Staging by iamzoltan · Pull Request #519 · neuromatch/NeuroAI_Course

iamzoltan · 2026-07-18T05:46:05Z

No description provided.

These notebooks failed to process in the original PR and need reprocessing: - projects/project-notebooks/Macrocircuits.ipynb - tutorials/W1D1_Generalization/W1D1_Tutorial1.ipynb - tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb - tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb - tutorials/W2D1_Macrocircuits/W2D1_Tutorial1.ipynb - tutorials/W2D1_Macrocircuits/W2D1_Tutorial2.ipynb - tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb - tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb - tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

Reprocess: Failed notebooks from PR #516

github-actions · 2026-07-18T06:05:07Z

Notebook Processing Failure Context

projects/project-notebooks/Macrocircuits.ipynb

2026-07-18T05:56:02.1315754Z Executing projects/project-notebooks/Macrocircuits.ipynb
2026-07-18T05:56:04.5763327Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T05:56:08.2044680Z projects/project-notebooks/Macrocircuits.ipynb failed quality control.
2026-07-18T05:56:08.2045901Z ============================== Failure ==============================
2026-07-18T05:56:08.2047178Z An error occurred while executing the following cell:
2026-07-18T05:56:08.2048008Z ------------------
2026-07-18T05:56:08.2049006Z #@title Installing Dependencies (Colab GPU case, uncomment if you want to use this one)
2026-07-18T05:56:08.2049678Z 
2026-07-18T05:56:08.2049826Z import distutils.util
2026-07-18T05:56:08.2050171Z import os
2026-07-18T05:56:08.2050473Z import subprocess
2026-07-18T05:56:08.2050862Z if shutil.which('nvidia-smi') is not None:
2026-07-18T05:56:08.2051315Z   raise RuntimeError(
2026-07-18T05:56:08.2051688Z       'Cannot communicate with GPU. '
2026-07-18T05:56:08.2052594Z       'Make sure you are using a GPU Colab runtime. '
2026-07-18T05:56:08.2053190Z       'Go to the Runtime menu and select Choose runtime type.')
2026-07-18T05:56:08.2053595Z 
2026-07-18T05:56:08.2053878Z # Add an ICD config so that glvnd can pick up the Nvidia EGL driver.
2026-07-18T05:56:08.2054511Z # This is usually installed as part of an Nvidia driver package, but the Colab
2026-07-18T05:56:08.2055159Z # kernel doesn't install its driver via APT, and as a result the ICD is missing.
2026-07-18T05:56:08.2055816Z # (https://github.com/NVIDIA/libglvnd/blob/master/src/EGL/icd_enumeration.md)
2026-07-18T05:56:08.2056731Z NVIDIA_ICD_CONFIG_PATH = '/usr/share/glvnd/egl_vendor.d/10_nvidia.json'
2026-07-18T05:56:08.2057256Z if not os.path.exists(NVIDIA_ICD_CONFIG_PATH):
2026-07-18T05:56:08.2057657Z   with open(NVIDIA_ICD_CONFIG_PATH, 'w') as f:
2026-07-18T05:56:08.2058003Z     f.write("""{
2026-07-18T05:56:08.2058261Z     "file_format_version" : "1.0.0",
2026-07-18T05:56:08.2058565Z     "ICD" : {
2026-07-18T05:56:08.2058831Z         "library_path" : "libEGL_nvidia.so.0"
2026-07-18T05:56:08.2059184Z     }
2026-07-18T05:56:08.2059395Z }
2026-07-18T05:56:08.2059594Z """)
2026-07-18T05:56:08.2059712Z 
2026-07-18T05:56:08.2059834Z print('Installing dm_control...')
2026-07-18T05:56:08.2060157Z !pip install --quiet dm_control
2026-07-18T05:56:08.2060582Z # Configure dm_control to use the EGL rendering backend (requires GPU)
2026-07-18T05:56:08.2061033Z %env MUJOCO_GL=egl
2026-07-18T05:56:08.2061194Z 
2026-07-18T05:56:08.2061466Z !echo Installed dm_control $(pip show dm_control | grep -Po "(?<=Version: ).+")
2026-07-18T05:56:08.2062002Z !pip install --quiet dm_acme!mkdir output_videos
2026-07-18T05:56:08.2062354Z ------------------
2026-07-18T05:56:08.2062500Z 
2026-07-18T05:56:08.2062505Z 
2026-07-18T05:56:08.2063194Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T05:56:08.2063843Z �[0;31mNameError�[0m                                 Traceback (most recent call last)
2026-07-18T05:56:08.2064307Z Cell �[0;32mIn[7], line 6�[0m
2026-07-18T05:56:08.2064713Z �[1;32m      4�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mos�[39;00m
2026-07-18T05:56:08.2065258Z �[1;32m      5�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01msubprocess�[39;00m
2026-07-18T05:56:08.2066272Z �[0;32m----> 6�[0m �[38;5;28;01mif�[39;00m �[43mshutil�[49m�[38;5;241m.�[39mwhich(�[38;5;124m'�[39m�[38;5;124mnvidia-smi�[39m�[38;5;124m'�[39m) �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:
2026-07-18T05:56:08.2067422Z �[1;32m      7�[0m   �[38;5;28;01mraise�[39;00m �[38;5;167;01mRuntimeError�[39;00m(
2026-07-18T05:56:08.2068005Z �[1;32m      8�[0m       �[38;5;124m'�[39m�[38;5;124mCannot communicate with GPU. �[39m�[38;5;124m'�[39m
2026-07-18T05:56:08.2068711Z �[1;32m      9�[0m       �[38;5;124m'�[39m�[38;5;124mMake sure you are using a GPU Colab runtime. �[39m�[38;5;124m'�[39m
2026-07-18T05:56:08.2069506Z �[1;32m     10�[0m       �[38;5;124m'�[39m�[38;5;124mGo to the Runtime menu and select Choose runtime type.�[39m�[38;5;124m'�[39m)
2026-07-18T05:56:08.2070260Z �[1;32m     12�[0m �[38;5;66;03m# Add an ICD config so that glvnd can pick up the Nvidia EGL driver.�[39;00m
2026-07-18T05:56:08.2071003Z �[1;32m     13�[0m �[38;5;66;03m# This is usually installed as part of an Nvidia driver package, but the Colab�[39;00m
2026-07-18T05:56:08.2071777Z �[1;32m     14�[0m �[38;5;66;03m# kernel doesn't install its driver via APT, and as a result the ICD is missing.�[39;00m
2026-07-18T05:56:08.2072570Z �[1;32m     15�[0m �[38;5;66;03m# (https://github.com/NVIDIA/libglvnd/blob/master/src/EGL/icd_enumeration.md)�[39;00m
2026-07-18T05:56:08.2072994Z 
2026-07-18T05:56:08.2073169Z �[0;31mNameError�[0m: name 'shutil' is not defined
2026-07-18T05:56:08.2073394Z 
2026-07-18T05:56:08.4672265Z ##[error]Process completed with exit code 1.

tutorials/W1D1_Generalization/W1D1_Tutorial1.ipynb

2026-07-18T05:56:18.9223392Z �[1;32m   1024�[0m �[43m        �[49m�[43metag_timeout�[49m�[38;5;241;43m=�[39;49m�[43metag_timeout�[49m�[43m,�[49m
2026-07-18T05:56:18.9224035Z �[1;32m   1025�[0m �[43m        �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mhf_headers�[49m�[43m,�[49m
2026-07-18T05:56:18.9224646Z �[1;32m   1026�[0m �[43m        �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-18T05:56:18.9225232Z �[1;32m   1027�[0m �[43m        �[49m�[43mtoken�[49m�[38;5;241;43m=�[39;49m�[43mtoken�[49m�[43m,�[49m
2026-07-18T05:56:18.9225763Z �[1;32m   1028�[0m �[43m        �[49m�[38;5;66;43;03m# Additional options�[39;49;00m
2026-07-18T05:56:18.9226384Z �[1;32m   1029�[0m �[43m        �[49m�[43mlocal_files_only�[49m�[38;5;241;43m=�[39;49m�[43mlocal_files_only�[49m�[43m,�[49m
2026-07-18T05:56:18.9227089Z �[1;32m   1030�[0m �[43m        �[49m�[43mforce_download�[49m�[38;5;241;43m=�[39;49m�[43mforce_download�[49m�[43m,�[49m
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2026-07-18T05:56:18.9227760Z 
2026-07-18T05:56:18.9228886Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:1175�[0m, in �[0;36m_hf_hub_download_to_cache_dir�[0;34m(cache_dir, repo_id, filename, repo_type, revision, endpoint, etag_timeout, headers, proxies, token, local_files_only, force_download)�[0m
2026-07-18T05:56:18.9230303Z �[1;32m   1172�[0m �[38;5;66;03m# Local file doesn't exist or etag isn't a match => retrieve file from remote (or cache)�[39;00m
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2026-07-18T05:56:18.9235514Z �[1;32m   1179�[0m �[43m        �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
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2026-07-18T05:56:18.9238079Z �[1;32m   1183�[0m �[43m        �[49m�[43mforce_download�[49m�[38;5;241;43m=�[39;49m�[43mforce_download�[49m�[43m,�[49m
2026-07-18T05:56:18.9238703Z �[1;32m   1184�[0m �[43m        �[49m�[43metag�[49m�[38;5;241;43m=�[39;49m�[43metag�[49m�[43m,�[49m
2026-07-18T05:56:18.9239324Z �[1;32m   1185�[0m �[43m        �[49m�[43mxet_file_data�[49m�[38;5;241;43m=�[39;49m�[43mxet_file_data�[49m�[43m,�[49m
2026-07-18T05:56:18.9239798Z �[1;32m   1186�[0m �[43m    �[49m�[43m)�[49m
2026-07-18T05:56:18.9240361Z �[1;32m   1187�[0m     �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m os�[38;5;241m.�[39mpath�[38;5;241m.�[39mexists(pointer_path):
2026-07-18T05:56:18.9241247Z �[1;32m   1188�[0m         _create_symlink(blob_path, pointer_path, new_blob�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)
2026-07-18T05:56:18.9241632Z 
2026-07-18T05:56:18.9243022Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:1742�[0m, in �[0;36m_download_to_tmp_and_move�[0;34m(incomplete_path, destination_path, url_to_download, proxies, headers, expected_size, filename, force_download, etag, xet_file_data)�[0m
2026-07-18T05:56:18.9244739Z �[1;32m   1735�[0m         �[38;5;28;01mif�[39;00m xet_file_data �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m �[38;5;129;01mand�[39;00m �[38;5;129;01mnot�[39;00m constants�[38;5;241m.�[39mHF_HUB_DISABLE_XET:
2026-07-18T05:56:18.9245552Z �[1;32m   1736�[0m             logger�[38;5;241m.�[39mwarning(
2026-07-18T05:56:18.9246461Z �[1;32m   1737�[0m                 �[38;5;124m"�[39m�[38;5;124mXet Storage is enabled for this repo, but the �[39m�[38;5;124m'�[39m�[38;5;124mhf_xet�[39m�[38;5;124m'�[39m�[38;5;124m package is not installed. �[39m�[38;5;124m"�[39m
2026-07-18T05:56:18.9247442Z �[1;32m   1738�[0m                 �[38;5;124m"�[39m�[38;5;124mFalling back to regular HTTP download. �[39m�[38;5;124m"�[39m
2026-07-18T05:56:18.9248425Z �[1;32m   1739�[0m                 �[38;5;124m"�[39m�[38;5;124mFor better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`�[39m�[38;5;124m"�[39m
2026-07-18T05:56:18.9249127Z �[1;32m   1740�[0m             )
2026-07-18T05:56:18.9249450Z �[0;32m-> 1742�[0m         �[43mhttp_get�[49m�[43m(�[49m
2026-07-18T05:56:18.9249864Z �[1;32m   1743�[0m �[43m            �[49m�[43murl_to_download�[49m�[43m,�[49m
2026-07-18T05:56:18.9250286Z �[1;32m   1744�[0m �[43m            �[49m�[43mf�[49m�[43m,�[49m
2026-07-18T05:56:18.9250802Z �[1;32m   1745�[0m �[43m            �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-18T05:56:18.9251590Z �[1;32m   1746�[0m �[43m            �[49m�[43mresume_size�[49m�[38;5;241;43m=�[39;49m�[43mresume_size�[49m�[43m,�[49m
2026-07-18T05:56:18.9252539Z �[1;32m   1747�[0m �[43m            �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mheaders�[49m�[43m,�[49m
2026-07-18T05:56:18.9253336Z �[1;32m   1748�[0m �[43m            �[49m�[43mexpected_size�[49m�[38;5;241;43m=�[39;49m�[43mexpected_size�[49m�[43m,�[49m
2026-07-18T05:56:18.9253866Z �[1;32m   1749�[0m �[43m        �[49m�[43m)�[49m
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2026-07-18T05:56:18.9255562Z �[1;32m   1752�[0m _chmod_and_move(incomplete_path, destination_path)
2026-07-18T05:56:18.9255822Z 
2026-07-18T05:56:18.9256771Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:455�[0m, in �[0;36mhttp_get�[0;34m(url, temp_file, proxies, resume_size, headers, expected_size, displayed_filename, _nb_retries, _tqdm_bar)�[0m
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2026-07-18T05:56:18.9263748Z �[1;32m    453�[0m     �[38;5;124m"�[39m�[38;5;124m Please retry with `force_download=True`.�[39m�[38;5;124m"�[39m
2026-07-18T05:56:18.9264236Z �[1;32m    454�[0m )
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2026-07-18T05:56:18.9266901Z �[1;32m    458�[0m �[43m    �[49m�[43mtotal�[49m�[38;5;241;43m=�[39;49m�[43mtotal�[49m�[43m,�[49m
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2026-07-18T05:56:18.9273842Z 
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2026-07-18T05:56:18.9283898Z 
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2026-07-18T05:56:18.9285395Z �[1;32m    223�[0m �[38;5;28;01mif�[39;00m are_progress_bars_disabled(name):
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2026-07-18T05:56:18.9288009Z 
2026-07-18T05:56:18.9288624Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:250�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
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2026-07-18T05:56:18.9291424Z �[1;32m    252�[0m �[38;5;66;03m# Print initial bar state�[39;00m
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2026-07-18T05:56:18.9292464Z 
2026-07-18T05:56:18.9293053Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:209�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
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2026-07-18T05:56:18.9297283Z 
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2026-07-18T05:56:18.9297639Z 
2026-07-18T05:56:18.9297799Z ============================== Failure ==============================
2026-07-18T05:56:19.1189050Z ##[error]Process completed with exit code 1.

tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb

2026-07-18T05:55:53.6314932Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T05:56:15.3212049Z tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb failed quality control.
2026-07-18T05:56:15.3212776Z ============================== Failure ==============================
2026-07-18T05:56:15.3213199Z An error occurred while executing the following cell:
2026-07-18T05:56:15.3213625Z ------------------
2026-07-18T05:56:15.3214076Z def perturb_inputs(model, inputs, perturbation_strength):
2026-07-18T05:56:15.3214595Z     device = inputs.device
2026-07-18T05:56:15.3215193Z     # Perturb the inputs by adding random noise scaled by the perturbation strength and input strength
2026-07-18T05:56:15.3215886Z     input_strength = torch.norm(inputs, p=2, dim=-1, keepdim=True)  # Calculate the L2 norm of inputs
2026-07-18T05:56:15.3217331Z     noise = torch.rand(inputs.shape[0], 1, inputs.shape[2], device=device) * perturbation_strength * input_strength
2026-07-18T05:56:15.3217841Z     perturbed_inputs = inputs + noise
2026-07-18T05:56:15.3218115Z     return perturbed_inputs
2026-07-18T05:56:15.3218280Z 
2026-07-18T05:56:15.3218440Z def compute_loss(model, inputs, targets, criterion, device):
2026-07-18T05:56:15.3218784Z     batch_size = inputs.size(0)
2026-07-18T05:56:15.3219139Z     h = model.init_hidden(batch_size).to(device)  # Initialize hidden state
2026-07-18T05:56:15.3219499Z     losses = []
2026-07-18T05:56:15.3219762Z     for t in range(inputs.shape[1]):  # Iterate over time steps
2026-07-18T05:56:15.3220122Z         model_output = model(inputs[:, t, :], h)
2026-07-18T05:56:15.3220440Z         output, h, *rest = model_output[:2]
2026-07-18T05:56:15.3220914Z         loss = criterion(output, targets[:, t])  # Assume targets is a sequence of same length as inputs
2026-07-18T05:56:15.3221355Z         losses.append(loss)
2026-07-18T05:56:15.3221642Z     mean_loss = torch.mean(torch.stack(losses)).item()
2026-07-18T05:56:15.3221942Z     return mean_loss
2026-07-18T05:56:15.3222078Z 
2026-07-18T05:56:15.3222370Z def test_perturbed_inputs(model, perturbation_strengths, test_loader, criterion, device, max_error):
2026-07-18T05:56:15.3222873Z     model.eval()  # Set the model to evaluation mode
2026-07-18T05:56:15.3223182Z     perturbation_results = []
2026-07-18T05:56:15.3223338Z 
2026-07-18T05:56:15.3223449Z     for strength in perturbation_strengths:
2026-07-18T05:56:15.3223873Z         all_errors = []  # Store all errors for each perturbation strength to compute mean and s.d.
2026-07-18T05:56:15.3224355Z         print(f"Testing perturbation strength {strength}")
2026-07-18T05:56:15.3224767Z         for iteration in tqdm(range(30)):  # Repeat the procedure 30 times
2026-07-18T05:56:15.3225170Z             batch_errors = []  # Store errors for each batch
2026-07-18T05:56:15.3225391Z 
2026-07-18T05:56:15.3225507Z             for inputs, targets in test_loader:
2026-07-18T05:56:15.3225867Z                 inputs, targets = inputs.to(device), targets.to(device)
2026-07-18T05:56:15.3226460Z                 # Compute error for original inputs
2026-07-18T05:56:15.3226872Z                 # original_loss = compute_loss(model, inputs, targets, criterion, device)
2026-07-18T05:56:15.3227296Z                 # Compute error for perturbed inputs
2026-07-18T05:56:15.3227497Z 
2026-07-18T05:56:15.3227671Z                 perturbed_inputs = perturb_inputs(model, inputs, strength)
2026-07-18T05:56:15.3228174Z                 perturbed_loss = compute_loss(model, perturbed_inputs, targets, criterion, device)
2026-07-18T05:56:15.3228503Z 
2026-07-18T05:56:15.3228615Z                 # Store the normalized error.
2026-07-18T05:56:15.3229130Z                 rel_error = perturbed_loss / max_error * 100
2026-07-18T05:56:15.3229447Z                 batch_errors.append(rel_error)
2026-07-18T05:56:15.3229638Z 
2026-07-18T05:56:15.3229740Z             all_errors.extend(batch_errors)
2026-07-18T05:56:15.3229931Z 
2026-07-18T05:56:15.3230035Z         mean_error = np.mean(all_errors)
2026-07-18T05:56:15.3230305Z         std_error = np.std(all_errors)
2026-07-18T05:56:15.3230612Z         perturbation_results.append((mean_error, std_error))
2026-07-18T05:56:15.3231013Z         print(f"Completed testing for perturbation strength {strength}.")
2026-07-18T05:56:15.3231287Z 
2026-07-18T05:56:15.3231383Z     return perturbation_results
2026-07-18T05:56:15.3231545Z 
2026-07-18T05:56:15.3231771Z # Calculate the maximum error for a null model, the error when the output is constant.
2026-07-18T05:56:15.3232299Z max_error = ((outputs - outputs.mean(axis=[0, 1], keepdims=True)) ** 2).mean()
2026-07-18T05:56:15.3232594Z 
2026-07-18T05:56:15.3232739Z perturbation_strengths = [0.0125, 0.025, 0.05, 0.1, 0.2]
2026-07-18T05:56:15.3233408Z results_unregularized = test_perturbed_inputs(unregularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-18T05:56:15.3234443Z results_regularized = test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-18T05:56:15.3235018Z ------------------
2026-07-18T05:56:15.3235140Z 
2026-07-18T05:56:15.3235226Z ----- stdout -----
2026-07-18T05:56:15.3235448Z Testing perturbation strength 0.0125
2026-07-18T05:56:15.3235722Z ------------------
2026-07-18T05:56:15.3235850Z 
2026-07-18T05:56:15.3236525Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T05:56:15.3237085Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T05:56:15.3237514Z Cell �[0;32mIn[44], line 57�[0m
2026-07-18T05:56:15.3238555Z �[1;32m     54�[0m max_error �[38;5;241m=�[39m ((outputs �[38;5;241m-�[39m outputs�[38;5;241m.�[39mmean(axis�[38;5;241m=�[39m[�[38;5;241m0�[39m, �[38;5;241m1�[39m], keepdims�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)) �[38;5;241m*�[39m�[38;5;241m*�[39m �[38;5;241m2�[39m)�[38;5;241m.�[39mmean()
2026-07-18T05:56:15.3239842Z �[1;32m     56�[0m perturbation_strengths �[38;5;241m=�[39m [�[38;5;241m0.0125�[39m, �[38;5;241m0.025�[39m, �[38;5;241m0.05�[39m, �[38;5;241m0.1�[39m, �[38;5;241m0.2�[39m]
2026-07-18T05:56:15.3241611Z �[0;32m---> 57�[0m results_unregularized �[38;5;241m=�[39m �[43mtest_perturbed_inputs�[49m�[43m(�[49m�[43munregularized_model�[49m�[43m,�[49m�[43m �[49m�[43mperturbation_strengths�[49m�[43m,�[49m�[43m �[49m�[43mtest_loader�[49m�[43m,�[49m�[43m �[49m�[43mnn�[49m�[38;5;241;43m.�[39;49m�[43mMSELoss�[49m�[43m(�[49m�[43m)�[49m�[43m,�[49m�[43m �[49m�[43mdevice�[49m�[43m,�[49m�[43m �[49m�[43mmax_error�[49m�[43m)�[49m
2026-07-18T05:56:15.3243336Z �[1;32m     58�[0m results_regularized �[38;5;241m=�[39m test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn�[38;5;241m.�[39mMSELoss(), device, max_error)
2026-07-18T05:56:15.3243938Z 
2026-07-18T05:56:15.3244451Z Cell �[0;32mIn[44], line 28�[0m, in �[0;36mtest_perturbed_inputs�[0;34m(model, perturbation_strengths, test_loader, criterion, device, max_error)�[0m
2026-07-18T05:56:15.3245407Z �[1;32m     26�[0m all_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store all errors for each perturbation strength to compute mean and s.d.�[39;00m
2026-07-18T05:56:15.3246621Z �[1;32m     27�[0m �[38;5;28mprint�[39m(�[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mTesting perturbation strength �[39m�[38;5;132;01m{�[39;00mstrength�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m)
2026-07-18T05:56:15.3247886Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m iteration �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[38;5;28;43mrange�[39;49m�[43m(�[49m�[38;5;241;43m30�[39;49m�[43m)�[49m�[43m)�[49m:  �[38;5;66;03m# Repeat the procedure 30 times�[39;00m
2026-07-18T05:56:15.3248818Z �[1;32m     29�[0m     batch_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store errors for each batch�[39;00m
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2026-07-18T05:56:15.3249891Z 
2026-07-18T05:56:15.3250534Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
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2026-07-18T05:56:15.3253277Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
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2026-07-18T05:56:15.3254130Z 
2026-07-18T05:56:15.3254836Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T05:56:15.3255569Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T05:56:15.3256328Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T05:56:15.3257095Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T05:56:15.3258308Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T05:56:15.3259019Z 
2026-07-18T05:56:15.3259178Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T05:56:15.3259386Z 
2026-07-18T05:56:15.6847936Z ##[error]Process completed with exit code 1.

tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb

2026-07-18T05:55:38.1275590Z Executing tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb
2026-07-18T05:55:39.0802479Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T05:55:54.0651071Z tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb failed quality control.
2026-07-18T05:55:54.0652176Z An error occurred while executing the following cell:
2026-07-18T05:55:54.0652552Z ------------------
2026-07-18T05:55:54.0652887Z # @title Extract model features with torchlens
2026-07-18T05:55:54.0653148Z 
2026-07-18T05:55:54.0653320Z return_layers = ['input_1', 'conv1', 'conv2', 'fc1', 'fc2']
2026-07-18T05:55:54.0654457Z features_model_imgs = extract_features(model, imgs, return_layers, plot = 'rolled') #comment this line if Graphviz installation was unsuccessful for you
2026-07-18T05:55:54.0655484Z 
2026-07-18T05:55:54.0655751Z features_model_advimgs = extract_features(model, adv_imgs, return_layers)
2026-07-18T05:55:54.0656270Z ============================== Failure ==============================
2026-07-18T05:55:54.0656810Z features_advmodel_imgs = extract_features(model_robust, imgs, return_layers)
2026-07-18T05:55:54.0657516Z features_advmodel_advimgs = extract_features(model_robust, adv_imgs_advmodel, return_layers)
2026-07-18T05:55:54.0658051Z ------------------
2026-07-18T05:55:54.0658194Z 
2026-07-18T05:55:54.0658293Z ----- stderr -----
2026-07-18T05:55:54.0659216Z /tmp/ipykernel_3494/1139971176.py:348: DeprecationWarning: torchlens.log_forward_pass is deprecated; use torchlens.trace instead. The old paper-era name remains available as a compatibility shim.
2026-07-18T05:55:54.0660339Z   model_history = tl.log_forward_pass(model, imgs, layers_to_save='all', )
2026-07-18T05:55:54.0660785Z ----- stderr -----
2026-07-18T05:55:54.0661926Z /opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/torchlens/backends/torch/wrappers.py:227: UserWarning: TorchLens torch capability HAS_FUNCTORCH_LEVEL_API is unavailable; functorch transform-boundary detection is disabled
2026-07-18T05:55:54.0663230Z   maybe_current_level = get_functorch_maybe_current_level()
2026-07-18T05:55:54.0663612Z ------------------
2026-07-18T05:55:54.0663752Z 
2026-07-18T05:55:54.0664487Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T05:55:54.0665171Z �[0;31mAttributeError�[0m                            Traceback (most recent call last)
2026-07-18T05:55:54.0665678Z Cell �[0;32mIn[23], line 4�[0m
2026-07-18T05:55:54.0666123Z �[1;32m      1�[0m �[38;5;66;03m# @title Extract model features with torchlens�[39;00m
2026-07-18T05:55:54.0667400Z �[1;32m      3�[0m return_layers �[38;5;241m=�[39m [�[38;5;124m'�[39m�[38;5;124minput_1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv2�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc2�[39m�[38;5;124m'�[39m]
2026-07-18T05:55:54.0669690Z �[0;32m----> 4�[0m features_model_imgs �[38;5;241m=�[39m �[43mextract_features�[49m�[43m(�[49m�[43mmodel�[49m�[43m,�[49m�[43m �[49m�[43mimgs�[49m�[43m,�[49m�[43m �[49m�[43mreturn_layers�[49m�[43m,�[49m�[43m �[49m�[43mplot�[49m�[43m �[49m�[38;5;241;43m=�[39;49m�[43m �[49m�[38;5;124;43m'�[39;49m�[38;5;124;43mrolled�[39;49m�[38;5;124;43m'�[39;49m�[43m)�[49m �[38;5;66;03m#comment this line if Graphviz installation was unsuccessful for you�[39;00m
2026-07-18T05:55:54.0671264Z �[1;32m      6�[0m features_model_advimgs �[38;5;241m=�[39m extract_features(model, adv_imgs, return_layers)
2026-07-18T05:55:54.0672281Z �[1;32m      7�[0m features_advmodel_imgs �[38;5;241m=�[39m extract_features(model_robust, imgs, return_layers)
2026-07-18T05:55:54.0672660Z 
2026-07-18T05:55:54.0673006Z Cell �[0;32mIn[8], line 351�[0m, in �[0;36mextract_features�[0;34m(model, imgs, return_layers, plot)�[0m
2026-07-18T05:55:54.0673523Z �[1;32m    349�[0m model_features �[38;5;241m=�[39m {}
2026-07-18T05:55:54.0673985Z �[1;32m    350�[0m �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m return_layers:
2026-07-18T05:55:54.0675376Z �[0;32m--> 351�[0m     model_features[layer] �[38;5;241m=�[39m �[43mmodel_history�[49m�[43m[�[49m�[43mlayer�[49m�[43m]�[49m�[38;5;241;43m.�[39;49m�[43mtensor_contents�[49m�[38;5;241m.�[39mflatten(�[38;5;241m1�[39m)
2026-07-18T05:55:54.0676198Z �[1;32m    353�[0m �[38;5;28;01mreturn�[39;00m model_features
2026-07-18T05:55:54.0676428Z 
2026-07-18T05:55:54.0677078Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/torchlens/data_classes/layer.py:1261�[0m, in �[0;36mLayer.__getattr__�[0;34m(self, name)�[0m
2026-07-18T05:55:54.0678363Z �[1;32m   1259�[0m �[38;5;28;01mif�[39;00m ops �[38;5;129;01mand�[39;00m �[38;5;28mlen�[39m(ops) �[38;5;241m>�[39m �[38;5;241m1�[39m �[38;5;129;01mand�[39;00m name �[38;5;129;01min�[39;00m _LAYER_DELEGATED_PASS_FIELDS:
2026-07-18T05:55:54.0679461Z �[1;32m   1260�[0m     �[38;5;28;01mreturn�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39m_single_pass_or_error(name)
2026-07-18T05:55:54.0681102Z �[0;32m-> 1261�[0m �[38;5;28;01mraise�[39;00m �[38;5;167;01mAttributeError�[39;00m(�[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124m'�[39m�[38;5;132;01m{�[39;00m�[38;5;28mtype�[39m(�[38;5;28mself�[39m)�[38;5;241m.�[39m�[38;5;18m__name__�[39m�[38;5;132;01m}�[39;00m�[38;5;124m'�[39m�[38;5;124m object has no attribute �[39m�[38;5;124m'�[39m�[38;5;132;01m{�[39;00mname�[38;5;132;01m}�[39;00m�[38;5;124m'�[39m�[38;5;124m"�[39m)
2026-07-18T05:55:54.0682211Z 
2026-07-18T05:55:54.0682462Z �[0;31mAttributeError�[0m: 'Layer' object has no attribute 'tensor_contents'
2026-07-18T05:55:54.0682763Z 
2026-07-18T05:55:54.2467210Z ##[error]Process completed with exit code 1.

tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb

2026-07-18T05:55:59.8920788Z Executing tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb
2026-07-18T05:56:01.1844306Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T05:56:29.3270606Z tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb failed quality control.
2026-07-18T05:56:29.3271200Z An error occurred while executing the following cell:
2026-07-18T05:56:29.3271573Z ------------------
2026-07-18T05:56:29.3271896Z ============================== Failure ==============================
2026-07-18T05:56:29.3272412Z modular_agent = Agent(arg, ModularActor)
2026-07-18T05:56:29.3272784Z modular_agent.load(Path('agents/modular'), 0)
2026-07-18T05:56:29.3273204Z modular_df = evaluation(modular_agent)
2026-07-18T05:56:29.3273564Z ------------------
2026-07-18T05:56:29.3273716Z 
2026-07-18T05:56:29.3273729Z 
2026-07-18T05:56:29.3274227Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T05:56:29.3275258Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T05:56:29.3275858Z Cell �[0;32mIn[38], line 3�[0m
2026-07-18T05:56:29.3276369Z �[1;32m      1�[0m modular_agent �[38;5;241m=�[39m Agent(arg, ModularActor)
2026-07-18T05:56:29.3277319Z �[1;32m      2�[0m modular_agent�[38;5;241m.�[39mload(Path(�[38;5;124m'�[39m�[38;5;124magents/modular�[39m�[38;5;124m'�[39m), �[38;5;241m0�[39m)
2026-07-18T05:56:29.3278659Z �[0;32m----> 3�[0m modular_df �[38;5;241m=�[39m �[43mevaluation�[49m�[43m(�[49m�[43mmodular_agent�[49m�[43m)�[49m
2026-07-18T05:56:29.3279170Z 
2026-07-18T05:56:29.3281658Z Cell �[0;32mIn[37], line 28�[0m, in �[0;36mevaluation�[0;34m(agent, gain_factor)�[0m
2026-07-18T05:56:29.3282730Z �[1;32m     25�[0m target_x �[38;5;241m=�[39m []; target_y �[38;5;241m=�[39m []; target_r �[38;5;241m=�[39m []
2026-07-18T05:56:29.3283552Z �[1;32m     26�[0m rewarded �[38;5;241m=�[39m []; state_input_ �[38;5;241m=�[39m []
2026-07-18T05:56:29.3284345Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m target_position �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtarget_positions�[49m�[43m)�[49m:
2026-07-18T05:56:29.3285575Z �[1;32m     29�[0m     state �[38;5;241m=�[39m env�[38;5;241m.�[39mreset(target_position�[38;5;241m=�[39mtarget_position, gain�[38;5;241m=�[39marg�[38;5;241m.�[39mprocess_gain_default �[38;5;241m*�[39m gain_factor)
2026-07-18T05:56:29.3286539Z �[1;32m     30�[0m     agent�[38;5;241m.�[39mobs_step�[38;5;241m.�[39mreset(env�[38;5;241m.�[39mgain)
2026-07-18T05:56:29.3286881Z 
2026-07-18T05:56:29.3287536Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:250�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T05:56:29.3288802Z �[1;32m    248�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T05:56:29.3289540Z �[1;32m    249�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T05:56:29.3290456Z �[0;32m--> 250�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T05:56:29.3290994Z �[1;32m    252�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T05:56:29.3291551Z �[1;32m    253�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T05:56:29.3291893Z 
2026-07-18T05:56:29.3292494Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:209�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T05:56:29.3293273Z �[1;32m    206�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T05:56:29.3293821Z �[1;32m    207�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T05:56:29.3294605Z �[1;32m    208�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T05:56:29.3295890Z �[0;32m--> 209�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T05:56:29.3296678Z 
2026-07-18T05:56:29.3296840Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T05:56:29.3297047Z 
2026-07-18T05:56:29.4851892Z ##[error]Process completed with exit code 1.

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb

2026-07-18T05:55:54.3686448Z Executing tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb
2026-07-18T05:55:55.2947017Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T05:56:05.3646533Z tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb failed quality control.
2026-07-18T05:56:05.3647409Z ============================== Failure ==============================
2026-07-18T05:56:05.3648248Z An error occurred while executing the following cell:
2026-07-18T05:56:05.3648860Z ------------------
2026-07-18T05:56:05.3649585Z train_sizes = np.linspace(0.25, 0.9, 5)
2026-07-18T05:56:05.3650314Z bound_performance, bound_models = test_performance(bound_phis, ys_rastrigin, train_sizes)
2026-07-18T05:56:05.3651347Z bundle_performance, bundle_models = test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-18T05:56:05.3653055Z plot_performance(bound_performance, bundle_performance, train_sizes * bound_phis.shape[0], "Rastrigin function - RMSE")
2026-07-18T05:56:05.3653958Z plt.ylim((-1, 20))
2026-07-18T05:56:05.3654269Z ------------------
2026-07-18T05:56:05.3654455Z 
2026-07-18T05:56:05.3654462Z 
2026-07-18T05:56:05.3655058Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T05:56:05.3655893Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T05:56:05.3656528Z Cell �[0;32mIn[15], line 2�[0m
2026-07-18T05:56:05.3657448Z �[1;32m      1�[0m train_sizes �[38;5;241m=�[39m np�[38;5;241m.�[39mlinspace(�[38;5;241m0.25�[39m, �[38;5;241m0.9�[39m, �[38;5;241m5�[39m)
2026-07-18T05:56:05.3659613Z �[0;32m----> 2�[0m bound_performance, bound_models �[38;5;241m=�[39m �[43mtest_performance�[49m�[43m(�[49m�[43mbound_phis�[49m�[43m,�[49m�[43m �[49m�[43mys_rastrigin�[49m�[43m,�[49m�[43m �[49m�[43mtrain_sizes�[49m�[43m)�[49m
2026-07-18T05:56:05.3661404Z �[1;32m      3�[0m bundle_performance, bundle_models �[38;5;241m=�[39m test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-18T05:56:05.3663296Z �[1;32m      4�[0m plot_performance(bound_performance, bundle_performance, train_sizes �[38;5;241m*�[39m bound_phis�[38;5;241m.�[39mshape[�[38;5;241m0�[39m], �[38;5;124m"�[39m�[38;5;124mRastrigin function - RMSE�[39m�[38;5;124m"�[39m)
2026-07-18T05:56:05.3664434Z 
2026-07-18T05:56:05.3664861Z Cell �[0;32mIn[14], line 24�[0m, in �[0;36mtest_performance�[0;34m(xs, ys, train_sizes)�[0m
2026-07-18T05:56:05.3665590Z �[1;32m     21�[0m performance �[38;5;241m=�[39m []
2026-07-18T05:56:05.3666120Z �[1;32m     23�[0m models �[38;5;241m=�[39m []
2026-07-18T05:56:05.3667050Z �[0;32m---> 24�[0m �[38;5;28;01mfor�[39;00m train_size �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtrain_sizes�[49m�[43m)�[49m:
2026-07-18T05:56:05.3668680Z �[1;32m     25�[0m     X_train, X_test, y_train, y_test �[38;5;241m=�[39m train_test_split(xs, ys, random_state�[38;5;241m=�[39m�[38;5;241m1�[39m, train_size�[38;5;241m=�[39mtrain_size)
2026-07-18T05:56:05.3670393Z �[1;32m     26�[0m     regr �[38;5;241m=�[39m LinearRegression()�[38;5;241m.�[39mfit(X_train, y_train)
2026-07-18T05:56:05.3670908Z 
2026-07-18T05:56:05.3671888Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:250�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T05:56:05.3673308Z �[1;32m    248�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T05:56:05.3674650Z �[1;32m    249�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T05:56:05.3675691Z �[0;32m--> 250�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T05:56:05.3676491Z �[1;32m    252�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T05:56:05.3677292Z �[1;32m    253�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T05:56:05.3677804Z 
2026-07-18T05:56:05.3678698Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:209�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T05:56:05.3680067Z �[1;32m    206�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T05:56:05.3680894Z �[1;32m    207�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T05:56:05.3682090Z �[1;32m    208�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T05:56:05.3684192Z �[0;32m--> 209�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T05:56:05.3685419Z 
2026-07-18T05:56:05.3685886Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T05:56:05.3686206Z 
2026-07-18T05:56:05.6945403Z ##[error]Process completed with exit code 1.

tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

2026-07-18T05:56:01.6382488Z Executing tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb
2026-07-18T05:56:02.7604459Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T05:57:22.9363694Z tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb failed quality control.
2026-07-18T05:57:22.9364248Z An error occurred while executing the following cell:
2026-07-18T05:57:22.9364611Z ------------------
2026-07-18T05:57:22.9364952Z # @title Make sure you execute this cell to observe the plot!
2026-07-18T05:57:22.9365562Z 
2026-07-18T05:57:22.9365655Z set_seed(42)
2026-07-18T05:57:22.9365785Z 
2026-07-18T05:57:22.9365877Z #define environment
2026-07-18T05:57:22.9366116Z env = ChangingEnv()
2026-07-18T05:57:22.9366356Z replay = ReplayBufferSolution()
2026-07-18T05:57:22.9366542Z 
2026-07-18T05:57:22.9366651Z #define agent and optimizer
2026-07-18T05:57:22.9366927Z agent = ActorCritic(hidden_size = 100)
2026-07-18T05:57:22.9367587Z optimizer_func = optim.RMSprop
2026-07-18T05:57:22.9367778Z 
2026-07-18T05:57:22.9367863Z #train agent
2026-07-18T05:57:22.9368152Z train_agent_with_replay(env, agent, optimizer_func, replay)
2026-07-18T05:57:22.9368422Z 
2026-07-18T05:57:22.9368660Z rewards, max_rewards = evaluate_agent(env, agent, num_evaluation_trials = 5000)
2026-07-18T05:57:22.9369122Z plot_confusion_matrix(rewards, max_rewards)
2026-07-18T05:57:22.9369423Z ------------------
2026-07-18T05:57:22.9369563Z 
2026-07-18T05:57:22.9369568Z 
2026-07-18T05:57:22.9370010Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T05:57:22.9370597Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T05:57:22.9371046Z Cell �[0;32mIn[32], line 14�[0m
2026-07-18T05:57:22.9371481Z �[1;32m     11�[0m optimizer_func �[38;5;241m=�[39m optim�[38;5;241m.�[39mRMSprop
2026-07-18T05:57:22.9371931Z ============================== Failure ==============================
2026-07-18T05:57:22.9372664Z �[1;32m     13�[0m �[38;5;66;03m#train agent�[39;00m
2026-07-18T05:57:22.9373962Z �[0;32m---> 14�[0m �[43mtrain_agent_with_replay�[49m�[43m(�[49m�[43menv�[49m�[43m,�[49m�[43m �[49m�[43magent�[49m�[43m,�[49m�[43m �[49m�[43moptimizer_func�[49m�[43m,�[49m�[43m �[49m�[43mreplay�[49m�[43m)�[49m
2026-07-18T05:57:22.9375724Z �[1;32m     16�[0m rewards, max_rewards �[38;5;241m=�[39m evaluate_agent(env, agent, num_evaluation_trials �[38;5;241m=�[39m �[38;5;241m5000�[39m)
2026-07-18T05:57:22.9376975Z �[1;32m     17�[0m plot_confusion_matrix(rewards, max_rewards)
2026-07-18T05:57:22.9377329Z 
2026-07-18T05:57:22.9378236Z Cell �[0;32mIn[31], line 22�[0m, in �[0;36mtrain_agent_with_replay�[0;34m(env, agent, optimizer_func, replay, mode, training_mode, num_gradient_steps, num_trials)�[0m
2026-07-18T05:57:22.9380039Z �[1;32m     19�[0m optimizer �[38;5;241m=�[39m optimizer_func(agent�[38;5;241m.�[39mparameters(), agent�[38;5;241m.�[39mlearning_rate, eps�[38;5;241m=�[39m�[38;5;241m1e-5�[39m)
2026-07-18T05:57:22.9381421Z �[1;32m     21�[0m �[38;5;66;03m# Initialize TQDM progress bar�[39;00m
2026-07-18T05:57:22.9382881Z �[0;32m---> 22�[0m �[38;5;28;01mwith�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtotal�[49m�[38;5;241;43m=�[39;49m�[43mnum_gradient_steps�[49m�[43m)�[49m �[38;5;28;01mas�[39;00m pbar:
2026-07-18T05:57:22.9384382Z �[1;32m     23�[0m     �[38;5;28;01mfor�[39;00m index �[38;5;129;01min�[39;00m �[38;5;28mrange�[39m(num_gradient_steps):
2026-07-18T05:57:22.9385711Z �[1;32m     24�[0m         �[38;5;66;03m# For storing variables for training�[39;00m
2026-07-18T05:57:22.9386369Z �[1;32m     25�[0m         log_probs �[38;5;241m=�[39m []
2026-07-18T05:57:22.9386594Z 
2026-07-18T05:57:22.9387232Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:250�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T05:57:22.9388154Z �[1;32m    248�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T05:57:22.9388845Z �[1;32m    249�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T05:57:22.9389505Z �[0;32m--> 250�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T05:57:22.9390014Z �[1;32m    252�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T05:57:22.9390552Z �[1;32m    253�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T05:57:22.9390882Z 
2026-07-18T05:57:22.9391473Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:209�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T05:57:22.9392236Z �[1;32m    206�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T05:57:22.9392782Z �[1;32m    207�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T05:57:22.9393751Z �[1;32m    208�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T05:57:22.9395450Z �[0;32m--> 209�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T05:57:22.9396579Z 
2026-07-18T05:57:22.9396765Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T05:57:22.9396978Z 
2026-07-18T05:57:23.1637068Z ##[error]Process completed with exit code 1.

