hubmap-swin-unet-w-focal-loss-train.ipynb

{"cells":[{"cell_type":"markdown","metadata":{"papermill":{"duration":0.013474,"end_time":"2022-08-23T14:57:58.144743","exception":false,"start_time":"2022-08-23T14:57:58.131269","status":"completed"},"tags":[]},"source":["<div style=\"height:200px;width:100%;margin: 0;\">\n","    <img src=\"https://storage.googleapis.com/kaggle-competitions/kaggle/34547/logos/header.png?t=2022-02-15-22-37-27\" style=\"width:100%;\" />\n","</div>"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.010548,"end_time":"2022-08-23T14:57:58.166907","exception":false,"start_time":"2022-08-23T14:57:58.156359","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"credits\"><center>Credits</center></h3>"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.012569,"end_time":"2022-08-23T14:57:58.190388","exception":false,"start_time":"2022-08-23T14:57:58.177819","status":"completed"},"tags":[]},"source":["# change log:\n","\n","|date|comment|cv/lb|outcome|\n","|-------|-------|-----|----|\n","|26/08|data pixel and thickness fixed|`0.767`/`0.69`| worked |\n","|28/08|runned on cutout [data: pixel and thickness fixed]|`0.779` / `0.65`| didn't work |\n","|28/08|running ~~cutout~~, data stain normed, pixel and thickness fixed| `--`| `--` |\n"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011799,"end_time":"2022-08-23T14:57:58.213446","exception":false,"start_time":"2022-08-23T14:57:58.201647","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"imports\"><center>Imports</center></h3>"]},{"cell_type":"code","execution_count":1,"metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-input":true,"_kg_hide-output":true,"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2022-08-29T15:01:52.722572Z","iopub.status.busy":"2022-08-29T15:01:52.721688Z","iopub.status.idle":"2022-08-29T15:01:54.306583Z","shell.execute_reply":"2022-08-29T15:01:54.305211Z","shell.execute_reply.started":"2022-08-29T15:01:52.722519Z"},"papermill":{"duration":4.765383,"end_time":"2022-08-23T14:58:02.989601","exception":false,"start_time":"2022-08-23T14:57:58.224218","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["import warnings\n","warnings.filterwarnings('ignore')\n","import os\n","import cv2\n","import time\n","import random\n","\n","import torch\n","from torch import nn\n","import torch.cuda.amp as amp\n","from torch.utils.data import Dataset\n","from torch.utils.data import DataLoader\n","from torch.utils.data import RandomSampler \n","from torch.utils.data import SequentialSampler\n","import torch.nn.functional as F\n","# from torchmetrics.functional import dice_score\n","from torch.optim.lr_scheduler import StepLR\n","import tifffile\n","\n","is_amp = True\n","import logging\n","import pandas as pd\n","from sklearn.model_selection import KFold\n","\n","import numpy as np\n","from itertools import repeat\n","import collections.abc"]},{"cell_type":"code","execution_count":2,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:54.312514Z","iopub.status.busy":"2022-08-29T15:01:54.311936Z","iopub.status.idle":"2022-08-29T15:01:54.341864Z","shell.execute_reply":"2022-08-29T15:01:54.340616Z","shell.execute_reply.started":"2022-08-29T15:01:54.312467Z"},"trusted":true},"outputs":[],"source":["def set_seed(seed = 42):\n","    '''Sets the seed of the entire notebook so results are the same every time we run.\n","    This is for REPRODUCIBILITY.'''\n","    np.random.seed(seed)\n","    random.seed(seed)\n","    torch.manual_seed(seed)\n","    torch.cuda.manual_seed(seed)\n","    # When running on the CuDNN backend, two further options must be set\n","    torch.backends.cudnn.deterministic = True\n","    torch.backends.cudnn.benchmark = False\n","    # Set a fixed value for the hash seed\n","    os.environ['PYTHONHASHSEED'] = str(seed)\n","    print('> SEEDING DONE')\n","    \n","# set_seed(42)"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011212,"end_time":"2022-08-23T14:58:03.013059","exception":false,"start_time":"2022-08-23T14:58:03.001847","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"paths\"><center>Paths</center></h3>"]},{"cell_type":"code","execution_count":3,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:54.349070Z","iopub.status.busy":"2022-08-29T15:01:54.343515Z","iopub.status.idle":"2022-08-29T15:01:56.679578Z","shell.execute_reply":"2022-08-29T15:01:56.678270Z","shell.execute_reply.started":"2022-08-29T15:01:54.349029Z"},"papermill":{"duration":2.625126,"end_time":"2022-08-23T14:58:05.649797","exception":false,"start_time":"2022-08-23T14:58:03.024671","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["# !mkdir /kaggle/working/result\n","# !mkdir /kaggle/working/checkpoint\n","\n","# root_dir = '.'\n","# pretrain_dir = '/home/lakshita/somusan/hubmap_kaggle/nbs/swin-tiny-small-22k-pretrained'\n","\n","# TRAIN = '/home/lakshita/somusan/hubmap_kaggle/hubmap_data/hubmap-22-aug-pixel-size'\n","# MASKS = '/home/lakshita/somusan/hubmap_kaggle/hubmap_data/mask_png/train_binary_masks'\n","# LABELS = '/home/lakshita/somusan/hubmap_kaggle/hubmap_data/hubmap-organ-segmentation/train.csv'\n","\n","# KAGGLE code =---------------------\n","# !mkdir /kaggle/working/result\n","# !mkdir /kaggle/working/checkpoint\n","\n","# root_dir = '/kaggle/working/'\n","# pretrain_dir = '/kaggle/input/swin-tiny-small-22k-pretrained'\n","\n","# TRAIN = '../input/hubmap-organ-segmentation/train_images/'\n","# MASKS = '../input/hacking-the-human-body-annotation-masks/train_binary_masks'\n","# LABELS = '../input/hubmap-organ-segmentation/train.csv'\n","\n","\n","# LOCAL code =---------------------\n","!mkdir -p ./result\n","!mkdir -p ./checkpoint\n","\n","root_dir = '.'\n","pretrain_dir = '/home/lakshita/somusan/hubmap_kaggle/nbs/swin-tiny-small-22k-pretrained'\n","\n","TRAIN = '/home/lakshita/somusan/hubmap_kaggle/nbs/hubmap-22-aug-pixel-size'\n","MASKS = '/home/lakshita/somusan/hubmap_kaggle/hubmap_data/mask_png/train_binary_masks'\n","LABELS = '/home/lakshita/somusan/hubmap_kaggle/hubmap_data/hubmap-organ-segmentation/train.csv'"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011987,"end_time":"2022-08-23T14:58:05.674627","exception":false,"start_time":"2022-08-23T14:58:05.662640","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"additionals\"><center>Additionals</center></h3>"]},{"cell_type":"code","execution_count":4,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:56.684492Z","iopub.status.busy":"2022-08-29T15:01:56.684155Z","iopub.status.idle":"2022-08-29T15:01:56.708769Z","shell.execute_reply":"2022-08-29T15:01:56.707732Z","shell.execute_reply.started":"2022-08-29T15:01:56.684459Z"},"papermill":{"duration":0.044719,"end_time":"2022-08-23T14:58:05.731300","exception":false,"start_time":"2022-08-23T14:58:05.686581","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def image_to_tensor(image, mode='bgr'): #image mode\n","    if mode=='bgr':\n","        image = image[:,:,::-1]\n","    x = image\n","    x = x.transpose(2,0,1)\n","    x = np.ascontiguousarray(x)\n","    x = torch.tensor(x, dtype=torch.float)\n","    return x\n","\n","\n","def mask_to_tensor(mask):\n","    x = mask\n","    x = torch.tensor(x, dtype=torch.float)\n","    return x\n","\n","\n","tensor_list = ['mask', 'image', 'organ']\n","\n","def null_collate(batch):\n","    d = {}\n","    key = batch[0].keys()\n","    for k in key:\n","        v = [b[k] for b in batch]\n","        if k in tensor_list:\n","            v = torch.stack(v)\n","        d[k] = v\n","\n","    d['mask'] = d['mask'].unsqueeze(1)\n","    d['organ'] = d['organ'].reshape(-1)\n","    return d\n","\n","\n","def _ntuple(n):\n","    def parse(x):\n","        if isinstance(x, collections.abc.Iterable):\n","            return x\n","        return tuple(repeat(x, n))\n","    return parse\n","\n","\n","to_2tuple = _ntuple(2)\n","\n","\n","def _no_grad_trunc_normal_(tensor, mean, std, a, b):\n","    # Cut & paste from PyTorch official master until it's in a few official releases - RW\n","    # Method based on https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf\n","    def norm_cdf(x):\n","        # Computes standard normal cumulative distribution function\n","        return (1. + math.erf(x / math.sqrt(2.))) / 2.\n","\n","    if (mean < a - 2 * std) or (mean > b + 2 * std):\n","        warnings.warn(\"mean is more than 2 std from [a, b] in nn.init.trunc_normal_. \"\n","                      \"The distribution of values may be incorrect.\",\n","                      stacklevel=2)\n","\n","        \n","def trunc_normal_(tensor, mean=0., std=1., a=-2., b=2.):\n","    return _no_grad_trunc_normal_(tensor, mean, std, a, b)\n","\n","\n","def drop_path(x, drop_prob: float = 0., training: bool = False, scale_by_keep: bool = True):\n","    \"\"\"Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).\n","    This is the same as the DropConnect impl I created for EfficientNet, etc networks, however,\n","    the original name is misleading as 'Drop Connect' is a different form of dropout in a separate paper...\n","    See discussion: https://github.com/tensorflow/tpu/issues/494#issuecomment-532968956 ... I've opted for\n","    changing the layer and argument names to 'drop path' rather than mix DropConnect as a layer name and use\n","    'survival rate' as the argument.\n","    \"\"\"\n","    if drop_prob == 0. or not training:\n","        return x\n","    keep_prob = 1 - drop_prob\n","    shape = (x.shape[0],) + (1,) * (x.ndim - 1)  # work with diff dim tensors, not just 2D ConvNets\n","    random_tensor = x.new_empty(shape).bernoulli_(keep_prob)\n","    if keep_prob > 0.0 and scale_by_keep:\n","        random_tensor.div_(keep_prob)\n","    return x * random_tensor\n","\n","\n","class DropPath(nn.Module):\n","    \"\"\"Drop paths (Stochastic Depth) per sample  (when applied in main path of residual blocks).\n","    \"\"\"\n","    def __init__(self, drop_prob: float = 0., scale_by_keep: bool = True):\n","        super(DropPath, self).__init__()\n","        self.drop_prob = drop_prob\n","        self.scale_by_keep = scale_by_keep\n","\n","    def forward(self, x):\n","        return drop_path(x, self.drop_prob, self.training, self.scale_by_keep)\n","\n","    def extra_repr(self):\n","        return f'drop_prob={round(self.drop_prob,3):0.3f}'\n","    \n","    \n","class RGB(nn.Module):\n","    IMAGE_RGB_MEAN = [0.485, 0.456, 0.406] #[0.5, 0.5, 0.5]\n","    IMAGE_RGB_STD  = [0.229, 0.224, 0.225] #[0.5, 0.5, 0.5]\n","\n","    def __init__(self,):\n","        super(RGB, self).__init__()\n","        self.register_buffer('mean', torch.zeros(1,3,1,1))\n","        self.register_buffer('std', torch.ones(1,3,1,1))\n","        self.mean.data = torch.FloatTensor(self.IMAGE_RGB_MEAN).view(self.mean.shape)\n","        self.std.data = torch.FloatTensor(self.IMAGE_RGB_STD).view(self.std.shape)\n","\n","    def forward(self, x):\n","        x = (x-self.mean)/self.std\n","        return x\n","    \n","    \n","def message(mode='print'):\n","    asterisk = ' '\n","    if mode==('print'):\n","        loss = batch_loss\n","    if mode==('log'):\n","        loss = train_loss\n","        if (iteration % iter_save == 0): asterisk = '*'\n","\n","    text = \\\n","        ('%0.2e   %08d%s %6.2f | '%(rate, iteration, asterisk, epoch,)).replace('e-0','e-').replace('e+0','e+') + \\\n","        '%4.3f  %4.3f  %4.4f  %4.3f   | '%(*valid_loss,) + \\\n","        '%4.3f  %4.3f   | '%(*loss,) + \\\n","        '%s' % ((time.time() - start_timer))\n","    print(\"=---------------------DEBUG\")\n","    print(loss)\n","    print(loss.shape)\n","    print(\"=---------------------DEBUG\")\n","\n","    return text"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011584,"end_time":"2022-08-23T14:58:05.754705","exception":false,"start_time":"2022-08-23T14:58:05.743121","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"randoms\"><center>Random choice</center></h3>"]},{"cell_type":"code","execution_count":5,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:56.712527Z","iopub.status.busy":"2022-08-29T15:01:56.712185Z","iopub.status.idle":"2022-08-29T15:01:56.724307Z","shell.execute_reply":"2022-08-29T15:01:56.723355Z","shell.execute_reply.started":"2022-08-29T15:01:56.712500Z"},"papermill":{"duration":0.026852,"end_time":"2022-08-23T14:58:05.792844","exception":false,"start_time":"2022-08-23T14:58:05.765992","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def valid_augment5(image, mask, organ):\n","    #image, mask  = do_crop(image, mask, image_size, xy=(None,None))\n","    return image, mask\n","\n","def train_augment5b(image, mask, organ):\n","    # image, mask = cutout_custom(image, mask)\n","    image, mask = do_random_flip(image, mask)\n","    image, mask = do_random_rot90(image, mask)\n","    \n","    for fn in np.random.choice([\n","        lambda image, mask: (image, mask),\n","        lambda image, mask: do_random_noise(image, mask, mag=0.1),\n","        lambda image, mask: do_random_contast(image, mask, mag=0.40),\n","        lambda image, mask: do_random_hsv(image, mask, mag=[0.40, 0.40, 0])\n","    ], 2): image, mask = fn(image, mask)\n","\n","    for fn in np.random.choice([\n","        lambda image, mask: (image, mask),\n","        lambda image, mask: do_random_rotate_scale(image, mask, angle=45, scale=[0.50, 