From 2a8e5801691c4d24dfb4c021c9a76dc841f53847 Mon Sep 17 00:00:00 2001 From: KW <54145971+Zero-coder@users.noreply.github.com> Date: Sun, 27 Nov 2022 11:40:45 -0500 Subject: [PATCH] fix predict.ipynb fix predict.ipynb for better convenience of predicting operation. --- predict.ipynb | 212 +++++++++++++++++++++++++++++++++++++------------- 1 file changed, 158 insertions(+), 54 deletions(-) diff --git a/predict.ipynb b/predict.ipynb index c6d8f82..981d491 100644 --- a/predict.ipynb +++ b/predict.ipynb @@ -4,24 +4,42 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Use GPU: cuda:0\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "#import os\n", + "import os\n", "\n", - "#args.output_attention = True\n", + "# args.output_attention = True\n", "\n", - "#exp = Exp(args)\n", + "exp = Exp(args)\n", "\n", - "#model = exp.model\n", + "model = exp.model\n", "\n", - "#setting = 'informer_ETTh1_ftM_sl96_ll48_pl24_dm512_nh8_el2_dl1_df2048_atprob_fc5_ebtimeF_dtTrue_mxTrue_exp_0'\n", - "#path = os.path.join(args.checkpoints,setting,'checkpoint.pth')\n", - "#model.load_state_dict(torch.load(path))" + "setting = 'ETTh1_96_24_Autoformer_ETTh1_ftM_sl96_ll48_pl24_dm512_nh8_el2_dl1_df2048_fc1_ebtimeF_dtTrue_Exp_0'\n", + "path = os.path.join(args.checkpoints,setting,'checkpoint.pth')\n", + "model.load_state_dict(torch.load(path))" ] }, { "cell_type": "code", - "execution_count": 41, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -45,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -56,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -210,7 +228,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -223,36 +241,36 @@ "train 8521\n", "val 2857\n", "test 2857\n", - "\titers: 100, epoch: 1 | loss: 0.3611072\n", - "\tspeed: 0.0614s/iter; left time: 157.2485s\n", - "\titers: 200, epoch: 1 | loss: 0.3248774\n", - "\tspeed: 0.0348s/iter; left time: 85.7256s\n", - "Epoch: 1 cost time: 12.040599346160889\n", - "Epoch: 1, Steps: 266 | Train Loss: 0.3626875 Vali Loss: 0.6365376 Test Loss: 0.4080311\n", - "Validation loss decreased (inf --> 0.636538). Saving model ...\n", + "\titers: 100, epoch: 1 | loss: 0.3452503\n", + "\tspeed: 0.0606s/iter; left time: 155.1843s\n", + "\titers: 200, epoch: 1 | loss: 0.3061770\n", + "\tspeed: 0.0336s/iter; left time: 82.5755s\n", + "Epoch: 1 cost time: 11.749736309051514\n", + "Epoch: 1, Steps: 266 | Train Loss: 0.3544893 Vali Loss: 0.5863745 Test Loss: 0.3798478\n", + "Validation loss decreased (inf --> 0.586374). Saving model ...\n", "Updating learning rate to 0.0001\n", - "\titers: 100, epoch: 2 | loss: 0.3774808\n", - "\tspeed: 0.1135s/iter; left time: 260.4290s\n", - "\titers: 200, epoch: 2 | loss: 0.3226640\n", - "\tspeed: 0.0346s/iter; left time: 76.0447s\n", - "Epoch: 2 cost time: 9.73805284500122\n", - "Epoch: 2, Steps: 266 | Train Loss: 0.3071145 Vali Loss: 0.6506287 Test Loss: 0.3897783\n", + "\titers: 100, epoch: 2 | loss: 0.2983823\n", + "\tspeed: 0.1027s/iter; left time: 235.7041s\n", + "\titers: 200, epoch: 2 | loss: 0.2859739\n", + "\tspeed: 0.0332s/iter; left time: 72.7752s\n", + "Epoch: 2 cost time: 9.083820819854736\n", + "Epoch: 2, Steps: 266 | Train Loss: 0.2927621 Vali Loss: 0.6249782 Test Loss: 0.4045280\n", "EarlyStopping counter: 1 out of 3\n", "Updating learning rate to 5e-05\n", - "\titers: 100, epoch: 3 | loss: 0.2361423\n", - "\tspeed: 0.1102s/iter; left time: 223.6741s\n", - "\titers: 200, epoch: 3 | loss: 0.2395305\n", - "\tspeed: 0.0349s/iter; left time: 67.4057s\n", - "Epoch: 3 cost time: 9.779260158538818\n", - "Epoch: 3, Steps: 266 | Train Loss: 0.2759721 Vali Loss: 0.6875055 Test Loss: 0.4026451\n", + "\titers: 100, epoch: 3 | loss: 0.2311743\n", + "\tspeed: 0.0964s/iter; left time: 195.4976s\n", + "\titers: 200, epoch: 3 | loss: 0.2433617\n", + "\tspeed: 0.0331s/iter; left