github-actions · 2026-07-18T06:05:14Z

Follow-up PR Created

A follow-up PR has been created for the notebooks that failed to process:

Follow-up PR: #520
Branch: reprocess-pr519-20260718060510

The failed notebooks have been reverted to their main branch versions in this PR.
Once this PR is merged, the follow-up PR can be used to reprocess the failed notebooks independently.

github-actions · 2026-07-18T14:19:08Z

Notebook Processing Failure Context

projects/project-notebooks/Macrocircuits.ipynb

2026-07-18T14:09:36.5989901Z Executing projects/project-notebooks/Macrocircuits.ipynb
2026-07-18T14:09:37.7019674Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T14:09:41.0373581Z projects/project-notebooks/Macrocircuits.ipynb failed quality control.
2026-07-18T14:09:41.0375146Z ============================== Failure ==============================
2026-07-18T14:09:41.0375886Z An error occurred while executing the following cell:
2026-07-18T14:09:41.0376448Z ------------------
2026-07-18T14:09:41.0377168Z #@title Installing Dependencies (Colab GPU case, uncomment if you want to use this one)
2026-07-18T14:09:41.0377830Z 
2026-07-18T14:09:41.0378001Z import distutils.util
2026-07-18T14:09:41.0378394Z import os
2026-07-18T14:09:41.0378735Z import subprocess
2026-07-18T14:09:41.0379154Z if subprocess.run('nvidia-smi').returncode:
2026-07-18T14:09:41.0379681Z   raise RuntimeError(
2026-07-18T14:09:41.0380095Z       'Cannot communicate with GPU. '
2026-07-18T14:09:41.0381079Z       'Make sure you are using a GPU Colab runtime. '
2026-07-18T14:09:41.0381749Z       'Go to the Runtime menu and select Choose runtime type.')
2026-07-18T14:09:41.0382197Z 
2026-07-18T14:09:41.0382512Z # Add an ICD config so that glvnd can pick up the Nvidia EGL driver.
2026-07-18T14:09:41.0383399Z # This is usually installed as part of an Nvidia driver package, but the Colab
2026-07-18T14:09:41.0384637Z # kernel doesn't install its driver via APT, and as a result the ICD is missing.
2026-07-18T14:09:41.0385445Z # (https://github.com/NVIDIA/libglvnd/blob/master/src/EGL/icd_enumeration.md)
2026-07-18T14:09:41.0386173Z NVIDIA_ICD_CONFIG_PATH = '/usr/share/glvnd/egl_vendor.d/10_nvidia.json'
2026-07-18T14:09:41.0386752Z if not os.path.exists(NVIDIA_ICD_CONFIG_PATH):
2026-07-18T14:09:41.0387210Z   with open(NVIDIA_ICD_CONFIG_PATH, 'w') as f:
2026-07-18T14:09:41.0387609Z     f.write("""{
2026-07-18T14:09:41.0387907Z     "file_format_version" : "1.0.0",
2026-07-18T14:09:41.0388267Z     "ICD" : {
2026-07-18T14:09:41.0388567Z         "library_path" : "libEGL_nvidia.so.0"
2026-07-18T14:09:41.0388950Z     }
2026-07-18T14:09:41.0389195Z }
2026-07-18T14:09:41.0389430Z """)
2026-07-18T14:09:41.0389569Z 
2026-07-18T14:09:41.0389715Z print('Installing dm_control...')
2026-07-18T14:09:41.0390279Z !pip install dm_control>=1.0.16 --quiet
2026-07-18T14:09:41.0390555Z 
2026-07-18T14:09:41.0390832Z # Configure dm_control to use the EGL rendering backend (requires GPU)
2026-07-18T14:09:41.0391363Z %env MUJOCO_GL=egl
2026-07-18T14:09:41.0391545Z 
2026-07-18T14:09:41.0391866Z !echo Installed dm_control $(pip show dm_control | grep -Po "(?<=Version: ).+")
2026-07-18T14:09:41.0392460Z !pip install dm-acme --quiet
2026-07-18T14:09:41.0392806Z !mkdir output_videos
2026-07-18T14:09:41.0393108Z ------------------
2026-07-18T14:09:41.0393277Z 
2026-07-18T14:09:41.0393282Z 
2026-07-18T14:09:41.0393831Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T14:09:41.0395070Z �[0;31mFileNotFoundError�[0m                         Traceback (most recent call last)
2026-07-18T14:09:41.0395620Z Cell �[0;32mIn[7], line 6�[0m
2026-07-18T14:09:41.0396100Z �[1;32m      4�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01mos�[39;00m
2026-07-18T14:09:41.0396766Z �[1;32m      5�[0m �[38;5;28;01mimport�[39;00m�[38;5;250m �[39m�[38;5;21;01msubprocess�[39;00m
2026-07-18T14:09:41.0397987Z �[0;32m----> 6�[0m �[38;5;28;01mif�[39;00m �[43msubprocess�[49m�[38;5;241;43m.�[39;49m�[43mrun�[49m�[43m(�[49m�[38;5;124;43m'�[39;49m�[38;5;124;43mnvidia-smi�[39;49m�[38;5;124;43m'�[39;49m�[43m)�[49m�[38;5;241m.�[39mreturncode:
2026-07-18T14:09:41.0399061Z �[1;32m      7�[0m   �[38;5;28;01mraise�[39;00m �[38;5;167;01mRuntimeError�[39;00m(
2026-07-18T14:09:41.0399744Z �[1;32m      8�[0m       �[38;5;124m'�[39m�[38;5;124mCannot communicate with GPU. �[39m�[38;5;124m'�[39m
2026-07-18T14:09:41.0400569Z �[1;32m      9�[0m       �[38;5;124m'�[39m�[38;5;124mMake sure you are using a GPU Colab runtime. �[39m�[38;5;124m'�[39m
2026-07-18T14:09:41.0401500Z �[1;32m     10�[0m       �[38;5;124m'�[39m�[38;5;124mGo to the Runtime menu and select Choose runtime type.�[39m�[38;5;124m'�[39m)
2026-07-18T14:09:41.0402382Z �[1;32m     12�[0m �[38;5;66;03m# Add an ICD config so that glvnd can pick up the Nvidia EGL driver.�[39;00m
2026-07-18T14:09:41.0403268Z �[1;32m     13�[0m �[38;5;66;03m# This is usually installed as part of an Nvidia driver package, but the Colab�[39;00m
2026-07-18T14:09:41.0404425Z �[1;32m     14�[0m �[38;5;66;03m# kernel doesn't install its driver via APT, and as a result the ICD is missing.�[39;00m
2026-07-18T14:09:41.0405380Z �[1;32m     15�[0m �[38;5;66;03m# (https://github.com/NVIDIA/libglvnd/blob/master/src/EGL/icd_enumeration.md)�[39;00m
2026-07-18T14:09:41.0405819Z 
2026-07-18T14:09:41.0406492Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/subprocess.py:503�[0m, in �[0;36mrun�[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)�[0m
2026-07-18T14:09:41.0407714Z �[1;32m    500�[0m     kwargs[�[38;5;124m'�[39m�[38;5;124mstdout�[39m�[38;5;124m'�[39m] �[38;5;241m=�[39m PIPE
2026-07-18T14:09:41.0408428Z �[1;32m    501�[0m     kwargs[�[38;5;124m'�[39m�[38;5;124mstderr�[39m�[38;5;124m'�[39m] �[38;5;241m=�[39m PIPE
2026-07-18T14:09:41.0409572Z �[0;32m--> 503�[0m �[38;5;28;01mwith�[39;00m �[43mPopen�[49m�[43m(�[49m�[38;5;241;43m*�[39;49m�[43mpopenargs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m*�[39;49m�[38;5;241;43m*�[39;49m�[43mkwargs�[49m�[43m)�[49m �[38;5;28;01mas�[39;00m process:
2026-07-18T14:09:41.0410434Z �[1;32m    504�[0m     �[38;5;28;01mtry�[39;00m:
2026-07-18T14:09:41.0411160Z �[1;32m    505�[0m         stdout, stderr �[38;5;241m=�[39m process�[38;5;241m.�[39mcommunicate(�[38;5;28minput�[39m, timeout�[38;5;241m=�[39mtimeout)
2026-07-18T14:09:41.0411654Z 
2026-07-18T14:09:41.0413189Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/subprocess.py:971�[0m, in �[0;36mPopen.__init__�[0;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize)�[0m
2026-07-18T14:09:41.0415216Z �[1;32m    967�[0m         �[38;5;28;01mif�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtext_mode:
2026-07-18T14:09:41.0416182Z �[1;32m    968�[0m             �[38;5;28mself�[39m�[38;5;241m.�[39mstderr �[38;5;241m=�[39m io�[38;5;241m.�[39mTextIOWrapper(�[38;5;28mself�[39m�[38;5;241m.�[39mstderr,
2026-07-18T14:09:41.0416952Z �[1;32m    969�[0m                     encoding�[38;5;241m=�[39mencoding, errors�[38;5;241m=�[39merrors)
2026-07-18T14:09:41.0418056Z �[0;32m--> 971�[0m     �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43m_execute_child�[49m�[43m(�[49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[43mexecutable�[49m�[43m,�[49m�[43m �[49m�[43mpreexec_fn�[49m�[43m,�[49m�[43m �[49m�[43mclose_fds�[49m�[43m,�[49m
2026-07-18T14:09:41.0419221Z �[1;32m    972�[0m �[43m                        �[49m�[43mpass_fds�[49m�[43m,�[49m�[43m �[49m�[43mcwd�[49m�[43m,�[49m�[43m �[49m�[43menv�[49m�[43m,�[49m
2026-07-18T14:09:41.0420129Z �[1;32m    973�[0m �[43m                        �[49m�[43mstartupinfo�[49m�[43m,�[49m�[43m �[49m�[43mcreationflags�[49m�[43m,�[49m�[43m �[49m�[43mshell�[49m�[43m,�[49m
2026-07-18T14:09:41.0420933Z �[1;32m    974�[0m �[43m                        �[49m�[43mp2cread�[49m�[43m,�[49m�[43m �[49m�[43mp2cwrite�[49m�[43m,�[49m
2026-07-18T14:09:41.0421590Z �[1;32m    975�[0m �[43m                        �[49m�[43mc2pread�[49m�[43m,�[49m�[43m �[49m�[43mc2pwrite�[49m�[43m,�[49m
2026-07-18T14:09:41.0422247Z �[1;32m    976�[0m �[43m                        �[49m�[43merrread�[49m�[43m,�[49m�[43m �[49m�[43merrwrite�[49m�[43m,�[49m
2026-07-18T14:09:41.0422802Z �[1;32m    977�[0m �[43m                        �[49m�[43mrestore_signals�[49m�[43m,�[49m
2026-07-18T14:09:41.0423626Z �[1;32m    978�[0m �[43m                        �[49m�[43mgid�[49m�[43m,�[49m�[43m �[49m�[43mgids�[49m�[43m,�[49m�[43m �[49m�[43muid�[49m�[43m,�[49m�[43m �[49m�[43mumask�[49m�[43m,�[49m
2026-07-18T14:09:41.0424938Z �[1;32m    979�[0m �[43m                        �[49m�[43mstart_new_session�[49m�[43m)�[49m
2026-07-18T14:09:41.0425381Z �[1;32m    980�[0m �[38;5;28;01mexcept�[39;00m:
2026-07-18T14:09:41.0425833Z �[1;32m    981�[0m     �[38;5;66;03m# Cleanup if the child failed starting.�[39;00m
2026-07-18T14:09:41.0426902Z �[1;32m    982�[0m     �[38;5;28;01mfor�[39;00m f �[38;5;129;01min�[39;00m �[38;5;28mfilter�[39m(�[38;5;28;01mNone�[39;00m, (�[38;5;28mself�[39m�[38;5;241m.�[39mstdin, �[38;5;28mself�[39m�[38;5;241m.�[39mstdout, �[38;5;28mself�[39m�[38;5;241m.�[39mstderr)):
2026-07-18T14:09:41.0427599Z 
2026-07-18T14:09:41.0429064Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/subprocess.py:1863�[0m, in �[0;36mPopen._execute_child�[0;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, restore_signals, gid, gids, uid, umask, start_new_session)�[0m
2026-07-18T14:09:41.0430523Z �[1;32m   1861�[0m     �[38;5;28;01mif�[39;00m errno_num �[38;5;241m!=�[39m �[38;5;241m0�[39m:
2026-07-18T14:09:41.0431073Z �[1;32m   1862�[0m         err_msg �[38;5;241m=�[39m os�[38;5;241m.�[39mstrerror(errno_num)
2026-07-18T14:09:41.0431680Z �[0;32m-> 1863�[0m     �[38;5;28;01mraise�[39;00m child_exception_type(errno_num, err_msg, err_filename)
2026-07-18T14:09:41.0432250Z �[1;32m   1864�[0m �[38;5;28;01mraise�[39;00m child_exception_type(err_msg)
2026-07-18T14:09:41.0432511Z 
2026-07-18T14:09:41.0432788Z �[0;31mFileNotFoundError�[0m: [Errno 2] No such file or directory: 'nvidia-smi'
2026-07-18T14:09:41.0433106Z 
2026-07-18T14:09:41.3036158Z ##[error]Process completed with exit code 1.

