DeepCell_tn_nuclear_K2a_train7_ari.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "330e05e3",
   "metadata": {},
   "source": [
    "**Further train DeepCell Models with K's Data and Make Predictions**<br>\n",
    "Starting from model trained with tn nuclear data, further train the model with resized K's images that is cut into 25 512x512 patches, one image at a time.\n",
    "200 epochs, semanticdatagenerator, resized<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a72e9c51",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-06T16:49:01.459533Z",
     "iopub.status.busy": "2022-11-06T16:49:01.458213Z",
     "iopub.status.idle": "2022-11-06T16:49:01.461680Z",
     "shell.execute_reply": "2022-11-06T16:49:01.460803Z"
    }
   },
   "outputs": [],
   "source": [
    "starting_model_path = 'tn1.0_nuclear_20221102.h5' # the model trained with nucleus data from the Tissuenet V1.0 dataset\n",
    "epochs=200 # 20 sec per step "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9e997e31",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ssl \n",
    "ssl._create_default_https_context = ssl._create_unverified_context"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c3a74833",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.cluster import adjusted_rand_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "90f2183c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-06T16:49:01.470717Z",
     "iopub.status.busy": "2022-11-06T16:49:01.469804Z",
     "iopub.status.idle": "2022-11-06T16:49:50.964739Z",
     "shell.execute_reply": "2022-11-06T16:49:50.965743Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.7.1\n",
      "0.11.1\n"
     ]
    }
   ],
   "source": [
    "from tsp.AP import csi\n",
    "\n",
    "import numpy as np\n",
    "from skimage import io\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "from timeit import default_timer\n",
    "import os\n",
    "from skimage import img_as_ubyte\n",
    "\n",
    "import deepcell\n",
    "from deepcell import image_generators\n",
    "from deepcell.utils.train_utils import rate_scheduler, get_callbacks, count_gpus\n",
    "from deepcell_toolbox.utils import resize, tile_image, untile_image\n",
    "from deepcell_toolbox.deep_watershed import deep_watershed\n",
    "from deepcell.losses import weighted_categorical_crossentropy\n",
    "from deepcell.model_zoo.panopticnet import PanopticNet\n",
    "\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.optimizers import SGD, Adam\n",
    "from tensorflow.keras.losses import MSE\n",
    "\n",
    "print(tf.__version__)\n",
    "print(deepcell.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1bac06f7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-06T16:49:51.002487Z",
     "iopub.status.busy": "2022-11-06T16:49:51.001208Z",
     "iopub.status.idle": "2022-11-06T22:05:32.486056Z",
     "shell.execute_reply": "2022-11-06T22:05:32.487031Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7\n",
      "(7, 1040, 1159, 1)\n",
      "(7, 1040, 1159, 1)\n",
      "2.0\n",
      "(7, 2080, 2318, 1)\n",
      "(7, 2080, 2318, 1)\n",
      "(7, 2080, 2318, 1)\n",
      "(7, 2080, 2318, 1)\n",
      "[0, 400, 800, 1200, 1568]\n",
      "[512, 912, 1312, 1712, 2080]\n",
      "[0, 512, 1024, 1536, 1806]\n",
      "[512, 1024, 1536, 2048, 2318]\n",
      "(175, 512, 512, 1)\n",
      "(175, 512, 512, 1)\n",
      "WARNING:tensorflow:Removing 6 of 175 images with fewer than 5 objects.\n",
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
      "94773248/94765736 [==============================] - 1s 0us/step\n",
      "94781440/94765736 [==============================] - 1s 0us/step\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/TensorFlow/2.7.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/keras/optimizer_v2/adam.py:105: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n",
      "  super(Adam, self).__init__(name, **kwargs)\n",
      "2023-07-03 00:31:29.624168: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /device:GPU:0 with 10429 MB memory:  -> device: 0, name: NVIDIA GeForce GTX 1080 Ti, pci bus id: 0000:5e:00.0, compute capability: 6.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training on 1 GPUs.\n",
      "Epoch 1/200\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-07-03 00:31:49.456756: I tensorflow/stream_executor/cuda/cuda_dnn.cc:366] Loaded cuDNN version 8202\n",
      "2023-07-03 00:32:12.234251: W tensorflow/core/common_runtime/bfc_allocator.cc:275] Allocator (GPU_0_bfc) ran out of memory trying to allocate 536.16MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.\n",
      "2023-07-03 00:32:12.248984: W tensorflow/core/common_runtime/bfc_allocator.cc:275] Allocator (GPU_0_bfc) ran out of memory trying to allocate 528.00MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.\n",
      "2023-07-03 00:32:12.249013: W tensorflow/core/kernels/gpu_utils.cc:49] Failed to allocate memory for convolution redzone checking; skipping this check. This is benign and only means that we won't check cudnn for out-of-bounds reads and writes. This message will only be printed once.\n",
      "2023-07-03 00:32:14.722666: W tensorflow/core/common_runtime/bfc_allocator.cc:275] Allocator (GPU_0_bfc) ran out of memory trying to allocate 536.16MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - ETA: 0s - loss: 0.0167 - semantic_0_loss: 0.0042 - semantic_1_loss: 0.0103 - semantic_2_loss: 0.0021WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 80s 649ms/step - loss: 0.0167 - semantic_0_loss: 0.0042 - semantic_1_loss: 0.0103 - semantic_2_loss: 0.0021 - lr: 1.0000e-04\n",
      "Epoch 2/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0146 - semantic_0_loss: 0.0037 - semantic_1_loss: 0.0093 - semantic_2_loss: 0.0016WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0146 - semantic_0_loss: 0.0037 - semantic_1_loss: 0.0093 - semantic_2_loss: 0.0016 - lr: 9.9000e-05\n",
      "Epoch 3/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0139 - semantic_0_loss: 0.0036 - semantic_1_loss: 0.0088 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0139 - semantic_0_loss: 0.0036 - semantic_1_loss: 0.0088 - semantic_2_loss: 0.0015 - lr: 9.8010e-05\n",
