/usr/bin/python3.6 /home/allen/Project/deep-learning/PlanDoseQA/train.py
2022-04-23 10:26:39.799518: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
Using TensorFlow backend.
2022-04-23 10:26:41.305521: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2022-04-23 10:26:41.306140: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2022-04-23 10:26:41.322925: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.323322: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2022-04-23 10:26:41.323336: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2022-04-23 10:26:41.324786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2022-04-23 10:26:41.324813: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2022-04-23 10:26:41.325407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2022-04-23 10:26:41.325547: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2022-04-23 10:26:41.327018: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2022-04-23 10:26:41.327348: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2022-04-23 10:26:41.327423: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2022-04-23 10:26:41.327472: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.327872: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.328281: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2022-04-23 10:26:41.328298: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2022-04-23 10:26:41.665340: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2022-04-23 10:26:41.665360: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2022-04-23 10:26:41.665366: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2022-04-23 10:26:41.665489: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.665861: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.666231: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.666592: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9892 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
2022-04-23 10:26:41.667566: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2022-04-23 10:26:41.667621: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.667998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2022-04-23 10:26:41.668015: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2022-04-23 10:26:41.668037: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2022-04-23 10:26:41.668046: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2022-04-23 10:26:41.668054: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2022-04-23 10:26:41.668061: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2022-04-23 10:26:41.668069: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2022-04-23 10:26:41.668077: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2022-04-23 10:26:41.668085: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2022-04-23 10:26:41.668114: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.668485: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.668829: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2022-04-23 10:26:41.668879: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2022-04-23 10:26:41.668910: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/mixed_precision/loss_scale.py:56: DynamicLossScale.__init__ (from tensorflow.python.training.experimental.loss_scale) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.keras.mixed_precision.LossScaleOptimizer instead. LossScaleOptimizer now has all the functionality of DynamicLossScale
2022-04-23 10:26:41.669700: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2022-04-23 10:26:41.669743: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.670065: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2022-04-23 10:26:41.670075: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2022-04-23 10:26:41.670086: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2022-04-23 10:26:41.670094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2022-04-23 10:26:41.670101: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2022-04-23 10:26:41.670108: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2022-04-23 10:26:41.670116: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2022-04-23 10:26:41.670123: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2022-04-23 10:26:41.670131: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2022-04-23 10:26:41.670157: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.670522: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.670864: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2022-04-23 10:26:41.670876: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2022-04-23 10:26:41.670879: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2022-04-23 10:26:41.670882: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2022-04-23 10:26:41.670920: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.671287: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-23 10:26:41.671629: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9892 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
WARNING:tensorflow:tf.keras.mixed_precision.experimental.LossScaleOptimizer is deprecated. Please use tf.keras.mixed_precision.LossScaleOptimizer instead. Note that the non-experimental LossScaleOptimizer does not take a DynamicLossScale but instead takes the dynamic configuration directly in the constructor. For example:
  opt = tf.keras.mixed_precision.experimental.LossScaleOptimizer(opt)

2022-04-23 10:26:42.070662: I tensorflow/core/profiler/lib/profiler_session.cc:136] Profiler session initializing.
2022-04-23 10:26:42.070676: I tensorflow/core/profiler/lib/profiler_session.cc:155] Profiler session started.
2022-04-23 10:26:42.070697: I tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1365] Profiler found 1 GPUs
2022-04-23 10:26:42.070820: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcupti.so.11.0'; dlerror: libcupti.so.11.0: cannot open shared object file: No such file or directory
2022-04-23 10:26:42.070860: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcupti.so'; dlerror: libcupti.so: cannot open shared object file: No such file or directory
2022-04-23 10:26:42.070868: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1415] function cupti_interface_->Subscribe( &subscriber_, (CUpti_CallbackFunc)ApiCallback, this)failed with error CUPTI could not be loaded or symbol could not be found.
2022-04-23 10:26:42.070879: I tensorflow/core/profiler/lib/profiler_session.cc:172] Profiler session tear down.
2022-04-23 10:26:42.070889: E tensorflow/core/profiler/internal/gpu/cupti_tracer.cc:1496] function cupti_interface_->Finalize()failed with error CUPTI could not be loaded or symbol could not be found.
2022-04-23 10:26:43.856450: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2022-04-23 10:26:43.876116: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 3800000000 Hz
Epoch 1/1000
2022-04-23 10:26:50.234553: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2022-04-23 10:26:51.574235: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2022-04-23 10:26:51.857949: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2022-04-23 10:26:53.014910: I tensorflow/stream_executor/cuda/cuda_driver.cc:789] failed to allocate 1.66G (1784399616 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
969/969 [==============================] - 679s 691ms/step - loss: 0.5165 - ssim: 0.9810 - accuracy: 0.7224

