{"cells":[{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"import os\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.preprocessing import StandardScaler \nfrom scipy.signal import argrelextrema\nfrom tqdm import tqdm\nfrom sklearn.svm import SVR,NuSVR\nfrom sklearn.model_selection import GridSearchCV\nfrom multiprocessing import Pool\nfrom scipy import stats\nfrom joblib import Parallel, delayed\nfrom sklearn.neural_network import MLPRegressor\nfrom tsfresh.feature_extraction import feature_calculators\n\nsubset_size = [629145481, \n               100147179,\n               18227196][0]","execution_count":340,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"034e94741aab678430c4f0de633a1669b0b39637"},"cell_type":"code","source":"train=pd.read_csv(\"../input/train.csv\",nrows=subset_size, dtype={\"acoustic_data\": np.int16, \"time_to_failure\": np.float32})","execution_count":311,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"dc8031ad8dd7152e1de817f9cad9cc50536bc383"},"cell_type":"code","source":"def exps_to_data(train):\n    diff = train['time_to_failure'].diff().abs()\n    diff[0] = 0.001\n    exps_indices = np.array(diff[diff > 0.1].index)\n    \n    l = 0\n    r = 150000\n    jump = 35345\n    while r < train.shape[0]:\n        if all(np.logical_or(exps_indices <= l, exps_indices >= r)):\n            if train.iloc[l: r, :]['time_to_failure'].values[-1]>0.5:\n                yield train.iloc[l: r, :]\n            l += jump\n            r += jump\n        else:\n            l += 1\n            r += 1\nsegments = sum(1 for i in exps_to_data(train))\nprint(segments)","execution_count":341,"outputs":[{"output_type":"stream","text":"454\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"col_names = ['mean','max','variance','min', 'stdev', 'q1', 'q5','q95', 'q99',\n             'A0',\n'fft0_mean','fft0_max','fft0_min','fft0_q1','fft0_q5','fft0_q25','fft0_q50','fft0_q75','fft0_q95','fft0_q99','fft0_std',\n'fft1_mean','fft1_max','fft1_min','fft1_q1','fft1_q5','fft1_q25','fft1_q50','fft1_q75','fft1_q95','fft1_q99','fft1_std',\n'fft2_mean','fft2_max','fft2_min','fft2_q1','fft2_q5','fft2_q25','fft2_q50','fft2_q75','fft2_q95','fft2_q99','fft2_std',\n'fft3_mean','fft3_max','fft3_min','fft3_q1','fft3_q5','fft3_q25','fft3_q50','fft3_q75','fft3_q95','fft3_q99','fft3_std',\n             'q05_rolling_std_100', 'num_peak_1', 'autocorrelation_1'\n            ]    \n\ndef preprocess(seg, segment, X1, Y1=None):\n        if not Y1 is None:\n            Y1.loc[segment, 'time_to_failure'] = seg['time_to_failure'].values[-1]\n\n        x = seg['acoustic_data'].values\n        X1.loc[segment, 'mean'] = x.mean()\n        X1.loc[segment, 'stdev'] = x.std()\n        X1.loc[segment, 'variance'] = X1.loc[segment, 'stdev']**2\n        X1.loc[segment, 'max'] = x.max()\n        X1.loc[segment, 'min'] = x.min()\n        X1.loc[segment][['q1','q5','q95','q99']] =  np.quantile(x, [0.01,0.05,0.95,0.99]).transpose()\n        X1.loc[segment, 'q05_rolling_std_100'] = np.quantile(seg['acoustic_data'].rolling(100).std().dropna().values, 0.05)\n        \n        X1.loc[segment, 'autocorrelation_1'] = feature_calculators.autocorrelation(x, 1)\n        X1.loc[segment, 'num_peak_1'] = feature_calculators.number_peaks(x, 1)\n        \n        fft = np.abs(np.fft.fft(x)[:11000])\n        X1.loc[segment, 'A0'] = fft[0]\n        fft_lines = [1500,2500,4100,7900,11000]\n        for i in range(len(fft_lines)-1):\n            cur = fft[fft_lines[i]:fft_lines[i+1]]\n            X1.loc[segment,f'fft{i}_mean'] = cur.mean()\n            X1.loc[segment,f'fft{i}_max'] = cur.max()\n            X1.loc[segment,f'fft{i}_min'] = cur.min()\n            X1.loc[segment,f'fft{i}_q1'] = np.quantile(cur, 0.5)\n            X1.loc[segment,f'fft{i}_q5'] = np.quantile(cur, 0.5)\n            X1.loc[segment,f'fft{i}_q25'] = np.quantile(cur, 0.5)\n            X1.loc[segment,f'fft{i}_q50'] = np.quantile(cur, 0.5)\n            X1.loc[segment,f'fft{i}_q75'] = np.quantile(cur, 0.5)\n            X1.loc[segment,f'fft{i}_q95'] = np.quantile(cur, 0.5)\n            X1.loc[segment,f'fft{i}_q99'] = np.quantile(cur, 0.5)\n            X1.loc[segment,f'fft{i}_std'] = cur.std()\ncnt_segments = sum([1 for _ in exps_to_data(train)])","execution_count":327,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"9774aebd884b3cc342e5b539b7fffd599bf41fd0"},"cell_type":"code","source":"X1 = pd.DataFrame(index=range(segments), dtype=np.float64, columns=col_names)\nY1 = pd.DataFrame(index=range(segments), dtype=np.float64, columns=['time_to_failure'])\n\n_=[preprocess(seg, segment, X1, Y1) for segment, seg in tqdm(enumerate(exps_to_data(train)),total=cnt_segments)]","execution_count":328,"outputs":[{"output_type":"stream","text":"\n  0%|          | 0/52 [00:00<?, ?it/s]\u001b[A\n  2%|▏         | 1/52 [00:00<00:06,  8.08it/s]\u001b[A\n  8%|▊         | 4/52 [00:00<00:04, 10.02it/s]\u001b[A\n 13%|█▎        | 7/52 [00:00<00:03, 12.14it/s]\u001b[A\n 19%|█▉        | 10/52 [00:00<00:02, 14.11it/s]\u001b[A\n 25%|██▌       | 13/52 [00:00<00:03, 12.60it/s]\u001b[A\n 31%|███       | 16/52 [00:00<00:02, 14.65it/s]\u001b[A\n 37%|███▋      | 19/52 [00:01<00:01, 16.52it/s]\u001b[A\n 42%|████▏     | 22/52 [00:01<00:01, 18.15it/s]\u001b[A\n 48%|████▊     | 25/52 [00:01<00:01, 19.36it/s]\u001b[A\n 54%|█████▍    | 28/52 [00:01<00:01, 20.40it/s]\u001b[A\n 60%|█████▉    | 31/52 [00:01<00:01, 21.00it/s]\u001b[A\n 65%|██████▌   | 34/52 [00:01<00:00, 21.71it/s]\u001b[A\n 71%|███████   | 37/52 [00:01<00:00, 22.31it/s]\u001b[A\n 77%|███████▋  | 40/52 [00:01<00:00, 22.85it/s]\u001b[A\n 83%|████████▎ | 43/52 [00:02<00:00, 23.17it/s]\u001b[A\n 88%|████████▊ | 46/52 [00:02<00:00, 23.46it/s]\u001b[A\n 94%|█████████▍| 49/52 [00:02<00:00, 23.50it/s]\u001b[A\n100%|██████████| 52/52 [00:02<00:00, 23.43it/s]\u001b[A","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# segments = [x for x in exps_to_data(train)]\n# X1 = pd.DataFrame(index=range(len(segments)), dtype=np.float64)\n# for seg_id, seg in enumerate(segments):\n#     x = seg['acoustic_data'].values\n#     X1.loc[seg_id,'time_to_failure'] = seg['time_to_failure'].values[-1]\n#     std_res = seg['acoustic_data'].rolling(1000).std().dropna().values\n#     X1.loc[seg_id, 'q5'] = np.quantile(std_res, 0.05)\n\n","execution_count":329,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# sc=StandardScaler()\n# X2 = pd.DataFrame(sc.fit_transform(X1), columns = X1.columns)\n# plt.plot(X2)\n# plt.show()","execution_count":330,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"f44d6c037fef642f05c386657f3e7a154a897462"},"cell_type":"code","source":"sc=StandardScaler()\nsc.fit(X1)\nscX = pd.DataFrame(sc.transform(X1), columns = X1.columns)","execution_count":331,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"aa2bdeca00dfdbfb00ab83613b4bf67cb6cb7f5c"},"cell_type":"code","source":"parameters = [{'hidden_layer_sizes': [(100,), (100,100,), (100,100,100,)], 'activation': ['logistic', 'tanh', 'relu']}]\nmodel = GridSearchCV(MLPRegressor(), parameters, cv=5, scoring='neg_mean_absolute_error', n_jobs=4)\nmodel.fit(scX, Y1.values.flatten())","execution_count":332,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_search.py:841: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.\n  DeprecationWarning)\n/opt/conda/lib/python3.6/site-packages/sklearn/neural_network/multilayer_perceptron.py:562: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n  % self.max_iter, ConvergenceWarning)\n","name":"stderr"},{"output_type":"execute_result","execution_count":332,"data":{"text/plain":"GridSearchCV(cv=5, error_score='raise-deprecating',\n       estimator=MLPRegressor(activation='relu', alpha=0.0001, batch_size='auto', beta_1=0.9,\n       beta_2=0.999, early_stopping=False, epsilon=1e-08,\n       hidden_layer_sizes=(100,), learning_rate='constant',\n       learning_rate_init=0.001, max_iter=200, momentum=0.9,\n       n_iter_no_change=10, nesterovs_momentum=True, power_t=0.5,\n       random_state=None, shuffle=True, solver='adam', tol=0.0001,\n       validation_fraction=0.1, verbose=False, warm_start=False),\n       fit_params=None, iid='warn', n_jobs=4,\n       param_grid=[{'hidden_layer_sizes': [(100,), (100, 100), (100, 100, 100, 100, 100)], 'activation': ['logistic', 'tanh', 'relu']}],\n       pre_dispatch='2*n_jobs', refit=True, return_train_score='warn',\n       scoring='neg_mean_absolute_error', verbose=0)"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"model.cv_results_","execution_count":333,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/sklearn/utils/deprecation.py:125: FutureWarning: You are accessing a training score ('split0_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n  warnings.warn(*warn_args, **warn_kwargs)\n/opt/conda/lib/python3.6/site-packages/sklearn/utils/deprecation.py:125: FutureWarning: You are accessing a training score ('split1_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n  warnings.warn(*warn_args, **warn_kwargs)\n/opt/conda/lib/python3.6/site-packages/sklearn/utils/deprecation.py:125: FutureWarning: You are accessing a training score ('split2_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n  warnings.warn(*warn_args, **warn_kwargs)\n/opt/conda/lib/python3.6/site-packages/sklearn/utils/deprecation.py:125: FutureWarning: You are accessing a training score ('split3_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n  warnings.warn(*warn_args, **warn_kwargs)\n/opt/conda/lib/python3.6/site-packages/sklearn/utils/deprecation.py:125: FutureWarning: You are accessing a training score ('split4_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n  