      "Epoch 4/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0140 - semantic_0_loss: 0.0036 - semantic_1_loss: 0.0089 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0140 - semantic_0_loss: 0.0036 - semantic_1_loss: 0.0089 - semantic_2_loss: 0.0015 - lr: 9.7030e-05\n",
      "Epoch 5/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0138 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0088 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 546ms/step - loss: 0.0138 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0088 - semantic_2_loss: 0.0015 - lr: 9.6060e-05\n",
      "Epoch 6/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0137 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0087 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0137 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0087 - semantic_2_loss: 0.0015 - lr: 9.5099e-05\n",
      "Epoch 7/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0136 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0086 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0136 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0086 - semantic_2_loss: 0.0015 - lr: 9.4148e-05\n",
      "Epoch 8/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0135 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0085 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0135 - semantic_0_loss: 0.0035 - semantic_1_loss: 0.0085 - semantic_2_loss: 0.0015 - lr: 9.3207e-05\n",
      "Epoch 9/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0134 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0085 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 546ms/step - loss: 0.0134 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0085 - semantic_2_loss: 0.0015 - lr: 9.2274e-05\n",
      "Epoch 10/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0134 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0085 - semantic_2_loss: 0.0015WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 561ms/step - loss: 0.0134 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0085 - semantic_2_loss: 0.0015 - lr: 9.1352e-05\n",
      "Epoch 11/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0133 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0084 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 541ms/step - loss: 0.0133 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0084 - semantic_2_loss: 0.0014 - lr: 9.0438e-05\n",
      "Epoch 12/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014 - lr: 8.9534e-05\n",
      "Epoch 13/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0133 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0084 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 555ms/step - loss: 0.0133 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0084 - semantic_2_loss: 0.0014 - lr: 8.8638e-05\n",
      "Epoch 14/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0133 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0084 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 549ms/step - loss: 0.0133 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0084 - semantic_2_loss: 0.0014 - lr: 8.7752e-05\n",
      "Epoch 15/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014 - lr: 8.6875e-05\n",
      "Epoch 16/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014 - lr: 8.6006e-05\n",
      "Epoch 17/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0132 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0083 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0132 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0083 - semantic_2_loss: 0.0014 - lr: 8.5146e-05\n",
      "Epoch 18/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0127 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0127 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014 - lr: 8.4294e-05\n",
      "Epoch 19/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0130 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014 - lr: 8.3451e-05\n",
      "Epoch 20/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0129 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 550ms/step - loss: 0.0129 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0082 - semantic_2_loss: 0.0014 - lr: 8.2617e-05\n",
      "Epoch 21/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0128 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0081 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 555ms/step - loss: 0.0128 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0081 - semantic_2_loss: 0.0014 - lr: 8.1791e-05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 22/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0127 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0127 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014 - lr: 8.0973e-05\n",
      "Epoch 23/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0129 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0081 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 561ms/step - loss: 0.0129 - semantic_0_loss: 0.0034 - semantic_1_loss: 0.0081 - semantic_2_loss: 0.0014 - lr: 8.0163e-05\n",
      "Epoch 24/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0125 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 546ms/step - loss: 0.0125 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0014 - lr: 7.9361e-05\n",
      "Epoch 25/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014 - lr: 7.8568e-05\n",
      "Epoch 26/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0127 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 555ms/step - loss: 0.0127 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014 - lr: 7.7782e-05\n",
      "Epoch 27/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0126 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0079 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0126 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0079 - semantic_2_loss: 0.0014 - lr: 7.7004e-05\n",
      "Epoch 28/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014 - lr: 7.6234e-05\n",
