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Description
Facing value error while testing the data augmentation scripts under examples.
Output of falsifier.py script:
$ python falsifier.py
Initializing server
Server ready
Traceback (most recent call last; use -b to show Scenic internals):
File "/home/username/verifai/VerifAI/examples/data_augmentation/falsifier.py", line 57, in
falsifier.run_falsifier()
File "/home/username/verifai/verifai_env/lib/python3.9/site-packages/verifai/falsifier.py", line 155, in run_falsifier
sample, rho, (sample_time, simulate_time) = self.server.run_server()
ValueError: not enough values to unpack (expected 3, got 2)
100% (20 of 20) |########################################################################################################################################################################| Elapsed Time: 0:00:00 ETA: 00:00:00
Output of classifier.py script:
$ python classifier.py
WARNING:tensorflow:From /home/username/verifai/verifai_env/lib/python3.9/site-packages/tensorflow/python/compat/v2_compat.py:111: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
Instructions for updating:
non-resource variables are not supported in the long term
2022-09-16 14:54:36.035546: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-09-16 14:54:36.563780: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 6892 MB memory: -> device: 0, name: NVIDIA GeForce GTX 1080, pci bus id: 0000:65:00.0, compute capability: 6.1
2022-09-16 14:54:37.920585: I tensorflow/stream_executor/cuda/cuda_dnn.cc:366] Loaded cuDNN version 8100
2022-09-16 14:54:39.340597: W tensorflow/stream_executor/gpu/asm_compiler.cc:111] *** WARNING *** You are using ptxas 9.1.108, which is older than 11.1. ptxas before 11.1 is known to miscompile XLA code, leading to incorrect results or invalid-address errors.
You may not need to update to CUDA 11.1; cherry-picking the ptxas binary is often sufficient.
No new sample received from server.
End of all classifier calls