time: 63.8016s\n", + "Epoch: 3 cost time: 9.000295639038086\n", + "Epoch: 3, Steps: 266 | Train Loss: 0.2644387 Vali Loss: 0.6007050 Test Loss: 0.4031203\n", "EarlyStopping counter: 2 out of 3\n", "Updating learning rate to 2.5e-05\n", - "\titers: 100, epoch: 4 | loss: 0.2673016\n", - "\tspeed: 0.1101s/iter; left time: 194.0347s\n", - "\titers: 200, epoch: 4 | loss: 0.2477031\n", - "\tspeed: 0.0351s/iter; left time: 58.3769s\n", - "Epoch: 4 cost time: 9.837982892990112\n", - "Epoch: 4, Steps: 266 | Train Loss: 0.2587591 Vali Loss: 0.6486462 Test Loss: 0.4047659\n", + "\titers: 100, epoch: 4 | loss: 0.2254572\n", + "\tspeed: 0.0979s/iter; left time: 172.6233s\n", + "\titers: 200, epoch: 4 | loss: 0.2654203\n", + "\tspeed: 0.0330s/iter; left time: 54.8957s\n", + "Epoch: 4 cost time: 9.05700421333313\n", + "Epoch: 4, Steps: 266 | Train Loss: 0.2476054 Vali Loss: 0.5942122 Test Loss: 0.4114987\n", "EarlyStopping counter: 3 out of 3\n", "Early stopping\n", "2\n", @@ -260,7 +278,7 @@ "test 2857\n", "test shape: (89, 32, 24, 7) (89, 32, 24, 7)\n", "test shape: (2848, 24, 7) (2848, 24, 7)\n", - "mse:0.408031165599823, mae:0.4408583343029022\n", + "mse:0.3798477351665497, mae:0.4185081720352173\n", "3\n" ] } @@ -302,7 +320,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -319,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -337,24 +355,83 @@ "if args.do_predict:\n", " print('>>>>>>>predicting : {}<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<'.format(setting))\n", " prediction=exp.predict(setting, True)#data_factory做好了pred里面的batch_size=1的情况,是autoformer在informer基础之上做的\n", - " torch.cuda.empty_cache()" + " torch.cuda.empty_cache()\n", + " # print(prediction.shape)" ] }, { "cell_type": "code", - "execution_count": 65, + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(1, 24, 7)\n" + "torch.Size([1, 7, 24])\n", + "torch.Size([24])\n" + ] + }, + { + "data": { + "image/png": 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HkRAdZjuS8iEistQYk97UNr3134FWb9vLA7NWM7hLDF/cosMRvVVavJ6pK/ekhe4g+6tq+cv7vxAdHsTzl/QlUhci9mqNS33cq1rqyj1ooTvIo3PWsrGwjGcu7kur8CDbcZQLHCj1kv1a6so9aKE7wLeZ+byzeAsThyYzuEuM7TjKhbTUlTvRQj9BBaUV3PHRSlLbR3LbWV1tx1EWpMVH8c7VJ2upK+u00E+AMYbbP1zJvsoanh/bl+AAnfrWV/WOb/mrUs/braWumlZR7bwVsbTQT8BbizbzfVYh957Tg5S2Os7c1zUu9bFTtdTVbxljGPDINzzx5TqnvL4W+nHKyi/l0TmZnNG9DZcN6mQ7jnITWurqSIr2VVFaWUPbiGCnvL4W+nGorKnl5vd+ITIkgCcu6E39Gh9K1dNSV4eTW1QGQFJsC6e8vhb6cXjyy/Ws21nKkxf2IdZJ/6ZVnu3QUt9TXmU7knIDuUX1s3Umx4Q75fW10I/Rwg2FvPZDLpef0olh3dvYjqPcWO/4lkwbP5C83ft544dc23GUG8gpKiPI348OLZ0z46oW+jHYVVbFbTNX0KVNC+4Z2cN2HOUB+ndsxfCe7Zj24yZKK6ptx1GW5RaW0al1GP5OmnVVC72ZjDHc/clK9pRX8/zYvoQE6hBF1Tw3DOtCSUUNby/ebDuKsiynqIwkJ11uAS30ZvtgyVbmrsnn9rO70bNDlO04yoOkxUdxWtdYXl+Yy/4q541BVu6tts6wubiMpFgtdKtyCvcx+fO1DO7SmglDkmzHUR7oxjO6UFxWxftLttiOoizZtns/1bXGaV+Ighb6UVXX1nHLB8sJDvTj6Yv66opD6rgMSIxmYGI0UxfkUFVTZzuOsiCnYYRLUoxzhiyCFvpRPfdNFivz9vL4+Wm0iwqxHUd5sBvO6MKOvRV8sizPdhRlwcEx6LbP0EVkuIisF5FsEbmrie2dRORbEVkpIt+JSLzjo7reTznFvPTdRi5JT2BEWnvbcZSHG5oSQ1pcFC9/v5GaWj1L9zW5RWVEBAcQ08J502s3Z01Rf2AKMAJIBcaJSOohuz0FvGWM6Q08BDzu6KCuVlpRza0zV9ApOoz7zzv0f65Sx05EuGFYFzYXlzN7lc+vo+5zcovqvxB15p3lzTlDHwhkG2NyjDFVwPvA6EP2SQXmNfw8v4ntHmfy52vZsXc/z1zSl/DgANtxlJc4K7UtXdu2YMr8bOrq7Kznq+zIKXTukEVoXqHHAVsbPc5reK6xFcCYhp/PByJE5DcLaorIRBHJEJGMwsLC48nrEnPX7OSjpXncMKwL/Tu2sh1HeRE/P+H607uQlb+PrzPzbcdRLlJRXcv2vfvdotCb42/AaSLyC3AasA34zYBbY8xUY0y6MSY9NjbWQYd2rKJ9ldzzySp6dojkpjNSbMdRXujc3u3pGB3GlPnZGKNn6b5gc3E5xjj3C1FoXqFvAxIaPY5veO4gY8x2Y8wYY0w/4O8Nz+1xVEhXqb8bdBWllTU8e0lfggJ0EJByvAB/Pyad3pmVeXtZuKHIdhzlAgcm5erspFkWD2hOYy0BUkQkSUSCgLHArMY7iEiMiBx4rbuBNxwb0zU+XraNr9fmc/tZ3eiqC1YoJxrTP452kSG8OD/bdhTlAjkNQxYTbZ+hG2NqgBuBuUAmMNMYs0ZEHhKRUQ27nQ6sF5EsoC3wqJPyOk3e7nImz1rDwKRoxuvdoMrJggP8mTg0mZ9zd7Fk0y7bcZST5RaW0SYimBZOHmDRrGsKxpg5xpiuxpjOxphHG5673xgzq+Hnj4wxKQ37XG2MqXRmaEerq6tfG7TOGJ6