      "Epoch 29/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0125 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0079 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 553ms/step - loss: 0.0125 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0079 - semantic_2_loss: 0.0014 - lr: 7.5472e-05\n",
      "Epoch 30/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0124 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 551ms/step - loss: 0.0124 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0014 - lr: 7.4717e-05\n",
      "Epoch 31/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0123 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 540ms/step - loss: 0.0123 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013 - lr: 7.3970e-05\n",
      "Epoch 32/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0123 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0123 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0013 - lr: 7.3230e-05\n",
      "Epoch 33/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0080 - semantic_2_loss: 0.0014 - lr: 7.2498e-05\n",
      "Epoch 34/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0079 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0126 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0079 - semantic_2_loss: 0.0014 - lr: 7.1773e-05\n",
      "Epoch 35/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0124 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 552ms/step - loss: 0.0124 - semantic_0_loss: 0.0033 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0013 - lr: 7.1055e-05\n",
      "Epoch 36/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013 - lr: 7.0345e-05\n",
      "Epoch 37/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0124 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0014WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 543ms/step - loss: 0.0124 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0014 - lr: 6.9641e-05\n",
      "Epoch 38/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0124 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 556ms/step - loss: 0.0124 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0078 - semantic_2_loss: 0.0013 - lr: 6.8945e-05\n",
      "Epoch 39/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0121 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0121 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013 - lr: 6.8255e-05\n",
      "Epoch 40/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013 - lr: 6.7573e-05\n",
      "Epoch 41/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0121 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 572ms/step - loss: 0.0121 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013 - lr: 6.6897e-05\n",
      "Epoch 42/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013 - lr: 6.6228e-05\n",
      "Epoch 43/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0077 - semantic_2_loss: 0.0013 - lr: 6.5566e-05\n",
      "Epoch 44/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0119 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0119 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 6.4910e-05\n",
      "Epoch 45/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013 - lr: 6.4261e-05\n",
      "Epoch 46/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0121 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 569ms/step - loss: 0.0121 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013 - lr: 6.3619e-05\n",
      "Epoch 47/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 6.2982e-05\n",
      "Epoch 48/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0120 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0075 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 570ms/step - loss: 0.0120 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0075 - semantic_2_loss: 0.0013 - lr: 6.2353e-05\n",
      "Epoch 49/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0119 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 549ms/step - loss: 0.0119 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 6.1729e-05\n",
      "Epoch 50/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0119 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 546ms/step - loss: 0.0119 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 6.1112e-05\n",
      "Epoch 51/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 6.0501e-05\n",
      "Epoch 52/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 5.9896e-05\n",
      "Epoch 53/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0119 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0119 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 5.9297e-05\n",
      "Epoch 54/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 568ms/step - loss: 0.0122 - semantic_0_loss: 0.0032 - semantic_1_loss: 0.0076 - semantic_2_loss: 0.0013 - lr: 5.8704e-05\n",
      "Epoch 55/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0120 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0075 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 553ms/step - loss: 0.0120 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0075 - semantic_2_loss: 0.0013 - lr: 5.8117e-05\n",
      "Epoch 56/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 5.7535e-05\n",
      "Epoch 57/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0117 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 561ms/step - loss: 0.0117 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013 - lr: 5.6960e-05\n",
      "Epoch 58/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 5.6391e-05\n",
      "Epoch 59/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 5.5827e-05\n",
      "Epoch 60/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 546ms/step - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013 - lr: 5.5268e-05\n",
      "Epoch 61/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013 - lr: 5.4716e-05\n",
      "Epoch 62/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0115 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0115 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013 - lr: 5.4169e-05\n",