tutorials/W1D1_Generalization/W1D1_Tutorial1.ipynb

2026-07-18T14:09:40.5021569Z �[1;32m   1023�[0m �[43m        �[49m�[43mendpoint�[49m�[38;5;241;43m=�[39;49m�[43mendpoint�[49m�[43m,�[49m
2026-07-18T14:09:40.5022605Z �[1;32m   1024�[0m �[43m        �[49m�[43metag_timeout�[49m�[38;5;241;43m=�[39;49m�[43metag_timeout�[49m�[43m,�[49m
2026-07-18T14:09:40.5023619Z �[1;32m   1025�[0m �[43m        �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mhf_headers�[49m�[43m,�[49m
2026-07-18T14:09:40.5024604Z �[1;32m   1026�[0m �[43m        �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-18T14:09:40.5025558Z �[1;32m   1027�[0m �[43m        �[49m�[43mtoken�[49m�[38;5;241;43m=�[39;49m�[43mtoken�[49m�[43m,�[49m
2026-07-18T14:09:40.5026638Z �[1;32m   1028�[0m �[43m        �[49m�[38;5;66;43;03m# Additional options�[39;49;00m
2026-07-18T14:09:40.5027633Z �[1;32m   1029�[0m �[43m        �[49m�[43mlocal_files_only�[49m�[38;5;241;43m=�[39;49m�[43mlocal_files_only�[49m�[43m,�[49m
2026-07-18T14:09:40.5028763Z �[1;32m   1030�[0m �[43m        �[49m�[43mforce_download�[49m�[38;5;241;43m=�[39;49m�[43mforce_download�[49m�[43m,�[49m
2026-07-18T14:09:40.5029546Z �[1;32m   1031�[0m �[43m    �[49m�[43m)�[49m
2026-07-18T14:09:40.5029830Z 
2026-07-18T14:09:40.5031621Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:1175�[0m, in �[0;36m_hf_hub_download_to_cache_dir�[0;34m(cache_dir, repo_id, filename, repo_type, revision, endpoint, etag_timeout, headers, proxies, token, local_files_only, force_download)�[0m
2026-07-18T14:09:40.5034043Z �[1;32m   1172�[0m �[38;5;66;03m# Local file doesn't exist or etag isn't a match => retrieve file from remote (or cache)�[39;00m
2026-07-18T14:09:40.5035048Z �[1;32m   1174�[0m �[38;5;28;01mwith�[39;00m WeakFileLock(lock_path):
2026-07-18T14:09:40.5035726Z �[0;32m-> 1175�[0m     �[43m_download_to_tmp_and_move�[49m�[43m(�[49m
2026-07-18T14:09:40.5037612Z �[1;32m   1176�[0m �[43m        �[49m�[43mincomplete_path�[49m�[38;5;241;43m=�[39;49m�[43mPath�[49m�[43m(�[49m�[43mblob_path�[49m�[43m �[49m�[38;5;241;43m+�[39;49m�[43m �[49m�[38;5;124;43m"�[39;49m�[38;5;124;43m.incomplete�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m�[43m,�[49m
2026-07-18T14:09:40.5039546Z �[1;32m   1177�[0m �[43m        �[49m�[43mdestination_path�[49m�[38;5;241;43m=�[39;49m�[43mPath�[49m�[43m(�[49m�[43mblob_path�[49m�[43m)�[49m�[43m,�[49m
2026-07-18T14:09:40.5040817Z �[1;32m   1178�[0m �[43m        �[49m�[43murl_to_download�[49m�[38;5;241;43m=�[39;49m�[43murl_to_download�[49m�[43m,�[49m
2026-07-18T14:09:40.5041875Z �[1;32m   1179�[0m �[43m        �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-18T14:09:40.5042842Z �[1;32m   1180�[0m �[43m        �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mheaders�[49m�[43m,�[49m
2026-07-18T14:09:40.5043863Z �[1;32m   1181�[0m �[43m        �[49m�[43mexpected_size�[49m�[38;5;241;43m=�[39;49m�[43mexpected_size�[49m�[43m,�[49m
2026-07-18T14:09:40.5044897Z �[1;32m   1182�[0m �[43m        �[49m�[43mfilename�[49m�[38;5;241;43m=�[39;49m�[43mfilename�[49m�[43m,�[49m
2026-07-18T14:09:40.5045903Z �[1;32m   1183�[0m �[43m        �[49m�[43mforce_download�[49m�[38;5;241;43m=�[39;49m�[43mforce_download�[49m�[43m,�[49m
2026-07-18T14:09:40.5047082Z �[1;32m   1184�[0m �[43m        �[49m�[43metag�[49m�[38;5;241;43m=�[39;49m�[43metag�[49m�[43m,�[49m
2026-07-18T14:09:40.5048048Z �[1;32m   1185�[0m �[43m        �[49m�[43mxet_file_data�[49m�[38;5;241;43m=�[39;49m�[43mxet_file_data�[49m�[43m,�[49m
2026-07-18T14:09:40.5048784Z �[1;32m   1186�[0m �[43m    �[49m�[43m)�[49m
2026-07-18T14:09:40.5049644Z �[1;32m   1187�[0m     �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m os�[38;5;241m.�[39mpath�[38;5;241m.�[39mexists(pointer_path):
2026-07-18T14:09:40.5050959Z �[1;32m   1188�[0m         _create_symlink(blob_path, pointer_path, new_blob�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)
2026-07-18T14:09:40.5051536Z 
2026-07-18T14:09:40.5053195Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:1742�[0m, in �[0;36m_download_to_tmp_and_move�[0;34m(incomplete_path, destination_path, url_to_download, proxies, headers, expected_size, filename, force_download, etag, xet_file_data)�[0m
2026-07-18T14:09:40.5055753Z �[1;32m   1735�[0m         �[38;5;28;01mif�[39;00m xet_file_data �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m �[38;5;129;01mand�[39;00m �[38;5;129;01mnot�[39;00m constants�[38;5;241m.�[39mHF_HUB_DISABLE_XET:
2026-07-18T14:09:40.5057214Z �[1;32m   1736�[0m             logger�[38;5;241m.�[39mwarning(
2026-07-18T14:09:40.5058571Z �[1;32m   1737�[0m                 �[38;5;124m"�[39m�[38;5;124mXet Storage is enabled for this repo, but the �[39m�[38;5;124m'�[39m�[38;5;124mhf_xet�[39m�[38;5;124m'�[39m�[38;5;124m package is not installed. �[39m�[38;5;124m"�[39m
2026-07-18T14:09:40.5060049Z �[1;32m   1738�[0m                 �[38;5;124m"�[39m�[38;5;124mFalling back to regular HTTP download. �[39m�[38;5;124m"�[39m
2026-07-18T14:09:40.5061549Z �[1;32m   1739�[0m                 �[38;5;124m"�[39m�[38;5;124mFor better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`�[39m�[38;5;124m"�[39m
2026-07-18T14:09:40.5062601Z �[1;32m   1740�[0m             )
2026-07-18T14:09:40.5063088Z �[0;32m-> 1742�[0m         �[43mhttp_get�[49m�[43m(�[49m
2026-07-18T14:09:40.5063726Z �[1;32m   1743�[0m �[43m            �[49m�[43murl_to_download�[49m�[43m,�[49m
2026-07-18T14:09:40.5064551Z �[1;32m   1744�[0m �[43m            �[49m�[43mf�[49m�[43m,�[49m
2026-07-18T14:09:40.5065353Z �[1;32m   1745�[0m �[43m            �[49m�[43mproxies�[49m�[38;5;241;43m=�[39;49m�[43mproxies�[49m�[43m,�[49m
2026-07-18T14:09:40.5066662Z �[1;32m   1746�[0m �[43m            �[49m�[43mresume_size�[49m�[38;5;241;43m=�[39;49m�[43mresume_size�[49m�[43m,�[49m
2026-07-18T14:09:40.5067891Z �[1;32m   1747�[0m �[43m            �[49m�[43mheaders�[49m�[38;5;241;43m=�[39;49m�[43mheaders�[49m�[43m,�[49m
2026-07-18T14:09:40.5068961Z �[1;32m   1748�[0m �[43m            �[49m�[43mexpected_size�[49m�[38;5;241;43m=�[39;49m�[43mexpected_size�[49m�[43m,�[49m
2026-07-18T14:09:40.5069733Z �[1;32m   1749�[0m �[43m        �[49m�[43m)�[49m
2026-07-18T14:09:40.5071048Z �[1;32m   1751�[0m logger�[38;5;241m.�[39minfo(�[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mDownload complete. Moving file to �[39m�[38;5;132;01m{�[39;00mdestination_path�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m)
2026-07-18T14:09:40.5072310Z �[1;32m   1752�[0m _chmod_and_move(incomplete_path, destination_path)
2026-07-18T14:09:40.5072704Z 
2026-07-18T14:09:40.5074110Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/file_download.py:455�[0m, in �[0;36mhttp_get�[0;34m(url, temp_file, proxies, resume_size, headers, expected_size, displayed_filename, _nb_retries, _tqdm_bar)�[0m
2026-07-18T14:09:40.5076784Z �[1;32m    448�[0m     displayed_filename �[38;5;241m=�[39m �[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124m(…)�[39m�[38;5;132;01m{�[39;00mdisplayed_filename[�[38;5;241m-�[39m�[38;5;241m40�[39m:]�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m
2026-07-18T14:09:40.5077725Z �[1;32m    450�[0m consistency_error_message �[38;5;241m=�[39m (
2026-07-18T14:09:40.5078694Z �[1;32m    451�[0m     �[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mConsistency check failed: file should be of size �[39m�[38;5;132;01m{�[39;00mexpected_size�[38;5;132;01m}�[39;00m�[38;5;124m but has size�[39m�[38;5;124m"�[39m
2026-07-18T14:09:40.5080692Z �[1;32m    452�[0m     �[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124m �[39m�[38;5;130;01m{{�[39;00m�[38;5;124mactual_size�[39m�[38;5;130;01m}}�[39;00m�[38;5;124m (�[39m�[38;5;132;01m{�[39;00mdisplayed_filename�[38;5;132;01m}�[39;00m�[38;5;124m).�[39m�[38;5;130;01m\n�[39;00m�[38;5;124mThis is usually due to network issues while downloading the file.�[39m�[38;5;124m"�[39m
2026-07-18T14:09:40.5082042Z �[1;32m    453�[0m     �[38;5;124m"�[39m�[38;5;124m Please retry with `force_download=True`.�[39m�[38;5;124m"�[39m
2026-07-18T14:09:40.5082519Z �[1;32m    454�[0m )
2026-07-18T14:09:40.5082949Z �[0;32m--> 455�[0m progress_cm �[38;5;241m=�[39m �[43m_get_progress_bar_context�[49m�[43m(�[49m
2026-07-18T14:09:40.5083595Z �[1;32m    456�[0m �[43m    �[49m�[43mdesc�[49m�[38;5;241;43m=�[39;49m�[43mdisplayed_filename�[49m�[43m,�[49m
2026-07-18T14:09:40.5084489Z �[1;32m    457�[0m �[43m    �[49m�[43mlog_level�[49m�[38;5;241;43m=�[39;49m�[43mlogger�[49m�[38;5;241;43m.�[39;49m�[43mgetEffectiveLevel�[49m�[43m(�[49m�[43m)�[49m�[43m,�[49m
2026-07-18T14:09:40.5088191Z �[1;32m    458�[0m �[43m    �[49m�[43mtotal�[49m�[38;5;241;43m=�[39;49m�[43mtotal�[49m�[43m,�[49m
2026-07-18T14:09:40.5089202Z �[1;32m    459�[0m �[43m    �[49m�[43minitial�[49m�[38;5;241;43m=�[39;49m�[43mresume_size�[49m�[43m,�[49m
2026-07-18T14:09:40.5090583Z �[1;32m    460�[0m �[43m    �[49m�[43mname�[49m�[38;5;241;43m=�[39;49m�[38;5;124;43m"�[39;49m�[38;5;124;43mhuggingface_hub.http_get�[39;49m�[38;5;124;43m"�[39;49m�[43m,�[49m
2026-07-18T14:09:40.5091615Z �[1;32m    461�[0m �[43m    �[49m�[43m_tqdm_bar�[49m�[38;5;241;43m=�[39;49m�[43m_tqdm_bar�[49m�[43m,�[49m
2026-07-18T14:09:40.5092081Z �[1;32m    462�[0m �[43m�[49m�[43m)�[49m
2026-07-18T14:09:40.5092542Z �[1;32m    464�[0m �[38;5;28;01mwith�[39;00m progress_cm �[38;5;28;01mas�[39;00m progress:
2026-07-18T14:09:40.5093760Z �[1;32m    465�[0m     �[38;5;28;01mif�[39;00m hf_transfer �[38;5;129;01mand�[39;00m total �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m �[38;5;129;01mand�[39;00m total �[38;5;241m>�[39m �[38;5;241m5�[39m �[38;5;241m*�[39m constants�[38;5;241m.�[39mDOWNLOAD_CHUNK_SIZE:
2026-07-18T14:09:40.5094803Z 
2026-07-18T14:09:40.5095690Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/utils/tqdm.py:299�[0m, in �[0;36m_get_progress_bar_context�[0;34m(desc, log_level, total, initial, unit, unit_scale, name, _tqdm_bar)�[0m
2026-07-18T14:09:40.5097051Z �[1;32m    294�[0m     �[38;5;28;01mreturn�[39;00m nullcontext(_tqdm_bar)
2026-07-18T14:09:40.5097697Z �[1;32m    295�[0m     �[38;5;66;03m# ^ `contextlib.nullcontext` mimics a context manager that does nothing�[39;00m
2026-07-18T14:09:40.5098470Z �[1;32m    296�[0m     �[38;5;66;03m#   Makes it easier to use the same code path for both cases but in the later�[39;00m
2026-07-18T14:09:40.5099212Z �[1;32m    297�[0m     �[38;5;66;03m#   case, the progress bar is not closed when exiting the context manager.�[39;00m
2026-07-18T14:09:40.5099796Z �[0;32m--> 299�[0m �[38;5;28;01mreturn�[39;00m �[43mtqdm�[49m�[43m(�[49m
2026-07-18T14:09:40.5100399Z �[1;32m    300�[0m �[43m    �[49m�[43munit�[49m�[38;5;241;43m=�[39;49m�[43munit�[49m�[43m,�[49m
2026-07-18T14:09:40.5101021Z �[1;32m    301�[0m �[43m    �[49m�[43munit_scale�[49m�[38;5;241;43m=�[39;49m�[43munit_scale�[49m�[43m,�[49m
2026-07-18T14:09:40.5101636Z �[1;32m    302�[0m �[43m    �[49m�[43mtotal�[49m�[38;5;241;43m=�[39;49m�[43mtotal�[49m�[43m,�[49m
2026-07-18T14:09:40.5102233Z �[1;32m    303�[0m �[43m    �[49m�[43minitial�[49m�[38;5;241;43m=�[39;49m�[43minitial�[49m�[43m,�[49m
2026-07-18T14:09:40.5102810Z �[1;32m    304�[0m �[43m    �[49m�[43mdesc�[49m�[38;5;241;43m=�[39;49m�[43mdesc�[49m�[43m,�[49m
2026-07-18T14:09:40.5103700Z �[1;32m    305�[0m �[43m    �[49m�[43mdisable�[49m�[38;5;241;43m=�[39;49m�[43mis_tqdm_disabled�[49m�[43m(�[49m�[43mlog_level�[49m�[38;5;241;43m=�[39;49m�[43mlog_level�[49m�[43m)�[49m�[43m,�[49m
2026-07-18T14:09:40.5104528Z �[1;32m    306�[0m �[43m    �[49m�[43mname�[49m�[38;5;241;43m=�[39;49m�[43mname�[49m�[43m,�[49m
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2026-07-18T14:09:40.5105129Z 
2026-07-18T14:09:40.5105777Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/huggingface_hub/utils/tqdm.py:225�[0m, in �[0;36mtqdm.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T14:09:40.5107021Z �[1;32m    223�[0m �[38;5;28;01mif�[39;00m are_progress_bars_disabled(name):
2026-07-18T14:09:40.5107694Z �[1;32m    224�[0m     kwargs[�[38;5;124m"�[39m�[38;5;124mdisable�[39m�[38;5;124m"�[39m] �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T14:09:40.5108863Z �[0;32m--> 225�[0m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[38;5;21;43m__init__�[39;49m�[43m(�[49m�[38;5;241;43m*�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m*�[39;49m�[38;5;241;43m*�[39;49m�[43mkwargs�[49m�[43m)�[49m
2026-07-18T14:09:40.5109556Z 
2026-07-18T14:09:40.5110179Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:250�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T14:09:40.5111108Z �[1;32m    248�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T14:09:40.5111811Z �[1;32m    249�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T14:09:40.5112480Z �[0;32m--> 250�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T14:09:40.5113005Z �[1;32m    252�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T14:09:40.5113554Z �[1;32m    253�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T14:09:40.5113893Z 
2026-07-18T14:09:40.5114524Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:209�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T14:09:40.5115286Z �[1;32m    206�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T14:09:40.5116259Z �[1;32m    207�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T14:09:40.5117102Z �[1;32m    208�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T14:09:40.5118389Z �[0;32m--> 209�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T14:09:40.5119142Z 
2026-07-18T14:09:40.5119300Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T14:09:40.5119507Z 
2026-07-18T14:09:40.7095335Z ##[error]Process completed with exit code 1.

tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb

2026-07-18T14:09:42.2367104Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T14:10:03.8583334Z tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb failed quality control.
2026-07-18T14:10:03.8583984Z ============================== Failure ==============================
2026-07-18T14:10:03.8585699Z An error occurred while executing the following cell:
2026-07-18T14:10:03.8586611Z ------------------
2026-07-18T14:10:03.8587261Z def perturb_inputs(model, inputs, perturbation_strength):
2026-07-18T14:10:03.8587968Z     device = inputs.device
2026-07-18T14:10:03.8588886Z     # Perturb the inputs by adding random noise scaled by the perturbation strength and input strength
2026-07-18T14:10:03.8590268Z     input_strength = torch.norm(inputs, p=2, dim=-1, keepdim=True)  # Calculate the L2 norm of inputs
2026-07-18T14:10:03.8592287Z     noise = torch.rand(inputs.shape[0], 1, inputs.shape[2], device=device) * perturbation_strength * input_strength
2026-07-18T14:10:03.8593417Z     perturbed_inputs = inputs + noise
2026-07-18T14:10:03.8593988Z     return perturbed_inputs
2026-07-18T14:10:03.8594321Z 
2026-07-18T14:10:03.8594667Z def compute_loss(model, inputs, targets, criterion, device):
2026-07-18T14:10:03.8595386Z     batch_size = inputs.size(0)
2026-07-18T14:10:03.8596117Z     h = model.init_hidden(batch_size).to(device)  # Initialize hidden state
2026-07-18T14:10:03.8597048Z     losses = []
2026-07-18T14:10:03.8597597Z     for t in range(inputs.shape[1]):  # Iterate over time steps
2026-07-18T14:10:03.8598341Z         model_output = model(inputs[:, t, :], h)
2026-07-18T14:10:03.8598977Z         output, h, *rest = model_output[:2]
2026-07-18T14:10:03.8599926Z         loss = criterion(output, targets[:, t])  # Assume targets is a sequence of same length as inputs
2026-07-18T14:10:03.8600872Z         losses.append(loss)
2026-07-18T14:10:03.8601458Z     mean_loss = torch.mean(torch.stack(losses)).item()
2026-07-18T14:10:03.8602113Z     return mean_loss
2026-07-18T14:10:03.8602385Z 
2026-07-18T14:10:03.8603011Z def test_perturbed_inputs(model, perturbation_strengths, test_loader, criterion, device, max_error):
2026-07-18T14:10:03.8604084Z     model.eval()  # Set the model to evaluation mode
2026-07-18T14:10:03.8604722Z     perturbation_results = []
2026-07-18T14:10:03.8605064Z 
2026-07-18T14:10:03.8605307Z     for strength in perturbation_strengths:
2026-07-18T14:10:03.8606223Z         all_errors = []  # Store all errors for each perturbation strength to compute mean and s.d.
2026-07-18T14:10:03.8607629Z         print(f"Testing perturbation strength {strength}")
2026-07-18T14:10:03.8608459Z         for iteration in tqdm(range(30)):  # Repeat the procedure 30 times
2026-07-18T14:10:03.8609298Z             batch_errors = []  # Store errors for each batch
2026-07-18T14:10:03.8609777Z 
2026-07-18T14:10:03.8610012Z             for inputs, targets in test_loader:
2026-07-18T14:10:03.8611012Z                 inputs, targets = inputs.to(device), targets.to(device)
2026-07-18T14:10:03.8611782Z                 # Compute error for original inputs
2026-07-18T14:10:03.8612655Z                 # original_loss = compute_loss(model, inputs, targets, criterion, device)
2026-07-18T14:10:03.8613527Z                 # Compute error for perturbed inputs
2026-07-18T14:10:03.8613951Z 
2026-07-18T14:10:03.8614314Z                 perturbed_inputs = perturb_inputs(model, inputs, strength)
2026-07-18T14:10:03.8615400Z                 perturbed_loss = compute_loss(model, perturbed_inputs, targets, criterion, device)
2026-07-18T14:10:03.8616156Z 
2026-07-18T14:10:03.8616373Z                 # Store the normalized error.
2026-07-18T14:10:03.8617108Z                 rel_error = perturbed_loss / max_error * 100
2026-07-18T14:10:03.8617873Z                 batch_errors.append(rel_error)
2026-07-18T14:10:03.8618310Z 
2026-07-18T14:10:03.8618531Z             all_errors.extend(batch_errors)
2026-07-18T14:10:03.8618932Z 
2026-07-18T14:10:03.8619148Z         mean_error = np.mean(all_errors)
2026-07-18T14:10:03.8619746Z         std_error = np.std(all_errors)
2026-07-18T14:10:03.8620423Z         perturbation_results.append((mean_error, std_error))
2026-07-18T14:10:03.8621284Z         print(f"Completed testing for perturbation strength {strength}.")
2026-07-18T14:10:03.8621893Z 
2026-07-18T14:10:03.8622095Z     return perturbation_results
2026-07-18T14:10:03.8622447Z 
2026-07-18T14:10:03.8622946Z # Calculate the maximum error for a null model, the error when the output is constant.
2026-07-18T14:10:03.8624071Z max_error = ((outputs - outputs.mean(axis=[0, 1], keepdims=True)) ** 2).mean()
2026-07-18T14:10:03.8624731Z 
2026-07-18T14:10:03.8625022Z perturbation_strengths = [0.0125, 0.025, 0.05, 0.1, 0.2]
2026-07-18T14:10:03.8626374Z results_unregularized = test_perturbed_inputs(unregularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-18T14:10:03.8628722Z results_regularized = test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn.MSELoss(), device, max_error)
2026-07-18T14:10:03.8630012Z ------------------
2026-07-18T14:10:03.8630271Z 
2026-07-18T14:10:03.8630460Z ----- stdout -----
2026-07-18T14:10:03.8630958Z Testing perturbation strength 0.0125
2026-07-18T14:10:03.8631510Z ------------------
2026-07-18T14:10:03.8631773Z 
2026-07-18T14:10:03.8632546Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T14:10:03.8633680Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T14:10:03.8634526Z Cell �[0;32mIn[44], line 57�[0m
2026-07-18T14:10:03.8637006Z �[1;32m     54�[0m max_error �[38;5;241m=�[39m ((outputs �[38;5;241m-�[39m outputs�[38;5;241m.�[39mmean(axis�[38;5;241m=�[39m[�[38;5;241m0�[39m, �[38;5;241m1�[39m], keepdims�[38;5;241m=�[39m�[38;5;28;01mTrue�[39;00m)) �[38;5;241m*�[39m�[38;5;241m*�[39m �[38;5;241m2�[39m)�[38;5;241m.�[39mmean()
2026-07-18T14:10:03.8639841Z �[1;32m     56�[0m perturbation_strengths �[38;5;241m=�[39m [�[38;5;241m0.0125�[39m, �[38;5;241m0.025�[39m, �[38;5;241m0.05�[39m, �[38;5;241m0.1�[39m, �[38;5;241m0.2�[39m]
2026-07-18T14:10:03.8643866Z �[0;32m---> 57�[0m results_unregularized �[38;5;241m=�[39m �[43mtest_perturbed_inputs�[49m�[43m(�[49m�[43munregularized_model�[49m�[43m,�[49m�[43m �[49m�[43mperturbation_strengths�[49m�[43m,�[49m�[43m �[49m�[43mtest_loader�[49m�[43m,�[49m�[43m �[49m�[43mnn�[49m�[38;5;241;43m.�[39;49m�[43mMSELoss�[49m�[43m(�[49m�[43m)�[49m�[43m,�[49m�[43m �[49m�[43mdevice�[49m�[43m,�[49m�[43m �[49m�[43mmax_error�[49m�[43m)�[49m
2026-07-18T14:10:03.8648018Z �[1;32m     58�[0m results_regularized �[38;5;241m=�[39m test_perturbed_inputs(regularized_model, perturbation_strengths, test_loader, nn�[38;5;241m.�[39mMSELoss(), device, max_error)
2026-07-18T14:10:03.8649368Z 
2026-07-18T14:10:03.8650504Z Cell �[0;32mIn[44], line 28�[0m, in �[0;36mtest_perturbed_inputs�[0;34m(model, perturbation_strengths, test_loader, criterion, device, max_error)�[0m
2026-07-18T14:10:03.8652829Z �[1;32m     26�[0m all_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store all errors for each perturbation strength to compute mean and s.d.�[39;00m
2026-07-18T14:10:03.8655097Z �[1;32m     27�[0m �[38;5;28mprint�[39m(�[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mTesting perturbation strength �[39m�[38;5;132;01m{�[39;00mstrength�[38;5;132;01m}�[39;00m�[38;5;124m"�[39m)
2026-07-18T14:10:03.8658017Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m iteration �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[38;5;28;43mrange�[39;49m�[43m(�[49m�[38;5;241;43m30�[39;49m�[43m)�[49m�[43m)�[49m:  �[38;5;66;03m# Repeat the procedure 30 times�[39;00m
2026-07-18T14:10:03.8660155Z �[1;32m     29�[0m     batch_errors �[38;5;241m=�[39m []  �[38;5;66;03m# Store errors for each batch�[39;00m
2026-07-18T14:10:03.8661444Z �[1;32m     31�[0m     �[38;5;28;01mfor�[39;00m inputs, targets �[38;5;129;01min�[39;00m test_loader:
2026-07-18T14:10:03.8662110Z 
2026-07-18T14:10:03.8663481Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T14:10:03.8665480Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T14:10:03.8667064Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T14:10:03.8668540Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T14:10:03.8669650Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T14:10:03.8670788Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T14:10:03.8671519Z 
2026-07-18T14:10:03.8672958Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T14:10:03.8674637Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T14:10:03.8675795Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T14:10:03.8677704Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T14:10:03.8680449Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T14:10:03.8682045Z 
2026-07-18T14:10:03.8682375Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T14:10:03.8682800Z 
2026-07-18T14:10:04.1463193Z ##[error]Process completed with exit code 1.

tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb

2026-07-18T14:10:56.6965502Z Executing tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb
2026-07-18T14:10:57.6064050Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T14:11:28.9154400Z tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb failed quality control.
2026-07-18T14:11:28.9155421Z ============================== Failure ==============================
2026-07-18T14:11:28.9157526Z An error occurred while executing the following cell:
2026-07-18T14:11:28.9158326Z ------------------
2026-07-18T14:11:28.9158744Z # @title Extract model features with torchlens
2026-07-18T14:11:28.9159088Z 
2026-07-18T14:11:28.9159331Z return_layers = ['input_1', 'conv1', 'conv2', 'fc1', 'fc2']
2026-07-18T14:11:28.9160854Z features_model_imgs = extract_features(model, imgs, return_layers, plot = 'rolled') #comment this line if Graphviz installation was unsuccessful for you
2026-07-18T14:11:28.9161803Z 
2026-07-18T14:11:28.9162125Z features_model_advimgs = extract_features(model, adv_imgs, return_layers)
2026-07-18T14:11:28.9162919Z features_advmodel_imgs = extract_features(model_robust, imgs, return_layers)
2026-07-18T14:11:28.9163796Z features_advmodel_advimgs = extract_features(model_robust, adv_imgs_advmodel, return_layers)
2026-07-18T14:11:28.9164505Z ------------------
2026-07-18T14:11:28.9164709Z 
2026-07-18T14:11:28.9164839Z ----- stderr -----
2026-07-18T14:11:28.9166048Z /tmp/ipykernel_3216/794751295.py:348: DeprecationWarning: torchlens.log_forward_pass is deprecated; use torchlens.trace instead. The old paper-era name remains available as a compatibility shim.
2026-07-18T14:11:28.9167588Z   model_history = tl.log_forward_pass(model, imgs, layers_to_save='all', vis_opt=plot)
2026-07-18T14:11:28.9168461Z ------------------
2026-07-18T14:11:28.9168650Z 
2026-07-18T14:11:28.9169261Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T14:11:28.9170088Z �[0;31mTypeError�[0m                                 Traceback (most recent call last)
2026-07-18T14:11:28.9170722Z Cell �[0;32mIn[23], line 4�[0m
2026-07-18T14:11:28.9171342Z �[1;32m      1�[0m �[38;5;66;03m# @title Extract model features with torchlens�[39;00m
2026-07-18T14:11:28.9173405Z �[1;32m      3�[0m return_layers �[38;5;241m=�[39m [�[38;5;124m'�[39m�[38;5;124minput_1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mconv2�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc1�[39m�[38;5;124m'�[39m, �[38;5;124m'�[39m�[38;5;124mfc2�[39m�[38;5;124m'�[39m]
2026-07-18T14:11:28.9177078Z �[0;32m----> 4�[0m features_model_imgs �[38;5;241m=�[39m �[43mextract_features�[49m�[43m(�[49m�[43mmodel�[49m�[43m,�[49m�[43m �[49m�[43mimgs�[49m�[43m,�[49m�[43m �[49m�[43mreturn_layers�[49m�[43m,�[49m�[43m �[49m�[43mplot�[49m�[43m �[49m�[38;5;241;43m=�[39;49m�[43m �[49m�[38;5;124;43m'�[39;49m�[38;5;124;43mrolled�[39;49m�[38;5;124;43m'�[39;49m�[43m)�[49m �[38;5;66;03m#comment this line if Graphviz installation was unsuccessful for you�[39;00m
2026-07-18T14:11:28.9180056Z �[1;32m      6�[0m features_model_advimgs �[38;5;241m=�[39m extract_features(model, adv_imgs, return_layers)
2026-07-18T14:11:28.9181175Z �[1;32m      7�[0m features_advmodel_imgs �[38;5;241m=�[39m extract_features(model_robust, imgs, return_layers)
2026-07-18T14:11:28.9181763Z 
2026-07-18T14:11:28.9182275Z Cell �[0;32mIn[8], line 348�[0m, in �[0;36mextract_features�[0;34m(model, imgs, return_layers, plot)�[0m
2026-07-18T14:11:28.9183786Z �[1;32m    335�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mextract_features�[39m(model, imgs, return_layers, plot�[38;5;241m=�[39m�[38;5;124m'�[39m�[38;5;124mnone�[39m�[38;5;124m'�[39m):
2026-07-18T14:11:28.9184955Z �[1;32m    336�[0m �[38;5;250m    �[39m�[38;5;124;03m"""�[39;00m
2026-07-18T14:11:28.9185808Z �[1;32m    337�[0m �[38;5;124;03m    Extracts features from specified layers of the model.�[39;00m
2026-07-18T14:11:28.9186822Z �[1;32m    338�[0m 
2026-07-18T14:11:28.9187189Z �[0;32m   (...)�[0m
2026-07-18T14:11:28.9188318Z �[1;32m    346�[0m �[38;5;124;03m    - model_features (dict): A dictionary with layer names as keys and extracted features as values.�[39;00m
2026-07-18T14:11:28.9189287Z �[1;32m    347�[0m �[38;5;124;03m    """�[39;00m
2026-07-18T14:11:28.9191557Z �[0;32m--> 348�[0m     model_history �[38;5;241m=�[39m �[43mtl�[49m�[38;5;241;43m.�[39;49m�[43mlog_forward_pass�[49m�[43m(�[49m�[43mmodel�[49m�[43m,�[49m�[43m �[49m�[43mimgs�[49m�[43m,�[49m�[43m �[49m�[43mlayers_to_save�[49m�[38;5;241;43m=�[39;49m�[38;5;124;43m'�[39;49m�[38;5;124;43mall�[39;49m�[38;5;124;43m'�[39;49m�[43m,�[49m�[43m �[49m�[43mvis_opt�[49m�[38;5;241;43m=�[39;49m�[43mplot�[49m�[43m)�[49m
2026-07-18T14:11:28.9193552Z �[1;32m    349�[0m     model_features �[38;5;241m=�[39m {}
2026-07-18T14:11:28.9194471Z �[1;32m    350�[0m     �[38;5;28;01mfor�[39;00m layer �[38;5;129;01min�[39;00m return_layers:
2026-07-18T14:11:28.9194943Z 
2026-07-18T14:11:28.9195981Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/torchlens/__init__.py:422�[0m, in �[0;36m_legacy_trace_alias.<locals>._shim�[0;34m(*args, **kwargs)�[0m
2026-07-18T14:11:28.9197259Z �[1;32m    420�[0m _warn_legacy_api_name(name, replacement)
2026-07-18T14:11:28.9198393Z �[1;32m    421�[0m �[38;5;28;01mif�[39;00m name �[38;5;241m==�[39m �[38;5;124m"�[39m�[38;5;124mlog_forward_pass�[39m�[38;5;124m"�[39m:
2026-07-18T14:11:28.9200876Z �[0;32m--> 422�[0m     �[38;5;28;01mreturn�[39;00m �[43m_resolve_top_level�[49m�[43m(�[49m�[38;5;124;43m"�[39;49m�[38;5;124;43m_trace�[39;49m�[38;5;124;43m"�[39;49m�[43m)�[49m�[43m(�[49m�[38;5;241;43m*�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m*�[39;49m�[38;5;241;43m*�[39;49m�[43m_translate_legacy_trace_kwargs�[49m�[43m(�[49m�[43mkwargs�[49m�[43m)�[49m�[43m)�[49m
2026-07-18T14:11:28.9203276Z �[1;32m    423�[0m �[38;5;28;01mif�[39;00m name �[38;5;241m==�[39m �[38;5;124m"�[39m�[38;5;124mvalidate_model_activations�[39m�[38;5;124m"�[39m:
2026-07-18T14:11:28.9204777Z �[1;32m    424�[0m     kwargs�[38;5;241m.�[39msetdefault(�[38;5;124m"�[39m�[38;5;124mscope�[39m�[38;5;124m"�[39m, �[38;5;124m"�[39m�[38;5;124mforward�[39m�[38;5;124m"�[39m)
2026-07-18T14:11:28.9205568Z 
2026-07-18T14:11:28.9205964Z �[0;31mTypeError�[0m: trace() got an unexpected keyword argument 'vis_opt'
2026-07-18T14:11:28.9206408Z 
2026-07-18T14:11:29.0700174Z ##[error]Process completed with exit code 1.

tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb

2026-07-18T14:09:37.1009375Z Executing tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb
2026-07-18T14:09:38.1068287Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T14:10:06.7480679Z tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb failed quality control.
2026-07-18T14:10:06.7481436Z ============================== Failure ==============================
2026-07-18T14:10:06.7482111Z An error occurred while executing the following cell:
2026-07-18T14:10:06.7483215Z ------------------
2026-07-18T14:10:06.7483668Z modular_agent = Agent(arg, ModularActor)
2026-07-18T14:10:06.7484336Z modular_agent.load(Path('agents/modular'), 0)
2026-07-18T14:10:06.7484830Z modular_df = evaluation(modular_agent)
2026-07-18T14:10:06.7485241Z ------------------
2026-07-18T14:10:06.7485428Z 
2026-07-18T14:10:06.7485434Z 
2026-07-18T14:10:06.7486093Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T14:10:06.7487445Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T14:10:06.7487899Z Cell �[0;32mIn[38], line 3�[0m
2026-07-18T14:10:06.7488311Z �[1;32m      1�[0m modular_agent �[38;5;241m=�[39m Agent(arg, ModularActor)
2026-07-18T14:10:06.7489081Z �[1;32m      2�[0m modular_agent�[38;5;241m.�[39mload(Path(�[38;5;124m'�[39m�[38;5;124magents/modular�[39m�[38;5;124m'�[39m), �[38;5;241m0�[39m)
2026-07-18T14:10:06.7489916Z �[0;32m----> 3�[0m modular_df �[38;5;241m=�[39m �[43mevaluation�[49m�[43m(�[49m�[43mmodular_agent�[49m�[43m)�[49m
2026-07-18T14:10:06.7490284Z 
2026-07-18T14:10:06.7490559Z Cell �[0;32mIn[37], line 28�[0m, in �[0;36mevaluation�[0;34m(agent, gain_factor)�[0m
2026-07-18T14:10:06.7491173Z �[1;32m     25�[0m target_x �[38;5;241m=�[39m []; target_y �[38;5;241m=�[39m []; target_r �[38;5;241m=�[39m []
2026-07-18T14:10:06.7491750Z �[1;32m     26�[0m rewarded �[38;5;241m=�[39m []; state_input_ �[38;5;241m=�[39m []
2026-07-18T14:10:06.7492481Z �[0;32m---> 28�[0m �[38;5;28;01mfor�[39;00m target_position �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtarget_positions�[49m�[43m)�[49m:
2026-07-18T14:10:06.7493621Z �[1;32m     29�[0m     state �[38;5;241m=�[39m env�[38;5;241m.�[39mreset(target_position�[38;5;241m=�[39mtarget_position, gain�[38;5;241m=�[39marg�[38;5;241m.�[39mprocess_gain_default �[38;5;241m*�[39m gain_factor)
2026-07-18T14:10:06.7494974Z �[1;32m     30�[0m     agent�[38;5;241m.�[39mobs_step�[38;5;241m.�[39mreset(env�[38;5;241m.�[39mgain)
2026-07-18T14:10:06.7495293Z 
2026-07-18T14:10:06.7495954Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:250�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T14:10:06.7496886Z �[1;32m    248�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T14:10:06.7497597Z �[1;32m    249�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T14:10:06.7498275Z �[0;32m--> 250�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T14:10:06.7498812Z �[1;32m    252�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T14:10:06.7499375Z �[1;32m    253�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T14:10:06.7499718Z 
2026-07-18T14:10:06.7500317Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:209�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T14:10:06.7501070Z �[1;32m    206�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T14:10:06.7501628Z �[1;32m    207�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T14:10:06.7502409Z �[1;32m    208�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T14:10:06.7503668Z �[0;32m--> 209�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T14:10:06.7504682Z 
2026-07-18T14:10:06.7504855Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T14:10:06.7505074Z 
2026-07-18T14:10:07.1329422Z ##[error]Process completed with exit code 1.