2.0]),\n","    ], 1): image, mask = fn(image, mask)\n","\n","    return image, mask"]},{"cell_type":"code","execution_count":6,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:56.728234Z","iopub.status.busy":"2022-08-29T15:01:56.727694Z","iopub.status.idle":"2022-08-29T15:01:56.734911Z","shell.execute_reply":"2022-08-29T15:01:56.733945Z","shell.execute_reply.started":"2022-08-29T15:01:56.728206Z"},"trusted":true},"outputs":[],"source":["# def albu_aug(p=1.0):\n","#     return A.Compose([\n","#         A.HorizontalFlip(),\n","#         A.VerticalFlip(),\n","#         A.RandomRotate90(),\n","#         A.ShiftScaleRotate(shift_limit=0.0625, scale_limit=0.2, rotate_limit=15, p=0.9, \n","#                          border_mode=cv2.BORDER_REFLECT),\n","#         A.OneOf([\n","#             A.OpticalDistortion(p=0.3),\n","#             A.GridDistortion(p=.1),\n","#             A.PiecewiseAffine(p=0.3),\n","#             A.GaussNoise(p=0.3)\n","#         ], p=0.3),\n","#         A.OneOf([\n","#             A.HueSaturationValue(10,15,10),\n","#             A.CLAHE(clip_limit=2),\n","#             A.RandomBrightnessContrast(),            \n","#         ], p=0.3),\n","#     ], p=p)"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011396,"end_time":"2022-08-23T14:58:05.816121","exception":false,"start_time":"2022-08-23T14:58:05.804725","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"augmentations\"><center>Augmentations</center></h3>"]},{"cell_type":"code","execution_count":7,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:56.737064Z","iopub.status.busy":"2022-08-29T15:01:56.736735Z","iopub.status.idle":"2022-08-29T15:01:56.761232Z","shell.execute_reply":"2022-08-29T15:01:56.760066Z","shell.execute_reply.started":"2022-08-29T15:01:56.737031Z"},"papermill":{"duration":0.036226,"end_time":"2022-08-23T14:58:05.864035","exception":false,"start_time":"2022-08-23T14:58:05.827809","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def do_random_flip(image, mask):\n","    if np.random.rand()>0.5:\n","        image = cv2.flip(image,0)\n","        mask = cv2.flip(mask,0)\n","    if np.random.rand()>0.5:\n","        image = cv2.flip(image,1)\n","        mask = cv2.flip(mask,1)\n","    if np.random.rand()>0.5:\n","        image = image.transpose(1,0,2)\n","        mask = mask.transpose(1,0)\n","    \n","    image = np.ascontiguousarray(image)\n","    mask = np.ascontiguousarray(mask)\n","    return image, mask\n","\n","def do_random_rot90(image, mask):\n","    r = np.random.choice([\n","        0,\n","        cv2.ROTATE_90_CLOCKWISE,\n","        cv2.ROTATE_90_COUNTERCLOCKWISE,\n","        cv2.ROTATE_180,\n","    ])\n","    if r==0:\n","        return image, mask\n","    else:\n","        image = cv2.rotate(image, r)\n","        mask = cv2.rotate(mask, r)\n","        return image, mask\n","    \n","def do_random_contast(image, mask, mag=0.3):\n","    alpha = 1 + random.uniform(-1,1)*mag\n","    image = image * alpha\n","    image = np.clip(image,0,1)\n","    return image, mask\n","\n","def do_random_hsv(image, mask, mag=[0.15,0.25,0.25]):\n","    image = (image*255).astype(np.uint8)\n","    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)\n","\n","    h = hsv[:, :, 0].astype(np.float32)  # hue\n","    s = hsv[:, :, 1].astype(np.float32)  # saturation\n","    v = hsv[:, :, 2].astype(np.float32)  # value\n","    h = (h*(1 + random.uniform(-1,1)*mag[0]))%180\n","    s =  s*(1 + random.uniform(-1,1)*mag[1])\n","    v =  v*(1 + random.uniform(-1,1)*mag[2])\n","\n","    hsv[:, :, 0] = np.clip(h,0,180).astype(np.uint8)\n","    hsv[:, :, 1] = np.clip(s,0,255).astype(np.uint8)\n","    hsv[:, :, 2] = np.clip(v,0,255).astype(np.uint8)\n","    image = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)\n","    image = image.astype(np.float32)/255\n","    return image, mask\n","\n","def do_random_noise(image, mask, mag=0.1):\n","    height, width = image.shape[:2]\n","    noise = np.random.uniform(-1,1, (height, width,1))*mag\n","    image = image + noise\n","    image = np.clip(image,0,1)\n","    return image, mask\n","\n","def do_random_rotate_scale(image, mask, angle=30, scale=[0.8,1.2] ):\n","    angle = np.random.uniform(-angle, angle)\n","    scale = np.random.uniform(*scale) if scale is not None else 1\n","    \n","    height, width = image.shape[:2]\n","    center = (height // 2, width // 2)\n","    \n","    transform = cv2.getRotationMatrix2D(center, angle, scale)\n","    image = cv2.warpAffine( image, transform, (width, height), flags=cv2.INTER_LINEAR,\n","                            borderMode=cv2.BORDER_CONSTANT, borderValue=(0,0,0))\n","    mask  = cv2.warpAffine( mask, transform, (width, height), flags=cv2.INTER_LINEAR,\n","                            borderMode=cv2.BORDER_CONSTANT, borderValue=0)\n","    return image, mask\n","\n","import matplotlib.pyplot as plt\n","def cutout_custom(image, mask, alpha=0.05):\n","    x=int(alpha*image.shape[0])\n","    y=int(alpha*image.shape[1])\n","    ctr_list = []\n","    for i in range(10):\n","        ctr_list.append(np.random.randint(0,image.shape[0],size=(2)))\n","    cut_image=np.copy(image)\n","    cut_mask=np.copy(mask)\n","    for center in ctr_list:\n","        cut_image[center[0]-x//2:center[0]+x//2,center[1]-y//2:center[1]+y//2,:]=0\n","        cut_mask[center[0]-x//2:center[0]+x//2,center[1]-y//2:center[1]+y//2]=0\n","    return cut_image, cut_mask\n","# img = cv2.cvtColor(tifffile.imread(\"/home/lakshita/somusan/hubmap_kaggle/hubmap_data/hubmap-organ-segmentation/train_images/127.tiff\"), cv2.COLOR_BGR2RGB)\n","# msk = cv2.imread(\"/home/lakshita/somusan/hubmap_kaggle/hubmap_data/mask_png/train_binary_masks/127.png\", 0)\n","# img_, msk_ = cutout_custom(img,msk)\n","# plt.figure(figsize=(8,10))\n","# plt.subplot(2,2,1)\n","# plt.imshow(img_)\n","# plt.subplot(2,2,2)\n","# plt.imshow(msk_)\n","\n","# plt.subplot(2,2,3)\n","# plt.imshow(img)\n","# plt.subplot(2,2,4)\n","# plt.imshow(msk)\n","# plt.show()"]},{"cell_type":"code","execution_count":8,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:56.764598Z","iopub.status.busy":"2022-08-29T15:01:56.764278Z","iopub.status.idle":"2022-08-29T15:01:56.779172Z","shell.execute_reply":"2022-08-29T15:01:56.777835Z","shell.execute_reply.started":"2022-08-29T15:01:56.764565Z"},"trusted":true},"outputs":[],"source":["import torch\n","import numpy as np\n","\n","\n","def rand_bbox(size, lam):\n","    \"\"\"\n","    Retuns the coordinate of a random rectangle in the image for cutmix.\n","\n","    Args:\n","        size (torch tensor [batch_size x c x W x H): Input size.\n","        lam (int): Lambda sampled by the beta distribution. Controls the size of the squares.\n","\n","    Returns:\n","        int: 4 coordinates of the rectangle.\n","        int: Proportion of the unmasked image.\n","    \"\"\"\n","    W = size[2]\n","    H = size[3]\n","    cut_rat = np.sqrt(1.0 - lam)\n","    cut_w = np.int(W * cut_rat)\n","    cut_h = np.int(H * cut_rat)\n","\n","    # uniform\n","    cx = np.random.randint(W)\n","    cy = np.random.randint(H)\n","\n","    bbx1 = np.clip(cx - cut_w // 2, 0, W)\n","    bby1 = np.clip(cy - cut_h // 2, 0, H)\n","    bbx2 = np.clip(cx + cut_w // 2, 0, W)\n","    bby2 = np.clip(cy + cut_h // 2, 0, H)\n","\n","    lam = 1 - ((bbx2 - bbx1) * (bby2 - bby1) / (W * H))\n","    return bbx1, bby1, bbx2, bby2, lam\n","\n","\n","def cutmix_data(x, y, alpha=1.0, device=\"cuda\"):\n","    \"\"\"\n","    Applies cutmix to a sample\n","\n","    Args:\n","        x (torch tensor [batch_size x input_size]): Input batch.\n","        y (torch tensor [batch_size x num_classes]): Labels.\n","        alpha (float, optional): Parameter of the beta distribution. Defaults to 1..\n","        device (str, optional): Device for torch. Defaults to \"cuda\".\n","\n","    Returns:\n","        torch tensor [batch_size x input_size]: Mixed input.\n","        torch tensor [batch_size x num_classes]: Mixed labels.\n","        float: Probability sampled by the beta distribution.\n","    \"\"\"\n","    lam = np.random.beta(alpha, alpha) if alpha > 0 else 1\n","\n","    index = torch.randperm(x.size()[0]).to(device)\n","\n","    bbx1, bby1, bbx2, bby2, lam = rand_bbox(x.size(), lam)\n","\n","    mixed_x = x.clone()\n","    mixed_y = y.clone()\n","\n","    mixed_x[:, :, bbx1:bbx2, bby1:bby2] = x[index, :, bbx1:bbx2, bby1:bby2]\n","    mixed_y[:, bbx1:bbx2, bby1:bby2] = y[index, bbx1:bbx2, bby1:bby2]\n","\n","    return mixed_x, mixed_y"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011062,"end_time":"2022-08-23T14:58:05.886508","exception":false,"start_time":"2022-08-23T14:58:05.875446","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"dataset\"><center>Dataset</center></h3>"]},{"cell_type":"code","execution_count":9,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:56.782654Z","iopub.status.busy":"2022-08-29T15:01:56.781947Z","iopub.status.idle":"2022-08-29T15:01:56.792525Z","shell.execute_reply":"2022-08-29T15:01:56.791513Z","shell.execute_reply.started":"2022-08-29T15:01:56.782617Z"},"papermill":{"duration":0.025808,"end_time":"2022-08-23T14:58:05.923760","exception":false,"start_time":"2022-08-23T14:58:05.897952","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def rle_decode(mask_rle, shape):\n","    '''\n","    mask_rle: run-length as string formated (start length)\n","    shape: (height,width) of array to return \n","    Returns numpy array, 1 - mask, 0 - background\n","\n","    '''\n","    s = mask_rle.split()\n","    starts, lengths = [np.asarray(x, dtype=int) for x in (s[0:][::2], s[1:][::2])]\n","    starts -= 1\n","    ends = starts + lengths\n","    img = np.zeros(shape[0]*shape[1], dtype=np.uint8)\n","    for lo, hi in zip(starts, ends):\n","        img[lo:hi] = 1\n","    return img.reshape(shape).T  # Needed to align to RLE direction\n","\n","\n","# ref.: https://www.kaggle.com/stainsby/fast-tested-rle\n","def rle_encode(img):\n","    '''\n","    img: numpy array, 1 - mask, 0 - background\n","    Returns run length as string formated\n","    '''\n","    pixels = img.flatten()\n","    pixels = np.concatenate([[0], pixels, [0]])\n","    runs = np.where(pixels[1:] != pixels[:-1])[0] + 1\n","    runs[1::2] -= runs[::2]\n","    return ' '.join(str(x) for x in runs)"]},{"cell_type":"code","execution_count":10,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:56.798624Z","iopub.status.busy":"2022-08-29T15:01:56.797895Z","iopub.status.idle":"2022-08-29T15:01:56.813027Z","shell.execute_reply":"2022-08-29T15:01:56.811848Z","shell.execute_reply.started":"2022-08-29T15:01:56.798588Z"},"papermill":{"duration":0.030346,"end_time":"2022-08-23T14:58:05.965164","exception":false,"start_time":"2022-08-23T14:58:05.934818","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["image_size = 512 #768\n","\n","class HubmapDataset(Dataset):\n","    def __init__(self, df, augment=None):\n","\n","        self.df = df\n","        self.augment = augment\n","        self.length = len(self.df)\n","#         ids = pd.read_csv(LABELS).id.astype(str).values\n","#         self.fnames = [fname for fname in os.listdir(TRAIN) if fname.split('_')[0] in ids]\n","        self.organ_to_label = {'kidney' : 0,\n","                               'prostate' : 1,\n","                               'largeintestine' : 2,\n","                               'spleen' : 3,\n","                               'lung' : 4}\n","\n","    def __str__(self):\n","        string = ''\n","        string += '\\tlen = %d\\n' % len(self)\n","\n","        d = self.df.organ.value_counts().to_dict()\n","        for k in ['kidney', 'prostate', 'largeintestine', 'spleen', 'lung']:\n","            string +=  '%24s %3d (%0.3f) \\n'%(k,d.get(k,0),d.get(k,0)/len(self.df))\n","        return string\n","\n","    def __len__(self):\n","        return self.length\n","\n","    def __getitem__(self, index):\n","        #fname = self.fnames[index]\n","        #img_id = self.df.iloc[index, 'id']\n","        d = self.df.iloc[index]\n","        img_height = self.df.loc[index, 'img_height']\n","        img_width = self.df.loc[index, 'img_width']\n","        organ = self.organ_to_label[d.organ]\n","#\n","        # image = cv2.cvtColor(tifffile.imread(os.path.join(TRAIN, f'{d.id}.tiff')), cv2.COLOR_BGR2RGB)\n","#         print(os.path.join(TRAIN , f'{d.id}.png'))\n","        image = cv2.imread(os.path.join(TRAIN , f'{d.id}.png'), cv2.COLOR_BGR2RGB)\n","        \n","        rle_mask = self.df.loc[index, 'rle']\n","        mask = rle_decode(rle_mask, (img_height, img_width))\n","        #mask = cv2.cvtColor(mask, cv2.IMREAD_GRAYSCALE)\n","        #mask = cv2.imread(os.path.join(MASKS,fname),cv2.IMREAD_GRAYSCALE)\n","        mask = np.expand_dims(mask, axis = 2)\n","        #print(mask.shape)\n","        \n","        image = image.astype(np.float32)/255\n","        #mask  = mask.astype(np.float32)/255\n","        mask = mask.astype(np.float32)\n","\n","        s = d.pixel_size/0.4 * (image_size/3000)\n","        image = cv2.resize(image,dsize=(image_size,image_size),interpolation=cv2.INTER_LINEAR)\n","        mask  = cv2.resize(mask, dsize=(image_size,image_size),interpolation=cv2.INTER_LINEAR)\n","        # print(image.shape, mask.shape)\n","        if self.augment is not None:\n","            # print(image.shape, mask.shape)\n","            image, mask = self.augment(image, mask, organ)\n","\n","\n","        r ={}\n","        r[\"id\"] = d.id\n","        r['index']= index\n","        r['organ'] = torch.tensor([organ], dtype=torch.long)\n","        r['image'] = image_to_tensor(image)\n","        r['mask' ] = mask_to_tensor(mask)\n","        return r"]},{"cell_type":"code","execution_count":11,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:56.814568Z","iopub.status.busy":"2022-08-29T15:01:56.814284Z","iopub.status.idle":"2022-08-29T15:01:57.823215Z","shell.execute_reply":"2022-08-29T15:01:57.822229Z","shell.execute_reply.started":"2022-08-29T15:01:56.814524Z"},"papermill":{"duration":0.019209,"end_time":"2022-08-23T14:58:05.995705","exception":false,"start_time":"2022-08-23T14:58:05.976496","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["df = pd.read_csv('/home/lakshita/somusan/hubmap_kaggle/hubmap_data/hubmap-organ-segmentation/train.csv')\n","ds = HubmapDataset(df)\n","# plt.imshow(ds[0][\"image\"].permute(1,2,0).detach().numpy()) #(512, 512, 3) (512, 512)\n","# ds[0][\"image\"]"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011168,"end_time":"2022-08-23T14:58:06.018030","exception":false,"start_time":"2022-08-23T14:58:06.006862","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"patching\"><center>Image Patching</center></h3>"]},{"cell_type":"code","execution_count":12,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:57.825051Z","iopub.status.busy":"2022-08-29T15:01:57.824683Z","iopub.status.idle":"2022-08-29T15:01:57.841960Z","shell.execute_reply":"2022-08-29T15:01:57.840996Z","shell.execute_reply.started":"2022-08-29T15:01:57.825014Z"},"papermill":{"duration":0.034976,"end_time":"2022-08-23T14:58:06.064554","exception":false,"start_time":"2022-08-23T14:58:06.029578","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class PatchEmbed(nn.Module):\n","    r\"\"\" Image to Patch Embedding\n","\n","    Args:\n","        patch_size (int): Patch token size. Default: 4.\n","        in_chans (int): Number of input image channels. Default: 3.\n","        embed_dim (int): Number of linear projection output channels. Default: 96.\n","        norm_layer (nn.Module, optional): Normalization layer. Default: None\n","    \"\"\"\n","    def __init__(self,\n","                 patch_size=4,\n","                 in_chans=3,\n","                 embed_dim=96,\n","                 norm_layer=None\n","                 ):\n","        super().__init__()\n","        patch_size = to_2tuple(patch_size)\n","        self.patch_size = patch_size\n","\n","        self.in_chans = in_chans\n","        self.embed_dim = embed_dim\n","\n","        self.proj = nn.Conv2d(in_chans, embed_dim, kernel_size=patch_size, stride=patch_size)\n","        if norm_layer is not None:\n","            self.norm = norm_layer(embed_dim)\n","        else:\n","            self.norm = None\n","\n","    def forward(self, x):\n","        B, C, H, W = x.shape\n","\n","        # padding\n","        if W % self.patch_size[1] != 0:\n","            x = F.pad(x, (0, self.patch_size[1] - W % self.patch_size[1]))\n","        if H % self.patch_size[0] != 0:\n","            x = F.pad(x, (0, 0, 0, self.patch_size[0] - H % self.patch_size[0]))\n","\n","\n","        x = self.proj(x)  # B C Wh Ww\n","        if self.norm is not None:\n","            Wh, Ww = x.size(2), x.size(3)\n","            x = x.flatten(2).transpose(1, 2)\n","            x = self.norm(x)\n","            x = x.transpose(1, 2).view(-1, self.embed_dim, Wh, Ww)\n","\n","        return x\n","    \n","class PatchMerging(nn.Module):\n","    r\"\"\" Patch Merging Layer.\n","\n","    Args:\n","        dim (int): Number of input channels.\n","        norm_layer (nn.Module, optional): Normalization layer.  Default: nn.LayerNorm\n","    \"\"\"\n","\n","    def __init__(self, dim, norm_layer=nn.LayerNorm):\n","        super().__init__()\n","        self.dim = dim\n","        self.reduction = nn.Linear(4 * dim, 2 * dim, bias=False)\n","        self.norm = norm_layer(4 * dim)\n","\n","    def forward(self, x, H, W):\n","        \"\"\"\n","        Args:\n","            x: Input feature, tensor size (B, H*W, C).\n","            H, W: Spatial resolution of the input feature.\n","        \"\"\"\n","\n","        B, L, C = x.shape\n","        assert L == H * W, \"input feature has wrong size\"\n","\n","\n","        x = x.view(B, H, W, C)\n","        # padding\n","        pad_input = (H % 2 == 1) or (W % 2 == 1)\n","        if pad_input:\n","            x = F.pad(x, (0, 0, 0, W % 2, 0, H % 2))\n","\n","        x0 = x[:, 0::2, 0::2, :]  # B H/2 W/2 C\n","        x1 = x[:, 1::2, 0::2, :]  # B H/2 W/2 C\n","        x2 = x[:, 0::2, 1::2, :]  # B H/2 W/2 C\n","        x3 = x[:, 1::2, 1::2, :]  # B H/2 W/2 C\n","        x = torch.cat([x0, x1, x2, x3], -1)  # B, H/2, W/2, 4*C\n","        x = x.view(B, -1, 4 * C)  # B, H/2*W/2, 4*C\n","\n","        x = self.norm(x)\n","        x = self.reduction(x)\n","\n","        return x"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011676,"end_time":"2022-08-23T14:58:06.088402","exception":false,"start_time":"2022-08-23T14:58:06.076726","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"swin\"><center>Swin Transformer</center></h3>"]},{"cell_type":"code","execution_count":13,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:57.844634Z","iopub.status.busy":"2022-08-29T15:01:57.843481Z","iopub.status.idle":"2022-08-29T15:01:57.862691Z","shell.execute_reply":"2022-08-29T15:01:57.861700Z","shell.execute_reply.started":"2022-08-29T15:01:57.844596Z"},"papermill":{"duration":0.033676,"end_time":"2022-08-23T14:58:06.133739","exception":false,"start_time":"2022-08-23T14:58:06.100063","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class BasicLayer(nn.Module):\n","    \"\"\" A basic Swin Transformer layer for one stage.\n","\n","    Args:\n","        dim (int): Number of input channels.\n","        depth (int): Number of blocks.\n","        num_heads (int): Number of attention heads.\n","        window_size (int): Local window size.\n","        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim.\n","        qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True\n","        qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set.\n","        drop (float, optional): Dropout rate. Default: 0.0\n","        attn_drop (float, optional): Attention dropout rate. Default: 0.0\n","        drop_path (float | tuple[float], optional): Stochastic depth rate. Default: 0.0\n","        norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm\n","        downsample (nn.Module | None, optional): Downsample layer at the end of the layer. Default: None\n","        use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False.\n","        fused_window_process (bool, optional): If True, use one kernel to fused window shift & window partition for acceleration, similar for the reversed part. Default: False\n","    \"\"\"\n","    def __init__(self,\n","        dim,\n","        depth,\n","        num_heads,\n","        window_size,\n","        mlp_ratio=4.,\n","        qkv_bias=True,\n","        qk_scale=None,\n","        drop=0.,\n","        attn_drop=0.,\n","        drop_path=0.,\n","        norm_layer=nn.LayerNorm,\n","        downsample=None,\n","        #use_checkpoint=False,\n","    ):\n","        super().__init__()\n","        self.window_size = window_size\n","        self.shift_size = window_size // 2\n","        self.depth = depth\n","\n","        self.blocks = nn.ModuleList([\n","            SwinTransformerBlock(\n","                dim=dim,\n","                num_heads=num_heads,\n","                window_size=window_size,\n","                shift_size=0 if (i % 2 == 0) else window_size // 2,\n","                mlp_ratio=mlp_ratio,\n","                qkv_bias=qkv_bias,\n","                qk_scale=qk_scale,\n","                drop=drop,\n","                attn_drop=attn_drop,\n","                drop_path=drop_path[i] if isinstance(drop_path, list) else drop_path,\n","                norm_layer=norm_layer,\n","            )\n","            for i in range(depth)\n","        ])\n","        # patch merging layer\n","        if downsample is not None:\n","            self.downsample = downsample(dim=dim, norm_layer=norm_layer)\n","        else:\n","            self.downsample = None\n","\n","    def forward(self, x, H, W):\n","        \"\"\"\n","        Args:\n","            x: Input feature, tensor size (B, H*W, C).\n","            H, W: Spatial resolution of the input feature.\n","        \"\"\"\n","\n","        # calculate attention mask for SW-MSA ----\n","        Hp = int(np.ceil(H / self.window_size)) * self.window_size\n","        Wp = int(np.ceil(W / self.window_size)) * self.window_size\n","        img_mask = torch.zeros((1, Hp, Wp, 1), device=x.device)  # 1 Hp Wp 1\n","        h_slices = (slice(0, -self.window_size),\n","                    slice(-self.window_size, -self.shift_size),\n","                    slice(-self.shift_size, None))\n","        w_slices = (slice(0, -self.window_size),\n","                    slice(-self.window_size, -self.shift_size),\n","                    slice(-self.shift_size, None))\n","        cnt = 0\n","        for h in h_slices:\n","            for w in w_slices:\n","                img_mask[:, h, w, :] = cnt\n","                cnt += 1\n","\n","        mask_windows = window_partition(img_mask, self.window_size)  # nW, window_size, window_size, 1\n","        mask_windows = mask_windows.view(-1, self.window_size * self.window_size)\n","        attn_mask = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2)\n","        attn_mask = attn_mask.masked_fill(attn_mask != 0, float(-100.0)).masked_fill(attn_mask == 0, float(0.0))\n","        #------\n","\n","\n","        for blk in self.blocks:\n","            x = blk(x, H, W, attn_mask)\n","\n","        if self.downsample is not None:\n","            x_down = self.downsample(x, H, W)\n","            Wh, Ww = (H + 1) // 2, (W + 1) // 2\n","            return x, H, W, x_down, Wh, Ww\n","        else:\n","            return x, H, W, x, H, W"]},{"cell_type":"code","execution_count":14,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:57.865252Z","iopub.status.busy":"2022-08-29T15:01:57.864577Z","iopub.status.idle":"2022-08-29T15:01:57.884220Z","shell.execute_reply":"2022-08-29T15:01:57.883057Z","shell.execute_reply.started":"2022-08-29T15:01:57.865163Z"},"papermill":{"duration":0.034771,"end_time":"2022-08-23T14:58:06.179868","exception":false,"start_time":"2022-08-23T14:58:06.145097","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class SwinTransformerBlock(nn.Module):\n","    r\"\"\" Swin Transformer Block.\n","\n","    Args:\n","        dim (int): Number of input channels.\n","        input_resolution (tuple[int]): Input resulotion.\n","        num_heads (int): Number of attention heads.\n","        window_size (int): Window size.\n","        shift_size (int): Shift size for SW-MSA.\n","        mlp_ratio (float): Ratio of mlp hidden dim to embedding dim.\n","        qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True\n","        qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set.\n","        drop (float, optional): Dropout rate. Default: 0.0\n","        attn_drop (float, optional): Attention dropout rate. Default: 0.0\n","        drop_path (float, optional): Stochastic depth rate. Default: 0.0\n","        act_layer (nn.Module, optional): Activation layer. Default: nn.GELU\n","        norm_layer (nn.Module, optional): Normalization layer.  Default: nn.LayerNorm\n","        fused_window_process (bool, optional): If True, use one kernel to fused window shift & window partition for acceleration, similar for the reversed part. Default: False\n","    \"\"\"\n","    def __init__(self,\n","        dim,\n","        num_heads,\n","        window_size=7,\n","        shift_size=0,\n","        mlp_ratio=4.,\n","        qkv_bias=True,\n","        qk_scale=None,\n","        drop=0.,\n","        attn_drop=0.,\n","        drop_path=0.,\n","        act_layer=nn.GELU,\n","        norm_layer=nn.LayerNorm,\n","    ):\n","        super().