      "Epoch 63/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - ETA: 0s - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013 - lr: 5.3627e-05\n",
      "Epoch 64/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 542ms/step - loss: 0.0118 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0074 - semantic_2_loss: 0.0013 - lr: 5.3091e-05\n",
      "Epoch 65/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 556ms/step - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013 - lr: 5.2560e-05\n",
      "Epoch 66/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 565ms/step - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013 - lr: 5.2034e-05\n",
      "Epoch 67/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013 - lr: 5.1514e-05\n",
      "Epoch 68/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0117 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 553ms/step - loss: 0.0117 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013 - lr: 5.0999e-05\n",
      "Epoch 69/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 562ms/step - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013 - lr: 5.0489e-05\n",
      "Epoch 70/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013 - lr: 4.9984e-05\n",
      "Epoch 71/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0116 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0073 - semantic_2_loss: 0.0013 - lr: 4.9484e-05\n",
      "Epoch 72/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013 - lr: 4.8989e-05\n",
      "Epoch 73/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013 - lr: 4.8499e-05\n",
      "Epoch 74/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 542ms/step - loss: 0.0115 - semantic_0_loss: 0.0031 - semantic_1_loss: 0.0072 - semantic_2_loss: 0.0013 - lr: 4.8014e-05\n",
      "Epoch 75/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013 - lr: 4.7534e-05\n",
      "Epoch 76/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 541ms/step - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0013 - lr: 4.7059e-05\n",
      "Epoch 77/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013 - lr: 4.6588e-05\n",
      "Epoch 78/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 569ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012 - lr: 4.6122e-05\n",
      "Epoch 79/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.5661e-05\n",
      "Epoch 80/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 551ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.5204e-05\n",
      "Epoch 81/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0114 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0071 - semantic_2_loss: 0.0013 - lr: 4.4752e-05\n",
      "Epoch 82/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 550ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.4305e-05\n",
      "Epoch 83/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.3862e-05\n",
      "Epoch 84/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 543ms/step - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.3423e-05\n",
      "Epoch 85/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012 - lr: 4.2989e-05\n",
      "Epoch 86/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.2559e-05\n",
      "Epoch 87/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 541ms/step - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 4.2133e-05\n",
      "Epoch 88/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 4.1712e-05\n",
      "Epoch 89/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 558ms/step - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012 - lr: 4.1295e-05\n",
      "Epoch 90/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 25s 575ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.0882e-05\n",
      "Epoch 91/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 561ms/step - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 4.0473e-05\n",
      "Epoch 92/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 559ms/step - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012 - lr: 4.0068e-05\n",
      "Epoch 93/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 3.9668e-05\n",
      "Epoch 94/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 562ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 3.9271e-05\n",
      "Epoch 95/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 557ms/step - loss: 0.0112 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 3.8878e-05\n",
      "Epoch 96/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.8490e-05\n",
      "Epoch 97/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.8105e-05\n",
      "Epoch 98/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 559ms/step - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.7724e-05\n",
      "Epoch 99/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 542ms/step - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 3.7346e-05\n",
      "Epoch 100/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 556ms/step - loss: 0.0113 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0070 - semantic_2_loss: 0.0012 - lr: 3.6973e-05\n",
      "Epoch 101/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 550ms/step - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.6603e-05\n",
      "Epoch 102/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 556ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.6237e-05\n",
      "Epoch 103/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0111 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 3.5875e-05\n",
      "Epoch 104/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.5516e-05\n",
      "Epoch 105/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.5161e-05\n",
      "Epoch 106/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 546ms/step - loss: 0.0110 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0069 - semantic_2_loss: 0.0012 - lr: 3.4809e-05\n",
      "Epoch 107/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.4461e-05\n",
      "Epoch 108/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.4117e-05\n",
      "Epoch 109/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.3775e-05\n",
