SumMe_CSTA/notebook.ipynb · AlgorithmicResearchGroup/dmlb

AlgorithmicResearchGroup/dmlb / SumMe_CSTA /notebook.ipynb

247 kB

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyNkPXOz97x0jGcJwa9CBOcp"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","source":["#change line 115 on /content/CSTA/train.py to train just on SumME data and set the code below on line 115.\n","#if dataset_name in ['SumMe']:"],"metadata":{"id":"CV1Y682Ucdh3","executionInfo":{"status":"ok","timestamp":1755072914452,"user_tz":-345,"elapsed":12,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}}},"execution_count":12,"outputs":[]},{"cell_type":"code","source":["!git clone https://github.com/e-apostolidis/PGL-SUM.git"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"XaRDW7vuYKQj","executionInfo":{"status":"ok","timestamp":1755072688418,"user_tz":-345,"elapsed":4740,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"fbe0a9ae-47df-456a-8af6-c657349e0d0d"},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'PGL-SUM'...\n","remote: Enumerating objects: 201, done.\u001b[K\n","remote: Counting objects: 100% (59/59), done.\u001b[K\n","remote: Compressing objects: 100% (24/24), done.\u001b[K\n","remote: Total 201 (delta 50), reused 40 (delta 35), pack-reused 142 (from 1)\u001b[K\n","Receiving objects: 100% (201/201), 91.79 MiB | 28.51 MiB/s, done.\n","Resolving deltas: 100% (95/95), done.\n"]}]},{"cell_type":"code","source":["%cd PGL-SUM/data/SumMe"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lDNgrC86YRlb","executionInfo":{"status":"ok","timestamp":1755072688484,"user_tz":-345,"elapsed":52,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"f4f830df-50a6-4275-f565-bfd1018e4f54"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["/content/PGL-SUM/data/SumMe\n"]}]},{"cell_type":"code","source":["!unrar x /content/PGL-SUM/data/SumMe/eccv16_dataset_summe_google_pool5.rar"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"GkL9WvZDYa76","executionInfo":{"status":"ok","timestamp":1755072688974,"user_tz":-345,"elapsed":488,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"f5cdf69d-36b7-4e68-be3d-a5a3b84de1b9"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","UNRAR 6.11 beta 1 freeware Copyright (c) 1993-2022 Alexander Roshal\n","\n","\n","Extracting from /content/PGL-SUM/data/SumMe/eccv16_dataset_summe_google_pool5.rar\n","\n","Extracting eccv16_dataset_summe_google_pool5.h5 \b\b\b\b 18%\b\b\b\b 37%\b\b\b\b 56%\b\b\b\b 74%\b\b\b\b 93%\b\b\b\b100%\b\b\b\b\b OK \n","All OK\n"]}]},{"cell_type":"code","source":["%cd ..\n","%cd TVSum"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"oWFCWiDaZWYb","executionInfo":{"status":"ok","timestamp":1755072688994,"user_tz":-345,"elapsed":26,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"8c6dc96d-2003-4155-8457-6b2a8864e000"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["/content/PGL-SUM/data\n","/content/PGL-SUM/data/TVSum\n"]}]},{"cell_type":"code","source":["!unrar x /content/PGL-SUM/data/TVSum/eccv16_dataset_tvsum_google_pool5.rar"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"RVDtFXgfZfkw","executionInfo":{"status":"ok","timestamp":1755072690775,"user_tz":-345,"elapsed":1771,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"4dca18ca-7d81-412e-aa2a-45e205b57bb8"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","UNRAR 6.11 beta 1 freeware Copyright (c) 1993-2022 Alexander Roshal\n","\n","\n","Extracting from /content/PGL-SUM/data/TVSum/eccv16_dataset_tvsum_google_pool5.rar\n","\n","Extracting eccv16_dataset_tvsum_google_pool5.h5 \b\b\b\b 5%\b\b\b\b 11%\b\b\b\b 17%\b\b\b\b 22%\b\b\b\b 28%\b\b\b\b 34%\b\b\b\b 39%\b\b\b\b 45%\b\b\b\b 51%\b\b\b\b 56%\b\b\b\b 62%\b\b\b\b 68%\b\b\b\b 73%\b\b\b\b 79%\b\b\b\b 85%\b\b\b\b 90%\b\b\b\b 96%\b\b\b\b100%\b\b\b\b\b OK \n","All OK\n"]}]},{"cell_type":"code","source":["%cd /content/"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7-HNqwtpZneY","executionInfo":{"status":"ok","timestamp":1755072690806,"user_tz":-345,"elapsed":29,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"e334c607-5c87-41ec-f822-d88c0363dc70"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["/content\n"]}]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"DcTzLGkrX5W_","executionInfo":{"status":"ok","timestamp":1755072691771,"user_tz":-345,"elapsed":963,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"6c796848-7c14-49e8-fad9-12d008d57f9a"},"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'CSTA'...\n","remote: Enumerating objects: 296, done.\u001b[K\n","remote: Counting objects: 100% (136/136), done.\u001b[K\n","remote: Compressing objects: 100% (62/62), done.\u001b[K\n","remote: Total 296 (delta 131), reused 74 (delta 74), pack-reused 160 (from 2)\u001b[K\n","Receiving objects: 100% (296/296), 256.35 KiB | 1.01 MiB/s, done.\n","Resolving deltas: 100% (157/157), done.\n","/content/CSTA\n"]}],"source":["!git clone https://github.com/thswodnjs3/CSTA.git\n","%cd CSTA\n"]},{"cell_type":"code","source":["!mv /content/PGL-SUM/data/SumMe/eccv16_dataset_summe_google_pool5.h5 /content/CSTA/data\n","!mv /content/PGL-SUM/data/TVSum/eccv16_dataset_tvsum_google_pool5.h5 /content/CSTA/data\n","!mv /content/PGL-SUM/data/splits/* /content/CSTA/data"],"metadata":{"id":"qccVXGWQaEVp","executionInfo":{"status":"ok","timestamp":1755072692093,"user_tz":-345,"elapsed":310,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}}},"execution_count":8,"outputs":[]},{"cell_type":"code","source":["!wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n","!chmod +x Miniconda3-latest-Linux-x86_64.sh\n","!bash ./Miniconda3-latest-Linux-x86_64.sh -b -f -p /usr/local\n","\n","import sys\n","sys.path.append('/usr/local/lib/python3.9/site-packages')\n","\n","!