warnings.warn(*warn_args, **warn_kwargs)\n/opt/conda/lib/python3.6/site-packages/sklearn/utils/deprecation.py:125: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n  warnings.warn(*warn_args, **warn_kwargs)\n/opt/conda/lib/python3.6/site-packages/sklearn/utils/deprecation.py:125: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n  warnings.warn(*warn_args, **warn_kwargs)\n","name":"stderr"},{"output_type":"execute_result","execution_count":333,"data":{"text/plain":"{'mean_fit_time': array([0.63217359, 2.41135283, 3.61105242, 0.55295267, 1.82050338,\n        3.374157  , 0.47811394, 1.48810306, 2.08771238]),\n 'std_fit_time': array([0.10002107, 0.27053276, 0.17376128, 0.21799129, 0.23695676,\n        1.3635432 , 0.06865193, 0.06488646, 0.5870199 ]),\n 'mean_score_time': array([0.00264935, 0.00194688, 0.00208597, 0.00455799, 0.00316343,\n        0.00210915, 0.00308304, 0.00165997, 0.00330353]),\n 'std_score_time': array([1.10658628e-03, 1.71539502e-04, 1.12528255e-04, 5.79634793e-03,\n        2.72444792e-03, 1.19738985e-04, 2.88030609e-03, 3.73977154e-05,\n        2.70761684e-03]),\n 'param_activation': masked_array(data=['logistic', 'logistic', 'logistic', 'tanh', 'tanh',\n                    'tanh', 'relu', 'relu', 'relu'],\n              mask=[False, False, False, False, False, False, False, False,\n                    False],\n        fill_value='?',\n             dtype=object),\n 'param_hidden_layer_sizes': masked_array(data=[(100,), (100, 100), (100, 100, 100, 100, 100), (100,),\n                    (100, 100), (100, 100, 100, 100, 100), (100,),\n                    (100, 100), (100, 100, 100, 100, 100)],\n              mask=[False, False, False, False, False, False, False, False,\n                    False],\n        fill_value='?',\n             dtype=object),\n 'params': [{'activation': 'logistic', 'hidden_layer_sizes': (100,)},\n  {'activation': 'logistic', 'hidden_layer_sizes': (100, 100)},\n  {'activation': 'logistic', 'hidden_layer_sizes': (100, 100, 100, 100, 100)},\n  {'activation': 'tanh', 'hidden_layer_sizes': (100,)},\n  {'activation': 'tanh', 'hidden_layer_sizes': (100, 100)},\n  {'activation': 'tanh', 'hidden_layer_sizes': (100, 100, 100, 100, 100)},\n  {'activation': 'relu', 'hidden_layer_sizes': (100,)},\n  {'activation': 'relu', 'hidden_layer_sizes': (100, 100)},\n  {'activation': 'relu', 'hidden_layer_sizes': (100, 100, 100, 100, 100)}],\n 'split0_test_score': array([-1.12998649, -4.7879104 , -8.64232226, -9.99035556, -4.58182314,\n        -3.11780845, -7.48070413, -7.11876634, -6.11786511]),\n 'split1_test_score': array([-0.9378458 , -2.04121973, -4.152642  , -3.08274016, -1.2177447 ,\n        -1.01310488, -1.40693613, -0.5710771 , -0.58124727]),\n 'split2_test_score': array([-0.25704024, -0.83879672, -3.05538036, -2.35055576, -0.77382476,\n        -0.5558812 , -1.04018927, -0.76899225, -0.72844573]),\n 'split3_test_score': array([-2.51036377, -0.94107159, -2.06057714, -5.50825351, -1.62861188,\n        -0.95770915, -3.31618141, -1.14630999, -1.5431633 ]),\n 'split4_test_score': array([-2.34527361, -1.01072839, -1.09327972, -4.55405534, -2.11595022,\n        -2.1461539 , -4.62297086, -3.12253752, -2.18634233]),\n 'mean_test_score': array([-1.4206333 , -1.98127689, -3.90071113, -5.1525519 , -2.09575221,\n        -1.57764402, -3.6068742 , -2.59551299, -2.27441826]),\n 'std_test_score': array([0.84872487, 1.51898978, 2.65964602, 2.73134285, 1.35963165,\n        0.95186194, 2.3832646 , 2.50875773, 2.07249966]),\n 'rank_test_score': array([1, 3, 8, 9, 4, 2, 7, 6, 5], dtype=int32),\n 'split0_train_score': array([-0.97267501, -0.80518697, -1.03272735, -1.55540405, -0.34374656,\n        -1.12605638, -1.40908384, -0.19722867, -0.04751161]),\n 'split1_train_score': array([-1.00683487, -1.34958715, -3.33012843, -1.30117987, -0.16896132,\n        -0.10135668, -0.97436779, -0.09318413, -0.01895114]),\n 'split2_train_score': array([-0.91066902, -1.48695616, -3.5883273 , -1.60385495, -0.21352732,\n        -0.11991555, -1.07422051, -0.0819712 , -0.02300287]),\n 'split3_train_score': array([-0.96485045, -1.6807811 , -3.70406432, -1.81627358, -0.25568601,\n        -0.14379541, -1.10013618, -0.05544559, -0.03531172]),\n 'split4_train_score': array([-0.79788193, -1.62787437, -3.83105472, -1.60223731, -0.20505558,\n        -0.20682778, -0.86468899, -0.18356138, -0.02219016]),\n 'mean_train_score': array([-0.93058226, -1.39007715, -3.09726043, -1.57578995, -0.23739536,\n        -0.33959036, -1.08449946, -0.1222782 , -0.0293935 ]),\n 'std_train_score': array([0.07316623, 0.31438124, 1.04540289, 0.16440545, 0.05990641,\n        0.39484242, 0.18229142, 0.05711553, 0.01063073])}"},"metadata":{}}]},{"metadata":{"trusted":true,"_uuid":"98d44d2f94773685e2023372371665d1c88b5862"},"cell_type":"code","source":"sub=pd.read_csv(\"../input/sample_submission.csv\",index_col='seg_id')\nxtest=pd.DataFrame(columns=X1.columns,dtype=np.float64,index=sub.index)","execution_count":334,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"_ = Parallel(n_jobs=20, require='sharedmem', verbose=0)(\n    delayed(preprocess)(pd.read_csv('../input/test/' + seg_id + '.csv'), seg_id, xtest) for seg_id in tqdm(xtest.index))","execution_count":335,"outputs":[{"output_type":"stream","text":"\n  0%|          | 0/2624 [00:00<?, ?it/s]\u001b[A\n  0%|          | 5/2624 [00:00<01:03, 40.96it/s]\u001b[A\n  0%|          | 8/2624 [00:00<01:17, 33.76it/s]\u001b[A\n  0%|          | 10/2624 [00:00<01:35, 27.47it/s]\u001b[A\n  0%|          | 13/2624 [00:00<01:40, 26.03it/s]\u001b[A\n  1%|          | 15/2624 [00:00<01:54, 22.81it/s]\u001b[A\n  1%|          | 17/2624 [00:00<02:01, 21.43it/s]\u001b[A\n  1%|          | 20/2624 [00:00<01:59, 21.76it/s]\u001b[A\n  1%|          | 23/2624 [00:00<01:56, 22.34it/s]\u001b[A\n  1%|          | 26/2624 [00:01<02:00, 21.54it/s]\u001b[A\n  1%|          | 29/2624 [00:01<02:00, 21.53it/s]\u001b[A\n  1%|          | 32/2624 [00:01<02:12, 19.61it/s]\u001b[A\n  1%|▏         | 34/2624 [00:01<02:17, 18.82it/s]\u001b[A\n  1%|▏         | 36/2624 [00:01<02:27, 17.60it/s]\u001b[A\n  1%|▏         | 38/2624 [00:01<02:24, 17.84it/s]\u001b[A\n  2%|▏         | 40/2624 [00:01<02:27, 17.53it/s]\u001b[A\n  2%|▏         | 42/2624 [00:02<02:22, 18.08it/s]\u001b[A\n  2%|▏         | 44/2624 [00:02<02:24, 17.89it/s]\u001b[A\n  2%|▏         | 47/2624 [00:02<02:12, 19.44it/s]\u001b[A\n  2%|▏         | 49/2624 [00:02<02:17, 18.75it/s]\u001b[A\n  2%|▏         | 51/2624 [00:02<02:17, 18.75it/s]\u001b[A\n  2%|▏         | 53/2624 [00:02<02:18, 18.60it/s]\u001b[A\n  2%|▏         | 56/2624 [00:02<02:09, 19.78it/s]\u001b[A\n  2%|▏         | 59/2624 [00:02<02:09, 19.80it/s]\u001b[A\n  2%|▏         | 62/2624 [00:03<02:07, 20.02it/s]\u001b[A\n  2%|▏         | 65/2624 [00:03<02:08, 19.92it/s]\u001b[A\n  3%|▎         | 68/2624 [00:03<02:04, 20.48it/s]\u001b[A\n  3%|▎         | 71/2624 [00:03<02:05, 20.42it/s]\u001b[A\n  3%|▎         | 74/2624 [00:03<02:13, 19.08it/s]\u001b[A\n  3%|▎         | 77/2624 [00:03<02:09, 19.61it/s]\u001b[A\n  3%|▎         | 80/2624 [00:03<02:08, 19.87it/s]\u001b[A\n  3%|▎         | 83/2624 [00:04<02:09, 19.68it/s]\u001b[A\n  3%|▎         | 85/2624 [00:04<02:20, 18.07it/s]\u001b[A\n  3%|▎         | 87/2624 [00:04<02:16, 18.61it/s]\u001b[A\n  3%|▎         | 89/2624 [00:04<02:13, 18.96it/s]\u001b[A\n  3%|▎         | 91/2624 [00:04<02:12, 19.11it/s]\u001b[A\n  4%|▎         | 94/2624 [00:04<02:04, 20.31it/s]\u001b[A\n  4%|▎         | 97/2624 [00:04<02:01, 20.88it/s]\u001b[A\n  4%|▍         | 100/2624 [00:04<02:03, 20.39it/s]\u001b[A\n  4%|▍         | 103/2624 [00:05<02:04, 20.30it/s]\u001b[A\n  4%|▍         | 106/2624 [00:05<01:58, 21.33it/s]\u001b[A\n  4%|▍         | 109/2624 [00:05<02:05, 20.02it/s]\u001b[A\n  4%|▍         | 112/2624 [00:05<02:02, 20.49it/s]\u001b[A\n  4%|▍         | 115/2624 [00:05<02:13, 18.85it/s]\u001b[A\n  4%|▍         | 118/2624 [00:05<02:06, 19.82it/s]\u001b[A\n  5%|▍         | 121/2624 [00:05<02:04, 20.02it/s]\u001b[A\n  5%|▍         | 124/2624 [00:06<02:10, 19.17it/s]\u001b[A\n  5%|▍         | 126/2624 [00:06<02:25, 17.18it/s]\u001b[A\n  5%|▍         | 128/2624 [00:06<02:27, 16.91it/s]\u001b[A\n  5%|▍         | 130/2624 [00:06<02:23, 17.33it/s]\u001b[A\n  5%|▌         | 133/2624 [00:06<02:13, 18.68it/s]\u001b[A\n  5%|▌         | 136/2624 [00:06<02:07, 19.55it/s]\u001b[A\n  5%|▌         | 139/2624 [00:06<02:03, 20.19it/s]\u001b[A\n  5%|▌         | 142/2624 [00:07<02:04, 19.89it/s]\u001b[A\n  6%|▌         | 145/2624 [00:07<02:08, 19.25it/s]\u001b[A\n  6%|▌         | 147/2624 [00:07<02:22, 17.38it/s]\u001b[A\n  6%|▌         | 149/2624 [00:07<02:17, 17.96it/s]\u001b[A\n  6%|▌         | 152/2624 [00:07<02:11, 18.85it/s]\u001b[A\n  6%|▌         | 155/2624 [00:07<02:05, 19.73it/s]\u001b[A\n  6%|▌         | 158/2624 [00:07<02:02, 20.18it/s]\u001b[A\n  6%|▌         | 161/2624 [00:08<02:01, 20.19it/s]\u001b[A\n  6%|▋         | 164/2624 [00:08<02:10, 18.88it/s]\u001b[A\n  6%|▋         | 166/2624 [00:08<02:13, 18.45it/s]\u001b[A\n  6%|▋         | 169/2624 [00:08<02:06, 19.45it/s]\u001b[A\n  7%|▋         | 171/2624 [00:08<02:07, 19.30it/s]\u001b[A\n  7%|▋         | 173/2624 [00:08<02:09, 18.89it/s]\u001b[A\n  7%|▋         | 176/2624 [00:08<02:03, 19.75it/s]\u001b[A\n  7%|▋         | 178/2624 [00:08<02:08, 19.07it/s]\u001b[A\n  7%|▋         | 180/2624 [00:09<02:11, 18.63it/s]\u001b[A\n  7%|▋         | 182/2624 [00:09<02:10, 18.69it/s]\u001b[A\n  7%|▋         | 184/2624 [00:09<02:09, 18.87it/s]\u001b[A\n  7%|▋         | 187/2624 [00:09<02:01, 20.06it/s]\u001b[A\n  7%|▋         | 190/2624 [00:09<01:54, 21.17it/s]\u001b[A\n  7%|▋         | 193/2624 [00:09<01:56, 20.86it/s]\u001b[A\n  7%|▋         | 196/2624 [00:09<02:03, 19.63it/s]\u001b[A\n  8%|▊         | 199/2624 [00:09<01:56, 20.87it/s]\u001b[A\n  8%|▊         | 202/2624 [00:10<02:01, 19.90it/s]\u001b[A\n  8%|▊         | 205/2624 [00:10<01:55, 20.90it/s]\u001b[A\n  8%|▊         | 208/2624 [00:10<02:00, 20.11it/s]\u001b[A\n  8%|▊         | 211/2624 [00:10<02:03, 19.52it/s]\u001b[A\n  8%|▊         | 214/2624 [00:10<01:56, 20.61it/s]\u001b[A\n  8%|▊         | 217/2624 [00:10<01:55, 20.84it/s]\u001b[A\n  8%|▊         | 220/2624 [00:11<01:56, 20.59it/s]\u001b[A\n  8%|▊         | 223/2624 [00:11<02:03, 19.48it/s]\u001b[A\n  9%|▊         | 225/2624 [00:11<02:07, 18.77it/s]\u001b[A\n  9%|▊         | 227/2624 [00:11<02:07, 18.77it/s]\u001b[A\n  9%|▊         | 229/2624 [00:11<02:10, 18.29it/s]\u001b[A\n  9%|▉         | 232/2624 [00:11<02:02, 19.52it/s]\u001b[A\n  9%|▉         | 235/2624 [00:11<01:57, 20.37it/s]\u001b[A\n  9%|▉         | 238/2624 [00:11<01:58, 20.13it/s]\u001b[A\n  9%|▉         | 241/2624 [00:12<01:56, 20.47it/s]\u001b[A\n  9%|▉         | 244/2624 [00:12<02:00, 19.80it/s]\u001b[A\n  9%|▉         | 246/2624 [00:12<02:08, 18.56it/s]\u001b[A\n  9%|▉         | 248/2624 [00:12<02:06, 18.82it/s]\u001b[A\n 10%|▉         | 250/2624 [00:12<02:07, 18.60it/s]\u001b[A\n 10%|▉         | 252/2624 [00:12<02:06, 18.69it/s]\u001b[A\n 10%|▉         | 255/2624 [00:12<01:59, 19.75it/s]\u001b[A\n 10%|▉         | 257/2624 [00:12<01:59, 19.80it/s]\u001b[A\n 10%|▉         | 260/2624 [00:13<01:56, 20.37it/s]\u001b[A\n 10%|█         | 263/2624 [00:13<01:54, 20.65it/s]\u001b[A\n 10%|█         | 266/2624 [00:13<01:48, 21.80it/s]\u001b[A\n 10%|█         | 269/2624 [00:13<01:52, 20.86it/s]\u001b[A\n 10%|█         | 272/2624 [00:13<01:57, 20.00it/s]\u001b[A\n 10%|█         | 275/2624 [00:13<02:01, 19.37it/s]\u001b[A\n 11%|█         | 277/2624 [00:13<02:01, 19.26it/s]\u001b[A\n 11%|█         | 279/2624 [00:14<02:01, 19.28it/s]\u001b[A\n 11%|█         | 281/2624 [00:14<02:03, 18.92it/s]\u001b[A\n 11%|█         | 283/2624 [00:14<02:12, 17.67it/s]\u001b[A\n 11%|█         | 285/2624 [00:14<02:10, 17.97it/s]\u001b[A\n 11%|█         | 287/2624 [00:14<02:06, 18.44it/s]\u001b[A\n 11%|█         | 289/2624 [00:14<02:04, 18.76it/s]\u001b[A\n 11%|█         | 292/2624 [00:14<01:56, 20.06it/s]\u001b[A\n 11%|█         | 295/2624 [00:14<01:48, 21.56it/s]\u001b[A\n 11%|█▏        | 298/2624 [00:14<01:49, 21.25it/s]\u001b[A\n 11%|█▏        | 301/2624 [00:15<01:49, 21.30it/s]\u001b[A\n 12%|█▏        | 304/2624 [00:15<01:46, 21.75it/s]\u001b[A\n 12%|█▏        | 307/2624 [00:15<01:54, 20.23it/s]\u001b[A\n 12%|█▏        | 310/2624 [00:15<02:01, 19.07it/s]\u001b[A\n 12%|█▏        | 312/2624 [00:15<02:09, 17.91it/s]\u001b[A\n 12%|█▏        | 315/2624 [00:15<02:03, 18.75it/s]\u001b[A\n 12%|█▏        | 318/2624 [00:15<01:51, 20.66it/s]\u001b[A\n 12%|█▏        | 321/2624 [00:16<01:54, 20.06it/s]\u001b[A\n 12%|█▏        | 324/2624 [00:16<01:57, 19.64it/s]\u001b[A\n 12%|█▏        | 327/2624 [00:16<02:00, 19.10it/s]\u001b[A\n 13%|█▎        | 329/2624 [00:16<02:06, 18.09it/s]\u001b[A\n 13%|█▎        | 331/2624 [00:16<02:10, 17.57it/s]\u001b[A\n 13%|█▎        | 333/2624 [00:16<02:07, 17.96it/s]\u001b[A\n 13%|█▎        | 335/2624 [00:16<02:04, 18.37it/s]\u001b[A\n 13%|█▎        | 337/2624 [00:17<02:04, 18.35it/s]\u001b[A\n 13%|█▎        | 340/2624 [00:17<01:56, 19.61it/s]\u001b[A\n 13%|█▎        | 342/2624 [00:17<02:02, 18.61it/s]\u001b[A\n 13%|█▎        | 344/2624 [00:17<02:10, 17.51it/s]\u001b[A\n 13%|█▎        | 347/2624 [00:17<01:59, 19.01it/s]\u001b[A\n 13%|█▎        | 349/2624 [00:17<01:59, 19.01it/s]\u001b[A\n 13%|█▎        | 352/2624 [00:17<01:51, 20.43it/s]\u001b[A\n 14%|█▎        | 355/2624 [00:17<01:57, 19.27it/s]\u001b[A\n 14%|█▎        | 357/2624 [00:18<01:56, 19.39it/s]\u001b[A\n 14%|█▎        | 359/2624 [00:18<02:00, 18.86it/s]\u001b[A\n 14%|█▍        | 361/2624 [00:18<02:00, 18.77it/s]\u001b[A\n 14%|█▍        | 363/2624 [00:18<01:59, 18.89it/s]\u001b[A\n 14%|█▍        | 366/2624 [00:18<01:51, 20.19it/s]\u001b[A\n 14%|█▍        | 369/2624 [00:18<01:41, 22.16it/s]\u001b[A\n 14%|█▍        | 372/2624 [00:18<01:50, 20.38it/s]\u001b[A\n 14%|█▍        | 375/2624 [00:18<01:53, 19.88it/s]\u001b[A\n 14%|█▍        | 378/2624 [00:19<01:58, 19.02it/s]\u001b[A\n 14%|█▍        | 380/2624 [00:19<01:59, 18.81it/s]\u001b[A\n 15%|█▍        | 382/2624 [00:19<02:01, 18.50it/s]\u001b[A\n 15%|█▍        | 385/2624 [00:19<01:54, 19.50it/s]\u001b[A\n 15%|█▍        | 387/2624 [00:19<01:57, 19.04it/s]\u001b[A\n 15%|█▍        | 390/2624 [00:19<01:53, 19.65it/s]\u001b[A\n 15%|█▍        | 393/2624 [00:19<01:50, 20.27it/s]\u001b[A\n 15%|█▌        | 396/2624 [00:19<01:48, 20.48it/s]\u001b[A\n","name":"stderr"},{"output_type":"stream","text":" 15%|█▌        | 399/2624 [00:20<01:47, 20.66it/s]\u001b[A\n 15%|█▌        | 402/2624 [00:20<01:49, 20.30it/s]\u001b[A\n 15%|█▌        | 405/2624 [00:20<01:55, 19.13it/s]\u001b[A\n 16%|█▌        | 408/2624 [00:20<01:46, 20.77it/s]\u001b[A\n 16%|█▌        | 411/2624 [00:20<01:43, 21.29it/s]\u001b[A\n 16%|█▌        | 414/2624 [00:20<01:46, 20.72it/s]\u001b[A\n 16%|█▌        | 417/2624 [00:20<01:46, 20.66it/s]\u001b[A\n 16%|█▌        | 420/2624 [00:21<01:56, 18.86it/s]\u001b[A\n 16%|█▌        | 422/2624 [00:21<01:58, 18.59it/s]\u001b[A\n 16%|█▌        | 424/2624 [00:21<01:56, 18.92it/s]\u001b[A\n 16%|█▋        | 427/2624 [00:21<01:53, 19.34it/s]\u001b[A\n 16%|█▋        | 430/2624 [00:21<01:46, 20.54it/s]\u001b[A\n 17%|█▋        | 433/2624 [00:21<01:52, 19.41it/s]\u001b[A\n 17%|█▋        | 435/2624 [00:21<01:56, 18.87it/s]\u001b[A\n 17%|█▋        | 438/2624 [00:22<01:49, 20.00it/s]\u001b[A\n 17%|█▋        | 441/2624 [00:22<01:46, 20.52it/s]\u001b[A\n 17%|█▋        | 444/2624 [00:22<01:50, 19.75it/s]\u001b[A\n 17%|█▋        | 447/2624 [00:22<01:57, 18.53it/s]\u001b[A\n 17%|█▋        | 449/2624 [00:22<02:05, 17.37it/s]\u001b[A\n 17%|█▋        | 451/2624 [00:22<02:03, 17.56it/s]\u001b[A\n 17%|█▋        | 454/2624 [00:22<01:52, 19.21it/s]\u001b[A\n 17%|█▋        | 456/2624 [00:23<01:56, 18.67it/s]\u001b[A\n 17%|█▋        | 458/2624 [00:23<02:07, 17.02it/s]\u001b[A\n 18%|█▊        | 460/2624 [00:23<02:04, 17.33it/s]\u001b[A\n 18%|█▊        | 462/2624 [00:23<02:00, 17.91it/s]\u001b[A\n 18%|█▊        | 464/2624 [00:23<01:57, 18.45it/s]\u001b[A\n 18%|█▊        | 467/2624 [00:23<01:45, 20.35it/s]\u001b[A\n 18%|█▊        | 470/2624 [00:23<01:48, 19.90it/s]\u001b[A\n 18%|█▊        | 473/2624 [00:23<01:47, 20.00it/s]\u001b[A\n 18%|█▊        | 476/2624 [00:24<01:42, 20.99it/s]\u001b[A\n 18%|█▊        | 479/2624 [00:24<01:40, 21.35it/s]\u001b[A\n 18%|█▊        | 482/2624 [00:24<01:46, 20.12it/s]\u001b[A\n 18%|█▊        | 485/2624 [00:24<01:45, 20.34it/s]\u001b[A\n 19%|█▊        | 488/2624 [00:24<01:44, 20.50it/s]\u001b[A\n 19%|█▊        | 491/2624 [00:24<01:45, 20.25it/s]\u001b[A\n 19%|█▉        | 494/2624 [00:24<01:45, 20.11it/s]\u001b[A\n 19%|█▉        | 497/2624 [00:25<01:43, 20.58it/s]\u001b[A\n 19%|█▉        | 500/2624 [00:25<01:44, 20.42it/s]\u001b[A\n 19%|█▉        | 503/2624 [00:25<01:47, 19.77it/s]\u001b[A\n 19%|█▉        | 505/2624 [00:25<01:53, 18.71it/s]\u001b[A\n 19%|█▉        | 507/2624 [00:25<01:54, 18.56it/s]\u001b[A\n 19%|█▉        | 510/2624 [00:25<01:49, 19.33it/s]\u001b[A\n 20%|█▉        | 512/2624 [00:25<01:49, 19.29it/s]\u001b[A\n 20%|█▉        | 515/2624 [00:25<01:42, 20.50it/s]\u001b[A\n 20%|█▉        | 518/2624 [00:26<01:40, 20.90it/s]\u001b[A\n 20%|█▉        | 521/2624 [00:26<01:47, 19.48it/s]\u001b[A\n 20%|█▉        | 524/2624 [00:26<01:41, 20.78it/s]\u001b[A\n 20%|██        | 527/2624 [00:26<01:39, 21.12it/s]\u001b[A\n 20%|██        | 530/2624 [00:26<01:40, 20.90it/s]\u001b[A\n 20%|██        | 533/2624 [00:26<01:41, 20.55it/s]\u001b[A\n 20%|██        | 536/2624 [00:27<01:44, 19.91it/s]\u001b[A\n 21%|██        | 539/2624 [00:27<01:47, 19.42it/s]\u001b[A\n 21%|██        | 541/2624 [00:27<01:46, 19.55it/s]\u001b[A\n 21%|██        | 543/2624 [00:27<01:48, 19.14it/s]\u001b[A\n 21%|██        | 545/2624 [00:27<01:54, 18.23it/s]\u001b[A\n 21%|██        | 548/2624 [00:27<01:42, 20.22it/s]\u001b[A\n 21%|██        | 551/2624 [00:27<01:41, 20.47it/s]\u001b[A\n 21%|██        | 554/2624 [00:27<01:42, 20.28it/s]\u001b[A\n 21%|██        | 557/2624 [00:28<01:39, 20.72it/s]\u001b[A\n 21%|██▏       | 560/2624 [00:28<01:56, 17.69it/s]\u001b[A\n 21%|██▏       | 562/2624 [00:28<02:29, 13.77it/s]\u001b[A\n 21%|██▏       | 564/2624 [00:28<02:38, 13.01it/s]\u001b[A\n 22%|██▏       | 566/2624 [00:28<02:33, 13.43it/s]\u001b[A\n 22%|██▏       | 569/2624 [00:28<02:12, 15.53it/s]\u001b[A\n 22%|██▏       | 571/2624 [00:29<02:05, 16.36it/s]\u001b[A\n 22%|██▏       | 573/2624 [00:29<02:02, 16.74it/s]\u001b[A\n 22%|██▏       | 575/2624 [00:29<02:02, 16.70it/s]\u001b[A\n 22%|██▏       | 578/2624 [00:29<01:49, 18.64it/s]\u001b[A\n 22%|██▏       | 580/2624 [00:29<01:47, 18.97it/s]\u001b[A\n 22%|██▏       | 582/2624 [00:29<01:47, 19.02it/s]\u001b[A\n 22%|██▏       | 584/2624 [00:29<01:49, 18.61it/s]\u001b[A\n 22%|██▏       | 586/2624 [00:29<01:54, 17.75it/s]\u001b[A\n 22%|██▏       | 588/2624 [00:29<01:51, 18.18it/s]\u001b[A\n 22%|██▏       | 590/2624 [00:30<01:52, 18.09it/s]\u001b[A\n 23%|██▎       | 593/2624 [00:30<01:45, 19.27it/s]\u001b[A\n 23%|██▎       | 596/2624 [00:30<01:35, 21.32it/s]\u001b[A\n 23%|██▎       | 599/2624 [00:30<01:38, 20.49it/s]\u001b[A\n 23%|██▎       | 602/2624 [00:30<01:43, 19.63it/s]\u001b[A\n 23%|██▎       | 605/2624 [00:30<01:40, 20.04it/s]\u001b[A\n 23%|██▎       | 608/2624 [00:30<01:38, 20.44it/s]\u001b[A\n 23%|██▎       | 611/2624 [00:31<01:35, 21.08it/s]\u001b[A\n 23%|██▎       | 614/2624 [00:31<01:40, 20.04it/s]\u001b[A\n 