      "Epoch 110/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.3438e-05\n",
      "Epoch 111/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 565ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.3103e-05\n",
      "Epoch 112/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 546ms/step - loss: 0.0108 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.2772e-05\n",
      "Epoch 113/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0109 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.2445e-05\n",
      "Epoch 114/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 550ms/step - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.2120e-05\n",
      "Epoch 115/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 3.1799e-05\n",
      "Epoch 116/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 557ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 3.1481e-05\n",
      "Epoch 117/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 553ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.1166e-05\n",
      "Epoch 118/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 571ms/step - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.0854e-05\n",
      "Epoch 119/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 3.0546e-05\n",
      "Epoch 120/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 559ms/step - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 3.0240e-05\n",
      "Epoch 121/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0109 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 2.9938e-05\n",
      "Epoch 122/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.9639e-05\n",
      "Epoch 123/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0110 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0068 - semantic_2_loss: 0.0012 - lr: 2.9342e-05\n",
      "Epoch 124/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - 24s 563ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.9049e-05\n",
      "Epoch 125/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.8758e-05\n",
      "Epoch 126/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 564ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.8471e-05\n",
      "Epoch 127/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.8186e-05\n",
      "Epoch 128/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 548ms/step - loss: 0.0108 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0067 - semantic_2_loss: 0.0012 - lr: 2.7904e-05\n",
      "Epoch 129/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.7625e-05\n",
      "Epoch 130/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 557ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.7349e-05\n",
      "Epoch 131/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.7075e-05\n",
      "Epoch 132/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 550ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.6805e-05\n",
      "Epoch 133/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.6537e-05\n",
      "Epoch 134/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.6271e-05\n",
      "Epoch 135/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.6009e-05\n",
      "Epoch 136/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 556ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.5748e-05\n",
      "Epoch 137/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.5491e-05\n",
      "Epoch 138/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0108 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 553ms/step - loss: 0.0108 - semantic_0_loss: 0.0030 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.5236e-05\n",
      "Epoch 139/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 543ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.4984e-05\n",
      "Epoch 140/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 549ms/step - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.4734e-05\n",
      "Epoch 141/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 541ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 2.4487e-05\n",
      "Epoch 142/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.4242e-05\n",
      "Epoch 143/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 537ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.3999e-05\n",
      "Epoch 144/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0107 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0066 - semantic_2_loss: 0.0012 - lr: 2.3759e-05\n",
      "Epoch 145/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 550ms/step - loss: 0.0104 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.3522e-05\n",
      "Epoch 146/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.3286e-05\n",
      "Epoch 147/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.3054e-05\n",
      "Epoch 148/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.2823e-05\n",
      "Epoch 149/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 558ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.2595e-05\n",
      "Epoch 150/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 558ms/step - loss: 0.0104 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.2369e-05\n",
      "Epoch 151/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 557ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.2145e-05\n",
      "Epoch 152/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 555ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 2.1924e-05\n",
      "Epoch 153/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 2.1704e-05\n",
      "Epoch 154/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 541ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.1487e-05\n",
      "Epoch 155/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.1273e-05\n",
      "Epoch 156/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 2.1060e-05\n",
      "Epoch 157/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 557ms/step - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 2.0849e-05\n",
      "Epoch 158/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 2.0641e-05\n",
      "Epoch 159/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.0434e-05\n",