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main\n","!conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lI1bjWjGZ7dq","executionInfo":{"status":"ok","timestamp":1755072719802,"user_tz":-345,"elapsed":27703,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"fb341fe9-d490-4b13-c35f-b1a6f5dd269f"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["--2025-08-13 08:11:35-- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n","Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.191.158, 104.16.32.241, 2606:4700::6810:20f1, ...\n","Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.191.158|:443... connected.\n","HTTP request sent, awaiting response... 200 OK\n","Length: 160039710 (153M) [application/octet-stream]\n","Saving to: ‘Miniconda3-latest-Linux-x86_64.sh’\n","\n","Miniconda3-latest-L 100%[===================>] 152.62M 188MB/s in 0.8s \n","\n","2025-08-13 08:11:36 (188 MB/s) - ‘Miniconda3-latest-Linux-x86_64.sh’ saved [160039710/160039710]\n","\n","PREFIX=/usr/local\n","Unpacking payload ...\n","entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n","entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n","\n","Installing base environment...\n","\n","Preparing transaction: ...working... done\n","Executing transaction: ...working... done\n","entry_point.py:256: DeprecationWarning: Python 3.14 will, by default, filter extracted tar archives and reject files or modify their metadata. Use the filter argument to control this behavior.\n","installation finished.\n","WARNING:\n"," You currently have a PYTHONPATH environment variable set. This may cause\n"," unexpected behavior when running the Python interpreter in Miniconda3.\n"," For best results, please verify that your PYTHONPATH only points to\n"," directories of packages that are compatible with the Python interpreter\n"," in Miniconda3: /usr/local\n","accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/main\u001b[0m\n","accepted Terms of Service for \u001b[4;94mhttps://repo.anaconda.com/pkgs/r\u001b[0m\n"]}]},{"cell_type":"code","source":["!conda create -n newenv python=3.8.5 -y"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"1oxorGk4Z_JP","executionInfo":{"status":"ok","timestamp":1755072728002,"user_tz":-345,"elapsed":8197,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"a56d99eb-2ed9-413b-c7d5-2aa5e8a10105"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;32m2\u001b[0m\u001b[1;32m channel Terms of Service accepted\u001b[0m\n","Channels:\n"," - defaults\n","Platform: linux-64\n","Collecting package metadata (repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n","Solving environment: | \b\bdone\n","\n","\n","==> WARNING: A newer version of conda exists. <==\n"," current version: 25.5.1\n"," latest version: 25.7.0\n","\n","Please update conda by running\n","\n"," $ conda update -n base -c defaults conda\n","\n","\n","\n","## Package Plan ##\n","\n"," environment location: /usr/local/envs/newenv\n","\n"," added / updated specs:\n"," - python=3.8.5\n","\n","\n","The following packages will be downloaded:\n","\n"," package | build\n"," ---------------------------|-----------------\n"," ca-certificates-2025.7.15 | h06a4308_0 126 KB\n"," libffi-3.3 | he6710b0_2 50 KB\n"," ncurses-6.5 | h7934f7d_0 1.1 MB\n"," openssl-1.1.1w | h7f8727e_0 3.7 MB\n"," pip-24.2 | py38h06a4308_0 2.2 MB\n"," python-3.8.5 | h7579374_1 49.3 MB\n"," readline-8.3 | hc2a1206_0 471 KB\n"," setuptools-75.1.0 | py38h06a4308_0 1.7 MB\n"," wheel-0.44.0 | py38h06a4308_0 108 KB\n"," ------------------------------------------------------------\n"," Total: 58.7 MB\n","\n","The following NEW packages will be INSTALLED:\n","\n"," _libgcc_mutex pkgs/main/linux-64::_libgcc_mutex-0.1-main \n"," _openmp_mutex pkgs/main/linux-64::_openmp_mutex-5.1-1_gnu \n"," ca-certificates pkgs/main/linux-64::ca-certificates-2025.7.15-h06a4308_0 \n"," ld_impl_linux-64 pkgs/main/linux-64::ld_impl_linux-64-2.40-h12ee557_0 \n"," libffi pkgs/main/linux-64::libffi-3.3-he6710b0_2 \n"," libgcc-ng pkgs/main/linux-64::libgcc-ng-11.2.0-h1234567_1 \n"," libgomp pkgs/main/linux-64::libgomp-11.2.0-h1234567_1 \n"," libstdcxx-ng pkgs/main/linux-64::libstdcxx-ng-11.2.0-h1234567_1 \n"," libxcb pkgs/main/linux-64::libxcb-1.17.0-h9b100fa_0 \n"," ncurses pkgs/main/linux-64::ncurses-6.5-h7934f7d_0 \n"," openssl pkgs/main/linux-64::openssl-1.1.1w-h7f8727e_0 \n"," pip pkgs/main/linux-64::pip-24.2-py38h06a4308_0 \n"," pthread-stubs pkgs/main/linux-64::pthread-stubs-0.3-h0ce48e5_1 \n"," python pkgs/main/linux-64::python-3.8.5-h7579374_1 \n"," readline pkgs/main/linux-64::readline-8.3-hc2a1206_0 \n"," setuptools pkgs/main/linux-64::setuptools-75.1.0-py38h06a4308_0 \n"," sqlite pkgs/main/linux-64::sqlite-3.50.2-hb25bd0a_1 \n"," tk pkgs/main/linux-64::tk-8.6.14-h993c535_1 \n"," wheel pkgs/main/linux-64::wheel-0.44.0-py38h06a4308_0 \n"," xorg-libx11 pkgs/main/linux-64::xorg-libx11-1.8.12-h9b100fa_1 \n"," xorg-libxau pkgs/main/linux-64::xorg-libxau-1.0.12-h9b100fa_0 \n"," xorg-libxdmcp pkgs/main/linux-64::xorg-libxdmcp-1.1.5-h9b100fa_0 \n"," xorg-xorgproto pkgs/main/linux-64::xorg-xorgproto-2024.1-h5eee18b_1 \n"," xz pkgs/main/linux-64::xz-5.6.4-h5eee18b_1 \n"," zlib pkgs/main/linux-64::zlib-1.2.13-h5eee18b_1 \n","\n","\n","\n","Downloading and Extracting Packages:\n","python-3.8.5 | 49.3 MB | : 0% 0/1 [00:00<?, ?it/s]\n","openssl-1.1.1w | 3.7 MB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\n","\n","pip-24.2 | 2.2 MB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n","\n","\n","setuptools-75.1.0 | 1.7 MB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","ncurses-6.5 | 1.1 MB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","readline-8.3 | 471 KB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","ca-certificates-2025 | 126 KB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","wheel-0.44.0 | 108 KB | : 0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","\n","\n","\n","python-3.8.5 | 49.3 MB | : 0% 0.0012682685162249195/1 [00:00<01:24, 84.67s/it]\n","\n","\n","setuptools-75.1.0 | 1.7 MB | : 2% 0.01849850907707298/1 [00:00<00:05, 5.69s/it]\u001b[A\u001b[A\u001b[A\n","openssl-1.1.1w | 3.7 MB | : 2% 0.016748775774793164/1 [00:00<00:06, 6.51s/it]\u001b[A\n","\n","pip-24.2 | 2.2 MB | : 3% 0.028292763794103833/1 [00:00<00:03, 3.95s/it]\u001b[A\u001b[A\n","\n","\n","\n","ncurses-6.5 | 1.1 MB | : 6% 0.05760662138607143/1 [00:00<00:01, 1.95s/it]\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","ncurses-6.5 | 1.1 MB | : 100% 1.0/1 [00:00<00:00, 1.95s/it] \u001b[A\u001b[A\u001b[A\u001b[A\n","python-3.8.5 | 49.3 MB | : 7% 0.07197423829576419/1 [00:00<00:02, 2.48s/it] \n","\n","pip-24.2 | 2.2 MB | : 100% 1.0/1 [00:00<00:00, 5.44it/s] \u001b[A\u001b[A\n","\n","pip-24.2 | 2.2 MB | : 100% 1.0/1 [00:00<00:00, 5.44it/s]\u001b[A\u001b[A\n","\n","\n","\n","\n","readline-8.3 | 471 KB | : 3% 0.03400397653924861/1 [00:00<00:06, 6.63s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n","\n","\n","setuptools-75.1.0 | 1.7 MB | : 100% 1.0/1 [00:00<00:00, 4.95it/s] \u001b[A\u001b[A\u001b[A\n","\n","\n","setuptools-75.1.0 | 1.7 MB | : 100% 1.0/1 [00:00<00:00, 4.95it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","\n","\n","readline-8.3 | 471 KB | : 100% 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Upreti","userId":"01961227760879466523"}},"outputId":"fda7a13f-2b37-4437-b1ca-929cfb5f649c"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting h5py==3.1.0 (from -r requirements.txt (line 1))\n"," Downloading h5py-3.1.0-cp38-cp38-manylinux1_x86_64.whl.metadata (2.1 kB)\n","Collecting numpy==1.19.5 (from -r requirements.txt (line 2))\n"," Downloading numpy-1.19.5-cp38-cp38-manylinux2010_x86_64.whl.metadata (2.0 kB)\n","Collecting scipy==1.5.2 (from -r requirements.txt (line 3))\n"," Downloading scipy-1.5.2-cp38-cp38-manylinux1_x86_64.whl.metadata (2.0 kB)\n","Collecting torch==2.2.1 (from -r requirements.txt (line 4))\n"," Downloading torch-2.2.1-cp38-cp38-manylinux1_x86_64.whl.metadata (25 kB)\n","Collecting torchvision==0.17.1 (from -r requirements.txt (line 5))\n"," Downloading torchvision-0.17.1-cp38-cp38-manylinux1_x86_64.whl.metadata (6.6 kB)\n","Collecting tqdm==4.61.0 (from -r requirements.txt (line 6))\n"," Downloading 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sympy-1.13.3 torch-2.2.1 torchvision-0.17.1 tqdm-4.61.0 triton-2.2.0 typing-extensions-4.13.2\n"]}]},{"cell_type":"code","source":["!source /usr/local/bin/activate newenv && python train.py \\\n"," --seed 123456 \\\n"," --device cuda:0 \\\n"," --epochs 50 \\\n"," --batch_size 4 \\\n"," --learning_rate 0.001 \\\n"," --weight_decay 1e-7 \\\n"," --model_name GoogleNet_Attention \\\n"," --Scale None \\\n"," --Softmax_axis TD \\\n"," --Balance None \\\n"," --Positional_encoding FPE \\\n"," --Positional_encoding_shape TD \\\n"," --Positional_encoding_way PGL_SUM \\\n"," --Dropout_on True \\\n"," --Dropout_ratio 0.5 \\\n"," --Classifier_on True \\\n"," --CLS_on True \\\n"," --CLS_mix Final \\\n"," --key_value_emb kv \\\n"," --Skip_connection KC \\\n"," --Layernorm True \\\n"," --input_is_file False \\\n"," --dir_path ./SumMe \\\n"," --ext mp4 \\\n"," --sample_rate 15 \\\n"," --save_path ./summary_videos \\\n"," --weight_path ./weights/SumMe/split4.pt"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"63VZ9aSIeyVd","executionInfo":{"status":"ok","timestamp":1755073403411,"user_tz":-345,"elapsed":339435,"user":{"displayName":"Santosh Upreti","userId":"01961227760879466523"}},"outputId":"43bd2547-bea5-46c6-c27c-1405388ac0c3"},"execution_count":14,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n","\n","\n","Epoch23_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 12.23it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch23_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 13.69it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split2: 46%|███████████▌ | 23/50 [00:33<00:38, 1.43s/it]\u001b[A\u001b[A\n","\n","\n","Epoch24_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch24_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 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13.67it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split2: 88%|██████████████████████ | 44/50 [01:02<00:08, 1.35s/it]\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 49.84it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 50.71it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 51.17it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 11.69it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 13.00it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split2: 90%|██████████████████████▌ | 45/50 [01:03<00:06, 1.34s/it]\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 49.45it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 50%|█████████ | 10/20 [00:00<00:00, 