24%|██▎       | 617/2624 [00:31<01:45, 19.01it/s]\u001b[A\n 24%|██▎       | 620/2624 [00:31<01:39, 20.13it/s]\u001b[A\n 24%|██▎       | 623/2624 [00:31<01:39, 20.11it/s]\u001b[A\n 24%|██▍       | 626/2624 [00:31<01:39, 20.04it/s]\u001b[A\n 24%|██▍       | 629/2624 [00:31<01:35, 20.95it/s]\u001b[A\n 24%|██▍       | 632/2624 [00:32<01:39, 20.03it/s]\u001b[A\n 24%|██▍       | 635/2624 [00:32<01:35, 20.76it/s]\u001b[A\n 24%|██▍       | 638/2624 [00:32<01:36, 20.53it/s]\u001b[A\n 24%|██▍       | 641/2624 [00:32<01:38, 20.13it/s]\u001b[A\n 25%|██▍       | 644/2624 [00:32<01:41, 19.51it/s]\u001b[A\n 25%|██▍       | 646/2624 [00:32<01:41, 19.47it/s]\u001b[A\n 25%|██▍       | 648/2624 [00:32<01:45, 18.70it/s]\u001b[A\n 25%|██▍       | 650/2624 [00:33<01:46, 18.48it/s]\u001b[A\n 25%|██▍       | 652/2624 [00:33<01:44, 18.81it/s]\u001b[A\n 25%|██▍       | 654/2624 [00:33<01:43, 18.96it/s]\u001b[A\n 25%|██▌       | 656/2624 [00:33<01:43, 19.00it/s]\u001b[A\n 25%|██▌       | 658/2624 [00:33<01:46, 18.53it/s]\u001b[A\n 25%|██▌       | 660/2624 [00:33<01:43, 18.89it/s]\u001b[A\n 25%|██▌       | 662/2624 [00:33<01:43, 19.00it/s]\u001b[A\n 25%|██▌       | 664/2624 [00:33<01:42, 19.18it/s]\u001b[A\n 25%|██▌       | 666/2624 [00:33<01:40, 19.41it/s]\u001b[A\n 25%|██▌       | 669/2624 [00:34<01:33, 20.84it/s]\u001b[A\n 26%|██▌       | 672/2624 [00:34<01:36, 20.33it/s]\u001b[A\n 26%|██▌       | 675/2624 [00:34<01:38, 19.80it/s]\u001b[A\n 26%|██▌       | 678/2624 [00:34<01:36, 20.23it/s]\u001b[A\n 26%|██▌       | 681/2624 [00:34<01:35, 20.34it/s]\u001b[A\n 26%|██▌       | 684/2624 [00:34<01:36, 20.21it/s]\u001b[A\n 26%|██▌       | 687/2624 [00:34<01:31, 21.13it/s]\u001b[A\n 26%|██▋       | 690/2624 [00:35<01:37, 19.75it/s]\u001b[A\n 26%|██▋       | 693/2624 [00:35<01:34, 20.42it/s]\u001b[A\n 27%|██▋       | 696/2624 [00:35<01:37, 19.69it/s]\u001b[A\n 27%|██▋       | 698/2624 [00:35<01:50, 17.38it/s]\u001b[A\n 27%|██▋       | 701/2624 [00:35<01:44, 18.46it/s]\u001b[A\n 27%|██▋       | 704/2624 [00:35<01:38, 19.55it/s]\u001b[A\n 27%|██▋       | 707/2624 [00:35<01:36, 19.85it/s]\u001b[A\n 27%|██▋       | 710/2624 [00:36<01:33, 20.56it/s]\u001b[A\n 27%|██▋       | 713/2624 [00:36<01:36, 19.76it/s]\u001b[A\n 27%|██▋       | 716/2624 [00:36<01:34, 20.25it/s]\u001b[A\n 27%|██▋       | 719/2624 [00:36<01:32, 20.56it/s]\u001b[A\n 28%|██▊       | 722/2624 [00:36<01:30, 21.04it/s]\u001b[A\n 28%|██▊       | 725/2624 [00:36<01:34, 20.01it/s]\u001b[A\n 28%|██▊       | 728/2624 [00:36<01:34, 20.14it/s]\u001b[A\n 28%|██▊       | 731/2624 [00:37<01:38, 19.24it/s]\u001b[A\n 28%|██▊       | 734/2624 [00:37<01:33, 20.22it/s]\u001b[A\n 28%|██▊       | 737/2624 [00:37<01:34, 20.02it/s]\u001b[A\n 28%|██▊       | 740/2624 [00:37<01:36, 19.47it/s]\u001b[A\n 28%|██▊       | 742/2624 [00:37<01:41, 18.51it/s]\u001b[A\n 28%|██▊       | 744/2624 [00:37<01:40, 18.79it/s]\u001b[A\n 28%|██▊       | 746/2624 [00:37<01:40, 18.72it/s]\u001b[A\n 29%|██▊       | 749/2624 [00:38<01:33, 20.00it/s]\u001b[A\n 29%|██▊       | 752/2624 [00:38<01:33, 19.97it/s]\u001b[A\n 29%|██▉       | 755/2624 [00:38<01:30, 20.56it/s]\u001b[A\n 29%|██▉       | 758/2624 [00:38<01:29, 20.79it/s]\u001b[A\n 29%|██▉       | 761/2624 [00:38<01:32, 20.12it/s]\u001b[A\n 29%|██▉       | 764/2624 [00:38<01:33, 19.95it/s]\u001b[A\n 29%|██▉       | 767/2624 [00:38<01:32, 20.10it/s]\u001b[A\n 29%|██▉       | 770/2624 [00:39<01:33, 19.90it/s]\u001b[A\n 29%|██▉       | 772/2624 [00:39<01:35, 19.49it/s]\u001b[A\n 29%|██▉       | 774/2624 [00:39<01:36, 19.10it/s]\u001b[A\n 30%|██▉       | 777/2624 [00:39<01:33, 19.69it/s]\u001b[A\n 30%|██▉       | 779/2624 [00:39<01:35, 19.27it/s]\u001b[A\n 30%|██▉       | 781/2624 [00:39<01:35, 19.20it/s]\u001b[A\n 30%|██▉       | 783/2624 [00:39<01:35, 19.37it/s]\u001b[A\n 30%|██▉       | 785/2624 [00:39<01:35, 19.17it/s]\u001b[A\n 30%|██▉       | 787/2624 [00:39<01:39, 18.45it/s]\u001b[A\n 30%|███       | 789/2624 [00:40<01:37, 18.78it/s]\u001b[A\n 30%|███       | 791/2624 [00:40<01:39, 18.33it/s]\u001b[A\n 30%|███       | 794/2624 [00:40<01:33, 19.51it/s]\u001b[A\n 30%|███       | 796/2624 [00:40<01:33, 19.45it/s]\u001b[A\n","name":"stderr"},{"output_type":"stream","text":" 30%|███       | 798/2624 [00:40<01:34, 19.39it/s]\u001b[A\n 30%|███       | 800/2624 [00:40<01:33, 19.41it/s]\u001b[A\n 31%|███       | 802/2624 [00:40<01:33, 19.46it/s]\u001b[A\n 31%|███       | 804/2624 [00:40<01:37, 18.72it/s]\u001b[A\n 31%|███       | 807/2624 [00:40<01:29, 20.31it/s]\u001b[A\n 31%|███       | 810/2624 [00:41<01:30, 20.07it/s]\u001b[A\n 31%|███       | 813/2624 [00:41<01:25, 21.13it/s]\u001b[A\n 31%|███       | 816/2624 [00:41<01:29, 20.25it/s]\u001b[A\n 31%|███       | 819/2624 [00:41<01:27, 20.67it/s]\u001b[A\n 31%|███▏      | 822/2624 [00:41<01:26, 20.92it/s]\u001b[A\n 31%|███▏      | 825/2624 [00:41<01:27, 20.48it/s]\u001b[A\n 32%|███▏      | 828/2624 [00:41<01:28, 20.39it/s]\u001b[A\n 32%|███▏      | 831/2624 [00:42<01:24, 21.20it/s]\u001b[A\n 32%|███▏      | 834/2624 [00:42<01:26, 20.64it/s]\u001b[A\n 32%|███▏      | 837/2624 [00:42<01:28, 20.30it/s]\u001b[A\n 32%|███▏      | 840/2624 [00:42<01:29, 20.04it/s]\u001b[A\n 32%|███▏      | 843/2624 [00:42<01:30, 19.70it/s]\u001b[A\n 32%|███▏      | 845/2624 [00:42<01:30, 19.60it/s]\u001b[A\n 32%|███▏      | 847/2624 [00:42<01:32, 19.11it/s]\u001b[A\n 32%|███▏      | 849/2624 [00:43<01:34, 18.85it/s]\u001b[A\n 32%|███▏      | 851/2624 [00:43<01:32, 19.09it/s]\u001b[A\n 33%|███▎      | 853/2624 [00:43<01:34, 18.82it/s]\u001b[A\n 33%|███▎      | 856/2624 [00:43<01:27, 20.19it/s]\u001b[A\n 33%|███▎      | 859/2624 [00:43<01:23, 21.19it/s]\u001b[A\n 33%|███▎      | 862/2624 [00:43<01:21, 21.49it/s]\u001b[A\n 33%|███▎      | 865/2624 [00:43<01:24, 20.84it/s]\u001b[A\n 33%|███▎      | 868/2624 [00:43<01:26, 20.23it/s]\u001b[A\n 33%|███▎      | 871/2624 [00:44<01:23, 21.04it/s]\u001b[A\n 33%|███▎      | 874/2624 [00:44<01:24, 20.70it/s]\u001b[A\n 33%|███▎      | 877/2624 [00:44<01:27, 19.92it/s]\u001b[A\n 34%|███▎      | 880/2624 [00:44<01:29, 19.46it/s]\u001b[A\n 34%|███▎      | 882/2624 [00:44<01:34, 18.47it/s]\u001b[A\n 34%|███▎      | 885/2624 [00:44<01:28, 19.74it/s]\u001b[A\n 34%|███▍      | 888/2624 [00:44<01:23, 20.80it/s]\u001b[A\n 34%|███▍      | 891/2624 [00:45<01:27, 19.70it/s]\u001b[A\n 34%|███▍      | 894/2624 [00:45<01:28, 19.46it/s]\u001b[A\n 34%|███▍      | 896/2624 [00:45<01:33, 18.48it/s]\u001b[A\n 34%|███▍      | 898/2624 [00:45<01:37, 17.69it/s]\u001b[A\n 34%|███▍      | 900/2624 [00:45<01:36, 17.90it/s]\u001b[A\n 34%|███▍      | 903/2624 [00:45<01:30, 19.04it/s]\u001b[A\n 34%|███▍      | 905/2624 [00:45<01:32, 18.51it/s]\u001b[A\n 35%|███▍      | 907/2624 [00:45<01:30, 18.88it/s]\u001b[A\n 35%|███▍      | 910/2624 [00:46<01:25, 20.05it/s]\u001b[A\n 35%|███▍      | 913/2624 [00:46<01:31, 18.76it/s]\u001b[A\n 35%|███▍      | 915/2624 [00:46<01:32, 18.43it/s]\u001b[A\n 35%|███▍      | 918/2624 [00:46<01:28, 19.27it/s]\u001b[A\n 35%|███▌      | 920/2624 [00:46<01:32, 18.37it/s]\u001b[A\n 35%|███▌      | 922/2624 [00:46<01:31, 18.63it/s]\u001b[A\n 35%|███▌      | 924/2624 [00:46<01:32, 18.31it/s]\u001b[A\n 35%|███▌      | 926/2624 [00:46<01:31, 18.52it/s]\u001b[A\n 35%|███▌      | 929/2624 [00:47<01:24, 19.95it/s]\u001b[A\n 36%|███▌      | 932/2624 [00:47<01:23, 20.21it/s]\u001b[A\n 36%|███▌      | 935/2624 [00:47<01:19, 21.27it/s]\u001b[A\n 36%|███▌      | 938/2624 [00:47<01:21, 20.61it/s]\u001b[A\n 36%|███▌      | 941/2624 [00:47<01:20, 20.92it/s]\u001b[A\n 36%|███▌      | 944/2624 [00:47<01:24, 19.95it/s]\u001b[A\n 36%|███▌      | 947/2624 [00:47<01:18, 21.26it/s]\u001b[A\n 36%|███▌      | 950/2624 [00:48<01:21, 20.57it/s]\u001b[A\n 36%|███▋      | 953/2624 [00:48<01:22, 20.29it/s]\u001b[A\n 36%|███▋      | 956/2624 [00:48<01:21, 20.51it/s]\u001b[A\n 37%|███▋      | 959/2624 [00:48<01:20, 20.74it/s]\u001b[A\n 37%|███▋      | 962/2624 [00:48<01:22, 20.13it/s]\u001b[A\n 37%|███▋      | 965/2624 [00:48<01:25, 19.31it/s]\u001b[A\n 37%|███▋      | 967/2624 [00:48<01:27, 19.02it/s]\u001b[A\n 37%|███▋      | 969/2624 [00:49<01:26, 19.16it/s]\u001b[A\n 37%|███▋      | 971/2624 [00:49<01:25, 19.26it/s]\u001b[A\n 37%|███▋      | 973/2624 [00:49<01:27, 18.94it/s]\u001b[A\n 37%|███▋      | 975/2624 [00:49<01:28, 18.59it/s]\u001b[A\n 37%|███▋      | 978/2624 [00:49<01:24, 19.55it/s]\u001b[A\n 37%|███▋      | 980/2624 [00:49<01:24, 19.35it/s]\u001b[A\n 37%|███▋      | 982/2624 [00:49<01:24, 19.45it/s]\u001b[A\n 38%|███▊      | 985/2624 [00:49<01:21, 20.19it/s]\u001b[A\n 38%|███▊      | 988/2624 [00:50<01:23, 19.70it/s]\u001b[A\n 38%|███▊      | 990/2624 [00:50<01:26, 18.82it/s]\u001b[A\n 38%|███▊      | 992/2624 [00:50<01:26, 18.79it/s]\u001b[A\n 38%|███▊      | 994/2624 [00:50<01:26, 18.89it/s]\u001b[A\n 38%|███▊      | 996/2624 [00:50<01:25, 18.95it/s]\u001b[A\n 38%|███▊      | 998/2624 [00:50<01:25, 19.08it/s]\u001b[A\n 38%|███▊      | 1001/2624 [00:50<01:21, 19.81it/s]\u001b[A\n 38%|███▊      | 1003/2624 [00:50<01:23, 19.41it/s]\u001b[A\n 38%|███▊      | 1005/2624 [00:50<01:23, 19.40it/s]\u001b[A\n 38%|███▊      | 1008/2624 [00:51<01:18, 20.57it/s]\u001b[A\n 39%|███▊      | 1011/2624 [00:51<01:21, 19.90it/s]\u001b[A\n 39%|███▊      | 1014/2624 [00:51<01:20, 20.11it/s]\u001b[A\n 39%|███▉      | 1017/2624 [00:51<01:19, 20.27it/s]\u001b[A\n 39%|███▉      | 1020/2624 [00:51<01:15, 21.29it/s]\u001b[A\n 39%|███▉      | 1023/2624 [00:51<01:17, 20.54it/s]\u001b[A\n 39%|███▉      | 1026/2624 [00:51<01:20, 19.79it/s]\u001b[A\n 39%|███▉      | 1028/2624 [00:52<01:22, 19.26it/s]\u001b[A\n 39%|███▉      | 1030/2624 [00:52<01:28, 17.96it/s]\u001b[A\n 39%|███▉      | 1032/2624 [00:52<01:29, 