+qI/TZkJTqrFxAzvSOjyIKXqW7vVynTwp1wF6kRiY9uMmFuUUc/95qSREh9mOo3xEaJA/44ck8d36QlZv22s7jnKi3KIykp04KdcBPl/o2QWlPPHlOn7fvQ0Xpycc/ReUcqA/n9KJiJAAPUv3YnvLqykuq9IzdGerrq3j1pkrCAvy5/EL0nRtUOVykSGBXHFKIl+u2Ul2QantOMoJcosPzOHi3BEu4OOFPmV+Nivz9vLY+Wm0idCJt5Qd44ckERLgz0vzN9qOopwg9+Asi3qG7jQrtu7hhXnZnN8vTifeUlZFhwfxp5M78tmK7WwpLrcdRzlYbmEZfgIdXfD9nE8WekV1LX+duZw2EcE8OKqn7ThKMXFoMv4i/GuBnqV7m5yiMhKiw1xyo6JPFvoTX64jp7CMJy/sQ1RooO04StE2MoQL0+P5KCOPnXsrbMdRDuSqIYvgg4X+Y3YRb/53E1eemsiQlBjbcZQ6aNJpnak1hlcX5tiOohzEGKOF7iwlFdX87cMVJMeEc+fw7rbjKPUrCdFhjO7TgRk/bWFXWZXtOMoB8ksqKa+qdeo6oo35VKFPnrWW/NJKnrmkL6FB/rbjKPUb1w/rTEVNLW/8kGs7inIAV6wj2pjPFPqXq3fy8bI8bji9M30TWtqOo1STurSJYHjPdkxftImSimrbcdQJOriOqAvuEgUfKfSs/FLu+fcqesVFcqPOca7c3A3DulBaUcOrC/RauqfLLSwjOMCP9pGuuc/F6ws9Y9MuLvrXIvz9hOfH9tM5zpXb6xUXxag+HXhlQY6OS/dwB74Q9XPRhH9e3W5fr83n0td+Ijo8iE8mner0yeWVcpR7RvYgwE94ePZa21HUCXDlCBfw4kL/YMkWrn07g+7tIvjoulN0FkXlUdpFhXDTGSl8vTaf+esLbMdRx6G6to4tu8q10E+EMYYX523gzo9XMSQllhnXDKJ1i2DbsZQ6ZuOHJJIcE85Dn6+lsuY3S/QqN5e3ez81dUYL/XjV1hkemLWGp77K4vx+cbx+RTrhTl4hRClnCQ7w54FRPcktKuONHzbZjqOO0YFJuZJdeKm3WYUuIsNFZL2IZIvIXU1s7ygi80XkFxFZKSIjHR/1yCprarnpvWW8tWgzE4cm8/RFfQj096p/XykfdFrXWP6Q2pYX5m1gx979tuOoY5BTWD9k0VU3FUEzCl1E/IEpwAggFRgnIqmH7HYv9WuN9qN+EemXHB30SEoqqrnijZ+Zs2on957Tg3tG9nDZt8pKOdv956ZSU2d4bM4621HUMcgtKqNlWCCtwoNcdszmnMIOBLKNMTnGmCrgfWD0IfsYILLh5yhgu+MiHllBSQWXvLKYjE27ee6Svlz9u2RXHVopl0iIDmPSaZ35fMV2FucU246jmsnVI1ygeYUeB2xt9Div4bnGHgQuE5E8YA5wU1MvJCITRSRDRDIKCwuPI+6v5RaVMeblH9lcXMYbVw7gj/0OjaWUd5h0emfiWobywGdrqKmtsx1HNYO7FnpzjAOmGWPigZHA2yLym9c2xkw1xqQbY9JjY2NP6IArtu7hgpd/pLyqlveuGcTQrif2ekq5s5BAf+47N5X1+aW8vXiz7TjqKMqratixt8Kl18+heYW+DWi8enJ8w3ONTQBmAhhjFgEhgNPmpv0+q5Bxry4mPNifjyedSh+dm0X5gLN7tuV3KTE883UWRfsqbcdRR7CpqP4OX1dNynVAcwp9CZAiIkkiEkT9l56zDtlnC/B7ABHpQX2hn/g1lSZ8tWYnE6YtoVPrcD6edKrL/5NGKVtEhAfO68n+qlr+8aV+QerODk7K5W5n6MaYGuBGYC6QSf1oljUi8pCIjGrY7TbgGhFZAbwHXGmMMc4I3CsuinN7t+eDawfpws7K53Rp04IJQ5KYmZHHL1t2246jDuPAGPTEGNfeoS5O6t2jSk9PNxkZGVaOrZQn21dZwxlPfUe7qBA+vX6wDtF1Q7fOXM6ijcUsuvv3Dn9tEVlqjElvapveeaOUh2kRHMA9I3uwMm8vMzO2Hv0XlMvZGOECWuhKeaTRfTswILEV/5i7nr3luhCGu9FCV0o1m4gweVQv9pRX8czX623HUY3sKqtiT3m1FrpSqvlSO0Ry2aBOvL14M2u3l9iOoxr8b1IuLXSl1DG49Q9diQoN5MFZa7A1wEH92oFJuVw9Bh200JXyaC3DgrhjeHd+3rSLWStcNoWSOoLcojIC/IT4VqEuP7YWulIe7uL0BHrHR/Ho7Ez2VdbYjuPzcovK6BgdZmX6bi10pTycv58weVRPCkoreWqufkFqm60RLqCFrpRX6NexFVeemsi0Hzfp2HSL6uqMFrpS6sT9/ZweDOkSw9//vYqfdN50K3aUVFBZU0eShREuoIWulNcI9Pdjyp/6k9AqjOveWcqW4nLbkXxO7sFl51w/wgW00JXyKlFhgbx+5QDqDEyYvoSSCr2L1JVsjkEHLXSlvE5STDgvX9af3KIybprxi65w5EI5RWWEBfnTJiLYyvG10JXyQqd2juGh0b34PquQR+dk2o7jMw58ISpiZwbMACtHVUo53Z9O7kh2wT7e+G8uXdq04NKTO9mO5PVyi8pIi4uydnw9Q1fKi/39nB6c3i2WBz5bw4/ZRbbjeLWqmjq27ip3+TqijWmhK+XF/P2EF8b1IykmnEnvLiOncJ/tSF5ry65y6gzWhixCMwtdRIaLyHoRyRaRu5rY/qyILG/4kyUiexyeVCl1XCJCAnn9igH4+wlXT8/Q+dOd5H/riNoZsgjNKHQR8QemACOAVGCciKQ23scY81djTF9jTF/gBeATJ2RVSh2njq3D+NdlJ7F1dznXz1hKtY58cbgDQxaTWrv3GfpAINsYk2OMqQLeB0YfYf9x1C8UrZRyIwOTonns/DT+m13M5M91ul1Hyy0qo3V4EFFhgdYyNKfQ44DGk0PkNTz3GyLSCUgC5h1m+0QRyRCRjMLCwmPNqpQ6QRelJ3Dtacm8s3gLby3abDuOV8kptDeHywGO/lJ0LPCRMaa2qY3GmKnGmHRjTHpsbKyDD62Uao47zu7OmT3aMvnzNSzI0hMrR7E5KdcBzSn0bUBCo8fxDc81ZSx6uUUpt+bvJzw/ti/d2kVyw4xlZBeU2o7k8fZV1lBQWml1hAs0r9CXACkikiQiQdSX9qxDdxKR7kArYJFjIyqlHC08OIDXrkgnOMCf8dMyKCyttB3Jo20qOjApl5sXujGmBrgRmAtkAjONMWtE5CERGdVo17HA+0a/aVHKI8S1DOW1K9IpLK1k/LQlutrRCdjYML7f5pBFaOY1dGPMHGNMV2NMZ2PMow3P3W+MmdVonweNMb8Zo66Ucl99E1ry0qX9WbujhEnvLKWqRoczHo/cojJEoFPrMKs59E5RpXzcsO5teHxMGgs3FHHnxyupq9P/yD5WuUVldIgKJSTQ32oOnZxLKcXF6QkUlFTw1FdZtIkM5u4RPWxH8ii5RWXW5kBvTM/QlVIA3DCsC38e1IlXvs/h9R9ybcfxGMYYct1gDDroGbpSqoGI8OConhSWVvLwf9bSJiKY8/p0sB3L7RXtq6K0ssYtCl3P0JVSB/n7Cc+N7cvAxGhum7lCp9xthgOTciXH2h3hAlroSqlDhAT68+rl6STGhDHx7aWs3V5iO5JbO7iOqJ6hK6XcUVRYINPHDyQiJIAr3/yZrbvKbUdyWzlFZQT5+9GhZajtKFroSqmmtY8KZfr4gVRU13LFmz+zq6zKdiS3lFtYRqfWYfj72VlHtDEtdKXUYXVtG8HrVw4gb/d+Jkxfwv6qJufd82nuMCnXAVroSqkjGpAYzT/H9mPF1j3cOGMZNbo4xkG1dYbNxeXWJ+U6QAtdKXVUw3u1Y/LoXny7roC//3u1Lo7RYPue/VTV1rnFF6Kg49CVUs3050GdKCip4IV52bSNDObWs7rZjmRdjhusI9qYFrpSqtlu/UNX8ksq+Oe8bAZ3ieHk5Na2I1mVe3CWRfc4Q9dLLkqpZhMRJo/qRdvIYP4xd73PX3rJLSojIjiAmBZBtqMAWuhKqWMUGuTPX37flaWbd/NNZoHtOFblFJWRFBuOiP0hi6CFrpQ6Dhenx5McE86Tc9dR68PT7brTkEXQQldKHYcAfz9uO6sbWfn7+Pcvh1ti2LtVVNeybc9+zyt0ERkuIutFJFtEmlyVSEQuFpG1IrJGRGY4NqZSyt2MTGtHWlwUz36dRUW1791wtHTzboxxny9EoRmFLiL+wBRgBJAKjBOR1EP2SQHuBgYbY3oCtzg+qlLKnYgIdw7vzrY9+3n3py2247jU9j37+cv7y+kYHcbp3drYjnNQc87QBwLZxpgcY0wV8D4w+pB9rgGmGGN2AxhjfPubEqV8xJCUGIZ0iWHK/GxKK6ptx3GJ8qoarnkrg4rqWl6/Ip2o0EDbkQ5qTqHHAVsbPc5reK6xrkBXEfmviCwWkeFNvZCITBSRDBHJKCwsPL7ESim3csfwbuwqq+LVhd6/ypExhts/XMnaHSW8MK4fKW0jbEf6FUd9KRoApACnA+OAV0Wk5aE7GWOmGmPSjTHpsbGxDjq0Usqm3vEtOSetPa8tzKGwtNJ2HKf657fZzF61g7tHdGdYd/e51HJAcwp9G5DQ6HF8w3ON5QGzjDHVxphcIIv6gldK+YDbzupKZU0dU+Zn247iNF+s2sGz32Qxpn8c1/wu2XacJjWn0JcAKSKSJCJBwFhg1iH7fEr92TkiEkP9JZgcx8VUSrmz5NgWXJyewLs/bWZLsfcthrF6215unbmC/h1b8tj5aW5zI9Ghjlroxpga4EZgLpAJzDTGrBGRh0RkVMNuc4FiEVkLzAduN8YUOyu0Usr93HJmCn4iPPtNlu0oDlVQWsHEtzJoFRbIv/58EiGB/rYjHVazJucyxswB5hzy3P2NfjbArQ1/lFI+qG1kCFcNTuKVBRuZODSZHu0jbUc6YZU1tVz39lJ2l1fz4XWn0CYixHakI9I7RZVSDjPptM5EBAfw5Nz1tqOcMGMMd3+yimVb9vD0xX3oFRdlO9JRaaErpRwmKiyQSad3Yd66An7O3WU7zgl5dWEOnyzbxi1npjAyrb3tOM2iha6UcqgrT02kbWQwT3y5zmOn1523Lp/Hv1jHOWntufkMzxmwp4WulHIoT59ed0N+KTe/t5yeHSJ56qI++Pm554iWpmihK6UczlOn191dVsWE6RmEBPoz9c/phAa574iWpmihK6UczhOn162ureP6d5exs6SCqZefRIeWobYjHTMtdKWUU3ja9LqTP1/Dopxi/m9MGv07trId57hooSulnMKTptf9MGMr7yzewrWnJTOmf7ztOMdNC10p5TSeML1u0b5KHpmdycDEaO44u7vtOCdEC10p5VTuPr3uI/9ZS3lVDY+N6YW/B41oaYoWulLKqRpPr1tQWmE7zq8s3FDIp8u3M+m0znRp415zmx8PLXSllNPddlZXauoME99aSlllje04QP0iz/d+upqkmHCuH9bFdhyH0EJXSjldcmwLXhzXj1Xb9nLt20uprLE/6uWFeRvYXFzOo3/s5dYzKB4LLXSllEuc1bMdT1zQmx+yi7jl/eVWbzjKyi/lle9zGNM/jlO7xFjL4Wha6Eopl7nwpHjuOzeVL1bv5J5PVlmZ66Wurn4WxYiQAO49J9Xlx3emZs2HrpRSjjJhSBJ7yqt4YV42LcMCuXtkD5ce//0lW1m6eTdPXtib6PAglx7b2bTQlVIud+sfurKnvJpXFuTQMiyISad3dslxC0or+L8vMhmUHM2FJ3nuDUSH06xLLiIyXETWi0i2iNzVxPYrRaRQRJY3/Lna8VGVUt5CRJg8qiej+3bgiS/XMcNFd5I+/J9MKqrreNSN1wU9EUc9QxcRf2AK8AcgD1giIrOMMWsP2fUDY8yNTsiolPJCfn7CUxf1oWR/NX//dBWRoQGc27uD04733foCPl+xnVvOTKFzbAunHcem5pyhDwSyjTE5xpgq4H1gtHNjKaV8QaC/Hy9dehLpnVrx1w+W831WoVOOs7+qlvs+W01ybLjLLu/Y0JxCjwO2Nnqc1/DcoS4QkZUi8pGIJDT1QiIyUUQyRCSjsNA5/8cppTxLaJA/r10xgJQ2EVz39lKWbnb80nXPf7uBrbv289j5aQQHeMeY86Y4atji50CiMaY38DUwvamdjDFTjTHpxpj02NhYBx1aKeXpokIDmT5+IG0jg7nqzSVk7ihx2Guv21nCawtzuDg9nkHJrR32uu6oOYW+DWh8xh3f8NxBxphiY0xlw8PXgJMcE08p5StiI4J5e8LJhAUFcPkbP7O5uOyEX/PAmPPI0EDuHuHa4ZE2NKfQlwApIpIkIkHAWGBW4x1EpPGS2KOATMdFVEr5ioToMN6eMJDq2joue/0n8ktObDKvd3/ewi9b9nDvOT1o5WVjzpty1EI3xtQANwJzqS/qmcaYNSLykIiMatjtZhFZIyIrgJuBK50VWCnl3VLaRjDtqoHs2lfFn1//6bhnaMwvqeAfX6xjcJfWnN+vqa/9vI/YuPUWID093WRkZFg5tlLK/f2YXcSVby6huq6O1PaRnJLcmlM6t2ZgUjQRIYFH/f0b3l3G15n5zL1lKEkx4S5I7BoistQYk97UNr1TVCnllk7tEsOsmwYzd3U+i3KKeGvxZl77IRc/gbS4KE7pHMMpnVuT3qkV4cG/rrJ56/KZvWoHfzurq1eV+dHoGbpSyiNUVNeybPNuFuUUs2hjMcu37qGmzhDgJ/RJaHnwDL5H+0jOe+EHQoP8mXPz7wgK8K45CI90hq6FrpTySOVVNWRs+l/Br9q291dT8n543SkMSIy2mNA59JKLUsrrhAUFMLRrLEO71t/TUlpRfbDgO0SFeGWZH40WulLKK0SEBDKsexuGdW9jO4o13nVxSSmlfJgWulJKeQktdKWU8hJa6Eop5SW00JVSyktooSullJfQQldKKS+hha6UUl7C2q3/IlIIbD7OX48BihwYx5Ppe1FP34d6+j7U8+b3oZMxpskl36wV+okQkYzDzWXga/S9qKfvQz19H+r56vugl1yUUspLaKErpZSX8NRCn2o7gBvR96Kevg/19H2o55Pvg0deQ1dKKfVbnnqGrpRS6hBa6Eop5SU8rtBFZLiIrBeRbBG5y3YeW0Rkk4isEpHlIuJTa/mJyBsiUiAiqxs9Fy0iX4vIhoa/W9nM6AqHeR8eFJFtDZ+L5SIy0mZGVxCRBBGZLyJrRWSNiPyl4Xmf+0x4VKGLiD8wBRgBpALjRCTVbiqrhhlj+vrgeNtpwPBDnrsL+NYYkwJ82/DY203jt+8DwLMNn4u+xpg5Ls5kQw1wmzEmFRgE3NDQCz73mfCoQgcGAtnGmBxjTBXwPjDaciblYsaYBcCuQ54eDUxv+Hk68EdXZrLhMO+DzzHG7DDGLGv4uRTIBOLwwc+EpxV6HLC10eO8hud8kQG+EpGlIjLRdhg30NYYs6Ph551AW5thLLtRRFY2XJLx+ssMjYlIItAP+Akf/Ex4WqGr/xlijOlP/eWnG0RkqO1A7sLUj8X11fG4LwOdgb7ADuBpq2lcSERaAB8DtxhjShpv85XPhKcV+jYgodHj+IbnfI4xZlvD3wXAv6m/HOXL8kWkPUDD3wWW81hhjMk3xtQaY+qAV/GRz4WIBFJf5u8aYz5peNrnPhOeVuhLgBQRSRKRIGAsMMtyJpcTkXARiTjwM3AWsPrIv+X1ZgFXNPx8BfCZxSzWHCiwBufjA58LERHgdSDTGPNMo00+95nwuDtFG4ZhPQf4A28YYx61m8j1RCSZ+rNygABghi+9DyLyHnA69VOk5gMPAJ8CM4GO1E/LfLExxqu/MDzM+3A69ZdbDLAJuLbRdWSvJCJDgIXAKqCu4el7qL+O7lufCU8rdKWUUk3ztEsuSimlDkMLXSmlvIQWulJKeQktdKWU8hJa6Eop5SW00JVSyktooSullJf4f7ughHMbktXvAAAAAElFTkSuQmCC", 