Epoch 00001: loss improved from inf to 0.44547, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 2/1000
969/969 [==============================] - 673s 691ms/step - loss: 0.5961 - ssim: 0.9802 - accuracy: 0.7237

Epoch 00002: loss did not improve from 0.44547
Epoch 3/1000
969/969 [==============================] - 673s 691ms/step - loss: 0.4399 - ssim: 0.9811 - accuracy: 0.7197

Epoch 00003: loss improved from 0.44547 to 0.35932, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 4/1000
969/969 [==============================] - 672s 690ms/step - loss: 0.3261 - ssim: 0.9805 - accuracy: 0.7256

Epoch 00004: loss did not improve from 0.35932
Epoch 5/1000
969/969 [==============================] - 673s 690ms/step - loss: 0.2731 - ssim: 0.9793 - accuracy: 0.7265

Epoch 00005: loss improved from 0.35932 to 0.31248, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 6/1000
969/969 [==============================] - 686s 705ms/step - loss: 0.4064 - ssim: 0.9819 - accuracy: 0.7294

Epoch 00006: loss did not improve from 0.31248
Epoch 7/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.9276 - ssim: 0.9714 - accuracy: 0.7244

Epoch 00007: loss did not improve from 0.31248
Epoch 8/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.2440 - ssim: 0.9842 - accuracy: 0.7269

Epoch 00008: loss did not improve from 0.31248
Epoch 9/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.5218 - ssim: 0.9784 - accuracy: 0.7206

Epoch 00009: loss did not improve from 0.31248
Epoch 10/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.3336 - ssim: 0.9809 - accuracy: 0.7335

Epoch 00010: loss improved from 0.31248 to 0.26970, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 11/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.3400 - ssim: 0.9823 - accuracy: 0.7307

Epoch 00011: loss did not improve from 0.26970
Epoch 12/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.2790 - ssim: 0.9837 - accuracy: 0.7330

Epoch 00012: loss did not improve from 0.26970
Epoch 13/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.3693 - ssim: 0.9848 - accuracy: 0.7310

Epoch 00013: loss did not improve from 0.26970
Epoch 14/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.7187 - ssim: 0.9772 - accuracy: 0.7242

Epoch 00014: loss did not improve from 0.26970
Epoch 15/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.1885 - ssim: 0.9861 - accuracy: 0.7472

Epoch 00015: loss improved from 0.26970 to 0.22638, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 16/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.2969 - ssim: 0.9827 - accuracy: 0.7240

Epoch 00016: loss did not improve from 0.22638
Epoch 17/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.4542 - ssim: 0.9811 - accuracy: 0.7276

Epoch 00017: loss did not improve from 0.22638
Epoch 18/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.4196 - ssim: 0.9817 - accuracy: 0.7297

Epoch 00018: loss did not improve from 0.22638
Epoch 19/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.2745 - ssim: 0.9846 - accuracy: 0.7342

Epoch 00019: loss did not improve from 0.22638
Epoch 20/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.3190 - ssim: 0.9838 - accuracy: 0.7228

Epoch 00020: loss did not improve from 0.22638
Epoch 21/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.2735 - ssim: 0.9871 - accuracy: 0.7315

Epoch 00021: loss did not improve from 0.22638
Epoch 22/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.3854 - ssim: 0.9811 - accuracy: 0.7333

Epoch 00022: loss did not improve from 0.22638
Epoch 23/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.2092 - ssim: 0.9862 - accuracy: 0.7249

Epoch 00023: loss did not improve from 0.22638
Epoch 24/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.4254 - ssim: 0.9810 - accuracy: 0.7290

Epoch 00024: loss did not improve from 0.22638
Epoch 25/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.3333 - ssim: 0.9856 - accuracy: 0.7278

Epoch 00025: loss did not improve from 0.22638
Epoch 26/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.3841 - ssim: 0.9822 - accuracy: 0.7251

Epoch 00026: loss did not improve from 0.22638
Epoch 27/1000
969/969 [==============================] - 692s 711ms/step - loss: 0.2765 - ssim: 0.9863 - accuracy: 0.7329