17.84it/s]\u001b[A\n 39%|███▉      | 1034/2624 [00:52<01:29, 17.83it/s]\u001b[A\n 39%|███▉      | 1036/2624 [00:52<01:26, 18.33it/s]\u001b[A\n 40%|███▉      | 1038/2624 [00:52<01:26, 18.31it/s]\u001b[A\n 40%|███▉      | 1041/2624 [00:52<01:19, 19.86it/s]\u001b[A\n 40%|███▉      | 1044/2624 [00:52<01:19, 19.88it/s]\u001b[A\n 40%|███▉      | 1047/2624 [00:53<01:16, 20.73it/s]\u001b[A\n 40%|████      | 1050/2624 [00:53<01:16, 20.65it/s]\u001b[A\n 40%|████      | 1053/2624 [00:53<01:20, 19.50it/s]\u001b[A\n 40%|████      | 1056/2624 [00:53<01:17, 20.25it/s]\u001b[A\n 40%|████      | 1059/2624 [00:53<01:18, 20.03it/s]\u001b[A\n 40%|████      | 1062/2624 [00:53<01:12, 21.54it/s]\u001b[A\n 41%|████      | 1065/2624 [00:53<01:13, 21.17it/s]\u001b[A\n 41%|████      | 1068/2624 [00:54<01:20, 19.44it/s]\u001b[A\n 41%|████      | 1070/2624 [00:54<01:26, 18.06it/s]\u001b[A\n 41%|████      | 1072/2624 [00:54<01:27, 17.69it/s]\u001b[A\n 41%|████      | 1075/2624 [00:54<01:23, 18.60it/s]\u001b[A\n 41%|████      | 1078/2624 [00:54<01:18, 19.62it/s]\u001b[A\n 41%|████      | 1081/2624 [00:54<01:12, 21.19it/s]\u001b[A\n 41%|████▏     | 1084/2624 [00:54<01:12, 21.18it/s]\u001b[A\n 41%|████▏     | 1087/2624 [00:55<01:13, 20.83it/s]\u001b[A\n 42%|████▏     | 1090/2624 [00:55<01:13, 20.89it/s]\u001b[A\n 42%|████▏     | 1093/2624 [00:55<01:18, 19.59it/s]\u001b[A\n 42%|████▏     | 1096/2624 [00:55<01:16, 19.97it/s]\u001b[A\n 42%|████▏     | 1099/2624 [00:55<01:16, 19.83it/s]\u001b[A\n 42%|████▏     | 1102/2624 [00:55<01:19, 19.22it/s]\u001b[A\n 42%|████▏     | 1105/2624 [00:55<01:15, 20.12it/s]\u001b[A\n 42%|████▏     | 1108/2624 [00:56<01:19, 19.00it/s]\u001b[A\n 42%|████▏     | 1110/2624 [00:56<01:27, 17.39it/s]\u001b[A\n 42%|████▏     | 1112/2624 [00:56<01:25, 17.69it/s]\u001b[A\n 42%|████▏     | 1114/2624 [00:56<01:25, 17.67it/s]\u001b[A\n 43%|████▎     | 1117/2624 [00:56<01:19, 19.05it/s]\u001b[A\n 43%|████▎     | 1119/2624 [00:56<01:20, 18.77it/s]\u001b[A\n 43%|████▎     | 1121/2624 [00:56<01:23, 17.94it/s]\u001b[A\n 43%|████▎     | 1124/2624 [00:56<01:19, 18.83it/s]\u001b[A\n 43%|████▎     | 1127/2624 [00:57<01:15, 19.80it/s]\u001b[A\n 43%|████▎     | 1130/2624 [00:57<01:14, 19.96it/s]\u001b[A\n 43%|████▎     | 1133/2624 [00:57<01:13, 20.24it/s]\u001b[A\n 43%|████▎     | 1136/2624 [00:57<01:14, 20.07it/s]\u001b[A\n 43%|████▎     | 1139/2624 [00:57<01:10, 21.08it/s]\u001b[A\n 44%|████▎     | 1142/2624 [00:57<01:09, 21.44it/s]\u001b[A\n 44%|████▎     | 1145/2624 [00:57<01:14, 19.99it/s]\u001b[A\n 44%|████▍     | 1148/2624 [00:58<01:17, 19.16it/s]\u001b[A\n 44%|████▍     | 1151/2624 [00:58<01:13, 20.13it/s]\u001b[A\n 44%|████▍     | 1154/2624 [00:58<01:12, 20.14it/s]\u001b[A\n 44%|████▍     | 1157/2624 [00:58<01:15, 19.51it/s]\u001b[A\n 44%|████▍     | 1159/2624 [00:58<01:15, 19.35it/s]\u001b[A\n 44%|████▍     | 1162/2624 [00:58<01:14, 19.74it/s]\u001b[A\n 44%|████▍     | 1165/2624 [00:59<01:12, 20.16it/s]\u001b[A\n 45%|████▍     | 1168/2624 [00:59<01:12, 20.11it/s]\u001b[A\n 45%|████▍     | 1171/2624 [00:59<01:14, 19.52it/s]\u001b[A\n 45%|████▍     | 1173/2624 [00:59<01:20, 18.05it/s]\u001b[A\n 45%|████▍     | 1175/2624 [00:59<01:18, 18.47it/s]\u001b[A\n 45%|████▍     | 1177/2624 [00:59<01:19, 18.15it/s]\u001b[A\n 45%|████▍     | 1179/2624 [00:59<01:17, 18.58it/s]\u001b[A\n 45%|████▌     | 1181/2624 [00:59<01:16, 18.82it/s]\u001b[A\n 45%|████▌     | 1184/2624 [00:59<01:11, 20.23it/s]\u001b[A\n 45%|████▌     | 1187/2624 [01:00<01:08, 20.99it/s]\u001b[A\n 45%|████▌     | 1190/2624 [01:00<01:11, 20.02it/s]\u001b[A\n 45%|████▌     | 1193/2624 [01:00<01:12, 19.87it/s]\u001b[A\n","name":"stderr"},{"output_type":"stream","text":" 46%|████▌     | 1196/2624 [01:00<01:11, 20.05it/s]\u001b[A\n 46%|████▌     | 1199/2624 [01:00<01:08, 20.74it/s]\u001b[A\n 46%|████▌     | 1202/2624 [01:00<01:10, 20.16it/s]\u001b[A\n 46%|████▌     | 1205/2624 [01:01<01:08, 20.76it/s]\u001b[A\n 46%|████▌     | 1208/2624 [01:01<01:08, 20.75it/s]\u001b[A\n 46%|████▌     | 1211/2624 [01:01<01:12, 19.47it/s]\u001b[A\n 46%|████▌     | 1213/2624 [01:01<01:16, 18.40it/s]\u001b[A\n 46%|████▋     | 1216/2624 [01:01<01:11, 19.70it/s]\u001b[A\n 46%|████▋     | 1219/2624 [01:01<01:09, 20.35it/s]\u001b[A\n 47%|████▋     | 1222/2624 [01:01<01:07, 20.73it/s]\u001b[A\n 47%|████▋     | 1225/2624 [01:02<01:10, 19.96it/s]\u001b[A\n 47%|████▋     | 1228/2624 [01:02<01:15, 18.59it/s]\u001b[A\n 47%|████▋     | 1230/2624 [01:02<01:19, 17.47it/s]\u001b[A\n 47%|████▋     | 1232/2624 [01:02<01:19, 17.53it/s]\u001b[A\n 47%|████▋     | 1235/2624 [01:02<01:12, 19.28it/s]\u001b[A\n 47%|████▋     | 1237/2624 [01:02<01:15, 18.29it/s]\u001b[A\n 47%|████▋     | 1239/2624 [01:02<01:15, 18.45it/s]\u001b[A\n 47%|████▋     | 1242/2624 [01:02<01:09, 20.00it/s]\u001b[A\n 47%|████▋     | 1245/2624 [01:03<01:04, 21.47it/s]\u001b[A\n 48%|████▊     | 1248/2624 [01:03<01:03, 21.55it/s]\u001b[A\n 48%|████▊     | 1251/2624 [01:03<01:07, 20.33it/s]\u001b[A\n 48%|████▊     | 1254/2624 [01:03<01:09, 19.83it/s]\u001b[A\n 48%|████▊     | 1257/2624 [01:03<01:11, 19.11it/s]\u001b[A\n 48%|████▊     | 1259/2624 [01:03<01:11, 19.01it/s]\u001b[A\n 48%|████▊     | 1261/2624 [01:03<01:21, 16.80it/s]\u001b[A\n 48%|████▊     | 1263/2624 [01:04<01:20, 16.98it/s]\u001b[A\n 48%|████▊     | 1265/2624 [01:04<01:18, 17.40it/s]\u001b[A\n 48%|████▊     | 1268/2624 [01:04<01:13, 18.43it/s]\u001b[A\n 48%|████▊     | 1270/2624 [01:04<01:16, 17.79it/s]\u001b[A\n 48%|████▊     | 1272/2624 [01:04<01:17, 17.52it/s]\u001b[A\n 49%|████▊     | 1274/2624 [01:04<01:17, 17.52it/s]\u001b[A\n 49%|████▊     | 1277/2624 [01:04<01:12, 18.61it/s]\u001b[A\n 49%|████▉     | 1280/2624 [01:04<01:09, 19.25it/s]\u001b[A\n 49%|████▉     | 1282/2624 [01:05<01:13, 18.29it/s]\u001b[A\n 49%|████▉     | 1284/2624 [01:05<01:14, 18.08it/s]\u001b[A\n 49%|████▉     | 1286/2624 [01:05<01:13, 18.11it/s]\u001b[A\n 49%|████▉     | 1289/2624 [01:05<01:09, 19.29it/s]\u001b[A\n 49%|████▉     | 1291/2624 [01:05<01:10, 18.98it/s]\u001b[A\n 49%|████▉     | 1294/2624 [01:05<01:06, 19.99it/s]\u001b[A\n 49%|████▉     | 1297/2624 [01:05<01:07, 19.74it/s]\u001b[A\n 50%|████▉     | 1299/2624 [01:05<01:07, 19.52it/s]\u001b[A\n 50%|████▉     | 1301/2624 [01:06<01:13, 18.04it/s]\u001b[A\n 50%|████▉     | 1303/2624 [01:06<01:15, 17.56it/s]\u001b[A\n 50%|████▉     | 1306/2624 [01:06<01:11, 18.47it/s]\u001b[A\n 50%|████▉     | 1309/2624 [01:06<01:05, 20.18it/s]\u001b[A\n 50%|█████     | 1312/2624 [01:06<01:02, 21.10it/s]\u001b[A\n 50%|█████     | 1315/2624 [01:06<01:01, 21.22it/s]\u001b[A\n 50%|█████     | 1318/2624 [01:06<01:02, 20.93it/s]\u001b[A\n 50%|█████     | 1321/2624 [01:06<01:04, 20.13it/s]\u001b[A\n 50%|█████     | 1324/2624 [01:07<01:04, 20.11it/s]\u001b[A\n 51%|█████     | 1327/2624 [01:07<01:09, 18.76it/s]\u001b[A\n 51%|█████     | 1329/2624 [01:07<01:08, 18.82it/s]\u001b[A\n 51%|█████     | 1331/2624 [01:07<01:09, 18.50it/s]\u001b[A\n 51%|█████     | 1333/2624 [01:07<01:11, 17.94it/s]\u001b[A\n 51%|█████     | 1335/2624 [01:07<01:11, 17.98it/s]\u001b[A\n 51%|█████     | 1337/2624 [01:07<01:11, 18.13it/s]\u001b[A\n 51%|█████     | 1339/2624 [01:07<01:11, 18.08it/s]\u001b[A\n 51%|█████     | 1342/2624 [01:08<01:05, 19.52it/s]\u001b[A\n 51%|█████     | 1344/2624 [01:08<01:07, 18.95it/s]\u001b[A\n 51%|█████▏    | 1346/2624 [01:08<01:06, 19.17it/s]\u001b[A\n 51%|█████▏    | 1348/2624 [01:08<01:07, 18.88it/s]\u001b[A\n 51%|█████▏    | 1351/2624 [01:08<01:03, 20.08it/s]\u001b[A\n 52%|█████▏    | 1354/2624 [01:08<01:02, 20.24it/s]\u001b[A\n 52%|█████▏    | 1357/2624 [01:08<01:01, 20.45it/s]\u001b[A\n 52%|█████▏    | 1360/2624 [01:09<01:01, 20.47it/s]\u001b[A\n 52%|█████▏    | 1363/2624 [01:09<01:05, 19.19it/s]\u001b[A\n 52%|█████▏    | 1365/2624 [01:09<01:08, 18.47it/s]\u001b[A\n 52%|█████▏    | 1367/2624 [01:09<01:07, 18.50it/s]\u001b[A\n 52%|█████▏    | 1369/2624 [01:09<01:11, 17.65it/s]\u001b[A\n 52%|█████▏    | 1372/2624 [01:09<01:05, 19.17it/s]\u001b[A\n 52%|█████▏    | 1375/2624 [01:09<01:03, 19.67it/s]\u001b[A\n 53%|█████▎    | 1378/2624 [01:09<01:02, 19.80it/s]\u001b[A\n 53%|█████▎    | 1381/2624 [01:10<01:01, 20.33it/s]\u001b[A\n 53%|█████▎    | 1384/2624 [01:10<01:01, 20.04it/s]\u001b[A\n 53%|█████▎    | 1387/2624 [01:10<00:59, 20.68it/s]\u001b[A\n 53%|█████▎    | 1390/2624 [01:10<00:59, 20.83it/s]\u001b[A\n 53%|█████▎    | 1393/2624 [01:10<01:02, 19.69it/s]\u001b[A\n 53%|█████▎    | 1395/2624 [01:10<01:09, 17.73it/s]\u001b[A\n 53%|█████▎    | 1397/2624 [01:10<01:11, 17.07it/s]\u001b[A\n 53%|█████▎    | 1400/2624 [01:11<01:05, 18.61it/s]\u001b[A\n 53%|█████▎    | 1403/2624 [01:11<01:02, 19.42it/s]\u001b[A\n 54%|█████▎    | 1406/2624 [01:11<01:01, 19.73it/s]\u001b[A\n 54%|█████▎    | 1409/2624 [01:11<01:05, 18.50it/s]\u001b[A\n 54%|█████▍    | 1411/2624 [01:11<01:06, 18.36it/s]\u001b[A\n 54%|█████▍    | 1413/2624 [01:11<01:05, 18.40it/s]\u001b[A\n 54%|█████▍    | 1415/2624 [01:11<01:04, 18.66it/s]\u001b[A\n 54%|█████▍    | 1417/2624 [01:11<01:04, 18.80it/s]\u001b[A\n 54%|█████▍    | 1420/2624 [01:12<01:00, 19.86it/s]\u001b[A\n 54%|█████▍    | 1423/2624 [01:12<01:01, 19.42it/s]\u001b[A\n 54%|█████▍    | 1425/2624 [01:12<01:02, 19.12it/s]\u001b[A\n 54%|█████▍    | 1427/2624 [01:12<01:03, 18.87it/s]\u001b[A\n 54%|█████▍    | 1429/2624 [01:12<01:03, 18.69it/s]\u001b[A\n 55%|█████▍    | 1432/2624 [01:12<01:00, 19.85it/s]\u001b[A\n 55%|█████▍    | 1435/2624 [01:12<00:56, 21.04it/s]\u001b[A\n 55%|█████▍    | 1438/2624 [01:13<00:57, 20.53it/s]\u001b[A\n 55%|█████▍    | 1441/2624 [01:13<00:57, 20.53it/s]\u001b[A\n 55%|█████▌    | 1444/2624 [01:13<00:58, 20.27it/s]\u001b[A\n 55%|█████▌    | 1447/2624 [01:13<01:00, 19.53it/s]\u001b[A\n 