while keeping pretrained weights HOT 3
- Uninformative error message when using `sim.compile` on a network with no probed outputs
- Support/examples for converting or embedding Keras RNNs HOT 1
- Support scale_firing_rates with Regular/Poisson/Stochastic spiking wrappers
- Warn if converter's scale_firing_rates would skew the nonlinearities
- Support opting in to spikes on the forward pass
- Nengo version of ModelCheckpoint callback
- Use no-input nodes by default in converter
- load_params misbehaves with scale_firing_rates for some architectures HOT 1
- Converter `synapse` not applied to `neurons`-to-`TensorNode` connections HOT 1
- Converter fails with `tf.keras.applications.EfficientNet`
- Mistake in documentation
- Trainable parameters in Nengo LIF neurons HOT 2
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- sim.predict make GPU full memory HOT 7
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- Importing Nengo_DL in Google Colab
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