__init__()\n","        self.dim = dim\n","        self.num_heads = num_heads\n","        self.window_size = window_size\n","        self.shift_size = shift_size\n","        self.mlp_ratio = mlp_ratio\n","        assert 0 <= self.shift_size < self.window_size, \"shift_size must in 0-window_size\"\n","\n","        self.norm1 = norm_layer(dim)\n","        self.attn = WindowAttention(\n","            dim,\n","            window_size=to_2tuple(self.window_size),\n","            num_heads=num_heads,\n","            qkv_bias=qkv_bias,\n","            qk_scale=qk_scale,\n","            attn_drop=attn_drop,\n","            proj_drop=drop,\n","        )\n","        self.drop_path = DropPath(drop_path) if drop_path > 0. else nn.Identity()\n","\n","        self.norm2 = norm_layer(dim)\n","        mlp_hidden_dim = int(dim * mlp_ratio)\n","        self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim, act_layer=act_layer, drop=drop)\n","\n","\n","    def forward(self, x, H, W, mask_matrix):\n","\n","        B, L, C = x.shape\n","        assert L == H * W, \"input feature has wrong size\"\n","\n","        shortcut = x\n","        x = self.norm1(x)\n","        x = x.view(B, H, W, C)\n","\n","        # pad feature maps to multiples of window size\n","        pad_l = pad_t = 0\n","        pad_r = (self.window_size - W % self.window_size) % self.window_size\n","        pad_b = (self.window_size - H % self.window_size) % self.window_size\n","        x = F.pad(x, (0, 0, pad_l, pad_r, pad_t, pad_b))\n","        _, Hp, Wp, _ = x.shape\n","\n","\n","        # cyclic shift ---\n","        if self.shift_size > 0:\n","            shifted_x = torch.roll(x, shifts=(-self.shift_size, -self.shift_size), dims=(1, 2))\n","            attn_mask = mask_matrix\n","        else:\n","            shifted_x = x\n","            attn_mask = None\n","\n","        x_windows = window_partition(shifted_x, self.window_size)  # nW*B, window_size, window_size, C\n","        x_windows = x_windows.view(-1, self.window_size * self.window_size, C)  # nW*B, window_size*window_size, C\n","        attn_windows = self.attn(x_windows, mask=attn_mask)  # nW*B, window_size*window_size, C\n","        attn_windows = attn_windows.view(-1, self.window_size, self.window_size, C)\n","\n","\n","        # reverse cyclic shift ---\n","        shifted_x = window_reverse(attn_windows, self.window_size, Hp, Wp)  # B H' W' C\n","        if self.shift_size > 0:\n","            x = torch.roll(shifted_x, shifts=(self.shift_size, self.shift_size), dims=(1, 2))\n","        else:\n","            x = shifted_x\n","\n","        if pad_r > 0 or pad_b > 0:\n","            x = x[:, :H, :W, :].contiguous()\n","        x = x.view(B, H * W, C)\n","\n","        # FFN\n","        x = shortcut + self.drop_path(x)\n","        x = x + self.drop_path(self.mlp(self.norm2(x)))\n","        return x\n","\n","    def extra_repr(self) -> str:\n","        return f\"dim={self.dim}, num_heads={self.num_heads}, \" \\\n","               f\"window_size={self.window_size}, shift_size={self.shift_size}, mlp_ratio={self.mlp_ratio}\""]},{"cell_type":"code","execution_count":15,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:57.888092Z","iopub.status.busy":"2022-08-29T15:01:57.887816Z","iopub.status.idle":"2022-08-29T15:01:57.905706Z","shell.execute_reply":"2022-08-29T15:01:57.904738Z","shell.execute_reply.started":"2022-08-29T15:01:57.888066Z"},"papermill":{"duration":0.034141,"end_time":"2022-08-23T14:58:06.225181","exception":false,"start_time":"2022-08-23T14:58:06.191040","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class SwinTransformerV1(nn.Module):\n","    def __init__(self,\n","        pretrain_img_size=224,\n","        patch_size=4,\n","        in_chans=3,\n","        embed_dim=96,\n","        depths=[2, 2, 6, 2],\n","        num_heads=[3, 6, 12, 24],\n","        window_size=7,\n","        mlp_ratio=4.,\n","        qkv_bias=True,\n","        qk_scale=None,\n","        drop_rate=0.,\n","        attn_drop_rate=0.,\n","        drop_path_rate=0.1,\n","        norm_layer=nn.LayerNorm,\n","        patch_norm=True,\n","        out_norm = nn.Identity, #use nn.Identity, nn.BatchNorm2d, LayerNorm2d\n","        **kwargs\n","    ):\n","        super().__init__()\n","        self.pretrain_img_size = pretrain_img_size\n","        self.num_layers = len(depths)\n","        self.embed_dim = embed_dim\n","        self.mlp_ratio = mlp_ratio\n","\n","\n","        self.patch_embed = PatchEmbed(\n","            patch_size=patch_size,\n","            in_chans=in_chans,\n","            embed_dim=embed_dim,\n","            norm_layer=norm_layer if patch_norm else None\n","        )\n","        self.pos_drop = nn.Dropout(p=drop_rate)\n","\n","        # stochastic depth\n","        dpr = np.linspace(0, drop_path_rate, sum(depths)).tolist() # stochastic depth decay rule\n","\n","        # build layers\n","        self.layers = nn.ModuleList()\n","        for i in range(self.num_layers):\n","            layer = BasicLayer(\n","                dim=int(embed_dim * 2 ** i),\n","                depth=depths[i],\n","                num_heads=num_heads[i],\n","                window_size=window_size,\n","                mlp_ratio=self.mlp_ratio,\n","                qkv_bias=qkv_bias, qk_scale=qk_scale,\n","                drop=drop_rate,\n","                attn_drop=attn_drop_rate,\n","                drop_path=dpr[sum(depths[:i]):sum(depths[:i + 1])],\n","                norm_layer=norm_layer,\n","                downsample=PatchMerging if (i < self.num_layers - 1) else None,\n","            )\n","            self.layers.append(layer)\n","\n","        #---\n","        # add a norm layer for each output\n","        self.out_norm = nn.ModuleList(\n","            [ out_norm(int(embed_dim * 2 ** i)) for i in range(self.num_layers)]\n","        )\n","\n","        #---\n","        self.apply(self._init_weights)\n","\n","\n","    def _init_weights(self, m):\n","        if isinstance(m, nn.Linear):\n","            trunc_normal_(m.weight, std=.02)\n","            if isinstance(m, nn.Linear) and m.bias is not None:\n","                nn.init.constant_(m.bias, 0)\n","        elif isinstance(m, nn.LayerNorm):\n","            nn.init.constant_(m.bias, 0)\n","            nn.init.constant_(m.weight, 1.0)\n","\n","\n","    def forward(self, x):\n","        x = self.patch_embed(x)\n","        Wh, Ww = x.size(2), x.size(3)\n","\n","        #positional encode?\n","        x = x.flatten(2).transpose(1, 2)\n","        x = self.pos_drop(x)\n","\n","        outs = []\n","        for i in range(self.num_layers):\n","            x_out, H, W, x, Wh, Ww = self.layers[i](x, Wh, Ww)\n","            out = x_out.view(-1, H, W, int(self.embed_dim * 2 ** i)).permute(0, 3, 1, 2).contiguous()\n","            out = self.out_norm[i](out)\n","            outs.append(out)\n","\n","        return outs"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011276,"end_time":"2022-08-23T14:58:06.247565","exception":false,"start_time":"2022-08-23T14:58:06.236289","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"window\"><center>Window functionalities</center></h3>"]},{"cell_type":"code","execution_count":16,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:57.909429Z","iopub.status.busy":"2022-08-29T15:01:57.909092Z","iopub.status.idle":"2022-08-29T15:01:57.933903Z","shell.execute_reply":"2022-08-29T15:01:57.932690Z","shell.execute_reply.started":"2022-08-29T15:01:57.909400Z"},"papermill":{"duration":0.040248,"end_time":"2022-08-23T14:58:06.299443","exception":false,"start_time":"2022-08-23T14:58:06.259195","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class WindowAttention(nn.Module):\n","    r\"\"\" Window based multi-head self attention (W-MSA) module with relative position bias.\n","    It supports both of shifted and non-shifted window.\n","\n","    Args:\n","        dim (int): Number of input channels.\n","        window_size (tuple[int]): The height and width of the window.\n","        num_heads (int): Number of attention heads.\n","        qkv_bias (bool, optional):  If True, add a learnable bias to query, key, value. Default: True\n","        qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set\n","        attn_drop (float, optional): Dropout ratio of attention weight. Default: 0.0\n","        proj_drop (float, optional): Dropout ratio of output. Default: 0.0\n","    \"\"\"\n","    def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scale=None, attn_drop=0., proj_drop=0.):\n","        super().__init__()\n","        self.dim = dim\n","        self.window_size = window_size  # Wh, Ww\n","        self.num_heads = num_heads\n","        head_dim = dim // num_heads\n","        self.scale = qk_scale or head_dim ** (-0.5)\n","\n","        # define a parameter table of relative position bias\n","        self.relative_position_bias_table = nn.Parameter(\n","            torch.zeros((2 * window_size[0] - 1) * (2 * window_size[1] - 1), num_heads))  # 2*Wh-1 * 2*Ww-1, nH\n","\n","        # get pair-wise relative position index for each token inside the window\n","        coords_h = torch.arange(self.window_size[0])\n","        coords_w = torch.arange(self.window_size[1])\n","        coords = torch.stack(torch.meshgrid([coords_h, coords_w]))  # 2, Wh, Ww\n","        coords_flatten = torch.flatten(coords, 1)  # 2, Wh*Ww\n","        relative_coords = coords_flatten[:, :, None] - coords_flatten[:, None, :]  # 2, Wh*Ww, Wh*Ww\n","        relative_coords = relative_coords.permute(1, 2, 0).contiguous()  # Wh*Ww, Wh*Ww, 2\n","        relative_coords[:, :, 0] += self.window_size[0] - 1  # shift to start from 0\n","        relative_coords[:, :, 1] += self.window_size[1] - 1\n","        relative_coords[:, :, 0] *= 2 * self.window_size[1] - 1\n","        relative_position_index = relative_coords.sum(-1)  # Wh*Ww, Wh*Ww\n","        self.register_buffer(\"relative_position_index\", relative_position_index)\n","\n","        self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias)\n","        self.proj = nn.Linear(dim, dim)\n","        self.softmax = nn.Softmax(dim=-1)\n","\n","        self.attn_drop = nn.Dropout(attn_drop)\n","        self.proj_drop = nn.Dropout(proj_drop)\n","\n","        trunc_normal_(self.relative_position_bias_table, std=.02)\n","\n","\n","    def forward(self, x, mask=None):\n","        \"\"\"\n","        Args:\n","            x: input features with shape of (num_windows*B, N, C)\n","            mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None\n","        \"\"\"\n","\n","        B_, N, C = x.shape\n","        qkv = self.qkv(x).reshape(B_, N, 3, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4)\n","        q, k, v = qkv[0], qkv[1], qkv[2]  # make torchscript happy (cannot use tensor as tuple)\n","\n","        q = q * self.scale\n","        attn = (q @ k.transpose(-2, -1))\n","\n","        relative_position_bias = \\\n","            self.relative_position_bias_table[self.relative_position_index.view(-1)].view(\n","            self.window_size[0] * self.window_size[1], self.window_size[0] * self.window_size[1], self.num_heads)\n","            # Wh*Ww,Wh*Ww,nH\n","        relative_position_bias = relative_position_bias.permute(2, 0, 1).contiguous()  # nH, Wh*Ww, Wh*Ww\n","\n","        attn = attn + relative_position_bias.unsqueeze(0)\n","\n","\n","        if mask is not None:\n","            nW = mask.shape[0]\n","            attn = attn.view(B_ // nW, nW, self.num_heads, N, N) + mask.unsqueeze(1).unsqueeze(0)\n","            attn = attn.view(-1, self.num_heads, N, N)\n","            attn = self.softmax(attn)\n","        else:\n","            attn = self.softmax(attn)\n","\n","        attn = self.attn_drop(attn)\n","        x = (attn @ v).transpose(1, 2).reshape(B_, N, C)\n","        x = self.proj(x)\n","        x = self.proj_drop(x)\n","        return x\n","\n","    def extra_repr(self) -> str:\n","        return f'dim={self.dim}, window_size={self.window_size}, num_heads={self.num_heads}'\n","    \n","    \n","def window_partition(x, window_size):\n","    \"\"\"\n","    Args:\n","        x: (B, H, W, C)\n","        window_size (int): window size\n","\n","    Returns:\n","        windows: (num_windows*B, window_size, window_size, C)\n","    \"\"\"\n","    B, H, W, C = x.shape\n","    x = x.view(B, H // window_size, window_size, W // window_size, window_size, C)\n","    windows = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, window_size, window_size, C)\n","    return windows\n","\n","\n","def window_reverse(windows, window_size, H, W):\n","    \"\"\"\n","    Args:\n","        windows: (num_windows*B, window_size, window_size, C)\n","        window_size (int): Window size\n","        H (int): Height of image\n","        W (int): Width of image\n","\n","    Returns:\n","        x: (B, H, W, C)\n","    \"\"\"\n","    B = int(windows.shape[0] / (H * W / window_size / window_size))\n","    x = windows.view(B, H // window_size, W // window_size, window_size, window_size, -1)\n","    x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, H, W, -1)\n","    return x"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011032,"end_time":"2022-08-23T14:58:06.321641","exception":false,"start_time":"2022-08-23T14:58:06.310609","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"ann\"><center>Upnet + Net + MLP</center></h3>"]},{"cell_type":"code","execution_count":17,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:57.936511Z","iopub.status.busy":"2022-08-29T15:01:57.935737Z","iopub.status.idle":"2022-08-29T15:01:57.946634Z","shell.execute_reply":"2022-08-29T15:01:57.945573Z","shell.execute_reply.started":"2022-08-29T15:01:57.936465Z"},"papermill":{"duration":0.022841,"end_time":"2022-08-23T14:58:06.356284","exception":false,"start_time":"2022-08-23T14:58:06.333443","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def conv3x3_bn_relu(in_planes, out_planes, stride=1):\n","    \"3x3 convolution + BN + relu\"\n","    return nn.Sequential(\n","        nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False),\n","        nn.BatchNorm2d(out_planes),\n","        nn.ReLU(inplace=True),\n","    )"]},{"cell_type":"code","execution_count":18,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:57.950310Z","iopub.status.busy":"2022-08-29T15:01:57.949912Z","iopub.status.idle":"2022-08-29T15:01:57.967295Z","shell.execute_reply":"2022-08-29T15:01:57.966164Z","shell.execute_reply.started":"2022-08-29T15:01:57.950191Z"},"papermill":{"duration":0.034972,"end_time":"2022-08-23T14:58:06.402216","exception":false,"start_time":"2022-08-23T14:58:06.367244","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class UPerDecoder(nn.Module):\n","    def __init__(self,\n","        in_dim=[256, 512, 1024, 2048],\n","        ppm_pool_scale=[1, 2, 3, 6],\n","        ppm_dim=512,\n","        fpn_out_dim=256\n","    ):\n","        super(UPerDecoder, self).