├── README.md └── SimCLR.ipynb /README.md: -------------------------------------------------------------------------------- 1 | # simclr 2 | This repository contains a PyTorch implementation of SimCLR based on the work [A Simple Framework for Contrastive Learning of Visual Representations](https://arxiv.org/abs/2002.05709) by Chen et al. 3 | 4 | SimCLR consists of 4 elements: 5 | 6 | - a random data augmentation (crops and color jitter) 7 | - a base encoder (ResNet50) 8 | - a projection head (2 layer MLP) 9 | - a contrastive loss (NT-Xent) 10 | 11 | Each input image is randomly tranformed twice. The task is to identify the second transformation among a batch of other source images. For efficiency, the other images in the batch are used as negative examples and the loss is calculated based on pairwise cosine similarities. 12 | 13 | ## TODOs / Differences to the paper 14 | 15 | - [ ] LARS instead of Adam 16 | - [ ] Same LR schedule 17 | - [x] Latent dimension of 128 18 | 19 | ## Results 20 | 21 | ### CIFAR-10 22 | 23 | Linear evalutation using modified ResNet50, t=0.5, bs=256. 24 | 25 | | Source | Epoch 100 | Epoch 200 | Epoch 300 | Epoch 400 | Epoch 500 | 26 | | --------- | ---------:| ---------:| ---------:| ---------:| ---------:| 27 | | Paper | 83.9% | 89.2% | 91.5% | 92.1% | 93.0% | 28 | | This repo | 79.5% | 82.8% | | | | 29 | 30 | As shown in Fugure B.6. These numbers aren't final yet. 31 | -------------------------------------------------------------------------------- /SimCLR.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "colab_type": "text", 7 | "id": "JEwbldGLI3jE" 8 | }, 9 | "source": [ 10 | "This notebook contains a PyTorch implementation of the paper [A Simple Framework for Contrastive Learning of Visual Representations](https://arxiv.org/abs/2002.05709) by Chen et al." 11 | ] 12 | }, 13 | { 14 | "cell_type": "code", 15 | "execution_count": null, 16 | "metadata": { 17 | "colab": { 18 | "base_uri": "https://localhost:8080/", 19 | "height": 34 20 | }, 21 | "colab_type": "code", 22 | "executionInfo": { 23 | "elapsed": 3780, 24 | "status": "ok", 25 | "timestamp": 1582535518144, 26 | "user": { 27 | "displayName": "Paul-Louis Pröve", 28 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 29 | "userId": "18006315251927326887" 30 | }, 31 | "user_tz": -60 32 | }, 33 | "id": "zSpSFIt5zuuk", 34 | "outputId": "1ba2d16f-ac9e-4980-b74b-ec150e2f33cb" 35 | }, 36 | "outputs": [], 37 | "source": [ 38 | "import numpy as np\n", 39 | "from tqdm import tqdm_notebook as tqdm\n", 40 | "from PIL import Image\n", 41 | "\n", 42 | "import torch\n", 43 | "import torch.nn as nn\n", 44 | "from torch.optim import Adam\n", 45 | "from torch.utils.data import DataLoader, Dataset\n", 46 | "import torchvision.transforms as tfs\n", 47 | "from torchvision.datasets import *\n", 48 | "from torchvision.models import *\n", 49 | "\n", 50 | "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n", 51 | "device" 52 | ] 53 | }, 54 | { 55 | "cell_type": "code", 56 | "execution_count": null, 57 | "metadata": { 58 | "colab": {}, 59 | "colab_type": "code", 60 | "id": "PZ0gavHPzuuq" 61 | }, 62 | "outputs": [], 63 | "source": [ 64 | "tf_tr = tfs.Compose([\n", 65 | " tfs.RandomResizedCrop(32),\n", 66 | " tfs.RandomHorizontalFlip(),\n", 67 | " tfs.ColorJitter(0.5, 0.5, 0.5, 0.5),\n", 68 | " tfs.ToTensor(),\n", 69 | " tfs.Normalize(mean=[0.485, 0.456, 0.406], \n", 70 | " std=[0.229, 0.224, 0.225])\n", 71 | "])\n", 72 | "\n", 73 | "tf_de = tfs.Compose([\n", 74 | " tfs.Resize(32),\n", 75 | " tfs.ToTensor(),\n", 76 | " tfs.Normalize(mean=[0.485, 0.456, 0.406], \n", 77 | " std=[0.229, 0.224, 0.225])\n", 78 | "])\n", 79 | "\n", 80 | "tf_te = tfs.Compose([\n", 81 | " tfs.Resize(32),\n", 82 | " tfs.ToTensor(),\n", 83 | " tfs.Normalize(mean=[0.485, 0.456, 0.406], \n", 84 | " std=[0.229, 0.224, 0.225])\n", 85 | "])" 86 | ] 87 | }, 88 | { 89 | "cell_type": "code", 90 | "execution_count": null, 91 | "metadata": { 92 | "colab": {}, 93 | "colab_type": "code", 94 | "id": "XYPE0H5ezuut" 95 | }, 96 | "outputs": [], 97 | "source": [ 98 | "class CustomCIFAR10(CIFAR10):\n", 99 | " def __init__(self, **kwds):\n", 100 | " super().__init__(**kwds)\n", 101 | " \n", 102 | " def __getitem__(self, idx):\n", 103 | " if not self.train:\n", 104 | " return super().__getitem__(idx)\n", 105 | " \n", 106 | " img = self.data[idx]\n", 107 | " img = Image.fromarray(img).convert('RGB')\n", 108 | " imgs = [self.transform(img), self.transform(img)]\n", 109 | " return torch.stack(imgs)" 110 | ] 111 | }, 112 | { 113 | "cell_type": "code", 114 | "execution_count": null, 115 | "metadata": { 116 | "colab": { 117 | "base_uri": "https://localhost:8080/", 118 | "height": 134, 119 | "referenced_widgets": [ 120 | "731ba3d5aa5d4c1d961f223f6996b5d4", 121 | "3e1b47fc4a10405187b008a837c909c4", 122 | "070fed20c87846c8a1732c39fd89ff90", 123 | "b31d13da87be4e698e8c47598c739a79", 124 | "be266bd269ef41429dab7c40f6ddfa6e", 125 | "eeed99c57b1d4e6bb780ad87ed0ad64c", 126 | "bfe73a9abb274e15ac46cc505a7c4341", 127 | "65e03ee1f6124b2b8372afbb733b7362" 128 | ] 129 | }, 130 | "colab_type": "code", 131 | "executionInfo": { 132 | "elapsed": 9439, 133 | "status": "ok", 134 | "timestamp": 1582535558415, 135 | "user": { 136 | "displayName": "Paul-Louis Pröve", 137 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 138 | "userId": "18006315251927326887" 139 | }, 140 | "user_tz": -60 141 | }, 142 | "id": "3diHt5Cszuuz", 143 | "outputId": "4d604523-59d3-4607-e240-1bf6807f9baf" 144 | }, 145 | "outputs": [], 146 | "source": [ 147 | "ds_tr = CustomCIFAR10(root='data', train=True, transform=tf_tr, download=True)\n", 148 | "ds_de = CIFAR10(root='data', train=True, transform=tf_de, download=True)\n", 149 | "ds_te = CIFAR10(root='data', train=False, transform=tf_te, download=True)" 150 | ] 151 | }, 152 | { 153 | "cell_type": "code", 154 | "execution_count": null, 155 | "metadata": { 156 | "colab": {}, 157 | "colab_type": "code", 158 | "id": "2WJ3Gu4Azuu6" 159 | }, 160 | "outputs": [], 161 | "source": [ 162 | "dl_tr = DataLoader(ds_tr, batch_size=256, shuffle=True)\n", 163 | "dl_de = DataLoader(ds_de, batch_size=256, shuffle=True)\n", 164 | "dl_te = DataLoader(ds_te, batch_size=256, shuffle=False)" 165 | ] 166 | }, 167 | { 168 | "cell_type": "code", 169 | "execution_count": null, 