      "Epoch 160/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 556ms/step - loss: 0.0106 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0065 - semantic_2_loss: 0.0012 - lr: 2.0230e-05\n",
      "Epoch 161/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 2.0028e-05\n",
      "Epoch 162/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 25s 574ms/step - loss: 0.0105 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 1.9827e-05\n",
      "Epoch 163/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.9629e-05\n",
      "Epoch 164/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 1.9433e-05\n",
      "Epoch 165/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - 24s 557ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.9239e-05\n",
      "Epoch 166/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 538ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 1.9046e-05\n",
      "Epoch 167/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.8856e-05\n",
      "Epoch 168/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 543ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.8667e-05\n",
      "Epoch 169/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.8480e-05\n",
      "Epoch 170/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 558ms/step - loss: 0.0104 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.8296e-05\n",
      "Epoch 171/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 541ms/step - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.8113e-05\n",
      "Epoch 172/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.7932e-05\n",
      "Epoch 173/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 540ms/step - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.7752e-05\n",
      "Epoch 174/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.7575e-05\n",
      "Epoch 175/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0104 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 550ms/step - loss: 0.0104 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0064 - semantic_2_loss: 0.0012 - lr: 1.7399e-05\n",
      "Epoch 176/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 559ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0011 - lr: 1.7225e-05\n",
      "Epoch 177/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.7053e-05\n",
      "Epoch 178/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.6882e-05\n",
      "Epoch 179/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011 - lr: 1.6713e-05\n",
      "Epoch 180/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.6546e-05\n",
      "Epoch 181/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0103 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.6381e-05\n",
      "Epoch 182/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 555ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.6217e-05\n",
      "Epoch 183/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 560ms/step - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0012 - lr: 1.6055e-05\n",
      "Epoch 184/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 25s 573ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.5894e-05\n",
      "Epoch 185/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 560ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.5735e-05\n",
      "Epoch 186/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42/42 [==============================] - ETA: 0s - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 545ms/step - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.5578e-05\n",
      "Epoch 187/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 552ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.5422e-05\n",
      "Epoch 188/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.5268e-05\n",
      "Epoch 189/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 556ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.5115e-05\n",
      "Epoch 190/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011 - lr: 1.4964e-05\n",
      "Epoch 191/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 562ms/step - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011 - lr: 1.4814e-05\n",
      "Epoch 192/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 544ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.4666e-05\n",
      "Epoch 193/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 549ms/step - loss: 0.0102 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.4520e-05\n",
      "Epoch 194/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011 - lr: 1.4374e-05\n",
      "Epoch 195/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 554ms/step - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011 - lr: 1.4231e-05\n",
      "Epoch 196/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 24s 551ms/step - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.4088e-05\n",
      "Epoch 197/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 548ms/step - loss: 0.0103 - semantic_0_loss: 0.0029 - semantic_1_loss: 0.0063 - semantic_2_loss: 0.0011 - lr: 1.3948e-05\n",
      "Epoch 198/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 547ms/step - loss: 0.0101 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0062 - semantic_2_loss: 0.0011 - lr: 1.3808e-05\n",
      "Epoch 199/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0099 - semantic_0_loss: 0.0027 - semantic_1_loss: 0.0060 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 542ms/step - loss: 0.0099 - semantic_0_loss: 0.0027 - semantic_1_loss: 0.0060 - semantic_2_loss: 0.0011 - lr: 1.3670e-05\n",
      "Epoch 200/200\n",
      "42/42 [==============================] - ETA: 0s - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
      "42/42 [==============================] - 23s 543ms/step - loss: 0.0100 - semantic_0_loss: 0.0028 - semantic_1_loss: 0.0061 - semantic_2_loss: 0.0011 - lr: 1.3533e-05\n",
      "/home/yfong/deeplearning/dense_cell_segmentation\n"
     ]
    },