__init__()\n","\n","        # PPM ----\n","        dim = in_dim[-1]\n","        ppm_pooling = []\n","        ppm_conv = []\n","\n","        for scale in ppm_pool_scale:\n","            ppm_pooling.append(\n","                nn.AdaptiveAvgPool2d(scale)\n","            )\n","            ppm_conv.append(\n","                nn.Sequential(\n","                    nn.Conv2d(dim, ppm_dim, kernel_size=1, bias=False),\n","                    nn.BatchNorm2d(ppm_dim),\n","                    nn.ReLU(inplace=True)\n","                )\n","            )\n","        self.ppm_pooling   = nn.ModuleList(ppm_pooling)\n","        self.ppm_conv      = nn.ModuleList(ppm_conv)\n","        self.ppm_out = conv3x3_bn_relu(dim + len(ppm_pool_scale)*ppm_dim, fpn_out_dim, 1)\n","\n","        # FPN ----\n","        fpn_in = []\n","        for i in range(0, len(in_dim)-1):  # skip the top layer\n","            fpn_in.append(\n","                nn.Sequential(\n","                    nn.Conv2d(in_dim[i], fpn_out_dim, kernel_size=1, bias=False),\n","                    nn.BatchNorm2d(fpn_out_dim),\n","                    nn.ReLU(inplace=True)\n","                )\n","            )\n","        self.fpn_in = nn.ModuleList(fpn_in)\n","\n","        fpn_out = []\n","        for i in range(len(in_dim) - 1):  # skip the top layer\n","            fpn_out.append(\n","                conv3x3_bn_relu(fpn_out_dim, fpn_out_dim, 1),\n","            )\n","        self.fpn_out = nn.ModuleList(fpn_out)\n","\n","        self.fpn_fuse = nn.Sequential(\n","            conv3x3_bn_relu(len(in_dim) * fpn_out_dim, fpn_out_dim, 1),\n","        )\n","\n","    def forward(self, feature):\n","        f = feature[-1]\n","        pool_shape = f.shape[2:]\n","\n","        ppm_out = [f]\n","        for pool, conv in zip(self.ppm_pooling, self.ppm_conv):\n","            p = pool(f)\n","            p = F.interpolate(p, size=pool_shape, mode='bilinear', align_corners=False)\n","            p = conv(p)\n","            ppm_out.append(p)\n","        ppm_out = torch.cat(ppm_out, 1)\n","        down = self.ppm_out(ppm_out)\n","\n","        fpn_out = [down]\n","        for i in reversed(range(len(feature) - 1)):\n","            lateral = feature[i]\n","            lateral = self.fpn_in[i](lateral) # lateral branch\n","            down = F.interpolate(down, size=lateral.shape[2:], mode='bilinear', align_corners=False) # top-down branch\n","            down = down + lateral\n","            fpn_out.append(self.fpn_out[i](down))\n","\n","        fpn_out.reverse() # [P2 - P5]\n","        fusion_shape = fpn_out[0].shape[2:]\n","        fusion = [fpn_out[0]]\n","        for i in range(1, len(fpn_out)):\n","            fusion.append(\n","                F.interpolate( fpn_out[i], fusion_shape, mode='bilinear', align_corners=False)\n","            )\n","        x = self.fpn_fuse( torch.cat(fusion, 1))\n","\n","        return x, fusion"]},{"cell_type":"code","execution_count":19,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:57.969427Z","iopub.status.busy":"2022-08-29T15:01:57.968974Z","iopub.status.idle":"2022-08-29T15:01:57.983246Z","shell.execute_reply":"2022-08-29T15:01:57.982118Z","shell.execute_reply.started":"2022-08-29T15:01:57.969391Z"},"papermill":{"duration":0.025255,"end_time":"2022-08-23T14:58:06.438999","exception":false,"start_time":"2022-08-23T14:58:06.413744","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class LayerNorm2d(nn.Module):\n","    def __init__(self, dim, eps=1e-6):\n","        super().__init__()\n","        self.weight = nn.Parameter(torch.ones(dim))\n","        self.bias = nn.Parameter(torch.zeros(dim))\n","        self.eps = eps\n","\n","    def forward(self, x):\n","        u = x.mean(1, keepdim=True)\n","        s = (x - u).pow(2).mean(1, keepdim=True)\n","        x = (x - u) / torch.sqrt(s + self.eps)\n","        x = self.weight[:, None, None] * x + self.bias[:, None, None]\n","        return x\n","    \n","def criterion_aux_loss(logit, mask):\n","    '''here we are resizing mask shape to logits h and w and then bce ----> [-2:] means last two elements'''\n","    mask = F.interpolate(mask,size=logit.shape[-2:], mode='nearest')\n","    loss = F.binary_cross_entropy_with_logits(logit,mask)\n","    return loss\n","\n","# FOCAL LOSS ----------------\n","ALPHA = 0.8\n","GAMMA = 2\n","\n","class FocalLoss(nn.Module):\n","    def __init__(self, weight=None, size_average=True):\n","        super(FocalLoss, self).__init__()\n","\n","    def forward(self, inputs, targets, alpha=ALPHA, gamma=GAMMA, smooth=1):\n","        \n","        #comment out if your model contains a sigmoid or equivalent activation layer\n","#         inputs = F.sigmoid(inputs)       \n","        \n","        #flatten label and prediction tensors\n","        inputs = inputs.view(-1)\n","        targets = targets.view(-1)\n","        \n","        #first compute binary cross-entropy \n","        BCE = F.binary_cross_entropy_with_logits(inputs, targets, reduction='mean')\n","        BCE_EXP = torch.exp(-BCE)\n","        focal_loss = alpha * (1-BCE_EXP)**gamma * BCE\n","                       \n","        return focal_loss"]},{"cell_type":"code","execution_count":20,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:57.985350Z","iopub.status.busy":"2022-08-29T15:01:57.984932Z","iopub.status.idle":"2022-08-29T15:01:58.001190Z","shell.execute_reply":"2022-08-29T15:01:58.000205Z","shell.execute_reply.started":"2022-08-29T15:01:57.985315Z"},"papermill":{"duration":0.032259,"end_time":"2022-08-23T14:58:06.482843","exception":false,"start_time":"2022-08-23T14:58:06.450584","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class Net(nn.Module):\n","\n","    def load_pretrain( self,):\n","\n","        checkpoint = cfg[self.arch]['checkpoint']\n","        print('loading %s ...'%checkpoint)\n","        checkpoint = torch.load(checkpoint, map_location=lambda storage, loc: storage)['model']\n","        if 0:\n","            print('in')\n","            skip = ['relative_coords_table','relative_position_index']\n","            filtered={}\n","            for k,v in checkpoint.items():\n","                if any([s in k for s in skip ]): continue\n","                filtered[k]=v\n","            checkpoint = filtered\n","        print(self.encoder.load_state_dict(checkpoint,strict=False))  #True\n","\n","\n","    def __init__( self,):\n","        super(Net, self).__init__()\n","        self.output_type = ['inference', 'loss']\n","        self.focal_loss = FocalLoss()\n","        self.rgb = RGB()\n","        self.arch = 'swin_tiny_patch4_window7_224'\n","\n","        self.encoder = SwinTransformerV1(\n","            ** {**cfg['basic']['swin'], **cfg[self.arch]['swin'],\n","                **{'out_norm' : LayerNorm2d} }\n","        )\n","        encoder_dim =cfg[self.arch]['upernet']['in_channels']\n","        #[96, 192, 384, 768]\n","\n","        self.decoder = UPerDecoder(\n","            in_dim=encoder_dim,\n","            ppm_pool_scale=[1, 2, 3, 6],\n","            ppm_dim=512,\n","            fpn_out_dim=256\n","        )\n","\n","        self.logit = nn.Sequential(\n","            nn.Conv2d(256, 1, kernel_size=1)\n","        )\n","        self.aux = nn.ModuleList([\n","            nn.Conv2d(256, 1, kernel_size=1, padding=0) for i in range(4)\n","        ])\n","\n","\n","\n","    def forward(self, batch):\n","        x = batch['image']\n","        B,C,H,W = x.shape\n","        x = self.rgb(x)\n","        encoder = self.encoder(x)\n","        last, decoder = self.decoder(encoder)\n","        logit = self.logit(last)\n","        logit = F.interpolate(logit, size=None, scale_factor=4, mode='bilinear', align_corners=False)\n","        print(\"logit shape\", logit.shape)\n","        output = {}\n","        if 'loss' in self.output_type:\n","            output['bce_loss'] = F.binary_cross_entropy_with_logits(logit,batch['mask'])\n","            for i in range(4):\n","                output['aux%d_loss'%i] = criterion_aux_loss(self.aux[i](decoder[i]),batch['mask'])\n","            output['focal_loss'] = self.focal_loss(logit,batch['mask'])\n","\n","            print(\"================================================\")\n","            print(output['bce_loss'], output['focal_loss'])\n","            print(\"================================================\")\n","\n","        if 'inference' in self.output_type:\n","            output['probability'] = torch.sigmoid(logit)\n","\n","        \n","\n","        return output"]},{"cell_type":"code","execution_count":21,"metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.execute_input":"2022-08-29T15:01:58.004704Z","iopub.status.busy":"2022-08-29T15:01:58.003900Z","iopub.status.idle":"2022-08-29T15:01:58.015840Z","shell.execute_reply":"2022-08-29T15:01:58.014688Z","shell.execute_reply.started":"2022-08-29T15:01:58.004666Z"},"papermill":{"duration":0.02719,"end_time":"2022-08-23T14:58:06.521040","exception":false,"start_time":"2022-08-23T14:58:06.493850","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def run_check_net():\n","    batch_size = 2\n","    image_size = 512\n","\n","    #---\n","    batch = {\n","        'image' : torch.from_numpy( np.random.uniform(-1,1,(batch_size,3,image_size,image_size)) ).float(),\n","        'mask'  : torch.from_numpy( np.random.choice(2,(batch_size,1,image_size,image_size)) ).float(),\n","        'organ' : torch.from_numpy( np.random.choice(5,(batch_size)) ).long(),\n","    }\n","    batch = {k:v.cuda() for k,v in batch.items()}\n","\n","    net = Net().cuda()\n","    net.load_pretrain()\n","\n","    with torch.no_grad():\n","        with torch.cuda.amp.autocast(enabled=True):\n","            output = net(batch)\n","\n","    print('batch')\n","    for k,v in batch.items():\n","        print('%32s :'%k, v.shape)\n","\n","    print('output')\n","    for k,v in output.items():\n","        if 'loss' not in k:\n","            print('%32s :'%k, v.shape)\n","    for k,v in output.items():\n","        if 'loss' in k:\n","            print('%32s :'%k, v.item())"]},{"cell_type":"code","execution_count":22,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.018023Z","iopub.status.busy":"2022-08-29T15:01:58.017656Z","iopub.status.idle":"2022-08-29T15:01:58.029808Z","shell.execute_reply":"2022-08-29T15:01:58.028796Z","shell.execute_reply.started":"2022-08-29T15:01:58.017988Z"},"papermill":{"duration":0.023425,"end_time":"2022-08-23T14:58:06.555710","exception":false,"start_time":"2022-08-23T14:58:06.532285","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["class Mlp(nn.Module):\n","    \"\"\" Multilayer perceptron.\"\"\"\n","\n","    def __init__(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.):\n","        super().__init__()\n","        out_features = out_features or in_features\n","        hidden_features = hidden_features or in_features\n","        self.fc1 = nn.Linear(in_features, hidden_features)\n","        self.act = act_layer()\n","        self.fc2 = nn.Linear(hidden_features, out_features)\n","        self.drop = nn.Dropout(drop)\n","\n","    def forward(self, x):\n","        x = self.fc1(x)\n","        x = self.act(x)\n","        x = self.drop(x)\n","        x = self.fc2(x)\n","        x = self.drop(x)\n","        return x"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.01143,"end_time":"2022-08-23T14:58:06.579001","exception":false,"start_time":"2022-08-23T14:58:06.567571","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"configs\"><center>Configuration</center></h3>"]},{"cell_type":"code","execution_count":23,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.032663Z","iopub.status.busy":"2022-08-29T15:01:58.032026Z","iopub.status.idle":"2022-08-29T15:01:58.043942Z","shell.execute_reply":"2022-08-29T15:01:58.042952Z","shell.execute_reply.started":"2022-08-29T15:01:58.032620Z"},"papermill":{"duration":0.027124,"end_time":"2022-08-23T14:58:06.617946","exception":false,"start_time":"2022-08-23T14:58:06.590822","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["cfg = dict(\n","\n","        #configs/_base_/models/upernet_swin.py\n","        basic = dict(\n","            swin=dict(\n","                embed_dim=96,\n","                depths=[2, 2, 6, 2],\n","                num_heads=[3, 6, 12, 24],\n","                window_size=7,\n","                mlp_ratio=4.,\n","                qkv_bias=True,\n","                qk_scale=None,\n","                drop_rate=0.,\n","                attn_drop_rate=0.,\n","                drop_path_rate=0.3,\n","                ape=False,\n","                patch_norm=True,\n","                out_indices=(0, 1, 2, 3),\n","                use_checkpoint=False\n","            ),\n","\n","        ),\n","\n","        #configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k.py\n","        swin_tiny_patch4_window7_224=dict(\n","            checkpoint = pretrain_dir+'/swin_tiny_patch4_window7_224_22k.pth',\n","\n","            swin = dict(\n","                embed_dim=96,\n","                depths=[2, 2, 6, 2],\n","                num_heads=[3, 6, 12, 24],\n","                window_size=7,\n","                ape=False,\n","                drop_path_rate=0.3,\n","                patch_norm=True,\n","                use_checkpoint=False,\n","            ),\n","            upernet=dict(\n","                in_channels=[96, 192, 384, 768],\n","            ),\n","        ),\n","\n","        #/configs/swin/upernet_swin_small_patch4_window7_512x512_160k_ade20k.py\n","        swin_small_patch4_window7_224_22k=dict(\n","            checkpoint = pretrain_dir+'/swin_small_patch4_window7_224_22k.pth',\n","\n","            swin = dict(\n","                embed_dim=96,\n","                depths=[2, 2, 18, 2],\n","                num_heads=[3, 6, 12, 24],\n","                window_size=7,\n","                ape=False,\n","                drop_path_rate=0.3,\n","                patch_norm=True,\n","                use_checkpoint=False\n","            ),\n","            upernet=dict(\n","                in_channels=[96, 192, 384, 768],\n","            ),\n","        ),\n","    )"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.010804,"end_time":"2022-08-23T14:58:06.640173","exception":false,"start_time":"2022-08-23T14:58:06.629369","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"folds\"><center>Folds</center></h3>"]},{"cell_type":"code","execution_count":24,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.046017Z","iopub.status.busy":"2022-08-29T15:01:58.045728Z","iopub.status.idle":"2022-08-29T15:01:58.059105Z","shell.execute_reply":"2022-08-29T15:01:58.057948Z","shell.execute_reply.started":"2022-08-29T15:01:58.045970Z"},"papermill":{"duration":0.026216,"end_time":"2022-08-23T14:58:06.677487","exception":false,"start_time":"2022-08-23T14:58:06.651271","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def make_fold(fold=0):\n","    df = pd.read_csv(LABELS)\n","\n","    num_fold = 4\n","    skf = KFold(n_splits = num_fold, shuffle = True,random_state = 42)\n","\n","    df.loc[:,'fold']=-1\n","    for f,(t_idx, v_idx) in enumerate(skf.split(X=df['id'], y=df['organ'])):\n","        df.iloc[v_idx,-1]=f\n","\n","    #check\n","    if 0:\n","        for f in range(num_fold):\n","            train_df=df[df.fold!=f].reset_index(drop=True)\n","            valid_df=df[df.fold==f].reset_index(drop=True)\n","\n","            print('fold %d'%f)\n","            t = train_df.organ.value_counts().to_dict()\n","            v = valid_df.organ.value_counts().to_dict()\n","            for k in ['kidney', 'prostate', 'largeintestine', 'spleen', 'lung']:\n","                print('%32s %3d (%0.3f)  %3d (%0.3f)'%(k,t.get(k,0),t.get(k,0)/len(train_df),v.get(k,0),v.get(k,0)/len(valid_df)))\n","\n","            print('')\n","            zz=0\n","\n","    train_df=df[df.fold!=fold].reset_index(drop=True)\n","    valid_df=df[df.fold==fold].reset_index(drop=True)\n","    return train_df,valid_df"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011186,"end_time":"2022-08-23T14:58:06.699703","exception":false,"start_time":"2022-08-23T14:58:06.688517","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"dice_score\"><center>Competition Metric</center></h3>"]},{"cell_type":"code","execution_count":25,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.061590Z","iopub.status.busy":"2022-08-29T15:01:58.060905Z","iopub.status.idle":"2022-08-29T15:01:58.072475Z","shell.execute_reply":"2022-08-29T15:01:58.071460Z","shell.execute_reply.started":"2022-08-29T15:01:58.061553Z"},"papermill":{"duration":0.022342,"end_time":"2022-08-23T14:58:06.735230","exception":false,"start_time":"2022-08-23T14:58:06.712888","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def compute_dice_score(probability, mask, smooth = 1):\n","    N = len(probability)\n","    p = probability.reshape(N,-1)\n","    t = mask.reshape(N,-1)\n","\n","    p = p>0.5\n","    t = t>0.5\n","    uion = p.sum(-1) + t.sum(-1)\n","    overlap = (p*t).sum(-1)\n","    dice = 2*overlap/(uion+0.0001)\n","    return dice"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.010405,"end_time":"2022-08-23T14:58:06.756686","exception":false,"start_time":"2022-08-23T14:58:06.746281","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"validation\"><center>Validation</center></h3>"]},{"cell_type":"code","execution_count":26,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.075621Z","iopub.status.busy":"2022-08-29T15:01:58.075154Z","iopub.status.idle":"2022-08-29T15:01:58.091439Z","shell.execute_reply":"2022-08-29T15:01:58.089982Z","shell.execute_reply.started":"2022-08-29T15:01:58.075586Z"},"trusted":true},"outputs":[],"source":["organ_threshold = {\n","    'Hubmap': {\n","        'kidney'        : 0.40,\n","        'prostate'      : 0.40,\n","        'largeintestine': 0.40,\n","        'spleen'        : 0.40,\n","        'lung'          : 0.10,\n","    },\n","    'HPA': {\n","        'kidney'        : 0.50,\n","        'prostate'      : 0.50,\n","        'largeintestine': 0.50,\n","        'spleen'        : 0.50,\n","        'lung'          : 0.10,\n","    },\n","}\n","\n","def valid_infer(net):\n","    infer_ids = {\"spleen\":1123, \"prostate\": 12244, \"lung\": 4301, \"largeintestine\": 9777, \"kidney\":15005}\n","    image_size = 512\n","    # create a batch\n","    infer_imgs = []\n","    img_list = []\n","    mask_list = []\n","    for infer_id in infer_ids.values():\n","        # kaggle changes\n","        image_org = cv2.imread(os.path.join(TRAIN, f'{str(infer_id)}.png'), cv2.IMREAD_COLOR) # changed\n","        mask_org = cv2.imread(os.path.join(MASKS, f'{str(infer_id)}.png'), 0)\n","        image = image_org.astype(np.float32)/255\n","\n","        H, W, _ = image.shape\n","\n","        \n","        image = cv2.resize(image, dsize=(image_size,image_size), interpolation=cv2.INTER_LINEAR)\n","        image_org = cv2.resize(image_org, dsize=(image_size,image_size), interpolation=cv2.INTER_LINEAR)\n","        mask_org = cv2.resize(mask_org, dsize=(image_size,image_size), interpolation=cv2.INTER_LINEAR)\n","\n","        image = image_to_tensor(image)\n","        image = image.cuda()\n","        infer_imgs.append(image)\n","        img_list.append(image_org)\n","        mask_list.append(mask_org)\n","\n","    # batch = {\n","    #     'image':\n","    #         torch.stack(infer_imgs),\n","    #     'mask':\n","    #         torch.stack([mask_to_tensor(msk_gt.reshape(1, image_size, image_size)).cuda() \\\n","    #             for msk_gt in mask_list])\n","    # }\n","    batch = {\n","        'image':\n","            torch.stack(infer_imgs),\n","    }\n","    \n","    # run model on batch ----------\n","    net.output_type = ['inference']\n","    net = net.eval()\n","    with torch.no_grad():\n","        with amp.autocast(enabled = is_amp):\n","            output = net(batch)\n","    pred = nn.Sigmoid()(output['probability'])\n","    msks = (pred.permute((0,2,3,1))>0.5).to(torch.uint8).cpu().detach().numpy()\n","    \n","    for idx in range(msks.shape[0]):\n","        pred_msk = msks[idx,:,:,:].reshape(512,512)\n","        true_msk = mask_list[idx]\n","        true_img = img_list[idx]\n","\n","        plt.figure(figsize= (12,14))\n","        plt.subplot(1,3,1)\n","        plt.imshow(true_img)\n","        plt.title(\"gt img\")\n","\n","        plt.subplot(1,3,2)\n","        plt.imshow(true_msk)\n","        plt.title(\"gt mask\")\n","\n","        plt.subplot(1,3,3)\n","        plt.imshow(pred_msk)\n","        plt.title(\"pred mask\")\n","\n","        plt.show()\n","    # output = net(batch)\n","    # pred = nn.Sigmoid()(output['probability'])\n","    # thr = organ_threshold[data_src][orgun]\n","    # msks = (pred.permute((0,2,3,1))>thr).to(torch.uint8).cpu().detach().numpy()\n","\n","\n","# valid_infer()"]},{"cell_type":"code","execution_count":27,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.093514Z","iopub.status.busy":"2022-08-29T15:01:58.093158Z","iopub.status.idle":"2022-08-29T15:01:58.109649Z","shell.execute_reply":"2022-08-29T15:01:58.108596Z","shell.execute_reply.started":"2022-08-29T15:01:58.093474Z"},"papermill":{"duration":0.030498,"end_time":"2022-08-23T14:58:06.797688","exception":false,"start_time":"2022-08-23T14:58:06.767190","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def validate(net, valid_loader, debug = False):\n","\n","    valid_num = 0\n","    valid_probability = []\n","    valid_mask = []\n","    valid_loss = 0\n","\n","    net = net.eval()\n","    start_timer = time.time()\n","    for t, batch in enumerate(valid_loader):\n","\n","        net.output_type = ['loss', 'inference']\n","        with torch.no_grad():\n","            with amp.autocast(enabled = is_amp):\n","#                 orgun = batch['organ']\n","                batch_size = len(batch['index'])\n","                batch['image'] = batch['image'].cuda()\n","                batch['mask' ] = batch['mask' ].cuda()\n","                batch['organ'] = batch['organ'].cuda()\n","\n","                output = net(batch)\n","                loss0  = output['bce_loss'].mean()\n","                \n","        \n","        valid_probability.append(output['probability'].data.cpu().numpy())\n","        valid_mask.append(batch['mask'].data.cpu().numpy())\n","        valid_num += batch_size\n","        valid_loss += batch_size*loss0.item()\n","\n","        #debug\n","        if debug :\n","            pass\n","            organ = batch['organ'].data.cpu().numpy()\n","            image = batch['image']\n","            mask  = batch['mask']\n","            probability  = output['probability']\n","\n","            for b in range(batch_size):\n","                m = tensor_to_image(image[b])\n","                t = tensor_to_mask(mask[b,0])\n","                p = tensor_to_mask(probability[b,0])\n","                overlay = result_to_overlay(m, t, p )\n","\n","                text = label_to_organ[organ[b]]\n","                draw_shadow_text(overlay,text,(5,15),0.7,(1,1,1),1)\n","\n","                image_show_norm('overlay',overlay,min=0,max=1,resize=1)\n","                cv2.waitKey(0)\n","\n","        print('\\r %8d / %d  %s'%(valid_num, len(valid_loader.dataset),(time.time() - start_timer)),end='',flush=True)\n","\n","    \n","    \n","    assert(valid_num == len(valid_loader.dataset))\n","\n","    probability = np.concatenate(valid_probability)\n","    mask = np.concatenate(valid_mask)\n","\n","    loss = valid_loss/valid_num\n","\n","    dice = compute_dice_score(probability, mask)\n","    dice = dice.mean()\n","    \n","    return [dice, loss,  0, 0]"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011318,"end_time":"2022-08-23T14:58:06.820775","exception":false,"start_time":"2022-08-23T14:58:06.809457","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"init\"><center>Initialization</center></h3>"]},{"cell_type":"code","execution_count":28,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.116916Z","iopub.status.busy":"2022-08-29T15:01:58.116218Z","iopub.status.idle":"2022-08-29T15:01:58.122756Z","shell.execute_reply":"2022-08-29T15:01:58.121575Z","shell.execute_reply.started":"2022-08-29T15:01:58.116889Z"},"papermill":{"duration":0.023146,"end_time":"2022-08-23T14:58:06.855210","exception":false,"start_time":"2022-08-23T14:58:06.832064","status":"completed"},"tags":[],"trusted":true},"outputs":[],"source":["def get_learning_rate(optimizer):\n","    return optimizer.param_groups[0]['lr']"]},{"cell_type":"code","execution_count":29,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:01:58.124856Z","iopub.status.busy":"2022-08-29T15:01:58.124431Z","iopub.status.idle":"2022-08-29T15:02:04.094914Z","shell.execute_reply":"2022-08-29T15:02:04.093901Z","shell.execute_reply.started":"2022-08-29T15:01:58.124780Z"},"papermill":{"duration":7.19907,"end_time":"2022-08-23T14:58:14.065497","exception":false,"start_time":"2022-08-23T14:58:06.866427","status":"completed"},"tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["loading /home/lakshita/somusan/hubmap_kaggle/nbs/swin-tiny-small-22k-pretrained/swin_tiny_patch4_window7_224_22k.pth ...