mduval1 / bumble-bot

Hi there 👋

bumble-bot's Issues

Crash on Training Attempt

Alright, so after playing around with the code a bit more, I managed to fix most of the issues but I get the following error when I try to train the model. Keep in mind I stopped (pressing CTRL+C) after 4 profiles this time since I ran out of swipes testing things out:

C:\Users\Public\Public Apps\bumble-bot-main>main.py --mode TRAIN
2022-10-18 16:53:03.951579: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-10-18 16:53:03.951665: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-10-18 16:53:05.858186: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
2022-10-18 16:53:05.858270: W tensorflow/stream_executor/cuda/cuda_driver.cc:269] failed call to cuInit: UNKNOWN ERROR (303)
2022-10-18 16:53:05.860825: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: DESKTOP-QT5RMCM
2022-10-18 16:53:05.860918: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: DESKTOP-QT5RMCM
2022-10-18 16:53:05.861368: 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: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
WARNING:tensorflow:There are non-GPU devices in tf.distribute.Strategy, not using nccl allreduce.
2022-10-18 16:53:07.156090: W tensorflow/core/grappler/optimizers/data/auto_shard.cc:776] AUTO sharding policy will apply DATA sharding policy as it failed to apply FILE sharding policy because of the following reason: Found an unshardable source dataset: name: "TensorSliceDataset/_2"
op: "TensorSliceDataset"
input: "Placeholder/_0"
input: "Placeholder/_1"
attr {
key: "Toutput_types"
value {
list {
type: DT_STRING
type: DT_INT32
}
}
}
attr {
key: "_cardinality"
value {
i: 1
}
}
attr {
key: "is_files"
value {
b: false
}
}
attr {
key: "metadata"
value {
s: "\n\024TensorSliceDataset:0"
}
}
attr {
key: "output_shapes"
value {
list {
shape {
}
shape {
}
}
}
}
experimental_type {
type_id: TFT_PRODUCT
args {
type_id: TFT_DATASET
args {
type_id: TFT_PRODUCT
args {
type_id: TFT_TENSOR
args {
type_id: TFT_STRING
}
}
args {
type_id: TFT_TENSOR
args {
type_id: TFT_INT32
}
}
}
}
args {
type_id: TFT_DATASET
args {
type_id: TFT_PRODUCT
args {
type_id: TFT_TENSOR
args {
type_id: TFT_STRING
}
}
args {
type_id: TFT_TENSOR
args {
type_id: TFT_INT32
}
}
}
}
}

2022-10-18 16:53:07.189851: W tensorflow/core/framework/dataset.cc:768] Input of GeneratorDatasetOp::Dataset will not be optimized because the dataset does not implement the AsGraphDefInternal() method needed to apply optimizations.
Epoch 1/15
Traceback (most recent call last):
File "C:\Users\Public\Public Apps\bumble-bot-main\main.py", line 73, in
main()
File "C:\Python39\lib\site-packages\click\core.py", line 1130, in call
return self.main(*args, **kwargs)
File "C:\Python39\lib\site-packages\click\core.py", line 1055, in main
rv = self.invoke(ctx)
File "C:\Python39\lib\site-packages\click\core.py", line 1404, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "C:\Python39\lib\site-packages\click\core.py", line 760, in invoke
return __callback(*args, **kwargs)
File "C:\Users\Public\Public Apps\bumble-bot-main\main.py", line 38, in main
train_model()
File "C:\Users\Public\Public Apps\bumble-bot-main\train.py", line 80, in train_model
model.fit(ds_train, epochs=epochs, validation_data=ds_test, verbose=2)
File "C:\Python39\lib\site-packages\keras\utils\traceback_utils.py", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
File "C:\Python39\lib\site-packages\keras\engine\training.py", line 1395, in fit
raise ValueError('Unexpected result of train_function '
ValueError: Unexpected result of train_function (Empty logs). Please use Model.compile(..., run_eagerly=True), or tf.config.run_functions_eagerly(True) for more information of where went wrong, or file a issue/bug to tf.keras.

Also I did test the two solutions proposed in the error, maybe I did them wrong but they both didn't seem to do anything (they didn't cause any errors though).

Hangs After Seeing First Profile

Had to do a few small changes to get this to work. Now it's starting and it's checking the first profile correctly, but after it hangs, the photo is added to the directory though, any idea what's wrong and do you have the same issue?

Here's the console log:

C:\Users\Public\Public Apps\bumble-bot-main>python main.py --mode GATHER_DATA --start FRESH
2022-10-18 12:01:21.163188: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-10-18 12:01:21.163271: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-10-18 12:01:22.994649: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
2022-10-18 12:01:22.994733: W tensorflow/stream_executor/cuda/cuda_driver.cc:269] failed call to cuInit: UNKNOWN ERROR (303)
2022-10-18 12:01:22.997505: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: DESKTOP-QT5RMCM
2022-10-18 12:01:22.997594: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: DESKTOP-QT5RMCM
2022-10-18 12:01:22.998077: 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: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
WARNING:tensorflow:There are non-GPU devices in tf.distribute.Strategy, not using nccl allreduce.
2022-10-18 12:01:24.876948: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-10-18 12:01:24.877031: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-10-18 12:01:26.672329: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
2022-10-18 12:01:26.672419: W tensorflow/stream_executor/cuda/cuda_driver.cc:269] failed call to cuInit: UNKNOWN ERROR (303)
2022-10-18 12:01:26.675188: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: DESKTOP-QT5RMCM
2022-10-18 12:01:26.675272: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: DESKTOP-QT5RMCM
2022-10-18 12:01:26.675785: 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: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
WARNING:tensorflow:There are non-GPU devices in tf.distribute.Strategy, not using nccl allreduce.
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