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", 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", 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", 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", 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" ] @@ -368,12 +445,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "(1, 24, 7)\n" + "torch.Size([24])\n" ] }, { "data": { - "image/png": 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", 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/V5t5b8/xHpWdOFnfzPv7SrgpI4kB4SFuxRI7IIx5Y4d0q+TEq9sLyKtq4JFrxhPcjeR5a2YKocHCK9t00PhM7iaCBGNMibVdCrgqMzgGqBaR1SKyS0SeEJGO13CPicheEXlSRM4e6bGIyDIRyRKRrIoKvTlE9S3tU0eHx/Xe1NF2wUHCfy6cyDvfvZCEyH7806u7uOu57Ryt6N5fzn/+opDmVgdLOik33VM3T0uivLaJz3IrO21T29jCbzceZs6IwcwbG9+t88YPCueqC4by5heFulbyGbpMBCKyQUSyXTwWdmxnnH9CuErhIcDFwI+AGcAI4NvWa48A46z9scBDncVhjFlhjMk0xmTGx3fvf7xS/qJ96qgdVwTtpqRE8873LuQ/F17AnsJqrn7qb/x63Zc0tnT+S9PhMKzaVkBmWgzjhkZ6JI7Lxw0hsl/IObuHVnxylKp6ZymJnoxJ3Dk7jVONrby3VxfD6ajLRGCMWWCMmejisQYoE5FEAOtnuYtTFAG7jTFHjTGtwDvANOvcJcapCXge5/iBUgGnfeqot9ch6EpwkHD3nHQ2/uhSrp00lN/+NZcrntzMpoOu/mnDp7mV5Fc1dLuuUHf0Cw3musnD+DC7lPqmswewy6xSEjdOGcbk5OgenXvW8FhGDxnIKh00/gZ3u4beBZZa20uBNS7a7ACiRaT9z/jLgQPwVfJAnCl9EZDtZjxK+aX2qaPeXoegu4YM6sdTt2Xwyj/MIiw4iHte2MF9L2Vx/Iy7c1/emk/sgDCumTTUo+9/87QkTre08WF26VmvPbn+EG0O841SEt0lIiyZlcqeohr2FdV4ItQ+wd1EsBy4QkQOAwus54hIpog8C2CMacPZLbRRRPYBAjxjHb/K2rcPiAMedTMepfxS+9TRYVERdofyDXNHxrH2+5fw4FVj2XyoggW/3swfNx+hpc1BSc1pNh4s51uZyYSHdD5183xkpsWQEhtxVvfQobJa3sgq5O456aTEnl/SvHl6MhGhwTqVtAO3hviNMVXAfBf7s4B7OzxfD0x20e5yd95fqb4ir7KeVBumjnZHWEgQ37tsFDdOGcbP3t3PL9Ye5K2dRYwdGonDGJbM9Fy3UDsR4aaMZH7318OU1Jwm0UqQj689yIDwEP7xsrNLSXRXZL9QbpwyjDV7ivnJdeOJigj1VNh+S+8sVsoH5FXV92ppifOREtuf5749gxV3Tae+qY339hznktHxpHqpO+umjCRMh5ITW45UsfFgOd+7bFSPaxmd6c7ZaTS2OFh9nkXu+hpNBErZzI6qo+648oKhrP/BJfz79RP49xsmeO19hscNICM1mtU7i3A4DL9Ym8OwqH58e2662+eelBzFlOQoVm0r8MpSnf5GE4FSNrOj6qi7+oeF8PcXDWdk/ECvvs/N05I5VFbHLz/6kr1FNfzwyrH0C/XMeMSS2Wnkltex9ahnF+bxR5oIlLJZXlXvVx31F9dPSiQ0WPjD5iOMT4xkUYZ7JSw6umHyMCL7hfDyNh001kSglM3yKturjvpH11BvihkQxmVjhwDwyDXjulVKorsiwoJZPD2Fj7JLKa/t+RoIfYkmAqVsll9VT1hw0FczY9Q3/fjqsfzXwgu4ZIznKwosmZ1Kq8Pwxo5Cj5/bn2giUMpmxyrrSR3c36N/7fYlo4YM4q456V4598j4gcwdOZhXtxd2WeSuL9NEoJTN/GnGUF905+w0iqtPd1pGIxBoIlDKRg6H8Yt7CPqyKyYkMGRQOKsCeNBYE4FSNiqrtaqO+tHU0b4mNDiI22ak8PGhCgpPBOZSKZoIlLLRsfaqo3pFYKvbZqYiwCvbA3PRGk0EStkov0qnjvqCYdERzB+fwBs7CmlqDbxFa9xbV04p5Za8Sp066ivunJ3G+gNlLPj15h5XU108PZn7Lx3ppci8TxOBUjbKq9Kpo77i4lFx3HvRcEpqenZz2ZGKOp5cf4jF05OJG9jpars+TROBUjbKq9Spo74iKEj46fU9L6KXW17HFU9uZuXnefzwyp4vluMLdIxAKZs4HIb8Ezp11N+NGjKQqyYMZeXnedS5WFrTH2giUMomZbWNNLbo1NG+4P55IznV2Mqr2/xz1pFbiUBEYkVkvYgctn7GuGhzmYjs7vBoFJFF1mvDRWSbiOSKyOsi4t5qE0r5kfZiczp11P9NTYlm7sjBPPvpUb+cdeTuFcHDwEZjzGhgo/X8G4wxm4wxU40xU3EuXN8ArLNefhx40hgzCjgJfMfNeJTyG+3lp31lwXrlngfmjaTsVBPvnLHOsj9wNxEsBFZa2yuBRV20XwysNcY0iIjgTAxv9uB4pfqMPKvq6LBonTraF1w0Ko6JSZH8cfNRvytg524iSDDGlFjbpUBCF+1vA161tgcD1caY9tGVIqDTVSdEZJmIZIlIVkVFhTsxK+UT8irrSYmN0KmjfYSI8MClozhaWc+6/aV2h9MjXSYCEdkgItkuHgs7tjPOhT87TYMikghMAj46n0CNMSuMMZnGmMz4eM/XJVeqt+VXNTBcB4r7lKsnDiV9cH+e3nzEr9ZC7jIRGGMWGGMmunisAcqsX/Dtv+jPVcf1VuBtY0yL9bwKiBaR9nsZkgH/61xT6jy0Vx1N04HiPiU4SLjv0pHsLarh8yNVdofTbe52Db0LLLW2lwJrztH2dr7uFmq/gtiEc9ygO8cr1WeU1zbR2OJfC9ar7rl5WhJDBoXz9MdH7A6l29xNBMuBK0TkMLDAeo6IZIrIs+2NRCQdSAE2n3H8Q8APRCQX55jBc27Go5RfaK86qncV9z3hIcF856LhfJpbyd6iarvD6Ra3EoExpsoYM98YM9rqQjph7c8yxtzboV2eMSbJGOM44/ijxpiZxphRxphvGWOa3IlHKX+RX9WeCPSKoC+6Y1Yqg/qF8IfN/nFVoHcWK2WDYzp1tE8b1C+Uu+eksTa7lKMVdXaH0yVNBErZIL+yQaeO9nHfnjucsOAgVnxy1O5QuqSJQCkb6DrFfV/8oHBuzUzhrZ1FlPawtHVv00SgVC8zxlqwXmcM9XnLLhmBw8Bzn/r2VYEmAqV6Wdkpa+qozhjq81Ji+3P95ERe2VZAdUOz3eF0ShOBUr2svdicXhEEhgfmjaS+uY2XtuTbHUqnNBEo1cvyKnXqaCAZNzSSy8cN4fnP8zjd7JslqjURKNXL8qoaCA0WnToaQB6YN5IT9c28kVVodyguaSJQqpc5q47qgvWBZEZ6LJlpMaz45CgtbY6uD+hlmgiU6mV5VfW6KlkAemDeSIqrT/P+3uN2h3IWTQRK9SJjDPlVDVp1NABdNnYIYxMG8fTHR3D42MI1mgiU6kXltU2cbmljeJxOHQ00QUHC/fNGcKisjk1fnqtif+/TRKBUL2qvOqpXBIHp+snDSIqO8LkS1ZoIlOpF7VNHdWWywBQaHMSyS0aQlX+SHXkn7A7nK5oIlOpF7VNHE6P62R2KssmtmSnEDgjzqasCTQRK9aL2qaMhwfpPL1BFhAXzrcxkNh+q8JkbzPTbqFQv0qqjCmBmeixtDsO+4hq7QwHcTAQiEisi60XksPUzxkWby0Rkd4dHo4gssl57QUSOdXhtqjvxKOXL2qeOaiJQU1OiAdhVcNLeQCzuXhE8DGw0xowGNlrPv8EYs8kYM9UYMxW4HGgA1nVo8mD768aY3W7Go5TPap86mq5TRwPe4IHhpA3uz66CartDAdxPBAuBldb2SmBRF+0XA2uNMQ1uvq9SfueYFptTHWSkRLOz4CTG2H9zmbuJIMEYU2JtlwIJXbS/DXj1jH2PicheEXlSRMLdjEcpn6UL1quOMlJjKK9tosQHVi/rMhGIyAYRyXbxWNixnXGmtU5Tm4gkApOAjzrsfgQYB8wAYoGHznH8MhHJEpGsioqKrsJWyuccq2yvOqpTRxVkpEYD+ET3UJeJwBizwBgz0cVjDVBm/YJv/0V/rvumbwXeNsa0dDh3iXFqAp4HZp4jjhXGmExjTGZ8fHx3//uU8hn5VfWkxOjUUeU0bmgk4SFBPjFg7O438l1gqbW9FFhzjra3c0a3UIckIjjHF7LdjEcpn3WsUtcpVl8LCwliUlIUuwqr7Q7F7USwHLhCRA4DC6zniEimiDzb3khE0oEUYPMZx68SkX3APiAOeNTNeJTySV9XHdUZQ+prGanR7CuuobnV3jUKQtw52BhTBcx3sT8LuLfD8zwgyUW7y915f6X8xddVR/WKQH0tIzWGZ/52jJySU0yx7i2wg3ZWKtUL8rTqqHLh6wFje8cJNBEo1QvyrKmjujKZ6igxKoKhkf1sHyfQRKBUL8iraiAkSKeOqrNlpEbbPoVUE4FSvSCvsp5UrTqqXMhIjabgRAOVdU22xaDfSqW8zBjDscp6nTGkXMpIddbq3G3jVYEmAqW8yOEwPPZBDgdLa8lMj7U7HOWDJg6LIiRI2FVo34CxW9NHlVKda2lz8NCbe1m9q5ilc9J44NKRdoekfFBEWDDjEyNtHSfQKwKlvOB0cxv3vfQFq3cV88MrxvCzGy8gKEjsDkv5qIzUaPYUVtPmsKcSqSYCpTyspqGFO5/bxqYvy3nspon80/zROKuoKOVaRmo09c1tHC6vteX9NREo5UGlNY3c+sct7Cuq4fd3TGPJrDS7Q1J+ICPFOWBsV/eQJgKlPORoRR23PP05RScbeOGeGVw7KdHukJSfSBvcn5j+obbdYayDxUp5wN6iar79/A4EeG3ZHCYlR9kdkvIjIkJGaoxeESjlrz7LreT2FVvpHxbMmw/M1SSgzktGSjSHy+uoOd3SdWMP00SglBs+2FvCPc/vIDmmP289MFeri6rz1n5j2d6i6l5/b00ESp2nl7bm84+v7mRychRv3DeHhEitI6TO3+SUKETsGTDWMQKlesgYw2835vLkhkPMHzeE/71jGhFhwXaHpfxcZL9QRg8ZaMuAsSYCpXqgudXBox8c4MUt+dwyLZnlt0wiVAvJKQ/JSInhowOlGGN69d4T/QYr1U2fH6nkmt98wotb8ll2yQj+51uTNQkoj8pIjaa6oYW8qoZefV+3v8UiEisi60XksPUzppN2vxSR/SKSIyK/tRasR0Smi8g+EcntuF8pX1Fe28g/v7aLO57ZRnObg+e/PYOfXDte7xZWHtc+YNzb3UOe+HPmYWCjMWY0sNF6/g0iMhe4EJgMTARmAJdaLz8N/AMw2npc7YGYlHJbm8Pw4pY85v9qM3/ZV8r/u3wU6//lUi4bN8Tu0FQfNWrIQAaGh/T6gLEnxggWAvOs7ZXAx8BDZ7QxQD8gDBAgFCgTkUQg0hizFUBEXgQWAWs9EJdS521PYTU/fSebfcU1XDhqMP+5cCIj4wfaHZbq44KDhCkpUb1ektoTiSDBGFNibZcCCWc2MMZsEZFNQAnORPC/xpgcEckEijo0LQKSXL2JiCwDlgGkpqZ6IGylzlbT0MIT6w6yalsBcQPD+e3tGdwwOVG7gVSvyUiJ4enNRzjd3NZrs9G6lQhEZAMw1MVL/9rxiTHGiMhZdVRFZBQwHki2dq0XkYuB090N1BizAlgBkJmZaU+tVtVnGWN4e1cx//2XHE7UN7N0Tjo/uHIMkf1C7Q5NBZiM1GjaHIZ9xTXMHN47ixl1KxEYYxZ09pqIlIlIojGmxOrqKXfR7CZgqzGmzjpmLTAHeImvkwPWdnF3g1fKEw6X1fLTd7LZduwEU1OieeGemUxM0jIRyh5TU6IB54BxbyUCTwwWvwsstbaXAmtctCkALhWREBEJxTlQnGN1KZ0SkdnWbKG7OzleKY9rbGlj+dqDXPObv3GwtJb/vmkSqx+Yq0lA2WrwwHDSBvfv1QFjT4wRLAfeEJHvAPnArQBW///9xph7gTeBy4F9OAeOPzTGvGcd/13gBSAC5yCxDhQrrzPG8KM/7+H9vSUsnp7MI9eMY/DAcLvDUgpwFqD7/EhVr91Y5nYiMMZUAfNd7M8C7rW224D7Ojk+C+eUUqV6zf99fIT395bw46vH8t15o+wOR6lvyEiN4Z3dxympaWRYdITX309vi1QBZ8OBMv5n3ZfcOGWYLiivfFJGajTQewXoNBGogHKorJbvv7aLicOi+OXiyTotVPmkcUMjCQ8J6rU7jDURqIBR3dDMP7yYRURYCCvunk6/UK0YqnxTWEgQk5Ki2FVY3Svvp4lABYTWNgffe2UnJdWN/PGu6SRGeb/fVSl3ZKRGs6+4huZWh9ffSxOBCgiPfpDDZ7lVPHrTRKanuayLqJRPyUiNobnVQU7JKa+/lyYC1ee9vqOAFz7P4+8vHM6tmSl2h6NUt3w9YOz9cQJNBKpPy8o7wU/fyebi0XH85NpxdoejVLclRkUwNLJfr4wTaCJQfVZx9Wnuf/kLkqIj+N3tGYToIjLKz2SkRvfKFFL9l6H6pNPNbSx7MYvGFgfPLs0kun+Y3SEp1WMZqdEUnGigsq7Jq++jicBLvP0/TnXOGMODb+7hQMkpfnPbVEYNGWR3SEqdl/YVy3Z7+apAE4EXvPVFEZmPbuD9vcftDiUgtZePePCqscwff9byGEr5jYnDoggJEq8vVKOJwMPKTzXy8/f2A/D4hwdpam2zOaLAsl7LR6g+JCIsmPGJkV4fJ9BE4EHGGH76TjaNrQ5+fuMFFJ44zctbC+wOK2AcKqvln7V8hOpjMlKj2VNYTZvDe+txeaIMtbJ8sK+EdQfKePiacSydm86GnDJ+99fDLJ6eTFSErnTVXXVNrZSfauzRMU2tDu5/+QstH6H6nIzUaF7cks/h8lrGDY30yntoIvCQqrom/mPNfiYnR3HvRcMBePiacVz/u095+uMjPHyNzmHvDofDsOj3n5FbXtfjY8OCg3h12WwtH6H6lIwU54DxroJqTQS+7ufvHeBUYwurFs/6ar76BcOiuCkjiT99doy75qSR1At1xf3dp7mV5JbXcf+lIxmf2LPZPmMSBjE+0Tv/UJSyS9rg/sT0D2VXwUlun5nqlffQROAB6/aX8u6e4/zLgjFnZewfXjmW9/eW8Ot1h/jVrVNsitB/vLw1n8EDwviXK0YTHqLdO0qJCBmpMV4dMHZrsFhEYkVkvYgctn66rOYlIr8Ukf0ikiMiv7XWJ0ZEPhaRL0Vkt/UY4k48dqg53cJP38lm3NBBPDDv7FkqSdER3HNhOqt3FXHguPeLR/mz49Wn2ZBTxq0zUjQJKNVBRko0h8vrqDnd4pXzuztr6GFgozFmNLDRev4NIjIXuBCYjHNJyhk4F69vt8QYM9V6lLsZT6977IMDVNU388TiKYSFuP44vztvFFERoSz/8GAvR+dfXttegAHu8NLlr1L+qv3Gsr1F1V45v7uJYCGw0tpeCSxy0cYA/YAwIBwIBcrcfF+f8MmhCt7IKmLZJSOYlBzVabuoiFD+8bJRfHKogr8drujFCP1HS5uD13YUMm9MPCmx/e0ORymfMjklChHvLV3pbiJIMMaUWNulwFm3cRpjtgCbgBLr8ZExJqdDk+etbqF/k3NM/BaRZSKSJSJZFRX2/zKta2rlkdX7GBE/gO/PH91l+7vmpJEcE8Ev/nIQhxfnA/ur9QfKKK9t4s7ZaXaHopTPiewXyughA71WkrrLRCAiG0Qk28VjYcd2xhiD86//M48fBYwHkoEk4HIRudh6eYkxZhJwsfW4q7M4jDErjDGZxpjM+Pj4bv8Hesvjaw9yvOY0Tyye3K056+EhwTx41VgOlJxizZ7iXojQv7y8NZ+k6AjmjfW7YSKlekVGSgy7Cqtx/qr1rC4TgTFmgTFmoovHGqBMRBIBrJ+u+vhvArYaY+qMMXXAWmCOde5i62ct8Aow0zP/Wd619WgVL23N5565w5meFtvt426YPIxJSVH8z0eHaGzR0hPtjlTU8fmRKu6YlUpwkN4NrJQrGanRVDe0kFfV4PFzu9s19C6w1NpeCqxx0aYAuFREQkQkFOdAcY71PA7A2n89kO1mPF53urmNh9/aS2psf3501ZgeHRsUJDxy7TiKq0/z4pY87wToh1ZtLSA0WHT1MKXO4eIx8TyxeDKxXiip7m4iWA5cISKHgQXWc0QkU0Setdq8CRwB9gF7gD3GmPdwDhx/JCJ7gd1AMfCMm/F43a/Xf0leVQPLb5lE/7Ce34Yxd2Qcl42N53//mkt1Q7MXIvQvp5vbePOLQq66YCjxg8LtDkcpn5UUHcG3MlOI6u/5cjVu3VBmjKkC5rvYnwXca223Afe5aFMPTHfn/Xuqsq6J6IjQ816pamfBSZ779BhLZqUyd2Tcecfx8DXjueY3n/D7Tbn863UTzvs8fcF7e49zqrFVB4mVslFAVR/9yep9TH90A//82i7e23OcU43dvzmjqbWNH7+5l6GR/dyuGzR26CBumZbMys/zKTzh+f4+f/Ly1nxGDxnIrOHdH2tRSnlWQJWY+LsZKQzqF8qmL8t5Z/dxQoKEWSNiWTA+gQXjE845f/13G3PJLa/j+XtmMKif+5dmP7hyDO/uOc6v1n3JU7dluH0+f7S3qJq9RTX8/MYLtGS0UjYKqEQwf3wC88cn0OYw7Co4yfqcMjbmlPPz9w7w8/cOMG7oIOaPH8KC8QlMSY4myJrBkl1cw9Obj3DLtGQu89D0xsSoCL5z0XD+7+Mj3HvxCCYmdX5DWl/18tZ8IkKDuWlakt2hKBXQxBtzUr0tMzPTZGVleex8xyrr2ZhTxoacMnbknaTNYYgbGM78cUOYP34IT204TEVdE+v/5RKPLoJ+qrGFS3+5ifGJkay6d1ZA/VVc09DCrF9s4KaMJH5x82S7w1EqIIjIF8aYzDP3B9QVQWeGxw3g3otHcO/FI6huaObjLyvYkFPGX/aV8HpWIQB/vGu6R5MAOO8W/H/zR/Pz9w6w+VBFQN1M9dbOIhpbHCyZpYPEStlNE8EZovuHsSgjiUUZSTS3Oth+7ATVp5u56oKhXnm/JbPSeP6zPJavPcjFo+MD4oYqYwyrtuUzNSU6ILvElPI1ATVrqKfCQoK4aHQc108e5tX3+PHVYzlYWsvqnUVeex9fsuVoFUcq6nXKqFI+QhOBD7huUiJTkqP41brAKD2xamsBURGhXD850e5QlFJoIvAJIsIj146n9FQjf9h8xO5wvKr8VCMf7S/lW9OTdYF5pXyEJgIfMXvEYG6YMozfb8rly9Jau8Pxmtd2FNLqMCzRbiGlfIYmAh/ysxsmMKhfKD9+cw+tbQ67w/G41jYHr24v4KJRcQyPG2B3OEopiyYCHzJ4YDg/u/EC9hTV8KfPjtkdjsf99WA5JTWN3Dlbl6JUypdoIvAxN0xO5IoJCfxq3SGOVtTZHY5HvbytgITIcBaMP2shO6WUjTQR+BgR4dFFEwkPCeKht/b2mWUt86vq+eRQBbfPTD3v6q9KKe/Qf5E+KCGyH/92/QR25J3kpa35dofjEa9sKyA4SLhthnYLKeVrNBH4qMXTk7lkTDyPf3jQ70tVN7a08UZWIVeMT2BoVD+7w1FKnUETgY8SEX5x8yQEeGT1Po8tWO1wGB7/8CALfr2Zf1+TzSeHKmhq9e5NbGuzSzjZ0KJ3Eivlo9xKBCISKyLrReSw9TOmk3aPi0i29fi7DvuHi8g2EckVkddFxPOLcfqxpOgIHr52PJ/mVvKGVfzOHS1tDn745z08/fERBoSH8OesIu7+03am/ed6vrvqC1bvLOJkveeXz3xpSz7D4wYwd+Rgj59bKeU+d4vOPQxsNMYsF5GHrecPdWwgItcB04CpONcp/lhE1hpjTgGPA08aY14TkT8A3wGedjOmPmXJzFTe33OcR9/P4dIxQ867a6WhuZXvrtrJx19W8OBVY/nuvJE0tTr4/Egl6w+UszGnjL/sKyVIIDMtlgUThjB/fAIj4we6Ff+B46fYWVDNT68b/9X6Dkop3+LWegQi8iUwzxhTIiKJwMfGmLFntHkQ6GeM+S/r+XPAR8CfgQpgqDGmVUTmAD8zxlzV1ft6ej0CX5dXWc/Vv/mEC0fG8ezSzB6vW1Dd0Mzfv7CD3YXV/PdNk7ht5tkDtg6HIft4DRtyytlwoIwDJacAGBE3gAUTnCu4TUuN7vGMn5+8vY+3vihi20/me7yMt1KqZ7y1HkGCMabE2i4FXE0Q3wP8h4j8CugPXAYcAAYD1caYVqtdEaBLVbmQHjeAH105lkc/yGHN7uMsyuj+x1RSc5q7n9tO/okG/m/JdK6e6LqcdlCQMDk5msnJ0fzgijEUV5/mrzllrM8p5/nPjrHik6P0DwvucX2g6oZmbspI1iSglA/rMhGIyAbA1W+Pf+34xBhjROSsywtjzDoRmQF8jvMKYAvQ49FJEVkGLANITQ28KYj3XDicD/aV8LP39nPhqDjiB4V3ecyRijrufm47NadbWHnPTOb0oI8+KTqCu+akc9ecdOqaWvnboQq2552gta1nV5DBQcJ3Lhreo2OUUr3L611DLo55BXgZWIt2DfVIbnkt1/7mU66YkMDvl0w7Z9s9hdXc88IOggReuGemLgCjlOq0a8jd6aPvAkut7aXAGhdvHCwig63tycBkYJ1xZqBNwOJzHa++NmrIIL6/YDQf7Cth7b6STtt9eriS25/ZyoDwYN68f64mAaXUObmbCJYDV4jIYWCB9RwRyRSRZ602ocDfROQAsAK4s8O4wEPAD0QkF+eYwXNuxtPnLbtkBBcMi+Tf1ux3OdXz/b3HueeF7aTG9uet++eSrlU+lVJdcKtryC6B2jXUbv/xGhb+72fcOGUYv/67qV/tf2lrPv++JpsZabE8szSTqIhQ+4JUSvkcb3UNKRtcMCyK784byepdxWw6WI4xhqc2HOLf3slm/rghvPidmZoElFLd5u70UWWT710+ig/3l/KTt/cxb+wQXt1ewOLpySy/eZJW91RK9Yj+xvBT4SHB/HLxFMpONfLq9gLuu3QETyyerElAKdVjekXgx6amRLP8lslg4NYZKXaHo5TyU5oI/NytmZoAlFLu0X4EpZQKcJoIlFIqwGkiUEqpAKeJQCmlApwmAqWUCnCaCJRSKsBpIlBKqQCniUAppQKcX1YfFZEKIP88D48DKj0Yjr/Sz8FJP4ev6Wfh1Jc/hzRjTPyZO/0yEbhDRLJclWENNPo5OOnn8DX9LJwC8XPQriGllApwmgiUUirABWIiWGF3AD5CPwcn/Ry+pp+FU8B9DgE3RqCUUuqbAvGKQCmlVAeaCJRSKsAFVCIQkatF5EsRyRWRh+2Oxy4ikici+0Rkt4hk2R1PbxGRP4lIuYhkd9gXKyLrReSw9TPGzhh7Qyefw89EpNj6TuwWkWvtjLE3iEiKiGwSkQMisl9Evm/tD7jvRMAkAhEJBn4PXANMAG4XkQn2RmWry4wxUwNsvvQLwNVn7HsY2GiMGQ1stJ73dS9w9ucA8KT1nZhqjPlLL8dkh1bgh8aYCcBs4HvW74SA+04ETCIAZgK5xpijxphm4DVgoc0xqV5kjPkEOHHG7oXASmt7JbCoN2OyQyefQ8AxxpQYY3Za27VADpBEAH4nAikRJAGFHZ4XWfsCkQHWicgXIrLM7mBslmCMKbG2S4EEO4Ox2T+KyF6r66jPd4d0JCLpQAawjQD8TgRSIlBfu8gYMw1nN9n3ROQSuwPyBcY5lzpQ51M/DYwEpgIlwK9sjaYXichA4C3gn40xpzq+FijfiUBKBMVASofnyda+gGOMKbZ+lgNv4+w2C1RlIpIIYP0stzkeWxhjyowxbcYYB/AMAfKdEJFQnElglTFmtbU74L4TgZQIdgCjRWS4iIQBtwHv2hxTrxORASIyqH0buBLIPvdRfdq7wFJreymwxsZYbNP+i89yEwHwnRARAZ4Dcowxv+7wUsB9JwLqzmJrStxTQDDwJ2PMY/ZG1PtEZATOqwCAEOCVQPkcRORVYB7OMsNlwH8A7wBvAKk4S5vfaozp0wOpnXwO83B2CxkgD7ivQz95nyQiFwF/A/YBDmv3T3COEwTWdyKQEoFSSqmzBVLXkFJKKRc0ESilVIDTRKCUUgFOE4FSSgU4TQRKKRXgNBEopVSA00SglFIB7v8D2Lx00LfSARUAAAAASUVORK5CYII=", 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" ] @@ -387,12 +464,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "(1, 24, 7)\n" + "torch.Size([24])\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -407,17 +484,44 @@ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "\n", + "import torch.nn.functional as F\n", + "import torch\n", + "import matplotlib.pyplot as plt \n", + "import numpy as np\n", + "import matplotlib\n", + "# data_pred = np.load('./results/ETTh1_96_24_Autoformer_ETTh1_ftM_sl96_ll48_pl24_dm512_nh8_el2_dl1_df2048_fc1_ebtimeF_dtTrue_Exp_0/pred.npy')\n", + "data_pred = np.load('./results/ETTh1_96_24_Autoformer_ETTh1_ftM_sl96_ll48_pl24_dm512_nh8_el2_dl1_df2048_fc1_ebtimeF_dtTrue_Exp_0/real_prediction.npy')\n", + "data_pred = torch.from_numpy(data_pred).permute(0,2,1)\n", + "\n", "plt.figure()\n", + "print(data_pred.shape)\n", + "#预测OT\n", + "plt.plot(data_pred[-1,-1,:])#由于prediction.shape是[1,24,7]那么batch只有1 索引只能是0或-1 都是代表batch这一维本身,如果是加载np文件就不一样了\n", + "print(data_pred[-1,-1,:].shape)\n", + "plt.show()\n", + "plt.plot(data_pred[0,-1,:])#没问题\n", + "print(data_pred[0,-1,:].shape)\n", + "plt.show()\n", + "# draw HUFL prediction\n", + "plt.plot(data_pred[0,0,:])#没问题\n", + "print(data_pred[-1,-1,:].shape)\n", + "plt.show()\n", + "'''\n", + "Ground Truth\n", + "'''\n", + "data_gt = np.load('./results/ETTh1_96_24_Autoformer_ETTh1_ftM_sl96_ll48_pl24_dm512_nh8_el2_dl1_df2048_fc1_ebtimeF_dtTrue_Exp_0/true.npy')\n", + "data_gt = torch.from_numpy(data_gt).permute(0,2,1)\n", + "\n", "#预测OT\n", - "plt.plot(prediction[-1,:,-1])#由于prediction.shape是[1,24,7]那么batch只有1 索引只能是0或-1 都是代表batch这一维本身\n", - "print(prediction.shape)\n", + "plt.plot(data_gt[-1,-1,:])#由于prediction.shape是[1,24,7]那么batch只有1 索引只能是0或-1 都是代表batch这一维本身,如果是加载np文件就不一样了\n", + "print(data_gt[-1,-1,:].shape)\n", "plt.show()\n", - "plt.plot(prediction[0,:,-1])#没问题\n", - "print(prediction.shape)\n", + "plt.plot(data_gt[0,-1,:])#没问题\n", + "print(data_gt[0,-1,:].shape)\n", "plt.show()\n", "# draw HUFL prediction\n", - "plt.plot(prediction[0,:,0])#没问题\n", - "print(prediction.shape)\n", + "plt.plot(data_gt[0,0,:])#没问题\n", + "print(data_gt[-1,-1,:].shape)\n", "plt.show()\n", "\n" ]