\n","_IncompatibleKeys(missing_keys=['out_norm.0.weight', 'out_norm.0.bias', 'out_norm.1.weight', 'out_norm.1.bias', 'out_norm.2.weight', 'out_norm.2.bias', 'out_norm.3.weight', 'out_norm.3.bias'], unexpected_keys=['norm.weight', 'norm.bias', 'head.weight', 'head.bias', 'layers.0.blocks.1.attn_mask', 'layers.1.blocks.1.attn_mask', 'layers.2.blocks.1.attn_mask', 'layers.2.blocks.3.attn_mask', 'layers.2.blocks.5.attn_mask'])\n","when to save model:  99\n"]}],"source":["fold = 3\n","\n","out_dir = root_dir + '/result/upernet-swin-v1-tiny-aux5-768/fold-%d' % (fold)\n","initial_checkpoint = None\n","#initial_checkpoint = '../input/swin-10k/result/upernet-swin-v1-tiny-aux5-768/fold-3/checkpoint/00009975.model.pth'\n","#initial_checkpoint = '../input/heng-hubmap-fold0-10k/result/upernet-swin-v1-tiny-aux5-768/fold-0/checkpoint/00009975.model.pth'\n","\n","start_lr   = 5e-5 #0.0001\n","batch_size = 8 #32 #32\n","\n","\n","## setup  ----------------------------------------\n","for f in ['checkpoint','train','valid','backup'] : os.makedirs(out_dir +'/'+f, exist_ok=True)\n","\n","    \n","log = open(out_dir+'/log.train.txt',mode='a')\n","log.write('\\n--- [START %s] %s\\n\\n' % ('Swin', '-' * 64))\n","log.write('\\n')\n","\n","\n","## dataset ----------------------------------------\n","log.write('** dataset setting **\\n')\n","\n","train_df, valid_df = make_fold(fold)\n","\n","train_dataset = HubmapDataset(train_df, train_augment5b)\n","valid_dataset = HubmapDataset(valid_df, valid_augment5)\n","\n","train_loader  = DataLoader(\n","    train_dataset,\n","    sampler = RandomSampler(train_dataset),\n","    batch_size  = batch_size,\n","    drop_last   = True,\n","    num_workers = 8,\n","    pin_memory  = False,\n","    worker_init_fn = lambda id: np.random.seed(torch.initial_seed() // 2 ** 32 + id),\n","    collate_fn = null_collate,\n",")\n","\n","valid_loader = DataLoader(\n","    valid_dataset,\n","    sampler = SequentialSampler(valid_dataset),\n","    batch_size  = 8,\n","    drop_last   = False,\n","    num_workers = 4,\n","    pin_memory  = False,\n","    collate_fn = null_collate,\n",")\n","\n","\n","log.write('fold = %s\\n'%str(fold))\n","log.write('train_dataset : \\n%s\\n'%(train_dataset))\n","log.write('valid_dataset : \\n%s\\n'%(valid_dataset))\n","log.write('\\n')\n","\n","\n","## net ----------------------------------------\n","log.write('** net setting **\\n')\n","\n","scaler = amp.GradScaler(enabled = is_amp)\n","net = Net().cuda()\n","\n","if initial_checkpoint is not None:\n","    f = torch.load(initial_checkpoint, map_location=lambda storage, loc: storage)\n","    start_iteration = f['iteration']\n","    start_epoch = f['epoch']\n","    state_dict  = f['state_dict']\n","    net.load_state_dict(state_dict,strict=False)  #True\n","else:\n","    start_iteration = 0\n","    start_epoch = 0\n","    net.load_pretrain()\n","\n","\n","log.write('\\tinitial_checkpoint = %s\\n' % initial_checkpoint)\n","log.write('\\n')\n","\n","\n","## optimiser ----------------------------------\n","if 0: ##freeze\n","    for p in net.stem.parameters():   p.requires_grad = False\n","    pass\n","\n","def freeze_bn(net):\n","    for m in net.modules():\n","        if isinstance(m, nn.BatchNorm2d):\n","            m.eval()\n","            m.weight.requires_grad = False\n","            m.bias.requires_grad = False\n","            \n","#freeze_bn(net)\n","\n","#-----------------------------------------------\n","\n","optimizer = torch.optim.AdamW(filter(lambda p: p.requires_grad, net.parameters()),lr=start_lr)\n","\n","log.write('optimizer\\n  %s\\n'%(optimizer))\n","log.write('\\n')\n","\n","#num_iteration = 1000*len(train_loader)\n","num_iteration = 12000\n","iter_log   = len(train_loader)*3 #479\n","iter_valid = iter_log\n","iter_save  = iter_log\n","print(\"when to save model: \",iter_log)"]},{"cell_type":"code","execution_count":30,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:02:04.097180Z","iopub.status.busy":"2022-08-29T15:02:04.096521Z","iopub.status.idle":"2022-08-29T15:02:04.125579Z","shell.execute_reply":"2022-08-29T15:02:04.124608Z","shell.execute_reply.started":"2022-08-29T15:02:04.097141Z"},"trusted":true},"outputs":[],"source":["# train_df"]},{"cell_type":"code","execution_count":31,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:02:04.127406Z","iopub.status.busy":"2022-08-29T15:02:04.127073Z","iopub.status.idle":"2022-08-29T15:02:23.380750Z","shell.execute_reply":"2022-08-29T15:02:23.379841Z","shell.execute_reply.started":"2022-08-29T15:02:04.127372Z"},"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["torch.Size([8, 512, 512, 3]) torch.Size([8, 512, 512, 1])\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 864x360 with 3 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","text/plain":["<Figure 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","text/plain":["<Figure size 864x360 with 3 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["items = next(iter(train_loader))\n","imgs = items[\"image\"].permute((0, 2, 3, 1))\n","msks = items[\"mask\"].permute((0, 2, 3, 1))\n","print(imgs.size(), msks.size())\n","\n","# torch.unique(msks)\n","\n","import matplotlib.pyplot as plt\n","def plot_batch(imgs, msks, size=3):\n","    for idx in range(size):\n","        plt.figure(figsize=(4*3, 5))\n","\n","        plt.subplot(1, 3, 1); plt.imshow(imgs[idx])\n","        plt.title('image', fontsize=15)\n","        plt.axis('OFF')\n","\n","        plt.subplot(1, 3, 2); plt.imshow(msks[idx])\n","        plt.title('mask', fontsize=15)\n","        plt.axis('OFF')\n","            \n","        plt.subplot(1, 3, 3); plt.imshow(imgs[idx]); plt.imshow(msks[idx], alpha=0.3)\n","        plt.title('overlay', fontsize=15)\n","        plt.axis('OFF')\n","        \n","        plt.tight_layout()\n","        plt.show()\n","\n","plot_batch(imgs, msks, size=3)"]},{"cell_type":"markdown","metadata":{"papermill":{"duration":0.011629,"end_time":"2022-08-23T14:58:14.089691","exception":false,"start_time":"2022-08-23T14:58:14.078062","status":"completed"},"tags":[]},"source":["<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" style=\"color:#c3448b; background:#efe9e9; border:1px dashed #efe50b;\" role=\"tab\" aria-controls=\"training\"><center>Training</center></h3>"]},{"cell_type":"code","execution_count":32,"metadata":{"execution":{"iopub.execute_input":"2022-08-29T15:02:23.383027Z","iopub.status.busy":"2022-08-29T15:02:23.382449Z","iopub.status.idle":"2022-08-29T15:14:30.107269Z","shell.execute_reply":"2022-08-29T15:14:30.103461Z","shell.execute_reply.started":"2022-08-29T15:02:23.382988Z"},"papermill":{"duration":null,"end_time":null,"exception":false,"start_time":"2022-08-23T14:58:14.101645","status":"running"},"tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7088, device='cuda:0') tensor(0.1462, device='cuda:0')\n","================================================\n","        8 / 87  4.0861334800720215logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7055, device='cuda:0') tensor(0.1446, device='cuda:0')\n","================================================\n","       16 / 87  4.219699144363403logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7101, device='cuda:0') tensor(0.1468, device='cuda:0')\n","================================================\n","       24 / 87  4.341715335845947logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7104, device='cuda:0') tensor(0.1470, device='cuda:0')\n","================================================\n","       32 / 87  4.480994939804077logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7101, device='cuda:0') tensor(0.1469, device='cuda:0')\n","================================================\n","       40 / 87  5.823458194732666logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7108, device='cuda:0') tensor(0.1472, device='cuda:0')\n","================================================\n","       48 / 87  5.941236972808838logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7100, device='cuda:0') tensor(0.1468, device='cuda:0')\n","================================================\n","       56 / 87  6.046666622161865logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7104, device='cuda:0') tensor(0.1470, device='cuda:0')\n","================================================\n","       64 / 87  6.151901006698608logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7107, device='cuda:0') tensor(0.1471, device='cuda:0')\n","================================================\n","       72 / 87  7.454245328903198logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.7112, device='cuda:0') tensor(0.1474, device='cuda:0')\n","================================================\n","       80 / 87  7.628531455993652logit shape torch.Size([7, 1, 512, 512])\n","================================================\n","tensor(0.7107, device='cuda:0') tensor(0.1471, device='cuda:0')\n","================================================\n","=---------------------DEBUG3573\n","[0. 0.]\n","(2,)\n","=---------------------DEBUG\n","logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.6394, device='cuda:0',\n","       grad_fn=<BinaryCrossEntropyWithLogitsBackward0>) tensor(0.1141, device='cuda:0', grad_fn=<MulBackward0>)\n","================================================\n","=-----------------------------\n","loss 0 0.63935786485672\n","loss 1 0.11412911862134933\n","=-----------------------------\n","=---------------------DEBUG\n","[0.63935786 0.11412912]\n","(2,)\n","=---------------------DEBUG\n","5.00e-5   00000000    0.00 | 0.180  0.710  0.0000  0.000   | 0.639  0.114   | 11.471107244491577logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.8639, device='cuda:0',\n","       grad_fn=<BinaryCrossEntropyWithLogitsBackward0>) tensor(0.2313, device='cuda:0', grad_fn=<MulBackward0>)\n","================================================\n","=-----------------------------\n","loss 0 0.8638824224472046\n","loss 1 0.23126919567584991\n","=-----------------------------\n","=---------------------DEBUG\n","[0.8638824 0.2312692]\n","(2,)\n","=---------------------DEBUG\n","5.00e-5   00000001    0.03 | 0.180  0.710  0.0000  0.000   | 0.864  0.231   | 11.811060905456543logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.6423, device='cuda:0',\n","       grad_fn=<BinaryCrossEntropyWithLogitsBackward0>) tensor(0.1154, device='cuda:0', grad_fn=<MulBackward0>)\n","================================================\n","=-----------------------------\n","loss 0 0.6422957181930542\n","loss 1 0.11540618538856506\n","=-----------------------------\n","=---------------------DEBUG\n","[0.6422957  0.11540619]\n","(2,)\n","=---------------------DEBUG\n","5.00e-5   00000002    0.06 | 0.180  0.710  0.0000  0.000   | 0.642  0.115   | 12.139779090881348logit shape torch.Size([8, 1, 512, 512])\n","================================================\n","tensor(0.6181, device='cuda:0',\n","       grad_fn=<BinaryCrossEntropyWithLogitsBackward0>) tensor(0.1051, device='cuda:0', grad_fn=<MulBackward0>)\n","================================================\n","=-----------------------------\n","loss 0 0.6181204319000244\n","loss 1 0.10511071234941483\n","=-----------------------------\n","=---------------------DEBUG\n","[0.61812043 0.10511071]\n","(2,)\n","=---------------------DEBUG\n","5.00e-5   00000003    0.09 | 0.180  0.710  0.0000  0.000 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\u001b[0mnum_iteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_loader\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     23\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0miteration\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0miter_save\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/somusan/hubmap_kaggle/.venv/lib/python3.7/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    650\u001b[0m                 \u001b[0;31m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    651\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[call-arg]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 652\u001b[0;31m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_next_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    653\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_num_yielded\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    654\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dataset_kind\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0m_DatasetKind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mIterable\u001b[0m \u001b[0;32mand\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/somusan/hubmap_kaggle/.venv/lib/python3.7/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m_next_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1329\u001b[0m             \u001b[0;32massert\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_shutdown\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_tasks_outstanding\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1330\u001b[0;31m             \u001b[0midx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1331\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_tasks_outstanding\u001b[0m \u001b[0;34m-=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1332\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dataset_kind\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0m_DatasetKind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mIterable\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/somusan/hubmap_kaggle/.venv/lib/python3.7/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m_get_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1294\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1295\u001b[0m             \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1296\u001b[0;31m                 \u001b[0msuccess\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_try_get_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1297\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0msuccess\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1298\u001b[0m                     \u001b[0;32mreturn\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/somusan/hubmap_kaggle/.venv/lib/python3.7/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m_try_get_data\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m   1132\u001b[0m         \u001b[0;31m#   (bool: whether successfully get data, any: data if successful else None)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1133\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1134\u001b[0;31m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data_queue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1135\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1136\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/.pyenv/versions/3.7.0/lib/python3.7/multiprocessing/queues.