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'images/training/testimages'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/loc/scratch/24187210/ipykernel_19394/4273105693.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m    157\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetcwd\u001b[0m\u001b[0;34m(\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    158\u001b[0m \u001b[0mINPUT_PATH\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"images/test/\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 159\u001b[0;31m \u001b[0mFILENAMES\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mf\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlistdir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"images/training/testimages\"\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[0m\u001b[1;32m    160\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFILENAMES\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'images/training/testimages'"
     ]
    }
   ],
   "source": [
    "#for ii in [1,2,3,4,5,6,7]:\n",
    "ii=7\n",
    "idx=\"training{}\".format(ii)\n",
    "INPUT_PATH=\"images/\"+idx+\"/\"\n",
    "model_name = 'tn1.0_nuclear_K_512x512resized_'+idx \n",
    "model_path = '{}.h5'.format(model_name)\n",
    "\n",
    "import glob\n",
    "FILENAMES = glob.glob(INPUT_PATH+\"*_img.png\")\n",
    "print(len(FILENAMES))\n",
    "\n",
    "imgs = [io.imread(CURR_IM_NAME)[:,:,0] for CURR_IM_NAME in FILENAMES]\n",
    "X_train = tf.stack(imgs)\n",
    "X_train = np.expand_dims(X_train, axis=-1)\n",
    "print(X_train.shape)\n",
    "\n",
    "masks = [io.imread(CURR_IM_NAME.replace(\"img\",\"masks\")) for CURR_IM_NAME in FILENAMES]\n",
    "y_train = tf.stack(masks)\n",
    "y_train = np.expand_dims(y_train, axis=-1)\n",
    "print(y_train.shape)\n",
    "\n",
    "# resize image\n",
    "mpp_select=1.3 # based on DeepCell_tn_nuclear.ipynb, the best value is 1.2, but 1.3 makes scale factor an integer\n",
    "shape = X_train.shape\n",
    "scale_factor = mpp_select / 0.65\n",
    "print(scale_factor)\n",
    "new_shape = (int(shape[1] * scale_factor),\n",
    "             int(shape[2] * scale_factor))\n",
    "\n",
    "X_train_resized = resize(X_train, new_shape, data_format='channels_last')\n",
    "y_train_resized = resize(y_train, new_shape, data_format='channels_last', labeled_image=True)\n",
    "print(X_train_resized.shape)\n",
    "print(y_train_resized.shape)\n",
    "\n",
    "# cut each resized image into 5x5 patches of size 512x512 \n",
    "print(X_train_resized.shape)\n",
    "print(y_train_resized.shape)\n",
    "\n",
    "x_starts=[0,400,400*2,400*3,X_train_resized.shape[1]-512]\n",
    "x_ends=[x+512 for x in x_starts]\n",
    "print(x_starts)\n",
    "print(x_ends)\n",
    "\n",
    "y_starts=[0,512,512*2,512*3,X_train_resized.shape[2]-512]\n",
    "y_ends=[x+512 for x in y_starts]\n",
    "print(y_starts)\n",
    "print(y_ends)\n",
    "\n",
    "sub_X=tf.concat([tf.concat([X_train_resized[:, x_starts[i]:x_ends[i], y_starts[j]:y_ends[j], :] for i in range(len(x_starts)) ], axis=0) for j in range(len(y_starts))], axis=0)\n",
    "sub_X = np.array(sub_X, dtype=np.uint8) # tf.stack changes the dtype \n",
    "print(sub_X.shape)\n",
    "sub_y=tf.concat([tf.concat([y_train_resized[:, x_starts[i]:x_ends[i], y_starts[j]:y_ends[j], :] for i in range(len(x_starts)) ], axis=0) for j in range(len(y_starts))], axis=0)\n",
    "sub_y = np.array(sub_y, dtype=np.uint16) # tf.stack changes the dtype \n",
    "print(sub_y.shape)\n",
    "\n",
    "# create dataloader\n",
    "seed=0\n",
    "min_objects = 5\n",
    "\n",
    "transforms = ['inner-distance', 'outer-distance', 'fgbg']\n",
    "transforms_kwargs = {'outer-distance': {'erosion_width': 0}}\n",
    "\n",
    "# use augmentation for training but not validation\n",
    "datagen = image_generators.SemanticDataGenerator(\n",
    "    rotation_range=180,\n",
    "    fill_mode='reflect',\n",
    "    zoom_range=(0.75, 1.25),\n",
    "    horizontal_flip=True,\n",
    "    vertical_flip=True)\n",
    "\n",
    "datagen_val = image_generators.CroppingDataGenerator()\n",
    "\n",
    "batch_size = 4 # 8 causes memory outage\n",
    "\n",
    "train_data = datagen.flow(\n",
    "    {'X': sub_X, 'y': sub_y},\n",
    "    seed=seed,\n",
    "    transforms=transforms,\n",
    "    transforms_kwargs=transforms_kwargs,\n",
    "    min_objects=min_objects,\n",
    "    batch_size=batch_size)\n",
    "\n",
    "val_data = None\n",
    "\n",
    "semantic_classes = [1, 1, 2] # inner distance, outer distance, fgbg\n",
    "\n",
    "model = PanopticNet(\n",
    "    backbone='resnet50',\n",
    "    input_shape=(512,512,1),\n",
    "    norm_method='whole_image',\n",
    "    num_semantic_classes=semantic_classes)\n",
    "\n",
    "lr = 1e-4\n",
    "optimizer = Adam(lr=lr, clipnorm=0.001)\n",
    "lr_sched = rate_scheduler(lr=lr, decay=0.99)\n",
    "\n",
    "# Create a dictionary of losses for each semantic head\n",
    "\n",
    "def semantic_loss(n_classes):\n",
    "    def _semantic_loss(y_pred, y_true):\n",
    "        if n_classes > 1:\n",
    "            return 0.01 * weighted_categorical_crossentropy(\n",
    "                y_pred, y_true, n_classes=n_classes)\n",
    "        return MSE(y_pred, y_true)\n",
    "    return _semantic_loss\n",
    "\n",
    "loss = {}\n",
    "\n",
    "# Give losses for all of the semantic heads\n",
    "for layer in model.layers:\n",
    "    if layer.name.startswith('semantic_'):\n",
    "        n_classes = layer.output_shape[-1]\n",
    "        loss[layer.name] = semantic_loss(n_classes)\n",
    "\n",
    "model.compile(loss=loss, optimizer=optimizer)\n",
    "\n",
    "model.load_weights(starting_model_path, by_name=True)\n",
    "\n",
    "[(layer.name, layer.output_shape) for layer in filter(lambda x: x.name.startswith('semantic_'), model.layers)]\n",
    "\n",
    "\n",
    "# fit the model\n",
    "print('Training on', count_gpus(), 'GPUs.')\n",
    "\n",
    "train_callbacks = get_callbacks(\n",
    "    model_path,\n",
    "    lr_sched=lr_sched,\n",
    "#     monitor=\"val_loss\",\n",
    "    # monitor='loss', # training loss\n",
    "    verbose=1)          \n",
    "\n",
    "loss_history = model.fit(\n",
    "    train_data,\n",
    "    steps_per_epoch=train_data.y.shape[0] // batch_size, # \n",
    "    epochs=epochs, \n",