170 | "metadata": { 171 | "colab": {}, 172 | "colab_type": "code", 173 | "id": "VR72XmwUzuu9" 174 | }, 175 | "outputs": [], 176 | "source": [ 177 | "model = resnet50(pretrained=False)\n", 178 | "model.conv1 = nn.Conv2d(3, 64, 3, 1, 1, bias=False)\n", 179 | "model.maxpool = nn.Identity()" 180 | ] 181 | }, 182 | { 183 | "cell_type": "code", 184 | "execution_count": null, 185 | "metadata": { 186 | "colab": { 187 | "base_uri": "https://localhost:8080/", 188 | "height": 1000 189 | }, 190 | "colab_type": "code", 191 | "executionInfo": { 192 | "elapsed": 17713, 193 | "status": "ok", 194 | "timestamp": 1582535569383, 195 | "user": { 196 | "displayName": "Paul-Louis Pröve", 197 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 198 | "userId": "18006315251927326887" 199 | }, 200 | "user_tz": -60 201 | }, 202 | "id": "qGByvqC00OST", 203 | "outputId": "4c1a644e-294e-4a67-dab8-f096fc6a19b2" 204 | }, 205 | "outputs": [], 206 | "source": [ 207 | "ch = model.fc.in_features\n", 208 | "model.fc = nn.Sequential(nn.Linear(ch, ch),\n", 209 | " nn.ReLU(),\n", 210 | " nn.Linear(ch, ch))\n", 211 | "model.to(device)\n", 212 | "model.train()" 213 | ] 214 | }, 215 | { 216 | "cell_type": "code", 217 | "execution_count": null, 218 | "metadata": { 219 | "colab": {}, 220 | "colab_type": "code", 221 | "id": "dXT6GGhEzuvA" 222 | }, 223 | "outputs": [], 224 | "source": [ 225 | "def pair_cosine_similarity(x, eps=1e-8):\n", 226 | " n = x.norm(p=2, dim=1, keepdim=True)\n", 227 | " return (x @ x.t()) / (n * n.t()).clamp(min=eps)\n", 228 | "\n", 229 | "def nt_xent(x, t=0.5):\n", 230 | " x = pair_cosine_similarity(x)\n", 231 | " x = torch.exp(x / t)\n", 232 | " idx = torch.arange(x.size()[0])\n", 233 | " # Put positive pairs on the diagonal\n", 234 | " idx[::2] += 1\n", 235 | " idx[1::2] -= 1\n", 236 | " x = x[idx]\n", 237 | " # subtract the similarity of 1 from the numerator\n", 238 | " x = x.diag() / (x.sum(0) - torch.exp(torch.tensor(1 / t)))\n", 239 | " return -torch.log(x.mean())" 240 | ] 241 | }, 242 | { 243 | "cell_type": "code", 244 | "execution_count": null, 245 | "metadata": { 246 | "colab": {}, 247 | "colab_type": "code", 248 | "id": "av1krLFbzuvD" 249 | }, 250 | "outputs": [], 251 | "source": [ 252 | "optimizer = Adam(model.parameters(), lr=0.001)" 253 | ] 254 | }, 255 | { 256 | "cell_type": "code", 257 | "execution_count": null, 258 | "metadata": { 259 | "colab": { 260 | "base_uri": "https://localhost:8080/", 261 | "height": 196, 262 | "referenced_widgets": [ 263 | "947033fad4ac43c98a562923b243d2f6", 264 | "064eed6d8ec94184addb8449bd9c02c5", 265 | "e9a6ba79990e4f6a8a0211a5724ddce9", 266 | "6b800e667f234a4683bfc53cf0c1f79a", 267 | "1a9722ec0e0a40b4b8d917b7dd6ad44b", 268 | "c1395fd85db54e13b145f82251803cd2", 269 | "bfd2873cfe1b48ecafe7866f11aea024", 270 | "b6b31c969a124d2cb8247fd7302e99d3", 271 | "79c02596c73e49ce8848ad622c503eaf", 272 | "c6dd435a3961499b9116ecd2b3924e76", 273 | "f4512ebc3445428aa9755ea68aed4aae", 274 | "a4628698ec9a48a3a5da642f3de3281c", 275 | "7a838c1aec384b5287b4c995435a9897", 276 | "53a9802383f34cbaba9c59b192a9071a", 277 | "e88ef7fad21c4c889edd1466414d864a", 278 | "5460bd914dc940e7801898322f43bd3a", 