47.85it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 75%|█████████████▌ | 15/20 [00:00<00:00, 47.77it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 11.20it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 11.55it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split2: 92%|███████████████████████ | 46/50 [01:05<00:05, 1.34s/it]\u001b[A\u001b[A\n","\n","\n","Epoch47_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch47_TRAIN: 30%|█████▋ | 6/20 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40.76it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch48_TRAIN: 75%|█████████████▌ | 15/20 [00:00<00:00, 41.28it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch48_TRAIN: 100%|██████████████████| 20/20 [00:00<00:00, 40.79it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch48_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch48_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 7.63it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch48_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 8.25it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split2: 96%|████████████████████████ | 48/50 [01:08<00:02, 1.49s/it]\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 20%|███▊ | 4/20 [00:00<00:00, 34.21it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 45%|████████▌ | 9/20 [00:00<00:00, 42.59it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 75%|█████████████▌ | 15/20 [00:00<00:00, 47.86it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 12.71it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 13.47it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split2: 98%|████████████████████████▌| 49/50 [01:09<00:01, 1.44s/it]\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 51.03it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 49.79it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 90%|████████████████▏ | 18/20 [00:00<00:00, 51.32it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 13.24it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 13.96it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split2: 100%|█████████████████████████| 50/50 [01:10<00:00, 1.39s/it]\u001b[A\u001b[A\n","\n"," \u001b[A\u001b[A\n","SumMe: 40%|███████████▏ | 2/5 [02:13<03:22, 67.65s/it]\u001b[A\n","\n","Split3: 0%| | 0/50 [00:00<?, ?it/s]\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 47.07it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 50%|█████████▌ | 10/20 [00:00<00:00, 46.50it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 75%|██████████████▎ | 15/20 [00:00<00:00, 46.83it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," 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1.37s/it]\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 30%|██████ | 6/20 [00:00<00:00, 51.08it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 60%|███████████▍ | 12/20 [00:00<00:00, 48.96it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 90%|█████████████████ | 18/20 [00:00<00:00, 48.68it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TEST: 40%|████████▊ | 2/5 [00:00<00:00, 12.88it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split3: 6%|█▌ | 3/50 [00:03<01:01, 1.31s/it]\u001b[A\u001b[A\n","\n","\n","Epoch4_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch4_TRAIN: 30%|██████ | 6/20 [00:00<00:00, 51.01it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch4_TRAIN: 60%|███████████▍ | 12/20 [00:00<00:00, 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40%|████████▊ | 2/5 [00:00<00:00, 11.47it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch5_TEST: 100%|██████████████████████| 5/5 [00:00<00:00, 19.80it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split3: 10%|██▌ | 5/50 [00:06<00:59, 1.32s/it]\u001b[A\u001b[A\n","\n","\n","Epoch6_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch6_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 48.08it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch6_TRAIN: 55%|██████████▍ | 11/20 [00:00<00:00, 50.45it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch6_TRAIN: 85%|████████████████▏ | 17/20 [00:00<00:00, 51.01it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch6_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch6_TEST: 40%|████████▊ | 2/5 [00:00<00:00, 7.66it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch6_TEST: 100%|██████████████████████| 5/5 [00:00<00:00, 14.82it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split3: 12%|███ | 6/50 [00:08<00:59, 1.36s/it]\u001b[A\u001b[A\n","\n","\n","Epoch7_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch7_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 39.99it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch7_TRAIN: 50%|█████████▌ | 10/20 [00:00<00:00, 42.16it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch7_TRAIN: 75%|██████████████▎ | 15/20 [00:00<00:00, 42.79it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch7_TRAIN: 100%|███████████████████| 20/20 [00:00<00:00, 40.74it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch7_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch7_TEST: 40%|████████▊ | 2/5 [00:00<00:00, 8.29it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split3: 14%|███▋ | 7/50 [00:09<01:01, 1.43s/it]\u001b[A\u001b[A\n","\n","\n","Epoch8_TRAIN: 0%| | 0/20 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[00:18<00:44, 1.23s/it]\u001b[A\u001b[A\n","\n","\n","Epoch15_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch15_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 