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb

2026-07-18T14:09:19.0364950Z Executing tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb
2026-07-18T14:09:20.3070319Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T14:09:48.4196215Z tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb failed quality control.
2026-07-18T14:09:48.4197028Z ============================== Failure ==============================
2026-07-18T14:09:48.4197718Z An error occurred while executing the following cell:
2026-07-18T14:09:48.4198205Z ------------------
2026-07-18T14:09:48.4198598Z train_sizes = np.linspace(0.25, 0.9, 5)
2026-07-18T14:09:48.4199273Z bound_performance, bound_models = test_performance(bound_phis, ys_rastrigin, train_sizes)
2026-07-18T14:09:48.4200189Z bundle_performance, bundle_models = test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-18T14:09:48.4201770Z plot_performance(bound_performance, bundle_performance, train_sizes * bound_phis.shape[0], "Rastrigin function - RMSE")
2026-07-18T14:09:48.4202614Z plt.ylim((-1, 20))
2026-07-18T14:09:48.4202935Z ------------------
2026-07-18T14:09:48.4203111Z 
2026-07-18T14:09:48.4203131Z 
2026-07-18T14:09:48.4203762Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T14:09:48.4204546Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T14:09:48.4205157Z Cell �[0;32mIn[15], line 2�[0m
2026-07-18T14:09:48.4206210Z �[1;32m      1�[0m train_sizes �[38;5;241m=�[39m np�[38;5;241m.�[39mlinspace(�[38;5;241m0.25�[39m, �[38;5;241m0.9�[39m, �[38;5;241m5�[39m)
2026-07-18T14:09:48.4207945Z �[0;32m----> 2�[0m bound_performance, bound_models �[38;5;241m=�[39m �[43mtest_performance�[49m�[43m(�[49m�[43mbound_phis�[49m�[43m,�[49m�[43m �[49m�[43mys_rastrigin�[49m�[43m,�[49m�[43m �[49m�[43mtrain_sizes�[49m�[43m)�[49m
2026-07-18T14:09:48.4209608Z �[1;32m      3�[0m bundle_performance, bundle_models �[38;5;241m=�[39m test_performance(bundle_phis, ys_rastrigin, train_sizes)
2026-07-18T14:09:48.4211421Z �[1;32m      4�[0m plot_performance(bound_performance, bundle_performance, train_sizes �[38;5;241m*�[39m bound_phis�[38;5;241m.�[39mshape[�[38;5;241m0�[39m], �[38;5;124m"�[39m�[38;5;124mRastrigin function - RMSE�[39m�[38;5;124m"�[39m)
2026-07-18T14:09:48.4212529Z 
2026-07-18T14:09:48.4212941Z Cell �[0;32mIn[14], line 24�[0m, in �[0;36mtest_performance�[0;34m(xs, ys, train_sizes)�[0m
2026-07-18T14:09:48.4213633Z �[1;32m     21�[0m performance �[38;5;241m=�[39m []
2026-07-18T14:09:48.4214127Z �[1;32m     23�[0m models �[38;5;241m=�[39m []
2026-07-18T14:09:48.4215255Z �[0;32m---> 24�[0m �[38;5;28;01mfor�[39;00m train_size �[38;5;129;01min�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtrain_sizes�[49m�[43m)�[49m:
2026-07-18T14:09:48.4216901Z �[1;32m     25�[0m     X_train, X_test, y_train, y_test �[38;5;241m=�[39m train_test_split(xs, ys, random_state�[38;5;241m=�[39m�[38;5;241m1�[39m, train_size�[38;5;241m=�[39mtrain_size)
2026-07-18T14:09:48.4218155Z �[1;32m     26�[0m     regr �[38;5;241m=�[39m LinearRegression()�[38;5;241m.�[39mfit(X_train, y_train)
2026-07-18T14:09:48.4218642Z 
2026-07-18T14:09:48.4219591Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:241�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T14:09:48.4221020Z �[1;32m    239�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T14:09:48.4222025Z �[1;32m    240�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T14:09:48.4223033Z �[0;32m--> 241�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T14:09:48.4223800Z �[1;32m    243�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T14:09:48.4224606Z �[1;32m    244�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T14:09:48.4225099Z 
2026-07-18T14:09:48.4226122Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:200�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T14:09:48.4227223Z �[1;32m    197�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T14:09:48.4228022Z �[1;32m    198�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T14:09:48.4229173Z �[1;32m    199�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T14:09:48.4231020Z �[0;32m--> 200�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T14:09:48.4232106Z 
2026-07-18T14:09:48.4232507Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T14:09:48.4232791Z 
2026-07-18T14:09:48.6156692Z ##[error]Process completed with exit code 1.

tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

2026-07-18T14:09:30.3795375Z Executing tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb
2026-07-18T14:09:31.3597267Z [IPKernelApp] WARNING | Kernel is running over TCP without encryption. All communication (including code and outputs) is sent in plain text and is susceptible to eavesdropping. Use IPC transport or launch with kernel manager-provisioned CurveZMQ keys to enable transport encryption.
2026-07-18T14:10:47.5091834Z tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb failed quality control.
2026-07-18T14:10:47.5092271Z An error occurred while executing the following cell:
2026-07-18T14:10:47.5092522Z ------------------
2026-07-18T14:10:47.5092798Z # @title Make sure you execute this cell to observe the plot!
2026-07-18T14:10:47.5093007Z 
2026-07-18T14:10:47.5093077Z set_seed(42)
2026-07-18T14:10:47.5093168Z 
2026-07-18T14:10:47.5093243Z #define environment
2026-07-18T14:10:47.5093411Z env = ChangingEnv()
2026-07-18T14:10:47.5093593Z replay = ReplayBufferSolution()
2026-07-18T14:10:47.5093725Z 
2026-07-18T14:10:47.5093809Z #define agent and optimizer
2026-07-18T14:10:47.5094013Z agent = ActorCritic(hidden_size = 100)
2026-07-18T14:10:47.5094594Z optimizer_func = optim.RMSprop
2026-07-18T14:10:47.5094730Z 
2026-07-18T14:10:47.5094802Z #train agent
2026-07-18T14:10:47.5095033Z train_agent_with_replay(env, agent, optimizer_func, replay)
2026-07-18T14:10:47.5095225Z 
2026-07-18T14:10:47.5095395Z rewards, max_rewards = evaluate_agent(env, agent, num_evaluation_trials = 5000)
2026-07-18T14:10:47.5095727Z plot_confusion_matrix(rewards, max_rewards)
2026-07-18T14:10:47.5095947Z ------------------
2026-07-18T14:10:47.5096050Z 
2026-07-18T14:10:47.5096053Z 
2026-07-18T14:10:47.5096491Z �[0;31m---------------------------------------------------------------------------�[0m
2026-07-18T14:10:47.5096921Z �[0;31mIndexError�[0m                                Traceback (most recent call last)
2026-07-18T14:10:47.5097258Z Cell �[0;32mIn[32], line 14�[0m
2026-07-18T14:10:47.5097838Z �[1;32m     11�[0m optimizer_func �[38;5;241m=�[39m optim�[38;5;241m.�[39mRMSprop
2026-07-18T14:10:47.5098221Z �[1;32m     13�[0m �[38;5;66;03m#train agent�[39;00m
2026-07-18T14:10:47.5098906Z �[0;32m---> 14�[0m �[43mtrain_agent_with_replay�[49m�[43m(�[49m�[43menv�[49m�[43m,�[49m�[43m �[49m�[43magent�[49m�[43m,�[49m�[43m �[49m�[43moptimizer_func�[49m�[43m,�[49m�[43m �[49m�[43mreplay�[49m�[43m)�[49m
2026-07-18T14:10:47.5099749Z �[1;32m     16�[0m rewards, max_rewards �[38;5;241m=�[39m evaluate_agent(env, agent, num_evaluation_trials �[38;5;241m=�[39m �[38;5;241m5000�[39m)
2026-07-18T14:10:47.5100265Z �[1;32m     17�[0m plot_confusion_matrix(rewards, max_rewards)
2026-07-18T14:10:47.5100449Z 
2026-07-18T14:10:47.5100891Z Cell �[0;32mIn[31], line 22�[0m, in �[0;36mtrain_agent_with_replay�[0;34m(env, agent, optimizer_func, replay, mode, training_mode, num_gradient_steps, num_trials)�[0m
2026-07-18T14:10:47.5101747Z �[1;32m     19�[0m optimizer �[38;5;241m=�[39m optimizer_func(agent�[38;5;241m.�[39mparameters(), agent�[38;5;241m.�[39mlearning_rate, eps�[38;5;241m=�[39m�[38;5;241m1e-5�[39m)
2026-07-18T14:10:47.5102352Z �[1;32m     21�[0m �[38;5;66;03m# Initialize TQDM progress bar�[39;00m
2026-07-18T14:10:47.5102668Z ============================== Failure ==============================
2026-07-18T14:10:47.5103759Z �[0;32m---> 22�[0m �[38;5;28;01mwith�[39;00m �[43mtqdm�[49m�[43m(�[49m�[43mtotal�[49m�[38;5;241;43m=�[39;49m�[43mnum_gradient_steps�[49m�[43m)�[49m �[38;5;28;01mas�[39;00m pbar:
2026-07-18T14:10:47.5104627Z �[1;32m     23�[0m     �[38;5;28;01mfor�[39;00m index �[38;5;129;01min�[39;00m �[38;5;28mrange�[39m(num_gradient_steps):
2026-07-18T14:10:47.5105255Z �[1;32m     24�[0m         �[38;5;66;03m# For storing variables for training�[39;00m
2026-07-18T14:10:47.5105758Z �[1;32m     25�[0m         log_probs �[38;5;241m=�[39m []
2026-07-18T14:10:47.5106006Z 
2026-07-18T14:10:47.5107016Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:250�[0m, in �[0;36mtqdm_notebook.__init__�[0;34m(self, *args, **kwargs)�[0m
2026-07-18T14:10:47.5108135Z �[1;32m    248�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mdisplayed �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
2026-07-18T14:10:47.5108700Z �[1;32m    249�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mdisp �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mdisplay
2026-07-18T14:10:47.5109257Z �[0;32m--> 250�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcolour�[49m �[38;5;241m=�[39m colour
2026-07-18T14:10:47.5109697Z �[1;32m    252�[0m �[38;5;66;03m# Print initial bar state�[39;00m
2026-07-18T14:10:47.5110137Z �[1;32m    253�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mdisable:
2026-07-18T14:10:47.5110395Z 
2026-07-18T14:10:47.5110862Z File �[0;32m/opt/hostedtoolcache/Python/3.10.20/x64/lib/python3.10/site-packages/tqdm/notebook.py:209�[0m, in �[0;36mtqdm_notebook.colour�[0;34m(self, bar_color)�[0m
2026-07-18T14:10:47.5111455Z �[1;32m    206�[0m �[38;5;129m@colour�[39m�[38;5;241m.�[39msetter
2026-07-18T14:10:47.5111888Z �[1;32m    207�[0m �[38;5;28;01mdef�[39;00m�[38;5;250m �[39m�[38;5;21mcolour�[39m(�[38;5;28mself�[39m, bar_color):
2026-07-18T14:10:47.5112647Z �[1;32m    208�[0m     �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(�[38;5;28mself�[39m, �[38;5;124m'�[39m�[38;5;124mcontainer�[39m�[38;5;124m'�[39m):
2026-07-18T14:10:47.5113630Z �[0;32m--> 209�[0m         �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mcontainer�[49m�[38;5;241;43m.�[39;49m�[43mchildren�[49m�[43m[�[49m�[38;5;241;43m-�[39;49m�[38;5;241;43m2�[39;49m�[43m]�[49m�[38;5;241m.�[39mstyle�[38;5;241m.�[39mbar_color �[38;5;241m=�[39m bar_color
2026-07-18T14:10:47.5114332Z 
2026-07-18T14:10:47.5114483Z �[0;31mIndexError�[0m: list index out of range
2026-07-18T14:10:47.5114645Z 
2026-07-18T14:10:47.6788182Z ##[error]Process completed with exit code 1.

github-actions · 2026-07-18T14:19:15Z

Follow-up PR Created

A follow-up PR has been created for the notebooks that failed to process:

Follow-up PR: #521
Branch: reprocess-pr519-20260718141911

The failed notebooks have been reverted to their main branch versions in this PR.
Once this PR is merged, the follow-up PR can be used to reprocess the failed notebooks independently.

actions-user and others added 2 commits July 17, 2026 06:28

Merge pull request #518 from neuromatch/reprocess-pr516-20260717062844

a889d02

Reprocess: Failed notebooks from PR #516

github-actions Bot mentioned this pull request Jul 18, 2026

Reprocess: Failed notebooks from PR #519 #520

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1aa8fdc

iamzoltan force-pushed the staging branch from 514f978 to 1aa8fdc Compare July 18, 2026 14:01

github-actions Bot mentioned this pull request Jul 18, 2026

Reprocess: Failed notebooks from PR #519 #521

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Process tutorial notebooks (some notebooks moved to follow-up PR)

9aecb31

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Staging#519
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iamzoltan commented Jul 18, 2026

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github-actions Bot commented Jul 18, 2026

Notebook Processing Failure Context

projects/project-notebooks/Macrocircuits.ipynb

tutorials/W1D1_Generalization/W1D1_Tutorial1.ipynb

tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb

tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb

tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb

tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

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github-actions Bot commented Jul 18, 2026

Follow-up PR Created

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github-actions Bot commented Jul 18, 2026

Notebook Processing Failure Context

projects/project-notebooks/Macrocircuits.ipynb

tutorials/W1D1_Generalization/W1D1_Tutorial1.ipynb

tutorials/W1D1_Generalization/W1D1_Tutorial2.ipynb

tutorials/W1D3_ComparingArtificialAndBiologicalNetworks/W1D3_Tutorial1.ipynb

tutorials/W2D1_Macrocircuits/W2D1_Tutorial3.ipynb

tutorials/W2D2_NeuroSymbolicMethods/W2D2_Tutorial5.ipynb

tutorials/W2D4_Macrolearning/W2D4_Tutorial5.ipynb

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github-actions Bot commented Jul 18, 2026

Follow-up PR Created

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