55%|█████▌    | 1449/2624 [01:13<01:03, 18.56it/s]\u001b[A\n 55%|█████▌    | 1452/2624 [01:13<01:01, 19.18it/s]\u001b[A\n 55%|█████▌    | 1454/2624 [01:13<01:01, 18.91it/s]\u001b[A\n 55%|█████▌    | 1456/2624 [01:13<01:02, 18.79it/s]\u001b[A\n 56%|█████▌    | 1458/2624 [01:14<01:02, 18.54it/s]\u001b[A\n 56%|█████▌    | 1461/2624 [01:14<00:58, 19.85it/s]\u001b[A\n 56%|█████▌    | 1464/2624 [01:14<00:58, 19.88it/s]\u001b[A\n 56%|█████▌    | 1467/2624 [01:14<00:55, 20.91it/s]\u001b[A\n 56%|█████▌    | 1470/2624 [01:14<00:54, 21.15it/s]\u001b[A\n 56%|█████▌    | 1473/2624 [01:14<00:51, 22.30it/s]\u001b[A\n 56%|█████▋    | 1476/2624 [01:14<00:56, 20.30it/s]\u001b[A\n 56%|█████▋    | 1479/2624 [01:15<01:01, 18.69it/s]\u001b[A\n 56%|█████▋    | 1481/2624 [01:15<01:03, 17.95it/s]\u001b[A\n 57%|█████▋    | 1483/2624 [01:15<01:02, 18.21it/s]\u001b[A\n 57%|█████▋    | 1486/2624 [01:15<00:59, 18.99it/s]\u001b[A\n 57%|█████▋    | 1488/2624 [01:15<00:59, 19.19it/s]\u001b[A\n 57%|█████▋    | 1490/2624 [01:15<01:00, 18.81it/s]\u001b[A\n 57%|█████▋    | 1493/2624 [01:15<00:57, 19.75it/s]\u001b[A\n 57%|█████▋    | 1496/2624 [01:15<00:56, 19.83it/s]\u001b[A\n 57%|█████▋    | 1499/2624 [01:16<00:55, 20.13it/s]\u001b[A\n 57%|█████▋    | 1502/2624 [01:16<00:57, 19.58it/s]\u001b[A\n 57%|█████▋    | 1504/2624 [01:16<00:58, 19.22it/s]\u001b[A\n 57%|█████▋    | 1507/2624 [01:16<00:55, 20.07it/s]\u001b[A\n 58%|█████▊    | 1510/2624 [01:16<00:56, 19.75it/s]\u001b[A\n 58%|█████▊    | 1512/2624 [01:16<00:57, 19.40it/s]\u001b[A\n 58%|█████▊    | 1514/2624 [01:16<00:56, 19.51it/s]\u001b[A\n 58%|█████▊    | 1516/2624 [01:17<00:58, 18.88it/s]\u001b[A\n 58%|█████▊    | 1519/2624 [01:17<00:56, 19.72it/s]\u001b[A\n 58%|█████▊    | 1522/2624 [01:17<00:54, 20.08it/s]\u001b[A\n 58%|█████▊    | 1525/2624 [01:17<00:56, 19.28it/s]\u001b[A\n 58%|█████▊    | 1527/2624 [01:17<00:59, 18.30it/s]\u001b[A\n 58%|█████▊    | 1529/2624 [01:17<01:01, 17.77it/s]\u001b[A\n 58%|█████▊    | 1531/2624 [01:17<01:06, 16.49it/s]\u001b[A\n 58%|█████▊    | 1534/2624 [01:17<00:57, 18.85it/s]\u001b[A\n 59%|█████▊    | 1537/2624 [01:18<00:56, 19.20it/s]\u001b[A\n 59%|█████▊    | 1540/2624 [01:18<00:57, 18.82it/s]\u001b[A\n 59%|█████▉    | 1542/2624 [01:18<00:57, 18.95it/s]\u001b[A\n 59%|█████▉    | 1544/2624 [01:18<00:58, 18.47it/s]\u001b[A\n 59%|█████▉    | 1546/2624 [01:18<00:58, 18.46it/s]\u001b[A\n 59%|█████▉    | 1548/2624 [01:18<00:59, 18.09it/s]\u001b[A\n 59%|█████▉    | 1551/2624 [01:18<00:55, 19.41it/s]\u001b[A\n 59%|█████▉    | 1553/2624 [01:18<00:55, 19.16it/s]\u001b[A\n 59%|█████▉    | 1555/2624 [01:19<00:56, 18.82it/s]\u001b[A\n 59%|█████▉    | 1558/2624 [01:19<00:53, 19.93it/s]\u001b[A\n 59%|█████▉    | 1561/2624 [01:19<00:56, 18.93it/s]\u001b[A\n 60%|█████▉    | 1563/2624 [01:19<00:59, 17.91it/s]\u001b[A\n 60%|█████▉    | 1565/2624 [01:19<00:58, 17.96it/s]\u001b[A\n 60%|█████▉    | 1568/2624 [01:19<00:54, 19.39it/s]\u001b[A\n 60%|█████▉    | 1570/2624 [01:19<00:55, 18.92it/s]\u001b[A\n 60%|█████▉    | 1573/2624 [01:19<00:51, 20.40it/s]\u001b[A\n","name":"stderr"},{"output_type":"stream","text":" 60%|██████    | 1576/2624 [01:20<00:50, 20.66it/s]\u001b[A\n 60%|██████    | 1579/2624 [01:20<00:54, 19.35it/s]\u001b[A\n 60%|██████    | 1582/2624 [01:20<00:51, 20.23it/s]\u001b[A\n 60%|██████    | 1585/2624 [01:20<00:52, 19.97it/s]\u001b[A\n 61%|██████    | 1588/2624 [01:20<00:50, 20.40it/s]\u001b[A\n 61%|██████    | 1591/2624 [01:20<00:52, 19.55it/s]\u001b[A\n 61%|██████    | 1594/2624 [01:21<00:50, 20.29it/s]\u001b[A\n 61%|██████    | 1597/2624 [01:21<00:55, 18.65it/s]\u001b[A\n 61%|██████    | 1599/2624 [01:21<00:58, 17.42it/s]\u001b[A\n 61%|██████    | 1601/2624 [01:21<00:59, 17.30it/s]\u001b[A\n 61%|██████    | 1604/2624 [01:21<00:54, 18.74it/s]\u001b[A\n 61%|██████    | 1607/2624 [01:21<00:51, 19.79it/s]\u001b[A\n 61%|██████▏   | 1610/2624 [01:21<00:50, 20.19it/s]\u001b[A\n 61%|██████▏   | 1613/2624 [01:21<00:48, 20.86it/s]\u001b[A\n 62%|██████▏   | 1616/2624 [01:22<00:52, 19.37it/s]\u001b[A\n 62%|██████▏   | 1618/2624 [01:22<00:55, 18.05it/s]\u001b[A\n 62%|██████▏   | 1620/2624 [01:22<00:56, 17.82it/s]\u001b[A\n 62%|██████▏   | 1622/2624 [01:22<00:54, 18.28it/s]\u001b[A\n 62%|██████▏   | 1625/2624 [01:22<00:49, 20.01it/s]\u001b[A\n 62%|██████▏   | 1628/2624 [01:22<00:50, 19.74it/s]\u001b[A\n 62%|██████▏   | 1631/2624 [01:22<00:51, 19.28it/s]\u001b[A\n 62%|██████▏   | 1634/2624 [01:23<00:50, 19.77it/s]\u001b[A\n 62%|██████▏   | 1637/2624 [01:23<00:49, 20.00it/s]\u001b[A\n 62%|██████▎   | 1640/2624 [01:23<00:50, 19.51it/s]\u001b[A\n 63%|██████▎   | 1642/2624 [01:23<00:51, 18.95it/s]\u001b[A\n 63%|██████▎   | 1645/2624 [01:23<00:48, 20.39it/s]\u001b[A\n 63%|██████▎   | 1648/2624 [01:23<00:50, 19.46it/s]\u001b[A\n 63%|██████▎   | 1651/2624 [01:23<00:49, 19.82it/s]\u001b[A\n 63%|██████▎   | 1654/2624 [01:24<00:49, 19.73it/s]\u001b[A\n 63%|██████▎   | 1657/2624 [01:24<00:47, 20.32it/s]\u001b[A\n 63%|██████▎   | 1660/2624 [01:24<00:46, 20.58it/s]\u001b[A\n 63%|██████▎   | 1663/2624 [01:24<00:48, 19.64it/s]\u001b[A\n 63%|██████▎   | 1665/2624 [01:24<00:50, 19.14it/s]\u001b[A\n 64%|██████▎   | 1668/2624 [01:24<00:47, 20.12it/s]\u001b[A\n 64%|██████▎   | 1671/2624 [01:24<00:45, 20.74it/s]\u001b[A\n 64%|██████▍   | 1674/2624 [01:25<00:44, 21.28it/s]\u001b[A\n 64%|██████▍   | 1677/2624 [01:25<00:46, 20.17it/s]\u001b[A\n 64%|██████▍   | 1680/2624 [01:25<00:44, 21.35it/s]\u001b[A\n 64%|██████▍   | 1683/2624 [01:25<00:43, 21.55it/s]\u001b[A\n 64%|██████▍   | 1686/2624 [01:25<00:47, 19.85it/s]\u001b[A\n 64%|██████▍   | 1689/2624 [01:25<00:46, 19.93it/s]\u001b[A\n 64%|██████▍   | 1692/2624 [01:25<00:49, 18.90it/s]\u001b[A\n 65%|██████▍   | 1694/2624 [01:26<00:51, 18.17it/s]\u001b[A\n 65%|██████▍   | 1697/2624 [01:26<00:47, 19.34it/s]\u001b[A\n 65%|██████▍   | 1700/2624 [01:26<00:44, 20.58it/s]\u001b[A\n 65%|██████▍   | 1703/2624 [01:26<00:46, 19.92it/s]\u001b[A\n 65%|██████▌   | 1706/2624 [01:26<00:46, 19.96it/s]\u001b[A\n 65%|██████▌   | 1709/2624 [01:26<00:45, 20.05it/s]\u001b[A\n 65%|██████▌   | 1712/2624 [01:26<00:44, 20.58it/s]\u001b[A\n 65%|██████▌   | 1715/2624 [01:27<00:45, 19.90it/s]\u001b[A\n 65%|██████▌   | 1718/2624 [01:27<00:44, 20.42it/s]\u001b[A\n 66%|██████▌   | 1721/2624 [01:27<00:44, 20.33it/s]\u001b[A\n 66%|██████▌   | 1724/2624 [01:27<00:45, 19.90it/s]\u001b[A\n 66%|██████▌   | 1726/2624 [01:27<00:46, 19.34it/s]\u001b[A\n 66%|██████▌   | 1728/2624 [01:27<00:47, 19.06it/s]\u001b[A\n 66%|██████▌   | 1730/2624 [01:27<00:49, 17.90it/s]\u001b[A\n 66%|██████▌   | 1733/2624 [01:28<00:46, 19.16it/s]\u001b[A\n 66%|██████▌   | 1735/2624 [01:28<00:46, 19.13it/s]\u001b[A\n 66%|██████▌   | 1737/2624 [01:28<00:48, 18.31it/s]\u001b[A\n 66%|██████▋   | 1739/2624 [01:28<00:47, 18.79it/s]\u001b[A\n 66%|██████▋   | 1742/2624 [01:28<00:44, 19.97it/s]\u001b[A\n 67%|██████▋   | 1745/2624 [01:28<00:43, 20.21it/s]\u001b[A\n 67%|██████▋   | 1748/2624 [01:28<00:44, 19.77it/s]\u001b[A\n 67%|██████▋   | 1751/2624 [01:28<00:42, 20.66it/s]\u001b[A\n 67%|██████▋   | 1754/2624 [01:29<00:40, 21.29it/s]\u001b[A\n 67%|██████▋   | 1757/2624 [01:29<00:41, 20.66it/s]\u001b[A\n 67%|██████▋   | 1760/2624 [01:29<00:42, 20.29it/s]\u001b[A\n 67%|██████▋   | 1763/2624 [01:29<00:44, 19.30it/s]\u001b[A\n 67%|██████▋   | 1765/2624 [01:29<00:44, 19.37it/s]\u001b[A\n 67%|██████▋   | 1768/2624 [01:29<00:41, 20.84it/s]\u001b[A\n 67%|██████▋   | 1771/2624 [01:29<00:39, 21.37it/s]\u001b[A\n 68%|██████▊   | 1774/2624 [01:30<00:40, 20.79it/s]\u001b[A\n 68%|██████▊   | 1777/2624 [01:30<00:43, 19.66it/s]\u001b[A\n 68%|██████▊   | 1779/2624 [01:30<00:44, 19.05it/s]\u001b[A\n 68%|██████▊   | 1781/2624 [01:30<00:46, 18.03it/s]\u001b[A\n 68%|██████▊   | 1783/2624 [01:30<00:48, 17.48it/s]\u001b[A\n 68%|██████▊   | 1785/2624 [01:30<00:47, 17.67it/s]\u001b[A\n 68%|██████▊   | 1787/2624 [01:30<00:46, 18.08it/s]\u001b[A\n 68%|██████▊   | 1789/2624 [01:30<00:45, 18.18it/s]\u001b[A\n 68%|██████▊   | 1792/2624 [01:31<00:43, 18.99it/s]\u001b[A\n 68%|██████▊   | 1794/2624 [01:31<00:45, 18.34it/s]\u001b[A\n 68%|██████▊   | 1797/2624 [01:31<00:42, 19.41it/s]\u001b[A\n 69%|██████▊   | 1799/2624 [01:31<00:42, 19.49it/s]\u001b[A\n 69%|██████▊   | 1801/2624 [01:31<00:43, 19.12it/s]\u001b[A\n 69%|██████▊   | 1803/2624 [01:31<00:42, 19.15it/s]\u001b[A\n 69%|██████▉   | 1805/2624 [01:31<00:42, 19.13it/s]\u001b[A\n 69%|██████▉   | 1807/2624 [01:31<00:42, 19.19it/s]\u001b[A\n 69%|██████▉   | 1810/2624 [01:31<00:39, 20.35it/s]\u001b[A\n 69%|██████▉   | 1813/2624 [01:32<00:40, 20.15it/s]\u001b[A\n 69%|██████▉   | 1816/2624 [01:32<00:40, 19.97it/s]\u001b[A\n 69%|██████▉   | 1819/2624 [01:32<00:40, 19.93it/s]\u001b[A\n 69%|██████▉   | 1822/2624 [01:32<00:41, 19.21it/s]\u001b[A\n 70%|██████▉   | 1824/2624 [01:32<00:41, 19.18it/s]\u001b[A\n 70%|██████▉   | 1827/2624 [01:32<00:40, 19.87it/s]\u001b[A\n 70%|██████▉   | 1829/2624 [01:32<00:41, 19.20it/s]\u001b[A\n 70%|██████▉   | 1831/2624 [01:33<00:41, 19.22it/s]\u001b[A\n 70%|██████▉   | 1833/2624 [01:33<00:40, 19.36it/s]\u001b[A\n 70%|██████▉   | 1836/2624 [01:33<00:38, 20.24it/s]\u001b[A\n 70%|███████   | 1839/2624 [01:33<00:38, 20.13it/s]\u001b[A\n 70%|███████   | 1842/2624 [01:33<00:38, 20.57it/s]\u001b[A\n 70%|███████   | 1845/2624 [01:33<00:39, 19.65it/s]\u001b[A\n 70%|███████   | 1848/2624 [01:33<00:38, 20.11it/s]\u001b[A\n 71%|███████   | 1851/2624 [01:34<00:39, 19.75it/s]\u001b[A\n 71%|███████   | 1853/2624 [01:34<00:41, 18.42it/s]\u001b[A\n 71%|███████   | 1855/2624 [01:34<00:42, 17.90it/s]\u001b[A\n 71%|███████   | 1857/2624 [01:34<00:43, 17.80it/s]\u001b[A\n 71%|███████   | 1860/2624 [01:34<00:40, 18.82it/s]\u001b[A\n 71%|███████   | 1863/2624 [01:34<00:37, 20.15it/s]\u001b[A\n 71%|███████   | 1866/2624 [01:34<00:35, 21.36it/s]\u001b[A\n 71%|███████   | 1869/2624 [01:34<00:35, 21.35it/s]\u001b[A\n 71%|███████▏  | 1872/2624 [01:35<00:37, 20.07it/s]\u001b[A\n 71%|███████▏  | 1875/2624 [01:35<00:37, 19.88it/s]\u001b[A\n 72%|███████▏  | 1878/2624 [01:35<00:37, 19.87it/s]\u001b[A\n 72%|███████▏  | 1881/2624 [01:35<00:36, 20.41it/s]\u001b[A\n 72%|███████▏  | 1884/2624 [01:35<00:35, 20.58it/s]\u001b[A\n 72%|███████▏  | 1887/2624 [01:35<00:35, 20.56it/s]\u001b[A\n 72%|███████▏  | 1890/2624 [01:35<00:36, 20.09it/s]\u001b[A\n 72%|███████▏  | 1893/2624 [01:36<00:35, 20.53it/s]\u001b[A\n 72%|███████▏  | 1896/2624 [01:36<00:36, 20.00it/s]\u001b[A\n 72%|███████▏  | 1899/2624 [01:36<00:37, 19.43it/s]\u001b[A\n 72%|███████▏  | 1901/2624 [01:36<00:38, 18.96it/s]\u001b[A\n 73%|███████▎  | 1903/2624 [01:36<00:39, 18.46it/s]\u001b[A\n 73%|███████▎  | 1906/2624 [01:36<00:35, 20.17it/s]\u001b[A\n 73%|███████▎  | 1909/2624 [01:36<00:33, 21.06it/s]\u001b[A\n 73%|███████▎  | 1912/2624 [01:37<00:33, 21.09it/s]\u001b[A\n 73%|███████▎  | 1915/2624 [01:37<00:35, 19.88it/s]\u001b[A\n 73%|███████▎  | 1918/2624 [01:37<00:37, 18.93it/s]\u001b[A\n 73%|███████▎  | 1920/2624 [01:37<00:37, 18.64it/s]\u001b[A\n 73%|███████▎  | 1923/2624 [01:37<00:35, 20.03it/s]\u001b[A\n 73%|███████▎  | 1926/2624 [01:37<00:33, 20.90it/s]\u001b[A\n 74%|███████▎  | 1929/2624 [01:37<00:34, 20.00it/s]\u001b[A\n 74%|███████▎  | 1932/2624 [01:38<00:34, 19.83it/s]\u001b[A\n 74%|███████▎  | 1935/2624 [01:38<00:33, 20.42it/s]\u001b[A\n 74%|███████▍  | 1938/2624 [01:38<00:34, 20.05it/s]\u001b[A\n 74%|███████▍  | 1941/2624 [01:38<00:36, 18.92it/s]\u001b[A\n 74%|███████▍  | 1943/2624 [01:38<00:35, 19.17it/s]\u001b[A\n 74%|███████▍  | 1946/2624 [01:38<00:34, 19.86it/s]\u001b[A\n 74%|███████▍  | 1949/2624 [01:38<00:33, 20.21it/s]\u001b[A\n 74%|███████▍  | 1952/2624 [01:39<00:31, 21.24it/s]\u001b[A\n 75%|███████▍  | 1955/2624 [01:39<00:33, 20.14it/s]\u001b[A\n 75%|███████▍  | 1958/2624 [01:39<00:34, 19.54it/s]\u001b[A\n 75%|███████▍  | 1960/2624 [01:39<00:34, 19.16it/s]\u001b[A\n 75%|███████▍  | 1962/2624 [01:39<00:34, 19.06it/s]\u001b[A\n 75%|███████▍  | 1964/2624 [01:39<00:36, 18.16it/s]\u001b[A\n 75%|███████▍  | 1966/2624 [01:39<00:36, 17.97it/s]\u001b[A\n 75%|███████▌  | 1969/2624 [01:39<00:34, 19.03it/s]\u001b[A\n 75%|███████▌  | 1971/2624 [01:40<00:34, 18.81it/s]\u001b[A\n 75%|███████▌  | 1973/2624 [01:40<00:36, 17.83it/s]\u001b[A\n","name":"stderr"},{"output_type":"stream","text":" 75%|███████▌  | 1975/2624 [01:40<00:37, 17.33it/s]\u001b[A\n 75%|███████▌  | 1977/2624 [01:40<00:36, 17.74it/s]\u001b[A\n 75%|███████▌  | 1980/2624 [01:40<00:33, 19.44it/s]\u001b[A\n 76%|███████▌  | 1983/2624 [01:40<00:31, 20.64it/s]\u001b[A\n 76%|███████▌  | 1986/2624 [01:40<00:31, 20.02it/s]\u001b[A\n 76%|███████▌  | 1989/2624 [01:40<00:31, 20.15it/s]\u001b[A\n 76%|███████▌  | 1992/2624 [01:41<00:30, 20.60it/s]\u001b[A\n 76%|███████▌  | 1995/2624 [01:41<00:30, 20.33it/s]\u001b[A\n 76%|███████▌  | 1998/2624 [01:41<00:31, 20.01it/s]\u001b[A\n 76%|███████▋  | 2001/2624 [01:41<00:31, 19.98it/s]\u001b[A\n 76%|███████▋  | 2004/2624 [01:41<00:29, 20.72it/s]\u001b[A\n 76%|███████▋  | 2007/2624 [01:41<00:31, 19.61it/s]\u001b[A\n 77%|███████▋  | 2009/2624 [01:42<00:33, 18.62it/s]\u001b[A\n 77%|███████▋  | 2011/2624 [01:42<00:36, 16.79it/s]\u001b[A\n 77%|███████▋  | 2013/2624 [01:42<00:35, 17.31it/s]\u001b[A\n 77%|███████▋  | 2016/2624 [01:42<00:32, 18.90it/s]\u001b[A\n 77%|███████▋  | 2019/2624 [01:42<00:31, 19.46it/s]\u001b[A\n 77%|███████▋  | 2022/2624 [01:42<00:29, 20.53it/s]\u001b[A\n 77%|███████▋  | 2025/2624 [01:42<00:29, 20.09it/s]\u001b[A\n 77%|███████▋  | 2028/2624 [01:42<00:30, 19.85it/s]\u001b[A\n 77%|███████▋  | 2031/2624 [01:43<00:29, 20.17it/s]\u001b[A\n 78%|███████▊  | 2034/2624 [01:43<00:28, 20.35it/s]\u001b[A\n 78%|███████▊  | 2037/2624 [01:43<00:28, 20.65it/s]\u001b[A\n 78%|███████▊  | 2040/2624 [01:43<00:28, 20.54it/s]\u001b[A\n 78%|███████▊  | 2043/2624 [01:43<00:28, 20.58it/s]\u001b[A\n 78%|███████▊  | 2046/2624 [01:43<00:26, 21.82it/s]\u001b[A\n 78%|███████▊  | 2049/2624 [01:43<00:27, 20.60it/s]\u001b[A\n 78%|███████▊  | 2052/2624 [01:44<00:27, 20.81it/s]\u001b[A\n 78%|███████▊  | 2055/2624 [01:44<00:28, 19.63it/s]\u001b[A\n 78%|███████▊  | 2058/2624 [01:44<00:27, 20.66it/s]\u001b[A\n 79%|███████▊  | 2061/2624 [01:44<00:27, 20.26it/s]\u001b[A\n 79%|███████▊  | 2064/2624 [01:44<00:27, 20.45it/s]\u001b[A\n 79%|███████▉  | 2067/2624 [01:44<00:29, 18.93it/s]\u001b[A\n 79%|███████▉  | 2070/2624 [01:45<00:27, 20.46it/s]\u001b[A\n 79%|███████▉  | 2073/2624 [01:45<00:26, 20.86it/s]\u001b[A\n 79%|███████▉  | 2076/2624 [01:45<00:27, 20.15it/s]\u001b[A\n 79%|███████▉  | 2079/2624 [01:45<00:27, 20.09it/s]\u001b[A\n 79%|███████▉  | 2082/2624 [01:45<00:28, 18.89it/s]\u001b[A\n 79%|███████▉  | 2085/2624 [01:45<00:26, 20.20it/s]\u001b[A\n 80%|███████▉  | 2088/2624 [01:45<00:25, 20.70it/s]\u001b[A\n 80%|███████▉  | 2091/2624 [01:46<00:25, 21.09it/s]\u001b[A\n 80%|███████▉  | 2094/2624 [01:46<00:24, 21.41it/s]\u001b[A\n 80%|███████▉  | 2097/2624 [01:46<00:25, 20.97it/s]\u001b[A\n 80%|████████  | 2100/2624 [01:46<00:26, 19.80it/s]\u001b[A\n 80%|████████  | 2103/2624 [01:46<00:27, 18.76it/s]\u001b[A\n 80%|████████  | 2105/2624 [01:46<00:28, 17.90it/s]\u001b[A\n 80%|████████  | 2107/2624 [01:46<00:28, 17.98it/s]\u001b[A\n 80%|████████  | 2109/2624 [01:46<00:28, 18.33it/s]\u001b[A\n 80%|████████  | 2112/2624 [01:47<00:25, 19.72it/s]\u001b[A\n 81%|████████  | 2115/2624 [01:47<00:24, 20.66it/s]\u001b[A\n 81%|████████  | 2118/2624 [01:47<00:24, 20.60it/s]\u001b[A\n 81%|████████  | 2121/2624 [01:47<00:25, 19.77it/s]\u001b[A\n 81%|████████  | 2124/2624 [01:47<00:25, 19.47it/s]\u001b[A\n 81%|████████  | 2126/2624 [01:47<00:26, 18.64it/s]\u001b[A\n 81%|████████  | 2129/2624 [01:47<00:25, 19.66it/s]\u001b[A\n 81%|████████  | 2131/2624 [01:48<00:25, 19.25it/s]\u001b[A\n 81%|████████▏ | 2133/2624 [01:48<00:25, 18.96it/s]\u001b[A\n 81%|████████▏ | 2135/2624 [01:48<00:26, 18.67it/s]\u001b[A\n 81%|████████▏ | 2137/2624 [01:48<00:26, 18.62it/s]\u001b[A\n 82%|████████▏ | 2139/2624 [01:48<00:25, 18.76it/s]\u001b[A\n 82%|████████▏ | 2142/2624 [01:48<00:24, 19.88it/s]\u001b[A\n 82%|████████▏ | 2145/2624 [01:48<00:22, 20.96it/s]\u001b[A\n 82%|████████▏ | 2148/2624 [01:48<00:23, 20.16it/s]\u001b[A\n 82%|████████▏ | 2151/2624 [01:49<00:23, 20.00it/s]\u001b[A\n 82%|████████▏ | 2154/2624 [01:49<00:25, 18.55it/s]\u001b[A\n 82%|████████▏ | 2157/2624 [01:49<00:23, 19.75it/s]\u001b[A\n 82%|████████▏ | 2160/2624 [01:49<00:23, 19.91it/s]\u001b[A\n 82%|████████▏ | 2163/2624 [01:49<00:23, 19.74it/s]\u001b[A\n 83%|████████▎ | 2165/2624 [01:49<00:24, 19.05it/s]\u001b[A\n 83%|████████▎ | 2167/2624 [01:49<00:24, 18.53it/s]\u001b[A\n 83%|████████▎ | 2169/2624 [01:50<00:25, 17.80it/s]\u001b[A\n 83%|████████▎ | 2172/2624 [01:50<00:23, 19.23it/s]\u001b[A\n 83%|████████▎ | 2175/2624 [01:50<00:22, 20.14it/s]\u001b[A\n 83%|████████▎ | 2178/2624 [01:50<00:21, 20.33it/s]\u001b[A\n 83%|████████▎ | 2181/2624 [01:50<00:21, 20.62it/s]\u001b[A\n 83%|████████▎ | 2184/2624 [01:50<00:21, 20.84it/s]\u001b[A\n 83%|████████▎ | 2187/2624 [01:50<00:21, 20.50it/s]\u001b[A\n 83%|████████▎ | 2190/2624 [01:51<00:22, 19.69it/s]\u001b[A\n 84%|████████▎ | 2192/2624 [01:51<00:22, 19.13it/s]\u001b[A\n 84%|████████▎ | 2194/2624 [01:51<00:22, 19.38it/s]\u001b[A\n 84%|████████▎ | 2196/2624 [01:51<00:22, 19.43it/s]\u001b[A\n 84%|████████▍ | 2198/2624 [01:51<00:21, 19.53it/s]\u001b[A\n 84%|████████▍ | 2201/2624 [01:51<00:21, 20.04it/s]\u001b[A\n 84%|████████▍ | 2204/2624 [01:51<00:20, 20.47it/s]\u001b[A\n 84%|████████▍ | 2207/2624 [01:51<00:20, 20.74it/s]\u001b[A\n 84%|████████▍ | 2210/2624 [01:52<00:21, 19.61it/s]\u001b[A\n 84%|████████▍ | 2212/2624 [01:52<00:21, 19.10it/s]\u001b[A\n 84%|████████▍ | 2214/2624 [01:52<00:23, 17.82it/s]\u001b[A\n 84%|████████▍ | 2216/2624 [01:52<00:23, 17.43it/s]\u001b[A\n 85%|████████▍ | 2218/2624 [01:52<00:22, 18.05it/s]\u001b[A\n 85%|████████▍ | 2221/2624 [01:52<00:20, 19.67it/s]\u001b[A\n 85%|████████▍ | 2224/2624 [01:52<00:20, 19.32it/s]\u001b[A\n 85%|████████▍ | 2226/2624 [01:52<00:21, 18.43it/s]\u001b[A\n 85%|████████▍ | 2229/2624 [01:53<00:20, 19.22it/s]\u001b[A\n 85%|████████▌ | 2232/2624 [01:53<00:19, 19.80it/s]\u001b[A\n 85%|████████▌ | 2235/2624 [01:53<00:19, 20.16it/s]\u001b[A\n 85%|████████▌ | 2238/2624 [01:53<00:18, 20.63it/s]\u001b[A\n 85%|████████▌ | 2241/2624 [01:53<00:19, 19.82it/s]\u001b[A\n 86%|████████▌ | 2244/2624 [01:53<00:18, 20.63it/s]\u001b[A\n 86%|████████▌ | 2247/2624 [01:53<00:18, 20.20it/s]\u001b[A\n 86%|████████▌ | 2250/2624 [01:54<00:18, 19.97it/s]\u001b[A\n 86%|████████▌ | 2253/2624 [01:54<00:19, 18.74it/s]\u001b[A\n 86%|████████▌ | 2255/2624 [01:54<00:20, 17.95it/s]\u001b[A\n 86%|████████▌ | 2258/2624 [01:54<00:18, 19.35it/s]\u001b[A\n 86%|████████▌ | 2261/2624 [01:54<00:18, 19.51it/s]\u001b[A\n 86%|████████▌ | 2263/2624 [01:54<00:18, 19.35it/s]\u001b[A\n 86%|████████▋ | 2265/2624 [01:54<00:19, 18.84it/s]\u001b[A\n 86%|████████▋ | 2268/2624 [01:55<00:17, 20.17it/s]\u001b[A\n 87%|████████▋ | 2271/2624 [01:55<00:17, 20.41it/s]\u001b[A\n 87%|████████▋ | 2274/2624 [01:55<00:17, 19.72it/s]\u001b[A\n 87%|████████▋ | 2276/2624 [01:55<00:17, 19.62it/s]\u001b[A\n 87%|████████▋ | 2279/2624 [01:55<00:17, 20.06it/s]\u001b[A\n 87%|████████▋ | 2282/2624 [01:55<00:16, 21.33it/s]\u001b[A\n 87%|████████▋ | 2285/2624 [01:55<00:16, 20.83it/s]\u001b[A\n 87%|████████▋ | 2288/2624 [01:56<00:16, 20.34it/s]\u001b[A\n 87%|████████▋ | 2291/2624 [01:56<00:17, 19.56it/s]\u001b[A\n 87%|████████▋ | 2293/2624 [01:56<00:17, 