50.42it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch15_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 46.65it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch15_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 47.19it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch15_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch15_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 13.43it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split3: 30%|███████▌ | 15/50 [00:19<00:43, 1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch16_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch16_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 53.46it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch16_TRAIN: 60%|██████████▊ | 12/20 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1.23s/it]\u001b[A\u001b[A\n","\n","\n","Epoch24_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch24_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 54.85it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch24_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 55.12it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch24_TRAIN: 90%|████████████████▏ | 18/20 [00:00<00:00, 52.56it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch24_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch24_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 14.38it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split3: 48%|████████████ | 24/50 [00:30<00:31, 1.22s/it]\u001b[A\u001b[A\n","\n","\n","Epoch25_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch25_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 48.93it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch25_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 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82%|████████████████████▌ | 41/50 [00:52<00:11, 1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch42_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 46.41it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 51.65it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 52.24it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 10.66it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split3: 84%|█████████████████████ | 42/50 [00:53<00:09, 1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch43_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch43_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 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100%|█████████████████████████| 50/50 [01:04<00:00, 1.26s/it]\u001b[A\u001b[A\n","\n"," \u001b[A\u001b[A\n","SumMe: 60%|████████████████▊ | 3/5 [03:18<02:12, 66.24s/it]\u001b[A\n","\n","Split4: 0%| | 0/50 [00:00<?, ?it/s]\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 48.72it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 50%|█████████▌ | 10/20 [00:00<00:00, 49.39it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 75%|██████████████▎ | 15/20 [00:00<00:00, 47.21it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TEST: 60%|█████████████▏ | 3/5 [00:00<00:00, 22.49it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 2%|▌ | 1/50 [00:01<01:04, 1.33s/it]\u001b[A\u001b[A\n","\n","\n","Epoch2_TRAIN: 0%| | 0/20 [00:00<?, 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18.64it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch9_TEST: 80%|█████████████████▌ | 4/5 [00:00<00:00, 18.05it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 18%|████▋ | 9/50 [00:11<00:50, 1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch10_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch10_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 48.49it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch10_TRAIN: 50%|█████████ | 10/20 [00:00<00:00, 46.25it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch10_TRAIN: 80%|██████████████▍ | 16/20 [00:00<00:00, 48.60it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch10_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch10_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 21.17it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 20%|█████ | 10/50 [00:12<00:49, 1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch11_TRAIN: 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1.31s/it]\u001b[A\u001b[A\n","\n","\n","Epoch16_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch16_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 48.57it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch16_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 51.95it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch16_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 51.22it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch16_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch16_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 19.65it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 32%|████████ | 16/50 [00:20<00:43, 1.28s/it]\u001b[A\u001b[A\n","\n","\n","Epoch17_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch17_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 52.09it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch17_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 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1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch20_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch20_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 