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, block, timeout)\u001b[0m\n\u001b[1;32m    102\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mblock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    103\u001b[0m                     \u001b[0mtimeout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdeadline\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 104\u001b[0;31m                     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_poll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    105\u001b[0m                         \u001b[0;32mraise\u001b[0m \u001b[0mEmpty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    106\u001b[0m                 \u001b[0;32melif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_poll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/.pyenv/versions/3.7.0/lib/python3.7/multiprocessing/connection.py\u001b[0m in \u001b[0;36mpoll\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    255\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_closed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    256\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_readable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 257\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_poll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    258\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    259\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__enter__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/.pyenv/versions/3.7.0/lib/python3.7/multiprocessing/connection.py\u001b[0m in \u001b[0;36m_poll\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    412\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    413\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_poll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 414\u001b[0;31m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    415\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mbool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    416\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/.pyenv/versions/3.7.0/lib/python3.7/multiprocessing/connection.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(object_list, timeout)\u001b[0m\n\u001b[1;32m    918\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    919\u001b[0m             \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 920\u001b[0;31m                 \u001b[0mready\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mselector\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mselect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    921\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mready\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    922\u001b[0m                     \u001b[0;32mreturn\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfileobj\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevents\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mready\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m~/.pyenv/versions/3.7.0/lib/python3.7/selectors.py\u001b[0m in \u001b[0;36mselect\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    413\u001b[0m         \u001b[0mready\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    414\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 415\u001b[0;31m             \u001b[0mfd_event_list\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_selector\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpoll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    416\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mInterruptedError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    417\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mready\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyboardInterrupt\u001b[0m: "]}],"source":["log.write('** start training here! **\\n')\n","log.write('   batch_size = %d \\n'%(batch_size))\n","log.write('                     |-------------- VALID---------|---- TRAIN/BATCH ----------------\\n')\n","log.write('rate     iter  epoch | dice   loss   tp     tn     | loss           | time           \\n')\n","log.write('-------------------------------------------------------------------------------------\\n')\n","\n","valid_loss = np.zeros(4,np.float32)\n","train_loss = np.zeros(2,np.float32)\n","batch_loss = np.zeros_like(train_loss)\n","sum_train_loss = np.zeros_like(train_loss)\n","sum_train = 0\n","\n","start_timer = time.time()\n","iteration = start_iteration\n","epoch = start_epoch\n","rate = 0\n","mix_proba = 0.4\n","mix_alpha = 0.4\n","device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n","\n","while iteration < num_iteration:\n","    for t, batch in enumerate(train_loader):\n","        \n","        if iteration%iter_save==0:\n","            if iteration != start_iteration:\n","                torch.save({\n","                    'state_dict': net.state_dict(),\n","                    'iteration': iteration,\n","                    'epoch': epoch,\n","                }, out_dir + '/checkpoint/%08d.model.pth' %  (iteration))\n","                pass\n","\n","\n","        if (iteration%iter_valid==0):\n","            valid_loss = validate(net, valid_loader)\n","            pass\n","\n","        # visualize output ------------------\n","        # if (iteration%1000==0):\n","        #     valid_infer(net)\n","        #     pass\n","            \n","        if (iteration%iter_log==0) or (iteration%iter_valid==0):\n","            print('\\r', end='', flush=True)\n","            log.write(message(mode='log') + '\\n')\n","\n","        # apply cutmix ----------------------\n","#         if np.random.random() > mix_proba:\n","#             batch['image'], batch['mask'] = cutmix_data(batch['image'], batch['mask'], alpha=mix_alpha, device=device) \n","\n","\n","        # learning rate schduler ------------\n","        rate = get_learning_rate(optimizer)\n","\n","        # one iteration update  -------------\n","        batch_size = len(batch['index'])\n","        \n","        #print(batch_size, iteration, epoch)\n","        batch['image'] = batch['image'].half().cuda()\n","        batch['mask' ] = batch['mask' ].half().cuda()\n","        batch['organ'] = batch['organ'].cuda()\n","\n","\n","        net.train()\n","        net.output_type = ['loss']\n","        if 1:\n","            with amp.autocast(enabled = is_amp):\n","                output = net(batch)\n","                loss0  = output['bce_loss'].mean()\n","                loss1  = output['focal_loss'].mean()\n","                \n","#                 print(type(output['bce_loss']))\n","#                 print(type(output['focal_loss']))\n","            optimizer.zero_grad()\n","            scaler.scale(loss0+0.2*loss1).backward()\n","\n","            scaler.unscale_(optimizer)\n","            scaler.step(optimizer)\n","            scaler.update()\n","\n","\n","        print(\"=-----------------------------\")\n","        print(\"loss 0\",loss0.item())\n","        print(\"loss 1\",loss1.item())\n","        print(\"=-----------------------------\")\n","\n","\n","        # print statistics  --------\n","        batch_loss[:2] = [loss0.item(),loss1.item()]\n","        sum_train_loss += batch_loss\n","        sum_train += 1\n","        if t % 100 == 0:\n","            train_loss = sum_train_loss / (sum_train + 1e-12)\n","            sum_train_loss[...] = 0\n","            sum_train = 0\n","\n","        print('\\r', end='', flush=True)\n","        print(message(mode='print'), end='', flush=True)\n","        epoch += 1 / len(train_loader)\n","        iteration += 1\n","    print()    \n","    torch.cuda.empty_cache()\n","    \n","log.write('\\n')\n","log.close()"]},{"cell_type":"code","execution_count":null,"metadata":{"execution":{"iopub.status.busy":"2022-08-29T15:14:30.109132Z","iopub.status.idle":"2022-08-29T15:14:30.109919Z","shell.execute_reply":"2022-08-29T15:14:30.109684Z","shell.execute_reply.started":"2022-08-29T15:14:30.109655Z"},"papermill":{"duration":null,"end_time":null,"exception":null,"start_time":null,"status":"pending"},"tags":[],"trusted":true},"outputs":[],"source":["# def image_to_tensor(image, mode='bgr'): #image mode\n","#     if mode=='bgr':\n","#         image = image[:,:,::-1]\n","#     x = image\n","#     x = x.transpose(2,0,1)\n","#     x = np.ascontiguousarray(x)\n","#     x = torch.tensor(x, dtype=torch.float)\n","#     return x\n","\n","# def tensor_to_image(x, mode='bgr'):\n","#     image = x.data.cpu().numpy()\n","#     image = image.transpose(1,2,0)\n","#     if mode=='bgr':\n","#         image = image[:,:,::-1]\n","#     image = np.ascontiguousarray(image)\n","#     image = image.astype(np.float32)\n","#     return image\n","\n","# def mask_to_tensor(mask):\n","#     x = mask\n","#     x = torch.tensor(x, dtype=torch.float)\n","#     return x\n","\n","# def tensor_to_mask(x):\n","#     mask = x.data.cpu().numpy()\n","#     mask = mask.astype(np.float32)\n","#     return mask"]},{"cell_type":"code","execution_count":null,"metadata":{"execution":{"iopub.status.busy":"2022-08-29T15:14:30.111351Z","iopub.status.idle":"2022-08-29T15:14:30.112101Z","shell.execute_reply":"2022-08-29T15:14:30.111871Z","shell.execute_reply.started":"2022-08-29T15:14:30.111846Z"},"papermill":{"duration":null,"end_time":null,"exception":null,"start_time":null,"status":"pending"},"tags":[],"trusted":true},"outputs":[],"source":["# valid_num = 0\n","# valid_probability = []\n","# valid_mask = []\n","# valid_loss = 0\n","\n","# net = net.eval()\n","# start_timer = time.time()\n","# for t, batch in enumerate(valid_loader):\n","\n","#     net.output_type = ['loss', 'inference']\n","#     with torch.no_grad():\n","#         with amp.autocast(enabled = is_amp):\n","\n","#             batch_size = len(batch['index'])\n","#             batch['image'] = batch['image'].cuda()\n","#             batch['mask' ] = batch['mask' ].cuda()\n","#             batch['organ'] = batch['organ'].cuda()\n","\n","#             output = net(batch)\n","#             loss0  = output['bce_loss'].mean()\n","\n","#     valid_probability.append(output['probability'].data.cpu().numpy())\n","#     valid_mask.append(batch['mask'].data.cpu().numpy())\n","#     valid_num += batch_size\n","#     valid_loss += batch_size*loss0.item()\n","\n","#     organ = batch['organ'].data.cpu().numpy()\n","#     image = batch['image']\n","#     mask  = batch['mask']\n","#     probability  = output['probability']\n","\n","#     for b in range(batch_size):\n","#         m = tensor_to_image(image[b])\n","#         t = tensor_to_mask(mask[b,0])\n","#         p = tensor_to_mask(probability[b,0])"]},{"cell_type":"code","execution_count":null,"metadata":{"execution":{"iopub.status.busy":"2022-08-29T15:14:30.113421Z","iopub.status.idle":"2022-08-29T15:14:30.114156Z","shell.execute_reply":"2022-08-29T15:14:30.113917Z","shell.execute_reply.started":"2022-08-29T15:14:30.113894Z"},"papermill":{"duration":null,"end_time":null,"exception":null,"start_time":null,"status":"pending"},"tags":[],"trusted":true},"outputs":[],"source":["# import matplotlib.pyplot as plt\n","\n","# plt.imshow(m), m.shape"]},{"cell_type":"code","execution_count":null,"metadata":{"execution":{"iopub.status.busy":"2022-08-29T15:14:30.115493Z","iopub.status.idle":"2022-08-29T15:14:30.116222Z","shell.execute_reply":"2022-08-29T15:14:30.115984Z","shell.execute_reply.started":"2022-08-29T15:14:30.115961Z"},"papermill":{"duration":null,"end_time":null,"exception":null,"start_time":null,"status":"pending"},"tags":[],"trusted":true},"outputs":[],"source":["# plt.imshow(t), t.shape"]},{"cell_type":"code","execution_count":null,"metadata":{"execution":{"iopub.status.busy":"2022-08-29T15:14:30.117562Z","iopub.status.idle":"2022-08-29T15:14:30.118291Z","shell.execute_reply":"2022-08-29T15:14:30.118061Z","shell.execute_reply.started":"2022-08-29T15:14:30.118037Z"},"papermill":{"duration":null,"end_time":null,"exception":null,"start_time":null,"status":"pending"},"tags":[],"trusted":true},"outputs":[],"source":["# plt.imshow(p), p.shape"]},{"cell_type":"code","execution_count":null,"metadata":{"papermill":{"duration":null,"end_time":null,"exception":null,"start_time":null,"status":"pending"},"tags":[]},"outputs":[],"source":[]}],"metadata":{"kernelspec":{"display_name":"Python 3.7.0 ('.venv': venv)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.0"},"vscode":{"interpreter":{"hash":"21a2a557654fc1676068684031cf9bb9dfda94e124d3623f4e9c9ed764d794ac"}}},"nbformat":4,"nbformat_minor":4}