18.97it/s]\u001b[A\n 87%|████████▋ | 2295/2624 [01:56<00:18, 17.70it/s]\u001b[A\n 88%|████████▊ | 2297/2624 [01:56<00:18, 17.98it/s]\u001b[A\n 88%|████████▊ | 2299/2624 [01:56<00:17, 18.31it/s]\u001b[A\n 88%|████████▊ | 2301/2624 [01:56<00:17, 18.53it/s]\u001b[A\n 88%|████████▊ | 2304/2624 [01:56<00:16, 19.95it/s]\u001b[A\n 88%|████████▊ | 2307/2624 [01:57<00:15, 20.31it/s]\u001b[A\n 88%|████████▊ | 2310/2624 [01:57<00:15, 20.24it/s]\u001b[A\n 88%|████████▊ | 2313/2624 [01:57<00:15, 19.48it/s]\u001b[A\n 88%|████████▊ | 2316/2624 [01:57<00:15, 20.09it/s]\u001b[A\n 88%|████████▊ | 2319/2624 [01:57<00:14, 20.49it/s]\u001b[A\n 88%|████████▊ | 2322/2624 [01:57<00:14, 20.56it/s]\u001b[A\n 89%|████████▊ | 2325/2624 [01:57<00:15, 19.73it/s]\u001b[A\n 89%|████████▊ | 2327/2624 [01:58<00:16, 18.04it/s]\u001b[A\n 89%|████████▉ | 2329/2624 [01:58<00:16, 17.95it/s]\u001b[A\n 89%|████████▉ | 2332/2624 [01:58<00:15, 19.38it/s]\u001b[A\n 89%|████████▉ | 2334/2624 [01:58<00:14, 19.33it/s]\u001b[A\n 89%|████████▉ | 2336/2624 [01:58<00:15, 18.62it/s]\u001b[A\n 89%|████████▉ | 2338/2624 [01:58<00:15, 18.33it/s]\u001b[A\n 89%|████████▉ | 2341/2624 [01:58<00:14, 19.18it/s]\u001b[A\n 89%|████████▉ | 2343/2624 [01:58<00:15, 18.62it/s]\u001b[A\n 89%|████████▉ | 2346/2624 [01:59<00:14, 19.48it/s]\u001b[A\n 89%|████████▉ | 2348/2624 [01:59<00:15, 17.56it/s]\u001b[A\n 90%|████████▉ | 2350/2624 [01:59<00:15, 17.66it/s]\u001b[A\n 90%|████████▉ | 2352/2624 [01:59<00:15, 17.64it/s]\u001b[A\n 90%|████████▉ | 2354/2624 [01:59<00:15, 17.71it/s]\u001b[A\n 90%|████████▉ | 2357/2624 [01:59<00:14, 18.93it/s]\u001b[A\n 90%|████████▉ | 2359/2624 [01:59<00:14, 18.83it/s]\u001b[A\n 90%|████████▉ | 2361/2624 [01:59<00:14, 18.39it/s]\u001b[A\n 90%|█████████ | 2364/2624 [01:59<00:12, 20.04it/s]\u001b[A\n 90%|█████████ | 2367/2624 [02:00<00:12, 20.60it/s]\u001b[A\n 90%|█████████ | 2370/2624 [02:00<00:12, 20.26it/s]\u001b[A\n","name":"stderr"},{"output_type":"stream","text":" 90%|█████████ | 2373/2624 [02:00<00:12, 20.47it/s]\u001b[A\n 91%|█████████ | 2376/2624 [02:00<00:12, 19.95it/s]\u001b[A\n 91%|█████████ | 2379/2624 [02:00<00:12, 19.86it/s]\u001b[A\n 91%|█████████ | 2381/2624 [02:00<00:12, 19.85it/s]\u001b[A\n 91%|█████████ | 2383/2624 [02:00<00:12, 18.81it/s]\u001b[A\n 91%|█████████ | 2385/2624 [02:01<00:13, 17.50it/s]\u001b[A\n 91%|█████████ | 2387/2624 [02:01<00:13, 17.77it/s]\u001b[A\n 91%|█████████ | 2390/2624 [02:01<00:12, 19.26it/s]\u001b[A\n 91%|█████████ | 2392/2624 [02:01<00:12, 19.01it/s]\u001b[A\n 91%|█████████▏| 2395/2624 [02:01<00:11, 19.35it/s]\u001b[A\n 91%|█████████▏| 2397/2624 [02:01<00:11, 19.13it/s]\u001b[A\n 91%|█████████▏| 2400/2624 [02:01<00:11, 20.24it/s]\u001b[A\n 92%|█████████▏| 2403/2624 [02:01<00:10, 20.78it/s]\u001b[A\n 92%|█████████▏| 2406/2624 [02:02<00:10, 20.73it/s]\u001b[A\n 92%|█████████▏| 2409/2624 [02:02<00:10, 20.48it/s]\u001b[A\n 92%|█████████▏| 2412/2624 [02:02<00:10, 20.36it/s]\u001b[A\n 92%|█████████▏| 2415/2624 [02:02<00:10, 19.69it/s]\u001b[A\n 92%|█████████▏| 2417/2624 [02:02<00:11, 18.27it/s]\u001b[A\n 92%|█████████▏| 2419/2624 [02:02<00:11, 18.11it/s]\u001b[A\n 92%|█████████▏| 2421/2624 [02:02<00:11, 17.84it/s]\u001b[A\n 92%|█████████▏| 2424/2624 [02:03<00:10, 19.19it/s]\u001b[A\n 92%|█████████▏| 2427/2624 [02:03<00:09, 20.26it/s]\u001b[A\n 93%|█████████▎| 2430/2624 [02:03<00:09, 20.27it/s]\u001b[A\n 93%|█████████▎| 2433/2624 [02:03<00:09, 20.99it/s]\u001b[A\n 93%|█████████▎| 2436/2624 [02:03<00:09, 20.63it/s]\u001b[A\n 93%|█████████▎| 2439/2624 [02:03<00:09, 20.06it/s]\u001b[A\n 93%|█████████▎| 2442/2624 [02:03<00:09, 19.60it/s]\u001b[A\n 93%|█████████▎| 2444/2624 [02:04<00:09, 19.01it/s]\u001b[A\n 93%|█████████▎| 2447/2624 [02:04<00:08, 19.78it/s]\u001b[A\n 93%|█████████▎| 2449/2624 [02:04<00:09, 18.24it/s]\u001b[A\n 93%|█████████▎| 2452/2624 [02:04<00:08, 19.44it/s]\u001b[A\n 94%|█████████▎| 2454/2624 [02:04<00:08, 18.94it/s]\u001b[A\n 94%|█████████▎| 2457/2624 [02:04<00:08, 19.88it/s]\u001b[A\n 94%|█████████▍| 2460/2624 [02:04<00:08, 19.29it/s]\u001b[A\n 94%|█████████▍| 2462/2624 [02:04<00:08, 18.57it/s]\u001b[A\n 94%|█████████▍| 2464/2624 [02:05<00:08, 18.27it/s]\u001b[A\n 94%|█████████▍| 2466/2624 [02:05<00:08, 17.76it/s]\u001b[A\n 94%|█████████▍| 2468/2624 [02:05<00:08, 17.71it/s]\u001b[A\n 94%|█████████▍| 2471/2624 [02:05<00:08, 18.96it/s]\u001b[A\n 94%|█████████▍| 2474/2624 [02:05<00:07, 19.90it/s]\u001b[A\n 94%|█████████▍| 2477/2624 [02:05<00:07, 20.51it/s]\u001b[A\n 95%|█████████▍| 2480/2624 [02:05<00:07, 19.77it/s]\u001b[A\n 95%|█████████▍| 2483/2624 [02:06<00:07, 19.12it/s]\u001b[A\n 95%|█████████▍| 2485/2624 [02:06<00:07, 19.37it/s]\u001b[A\n 95%|█████████▍| 2487/2624 [02:06<00:07, 19.04it/s]\u001b[A\n 95%|█████████▍| 2489/2624 [02:06<00:07, 18.42it/s]\u001b[A\n 95%|█████████▍| 2492/2624 [02:06<00:06, 19.76it/s]\u001b[A\n 95%|█████████▌| 2495/2624 [02:06<00:06, 19.72it/s]\u001b[A\n 95%|█████████▌| 2497/2624 [02:06<00:06, 19.38it/s]\u001b[A\n 95%|█████████▌| 2499/2624 [02:06<00:06, 19.44it/s]\u001b[A\n 95%|█████████▌| 2501/2624 [02:06<00:06, 19.59it/s]\u001b[A\n 95%|█████████▌| 2504/2624 [02:07<00:05, 21.00it/s]\u001b[A\n 96%|█████████▌| 2507/2624 [02:07<00:05, 20.68it/s]\u001b[A\n 96%|█████████▌| 2510/2624 [02:07<00:05, 20.60it/s]\u001b[A\n 96%|█████████▌| 2513/2624 [02:07<00:05, 19.70it/s]\u001b[A\n 96%|█████████▌| 2515/2624 [02:07<00:05, 19.10it/s]\u001b[A\n 96%|█████████▌| 2517/2624 [02:07<00:06, 17.83it/s]\u001b[A\n 96%|█████████▌| 2520/2624 [02:07<00:05, 19.14it/s]\u001b[A\n 96%|█████████▌| 2523/2624 [02:08<00:04, 20.54it/s]\u001b[A\n 96%|█████████▋| 2526/2624 [02:08<00:04, 20.98it/s]\u001b[A\n 96%|█████████▋| 2529/2624 [02:08<00:04, 19.35it/s]\u001b[A\n 96%|█████████▋| 2531/2624 [02:08<00:04, 18.84it/s]\u001b[A\n 97%|█████████▋| 2533/2624 [02:08<00:04, 18.42it/s]\u001b[A\n 97%|█████████▋| 2535/2624 [02:08<00:04, 18.77it/s]\u001b[A\n 97%|█████████▋| 2538/2624 [02:08<00:04, 20.37it/s]\u001b[A\n 97%|█████████▋| 2541/2624 [02:08<00:04, 20.32it/s]\u001b[A\n 97%|█████████▋| 2544/2624 [02:09<00:04, 19.88it/s]\u001b[A\n 97%|█████████▋| 2547/2624 [02:09<00:03, 20.13it/s]\u001b[A\n 97%|█████████▋| 2550/2624 [02:09<00:03, 20.39it/s]\u001b[A\n 97%|█████████▋| 2553/2624 [02:09<00:03, 20.61it/s]\u001b[A\n 97%|█████████▋| 2556/2624 [02:09<00:03, 19.36it/s]\u001b[A\n 97%|█████████▋| 2558/2624 [02:09<00:03, 18.54it/s]\u001b[A\n 98%|█████████▊| 2561/2624 [02:09<00:03, 19.55it/s]\u001b[A\n 98%|█████████▊| 2563/2624 [02:10<00:03, 19.42it/s]\u001b[A\n 98%|█████████▊| 2565/2624 [02:10<00:03, 19.20it/s]\u001b[A\n 98%|█████████▊| 2567/2624 [02:10<00:03, 18.93it/s]\u001b[A\n 98%|█████████▊| 2570/2624 [02:10<00:02, 19.69it/s]\u001b[A\n 98%|█████████▊| 2572/2624 [02:10<00:02, 19.53it/s]\u001b[A\n 98%|█████████▊| 2575/2624 [02:10<00:02, 20.42it/s]\u001b[A\n 98%|█████████▊| 2578/2624 [02:10<00:02, 21.68it/s]\u001b[A\n 98%|█████████▊| 2581/2624 [02:10<00:02, 21.45it/s]\u001b[A\n 98%|█████████▊| 2584/2624 [02:11<00:01, 21.35it/s]\u001b[A\n 99%|█████████▊| 2587/2624 [02:11<00:01, 19.38it/s]\u001b[A\n 99%|█████████▊| 2589/2624 [02:11<00:01, 18.46it/s]\u001b[A\n 99%|█████████▊| 2591/2624 [02:11<00:01, 18.41it/s]\u001b[A\n 99%|█████████▉| 2593/2624 [02:11<00:01, 18.42it/s]\u001b[A\n 99%|█████████▉| 2595/2624 [02:11<00:01, 18.69it/s]\u001b[A\n 99%|█████████▉| 2598/2624 [02:11<00:01, 19.51it/s]\u001b[A\n 99%|█████████▉| 2601/2624 [02:11<00:01, 19.91it/s]\u001b[A\n 99%|█████████▉| 2604/2624 [02:12<00:00, 20.12it/s]\u001b[A\n 99%|█████████▉| 2607/2624 [02:12<00:00, 19.82it/s]\u001b[A\n 99%|█████████▉| 2609/2624 [02:12<00:00, 19.15it/s]\u001b[A\n100%|█████████▉| 2611/2624 [02:12<00:00, 18.51it/s]\u001b[A\n100%|█████████▉| 2614/2624 [02:12<00:00, 19.37it/s]\u001b[A\n100%|█████████▉| 2617/2624 [02:12<00:00, 20.50it/s]\u001b[A\n100%|█████████▉| 2620/2624 [02:12<00:00, 20.59it/s]\u001b[A\n100%|█████████▉| 2623/2624 [02:13<00:00, 20.26it/s]\u001b[A\n100%|██████████| 2624/2624 [02:13<00:00, 19.71it/s]\u001b[A","name":"stderr"}]},{"metadata":{"trusted":true,"_uuid":"8b67071f48cd1368f3cafe73ab5bb6945ddb59d9"},"cell_type":"code","source":"sctestx = pd.DataFrame(sc.transform(xtest), columns = xtest.columns)","execution_count":336,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"2bb84c52fcece3a85569dddddd7e57d14a6d2b97"},"cell_type":"code","source":"pred = model.predict(sctestx)\nprint(pred.shape)","execution_count":337,"outputs":[{"output_type":"stream","text":"(2624,)\n","name":"stdout"}]},{"metadata":{"trusted":true,"_uuid":"e537257a90f842ea9168bdd40b62aed3b2b31f0f"},"cell_type":"code","source":"sub['time_to_failure'] = pred\nsub.head()","execution_count":338,"outputs":[{"output_type":"execute_result","execution_count":338,"data":{"text/plain":"            time_to_failure\nseg_id                     \nseg_00030f         5.524024\nseg_0012b5         3.347173\nseg_00184e         3.778955\nseg_003339         9.521089\nseg_0042cc         6.488661","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>time_to_failure</th>\n    </tr>\n    <tr>\n      <th>seg_id</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>seg_00030f</th>\n      <td>5.524024</td>\n    </tr>\n    <tr>\n      <th>seg_0012b5</th>\n      <td>3.347173</td>\n    </tr>\n    <tr>\n      <th>seg_00184e</th>\n      <td>3.778955</td>\n    </tr>\n    <tr>\n      <th>seg_003339</th>\n      <td>9.521089</td>\n    </tr>\n    <tr>\n      <th>seg_0042cc</th>\n      <td>6.488661</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true,"_uuid":"97bbfe02fdf7ed383e709ecf0f35eecdd6e763d9"},"cell_type":"code","source":"sub.to_csv(\"submittedoutput.csv\")","execution_count":339,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}