50.85it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch20_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 50.54it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch20_TRAIN: 90%|████████████████▏ | 18/20 [00:00<00:00, 51.64it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch20_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch20_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 19.56it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch20_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 17.53it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 40%|██████████ | 20/50 [00:25<00:37, 1.23s/it]\u001b[A\u001b[A\n","\n","\n","Epoch21_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch21_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 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50%|████████████▌ | 25/50 [00:32<00:32, 1.31s/it]\u001b[A\u001b[A\n","\n","\n","Epoch26_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch26_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 46.75it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch26_TRAIN: 50%|█████████ | 10/20 [00:00<00:00, 47.52it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch26_TRAIN: 80%|██████████████▍ | 16/20 [00:00<00:00, 50.42it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch26_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch26_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 23.78it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 52%|█████████████ | 26/50 [00:33<00:30, 1.29s/it]\u001b[A\u001b[A\n","\n","\n","Epoch27_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch27_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 48.42it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch27_TRAIN: 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1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch30_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch30_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 47.01it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch30_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 51.25it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch30_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 50.21it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch30_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch30_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 18.81it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch30_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 18.21it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 60%|███████████████ | 30/50 [00:38<00:24, 1.23s/it]\u001b[A\u001b[A\n","\n","\n","Epoch31_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 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\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 16.15it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch42_TEST: 100%|█████████████████████| 5/5 [00:00<00:00, 15.79it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 84%|█████████████████████ | 42/50 [00:53<00:10, 1.27s/it]\u001b[A\u001b[A\n","\n","\n","Epoch43_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch43_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 39.07it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch43_TRAIN: 45%|████████▌ | 9/20 [00:00<00:00, 39.26it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch43_TRAIN: 70%|████████████▌ | 14/20 [00:00<00:00, 41.63it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch43_TRAIN: 95%|█████████████████ | 19/20 [00:00<00:00, 41.77it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch43_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch43_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 21.46it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 86%|█████████████████████▌ | 43/50 [00:55<00:09, 1.34s/it]\u001b[A\u001b[A\n","\n","\n","Epoch44_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch44_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 47.68it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch44_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 50.51it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch44_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 50.93it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch44_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch44_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 22.79it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 88%|██████████████████████ | 44/50 [00:56<00:07, 1.29s/it]\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 49.60it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 53.00it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 51.01it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch45_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 21.44it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 90%|██████████████████████▌ | 45/50 [00:57<00:06, 1.26s/it]\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 49.46it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 49.74it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TRAIN: 80%|██████████████▍ | 16/20 [00:00<00:00, 49.80it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch46_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 20.27it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 92%|███████████████████████ | 46/50 [00:58<00:05, 