279 | "20fe00531ca94f47bf347077a0a87269", 280 | "23de046024994667adc5ab068e73fd88", 281 | "9098e5ef8a384534aa41b1dae4b19035", 282 | "473ecff61a9c4f7bad6947971f8bea71", 283 | "4f3cb10874504f1f8108a578771ab8f0", 284 | "50c55512937944229eb9f6e73cde7e81", 285 | "f37a00667b0b44a890cbf3d4e2391c69", 286 | "df9de6c8369f4714b869beeb62f001f9", 287 | "60bfb15c274b4d58950a1ee56fc10110", 288 | "3af22a4f2a514ab480d1d2d585db1e3a", 289 | "565755c60db446d3bad6c4cc3ab60c1c", 290 | "cc1152d3a3d04d5b944f37f06f588654", 291 | "bb66412f4be340a49172a866007feb8b", 292 | "161daee249724589a7e3ebfcb37d20cf", 293 | "6385506b5ab94e97ba8e61518d0dac8e", 294 | "2e7213116065458ca069499826e8bd6f" 295 | ] 296 | }, 297 | "colab_type": "code", 298 | "executionInfo": { 299 | "elapsed": 311089, 300 | "status": "error", 301 | "timestamp": 1582296971527, 302 | "user": { 303 | "displayName": "Paul-Louis Pröve", 304 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 305 | "userId": "18006315251927326887" 306 | }, 307 | "user_tz": -60 308 | }, 309 | "id": "1cGKFbmtzuvG", 310 | "outputId": "1226785e-4e48-4364-c0fc-9a14c6d3af46" 311 | }, 312 | "outputs": [], 313 | "source": [ 314 | "model.train()\n", 315 | "for i in range(100):\n", 316 | " c, s = 0, 0\n", 317 | " pBar = tqdm(dl_tr)\n", 318 | " for data in pBar:\n", 319 | " d = data.size()\n", 320 | " x = data.view(d[0]*2, d[2], d[3], d[4]).to(device)\n", 321 | " optimizer.zero_grad()\n", 322 | " p = model(x)\n", 323 | " loss = nt_xent(p)\n", 324 | " s = ((s*c)+(float(loss)*len(p)))/(c+len(p))\n", 325 | " c += len(p)\n", 326 | " pBar.set_description('Train: '+str(round(float(s),3)))\n", 327 | " loss.backward()\n", 328 | " optimizer.step()\n", 329 | " if (i+1) % 10 == 0:\n", 330 | " torch.save(model.state_dict(), path+'cifar10-rn50-mlp-b256-t0.5-e'+str(i+1)+'.pt')" 331 | ] 332 | }, 333 | { 334 | "cell_type": "code", 335 | "execution_count": null, 336 | "metadata": { 337 | "colab": {}, 338 | "colab_type": "code", 339 | "id": "XIUNcQ8hzuvJ" 340 | }, 341 | "outputs": [], 342 | "source": [ 343 | "for param in model.parameters():\n", 344 | " param.requires_grad = False" 345 | ] 346 | }, 347 | { 348 | "cell_type": "code", 349 | "execution_count": null, 350 | "metadata": { 351 | "colab": { 352 | "base_uri": "https://localhost:8080/", 353 | "height": 1000 354 | }, 355 | "colab_type": "code", 356 | "executionInfo": { 357 | "elapsed": 479, 358 | "status": "ok", 359 | "timestamp": 1582529195468, 360 | "user": { 361 | "displayName": "Paul-Louis Pröve", 362 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 363 | "userId": "18006315251927326887" 364 | }, 365 | "user_tz": -60 366 | }, 367 | "id": "5D3vwJfCzuvM", 368 | "outputId": "efdce4d8-bcd7-4f99-daed-f81141e18750" 369 | }, 370 | "outputs": [], 371 | "source": [ 372 | "model.fc = nn.Linear(ch, len(ds_de.classes))\n", 373 | "model.to(device)" 374 | ] 375 | }, 376 | { 377 | "cell_type": "code", 378 | "execution_count": null, 379 | "metadata": { 380 | "colab": {}, 381 | "colab_type": "code", 382 | "id": "yU_vtz07zuvO" 383 | }, 384 | "outputs": [], 385 | "source": [ 386 | "optimizer = Adam(model.parameters(), lr=0.003)\n", 387 | "criterion = nn.CrossEntropyLoss()" 388 | ] 389 | }, 390 | { 391 | "cell_type": "code", 392 | "execution_count": null, 393 | "metadata": { 394 | "colab": { 395 | "base_uri": "https://localhost:8080/", 396 | "height": 262, 397 | "referenced_widgets": [ 398 | 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"https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 448 | "userId": "18006315251927326887" 449 | }, 450 | "user_tz": -60 451 | }, 452 | "id": "T2cEyaelzuvR", 453 | "outputId": "a7fe46f2-c146-4d8d-da54-3857a94d45e2" 454 | }, 455 | "outputs": [], 456 | "source": [ 457 | "model.train()\n", 458 | "for i in range(5):\n", 459 | " c, s = 0, 0\n", 460 | " pBar = tqdm(dl_de)\n", 461 | " for data in pBar:\n", 462 | " x, y = data[0].to(device), data[1].to(device)\n", 463 | " optimizer.zero_grad()\n", 464 | " p = model(x)\n", 465 | " loss = criterion(p, y)\n", 466 | " s = ((s*c)+(float(loss)*len(p)))/(c+len(p))\n", 467 | " c += len(p)\n", 468 | " pBar.set_description('Train: '+str(round(float(s),3)))\n", 469 | " loss.backward()\n", 470 | " optimizer.step()" 471 | ] 472 | }, 473 | { 474 | "cell_type": "code", 475 | "execution_count": null, 476 | "metadata": { 477 | "colab": {}, 478 | "colab_type": "code", 479 | "id": "dHvJFQtu9V6Z" 480 | }, 481 | "outputs": [], 482 | "source": [ 483 | "optimizer = Adam(model.parameters(), lr=0.0001)\n", 484 | "criterion = nn.CrossEntropyLoss()" 485 | ] 486 | }, 487 | { 488 | "cell_type": "code", 489 | "execution_count": null, 490 | "metadata": { 491 | "colab": { 492 | "base_uri": "https://localhost:8080/", 493 | "height": 262, 494 | "referenced_widgets": [ 495 | "12f3ce3d43e24147840ee70fa2b780c3", 496 | "afdfda257c1343fe99bbbe3c4ae65d34", 497 | "c1a2b04f37a645b693991cc13671fd3a", 498 | "aa0d51773f5145c0b928f523a20c145e", 499 | "11429087444b4bd88a849fbe15bbc7bc", 500 | "41951e7bfb594a72bfb8af515704fb06", 501 | "3223b9e44f1d47119ef5fa9a43174fe0", 502 | "01fe95ebba164606bee323f2571dfc1d", 503 | "eadf6340cc2d4de4b7417d854b6a2aae", 504 | "d400dd7dec8c4cc3bda51eaac6ec9568", 505 | "30be5a9315fa4ad6a3905b0f84b5876a", 506 | "03b4bd6d418146acb24b4038360e35ad", 507 | "ac3a3d4db5b64294b439e3af4d0e5dd4", 508 | "787a50aa4788401cb5e56e8c426c9c26", 509 | "6ccd7a1970c641f78d5db9d652ea8411", 510 | 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"43990b7bc3764957ba28c0d65f7d7cad", 534 | "276ca45ef2154fe68bf87dcccaecc241" 535 | ] 536 | }, 537 | "colab_type": "code", 538 | "executionInfo": { 539 | "elapsed": 366708, 540 | "status": "ok", 541 | "timestamp": 1582529591922, 542 | "user": { 543 | "displayName": "Paul-Louis Pröve", 544 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 545 | "userId": "18006315251927326887" 546 | }, 547 | "user_tz": -60 548 | }, 549 | "id": "6kOT_AtB9V9S", 550 | "outputId": "3bd161ae-5f0d-4fc5-e886-bc218f422662" 551 | }, 552 | "outputs": [], 553 | "source": [ 554 | "model.train()\n", 555 | "for i in range(5):\n", 556 | " c, s = 0, 0\n", 557 | " pBar = tqdm(dl_de)\n", 558 | " for data in pBar:\n", 559 | " x, y = data[0].to(device), data[1].to(device)\n", 560 | " optimizer.zero_grad()\n", 561 | " p = model(x)\n", 562 | " loss = criterion(p, y)\n", 