    "#     validation_data=val_data,\n",
    "#     validation_steps=val_data.y.shape[0] // batch_size,\n",
    "    callbacks=train_callbacks)\n",
    "\n",
    "model.save_weights(model_path)\n",
    "\n",
    "prediction_model = PanopticNet(\n",
    "    backbone='resnet50',\n",
    "    norm_method='whole_image',\n",
    "    num_semantic_classes=[1, 1], # inner distance, outer distance\n",
    "    input_shape= (512,512,1)\n",
    ")\n",
    "\n",
    "prediction_model.load_weights(model_path, by_name=True)\n",
    "\n",
    "from deepcell.applications import NuclearSegmentation\n",
    "app = NuclearSegmentation(prediction_model)\n",
    "[(layer.name, layer.output_shape) for layer in filter(lambda x: x.name.startswith('semantic_'), app.model.layers)]\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8190b6c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/yfong/deeplearning/dense_cell_segmentation\n",
      "['M872956_JML_Position9_CD3_test_masks.png', 'M872956_JML_Position8_CD3_test_masks.png', 'M872956_JML_Position10_CD3_test_masks.png', 'M872956_JML_Position8_CD4_test_masks.png', 'M926910_CFL_Position13_CD3_test_masks.png', 'M872956_JML_Position8_CD8_test_masks.png', 'M926910_CFL_Position7_CD3_test_masks.png']\n",
      "M872956_JML_Position9_CD3_test_masks.png\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n",
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M872956_JML_Position8_CD3_test_masks.png\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n",
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M872956_JML_Position10_CD3_test_masks.png\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n",
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M872956_JML_Position8_CD4_test_masks.png\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n",
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M926910_CFL_Position13_CD3_test_masks.png\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n",
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M872956_JML_Position8_CD8_test_masks.png\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n",
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M926910_CFL_Position7_CD3_test_masks.png\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n",
      "/app/software/DeepCell/0.11.1-foss-2021b-CUDA-11.4.1/lib/python3.9/site-packages/deepcell_toolbox/deep_watershed.py:179: FutureWarning: `selem` is a deprecated argument name for `h_maxima`. It will be removed in version 1.0.Please use `footprint` instead.\n",
      "  markers = h_maxima(image=maxima,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.34763948497854075, 0.4405737704918033], [0.4597069597069597, 0.6043956043956044], [0.3596330275229358, 0.46371681415929206], [0.5792349726775956, 0.5714285714285714], [0.30133333333333334, 0.3713592233009709], [0.48863636363636365, 0.48756218905472637], [0.3959731543624161, 0.42484662576687116]]\n",
      "[[0.6792525921434196, 0.7008687737987954], [0.6312479463058475, 0.6661010014792792], [0.6452686501958117, 0.6459803567964051], [0.7351109824507992, 0.7340661472858063], [0.6644093678134864, 0.6337896724337856], [0.7491257244978152, 0.749604177689936], [0.5589633015274665, 0.5531025309833009]]\n",
      "                                           0         1         2\n",
      "0   M872956_JML_Position9_CD3_test_masks.png  0.347639  0.440574\n",
      "1   M872956_JML_Position8_CD3_test_masks.png  0.459707  0.604396\n",
      "2  M872956_JML_Position10_CD3_test_masks.png  0.359633  0.463717\n",
      "3   M872956_JML_Position8_CD4_test_masks.png  0.579235  0.571429\n",
      "4  M926910_CFL_Position13_CD3_test_masks.png  0.301333  0.371359\n",
      "5   M872956_JML_Position8_CD8_test_masks.png  0.488636  0.487562\n",
      "6   M926910_CFL_Position7_CD3_test_masks.png  0.395973  0.424847\n",
      "                                           0         1         2\n",
      "0   M872956_JML_Position9_CD3_test_masks.png  0.679253  0.700869\n",
      "1   M872956_JML_Position8_CD3_test_masks.png  0.631248  0.666101\n",
      "2  M872956_JML_Position10_CD3_test_masks.png  0.645269   0.64598\n",
      "3   M872956_JML_Position8_CD4_test_masks.png  0.735111  0.734066\n",
      "4  M926910_CFL_Position13_CD3_test_masks.png  0.664409   0.63379\n",
      "5   M872956_JML_Position8_CD8_test_masks.png  0.749126  0.749604\n",
      "6   M926910_CFL_Position7_CD3_test_masks.png  0.558963  0.553103\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "print(os.getcwd())\n",
    "INPUT_PATH=\"images/test_images/\"\n",
    "MASK_PATH=\"images/test_gtmasks/\"\n",
    "FILENAMES = [f for f in os.listdir(MASK_PATH)]\n",
    "print(FILENAMES)\n",
    "\n",
    "\n",
    "# more detailed mapping of image_mpp parameter\n",
    "mpps=[1,1.3]\n",
    "\n",
    "AP_mat=[]\n",
    "ARI_mat=[]\n",
    "for CURR_IM_NAME in FILENAMES:\n",
    "    print(CURR_IM_NAME)\n",
    "    im0      = io.imread(os.path.join(INPUT_PATH, CURR_IM_NAME.replace(\"masks\",\"img\")))\n",
    "    mask_true= io.imread(os.path.join(MASK_PATH,  CURR_IM_NAME))\n",
    "\n",
    "    x = np.expand_dims(im0, axis=-1)\n",
    "    x = np.expand_dims(x, axis=0)\n",
    "    y, tile_info = app._tile_input(x)\n",
    "    AP_arr=[]\n",
    "    ARI_arr=[]\n",
    "    for mpp in mpps:\n",
    "        prd = app._untile_output(app.predict(y, image_mpp=mpp), tile_info)[0,:,:,0]\n",
    "        AP_arr.append(csi(mask_true, prd))\n",
    "        ARI_arr.append(adjusted_rand_score(mask_true.flatten(), prd.flatten()))\n",
    "    AP_mat.append(AP_arr)\n",
    "    ARI_mat.append(ARI_arr)\n",
    "\n",
    "print(AP_mat)\n",
    "print(ARI_mat)\n",
    "\n",
    "import pandas as pd\n",
    "df = pd.DataFrame([FILENAMES, [x[0] for x in AP_mat], [x[1] for x in AP_mat]])\n",
    "print(df.transpose())\n",
    "df.to_csv('images/training/csi_'+model_name+'.txt', index=False, header=False)\n",
    "\n",
    "df = pd.DataFrame([FILENAMES, [x[0] for x in ARI_mat], [x[1] for x in ARI_mat]])\n",
    "print(df.transpose())\n",
    "df.to_csv('images/training/ari_'+model_name+'.txt', index=False, header=False)"
   ]
  }
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