1.26s/it]\u001b[A\u001b[A\n","\n","\n","Epoch47_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch47_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 45.29it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch47_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 49.11it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch47_TRAIN: 80%|██████████████▍ | 16/20 [00:00<00:00, 46.86it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch47_TEST: 0%| | 0/5 [00:00<?, 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1.29s/it]\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 49.44it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 51.18it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 50.32it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch49_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 23.91it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 98%|████████████████████████▌| 49/50 [01:02<00:01, 1.26s/it]\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 46.01it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 55%|█████████▉ | 11/20 [00:00<00:00, 50.14it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TRAIN: 85%|███████████████▎ | 17/20 [00:00<00:00, 49.08it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 16.81it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch50_TEST: 80%|████████████████▊ | 4/5 [00:00<00:00, 17.33it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split4: 100%|█████████████████████████| 50/50 [01:03<00:00, 1.26s/it]\u001b[A\u001b[A\n","\n"," \u001b[A\u001b[A\n","SumMe: 80%|██████████████████████▍ | 4/5 [04:22<01:05, 65.30s/it]\u001b[A\n","\n","Split5: 0%| | 0/50 [00:00<?, ?it/s]\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 49.36it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 55%|██████████▍ | 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100%|███████████████████| 20/20 [00:00<00:00, 41.37it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch2_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch2_TEST: 40%|████████▊ | 2/5 [00:00<00:00, 16.20it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch2_TEST: 100%|██████████████████████| 5/5 [00:00<00:00, 18.18it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split5: 4%|█ | 2/50 [00:03<01:16, 1.59s/it]\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 20%|████ | 4/20 [00:00<00:00, 39.45it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 50%|█████████▌ | 10/20 [00:00<00:00, 48.38it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TRAIN: 75%|██████████████▎ | 15/20 [00:00<00:00, 48.03it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch3_TEST: 0%| | 0/5 [00:00<?, 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\u001b[A\u001b[A\u001b[A\n","\n","Split5: 8%|██ | 4/50 [00:05<01:03, 1.39s/it]\u001b[A\u001b[A\n","\n","\n","Epoch5_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch5_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 48.93it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch5_TRAIN: 55%|██████████▍ | 11/20 [00:00<00:00, 50.30it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch5_TRAIN: 85%|████████████████▏ | 17/20 [00:00<00:00, 50.84it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch5_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch5_TEST: 60%|█████████████▏ | 3/5 [00:00<00:00, 25.16it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split5: 10%|██▌ | 5/50 [00:06<00:59, 1.31s/it]\u001b[A\u001b[A\n","\n","\n","Epoch6_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch6_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 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1.22s/it]\u001b[A\u001b[A\n","\n","\n","Epoch9_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch9_TRAIN: 25%|█████ | 5/20 [00:00<00:00, 47.33it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch9_TRAIN: 55%|██████████▍ | 11/20 [00:00<00:00, 49.80it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch9_TRAIN: 80%|███████████████▏ | 16/20 [00:00<00:00, 48.98it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch9_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch9_TEST: 40%|████████▊ | 2/5 [00:00<00:00, 17.60it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split5: 18%|████▋ | 9/50 [00:11<00:52, 1.27s/it]\u001b[A\u001b[A\n","\n","\n","Epoch10_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch10_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 48.89it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch10_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 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[00:26<00:38, 1.32s/it]\u001b[A\u001b[A\n","\n","\n","Epoch22_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TRAIN: 20%|███▊ | 4/20 [00:00<00:00, 35.28it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TRAIN: 40%|███████▌ | 8/20 [00:00<00:00, 37.75it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 35.26it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TRAIN: 80%|██████████████▍ | 16/20 [00:00<00:00, 35.79it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TRAIN: 100%|██████████████████| 20/20 [00:00<00:00, 32.01it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 18.29it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch22_TEST: 100%|█████████████████████| 5/5 [00:00<00:00, 24.22it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," 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52%|█████████████ | 26/50 [00:33<00:29, 1.23s/it]\u001b[A\u001b[A\n","\n","\n","Epoch27_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch27_TRAIN: 