563 | " s = ((s*c)+(float(loss)*len(p)))/(c+len(p))\n", 564 | " c += len(p)\n", 565 | " pBar.set_description('Train: '+str(round(float(s),3)))\n", 566 | " loss.backward()\n", 567 | " optimizer.step()" 568 | ] 569 | }, 570 | { 571 | "cell_type": "code", 572 | "execution_count": null, 573 | "metadata": { 574 | "colab": { 575 | "base_uri": "https://localhost:8080/", 576 | "height": 66, 577 | "referenced_widgets": [ 578 | "cce88aa57da24ca7a38f4fa5bc7d6599", 579 | "eff3f982df9b402eae5eb5f82ea62a4d", 580 | "890a08454c1b4f36a5b8fc36c790b6d1", 581 | "c13d019d135f4363868f7f507e895b4b", 582 | "4109f738d800434babaa23cb6038b513", 583 | "b9cd3d997ec54052824848f6ae4f7efb", 584 | "0c1f5a09edc74aa09b0938ecd06464ff", 585 | "6d3e430d64f94883854770cac4432e02" 586 | ] 587 | }, 588 | "colab_type": "code", 589 | "executionInfo": { 590 | "elapsed": 368514, 591 | "status": "ok", 592 | "timestamp": 1582529599518, 593 | "user": { 594 | "displayName": "Paul-Louis Pröve", 595 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 596 | "userId": "18006315251927326887" 597 | }, 598 | "user_tz": -60 599 | }, 600 | "id": "2mWaBDzuzuvV", 601 | "outputId": "9826b3cb-515b-4de6-9966-168f184fcc89" 602 | }, 603 | "outputs": [], 604 | "source": [ 605 | "model.eval()\n", 606 | "c, s = 0, 0\n", 607 | "pBar = tqdm(dl_te)\n", 608 | "for data in pBar:\n", 609 | " x, y, = data[0].to(device), data[1].to(device)\n", 610 | " p = model(x)\n", 611 | " loss = criterion(p, y)\n", 612 | " s = ((s*c)+(float(loss)*len(p)))/(c+len(p))\n", 613 | " c += len(p)\n", 614 | " pBar.set_description('Test: '+str(round(float(s),3)))" 615 | ] 616 | }, 617 | { 618 | "cell_type": "code", 619 | "execution_count": null, 620 | "metadata": { 621 | "colab": { 622 | "base_uri": "https://localhost:8080/", 623 | "height": 66, 624 | "referenced_widgets": [ 625 | "f7eef972201843e7b666f867d7460245", 626 | "6b5c0a57a5a742c1a81cf6e32b2778a9", 627 | "fe7a619dd4b04038be7e4422dc93272f", 628 | "792aed0ff391427fac4a7239a3db50bf", 629 | "cbe0677decee40f6891eba2c437e89a4", 630 | 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| "y_true = np.concatenate(y_true)" 662 | ] 663 | }, 664 | { 665 | "cell_type": "code", 666 | "execution_count": null, 667 | "metadata": { 668 | "colab": { 669 | "base_uri": "https://localhost:8080/", 670 | "height": 34 671 | }, 672 | "colab_type": "code", 673 | "executionInfo": { 674 | "elapsed": 374336, 675 | "status": "ok", 676 | "timestamp": 1582529607342, 677 | "user": { 678 | "displayName": "Paul-Louis Pröve", 679 | "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mBIJHL1eksPu8u10g0jCRGA8aNiBB7M8xHyzyiIYto=s64", 680 | "userId": "18006315251927326887" 681 | }, 682 | "user_tz": -60 683 | }, 684 | "id": "rne3BUImzuvb", 685 | "outputId": "a76c4452-f780-4060-fd1f-ddc52e5c9c70" 686 | }, 687 | "outputs": [], 688 | "source": [ 689 | "(y_true == y_pred.argmax(axis=1)).mean()" 690 | ] 691 | }, 692 | { 693 | "cell_type": "code", 694 | "execution_count": null, 695 | "metadata": { 696 | "colab": {}, 697 | "colab_type": "code", 698 | "id": "b6E-ItwDd9dw" 699 | }, 700 | "outputs": [], 701 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