30%|█████▋ | 6/20 [00:00<00:00, 50.15it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch27_TRAIN: 60%|██████████▊ | 12/20 [00:00<00:00, 49.42it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch27_TRAIN: 90%|████████████████▏ | 18/20 [00:00<00:00, 51.98it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch27_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch27_TEST: 60%|████████████▌ | 3/5 [00:00<00:00, 24.32it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split5: 54%|█████████████▌ | 27/50 [00:34<00:27, 1.21s/it]\u001b[A\u001b[A\n","\n","\n","Epoch28_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch28_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 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18.26it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split5: 60%|███████████████ | 30/50 [00:37<00:24, 1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch31_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 42.99it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TRAIN: 50%|█████████ | 10/20 [00:00<00:00, 43.12it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TRAIN: 75%|█████████████▌ | 15/20 [00:00<00:00, 42.28it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TRAIN: 100%|██████████████████| 20/20 [00:00<00:00, 41.71it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 17.68it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch31_TEST: 100%|█████████████████████| 5/5 [00:00<00:00, 19.13it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," 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1.24s/it]\u001b[A\u001b[A\n","\n","\n","Epoch41_TRAIN: 0%| | 0/20 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch41_TRAIN: 25%|████▊ | 5/20 [00:00<00:00, 42.46it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch41_TRAIN: 50%|█████████ | 10/20 [00:00<00:00, 42.19it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch41_TRAIN: 75%|█████████████▌ | 15/20 [00:00<00:00, 42.49it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch41_TRAIN: 100%|██████████████████| 20/20 [00:00<00:00, 43.79it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch41_TEST: 0%| | 0/5 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch41_TEST: 40%|████████▍ | 2/5 [00:00<00:00, 16.45it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch41_TEST: 100%|█████████████████████| 5/5 [00:00<00:00, 18.27it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n","Split5: 82%|████████████████████▌ | 41/50 [00:51<00:11, 1.30s/it]\u001b[A\u001b[A\n","\n","\n","Epoch42_TRAIN: 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14.48it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 35%|██████▋ | 14/40 [00:01<00:01, 14.54it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 42%|████████ | 17/40 [00:01<00:01, 15.28it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 48%|█████████ | 19/40 [00:01<00:01, 14.95it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 55%|██████████▍ | 22/40 [00:01<00:01, 16.47it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 60%|███████████▍ | 24/40 [00:01<00:01, 14.06it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n","Epoch1_TRAIN: 70%|█████████████▎ | 28/40 [00:01<00:00, 16.17it/s]\u001b[A\u001b[A\u001b[A\n","\n","\n"," \u001b[A\u001b[A\u001b[A\n","\n"," \u001b[A\u001b[A\n"," 50%|█████████████████ | 1/2 [05:32<05:32, 332.22s/it]\n","Traceback (most recent call last):\n"," File \"train.py\", line 82, in <module>\n"," output = model(feature)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1511, in _wrapped_call_impl\n"," return self._call_impl(*args, **kwargs)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1520, in _call_impl\n"," return forward_call(*args, **kwargs)\n"," File \"/content/CSTA/models/GoogleNet.py\", line 309, in forward\n"," x_att = self.googlenet(key)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1511, in _wrapped_call_impl\n"," return self._call_impl(*args, **kwargs)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1520, in _call_impl\n"," return forward_call(*args, **kwargs)\n"," File \"/content/CSTA/models/GoogleNet.py\", line 89, in forward\n"," x = self._forward(x,n_frame)\n"," File \"/content/CSTA/models/GoogleNet.py\", line 58, in _forward\n"," x = self.conv3(x)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1511, in _wrapped_call_impl\n"," return self._call_impl(*args, **kwargs)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1520, in _call_impl\n"," return forward_call(*args, **kwargs)\n"," File \"/content/CSTA/models/GoogleNet.py\", line 143, in forward\n"," x = self.conv(x)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1511, in _wrapped_call_impl\n"," return self._call_impl(*args, **kwargs)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/module.py\", line 1520, in _call_impl\n"," return forward_call(*args, **kwargs)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/conv.py\", line 460, in forward\n"," return self._conv_forward(input, self.weight, self.bias)\n"," File \"/usr/local/envs/newenv/lib/python3.8/site-packages/torch/nn/modules/conv.py\", line 456, in _conv_forward\n"," return F.conv2d(input, weight, bias, self.stride,\n","torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 6.12 MiB is free. Process 25174 has 14.73 GiB memory in use. Of the allocated memory 14.55 GiB is allocated by PyTorch, and 35.12 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)\n"]}]}]}

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