Epoch 00027: loss did not improve from 0.22638
Epoch 28/1000
969/969 [==============================] - 694s 713ms/step - loss: 0.3334 - ssim: 0.9838 - accuracy: 0.7342

Epoch 00028: loss did not improve from 0.22638
Epoch 29/1000
969/969 [==============================] - 695s 713ms/step - loss: 0.2289 - ssim: 0.9869 - accuracy: 0.7281

Epoch 00029: loss did not improve from 0.22638
Epoch 30/1000
969/969 [==============================] - 694s 713ms/step - loss: 0.3447 - ssim: 0.9833 - accuracy: 0.7217

Epoch 00030: loss did not improve from 0.22638
Epoch 31/1000
969/969 [==============================] - 695s 712ms/step - loss: 0.2062 - ssim: 0.9822 - accuracy: 0.7269

Epoch 00031: loss improved from 0.22638 to 0.19987, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 32/1000
969/969 [==============================] - 694s 713ms/step - loss: 0.2560 - ssim: 0.9836 - accuracy: 0.7219

Epoch 00032: loss did not improve from 0.19987
Epoch 33/1000
969/969 [==============================] - 695s 713ms/step - loss: 0.2703 - ssim: 0.9849 - accuracy: 0.7305

Epoch 00033: loss did not improve from 0.19987
Epoch 34/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.3016 - ssim: 0.9854 - accuracy: 0.7278

Epoch 00034: loss did not improve from 0.19987
Epoch 35/1000
969/969 [==============================] - 692s 710ms/step - loss: 0.2487 - ssim: 0.9841 - accuracy: 0.7350

Epoch 00035: loss did not improve from 0.19987
Epoch 36/1000
969/969 [==============================] - 674s 692ms/step - loss: 0.2938 - ssim: 0.9867 - accuracy: 0.7317

Epoch 00036: loss did not improve from 0.19987
Epoch 37/1000
969/969 [==============================] - 672s 690ms/step - loss: 0.3406 - ssim: 0.9848 - accuracy: 0.7316

Epoch 00037: loss did not improve from 0.19987
Epoch 38/1000
969/969 [==============================] - 672s 690ms/step - loss: 0.2399 - ssim: 0.9845 - accuracy: 0.7306

Epoch 00038: loss did not improve from 0.19987
Epoch 39/1000
969/969 [==============================] - 671s 689ms/step - loss: 0.3537 - ssim: 0.9842 - accuracy: 0.7322

Epoch 00039: loss did not improve from 0.19987
Epoch 40/1000
969/969 [==============================] - 671s 689ms/step - loss: 0.2485 - ssim: 0.9880 - accuracy: 0.7378

Epoch 00040: loss did not improve from 0.19987
Epoch 41/1000
969/969 [==============================] - 684s 702ms/step - loss: 0.2620 - ssim: 0.9869 - accuracy: 0.7277

Epoch 00041: loss did not improve from 0.19987
Epoch 42/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.2691 - ssim: 0.9865 - accuracy: 0.7311

Epoch 00042: loss did not improve from 0.19987
Epoch 43/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.8826 - ssim: 0.9814 - accuracy: 0.7291

Epoch 00043: loss did not improve from 0.19987
Epoch 44/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.2065 - ssim: 0.9847 - accuracy: 0.7271

Epoch 00044: loss did not improve from 0.19987
Epoch 45/1000
969/969 [==============================] - 692s 711ms/step - loss: 0.1645 - ssim: 0.9870 - accuracy: 0.7374

Epoch 00045: loss did not improve from 0.19987
Epoch 46/1000
969/969 [==============================] - 693s 711ms/step - loss: 0.2137 - ssim: 0.9877 - accuracy: 0.7327

Epoch 00046: loss did not improve from 0.19987
Epoch 47/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.3256 - ssim: 0.9819 - accuracy: 0.7339

Epoch 00047: loss did not improve from 0.19987
Epoch 48/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.2760 - ssim: 0.9871 - accuracy: 0.7336

Epoch 00048: loss did not improve from 0.19987
Epoch 49/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.2717 - ssim: 0.9854 - accuracy: 0.7350

Epoch 00049: loss did not improve from 0.19987
Epoch 50/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.2533 - ssim: 0.9826 - accuracy: 0.7244

Epoch 00050: loss did not improve from 0.19987
Epoch 51/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.1772 - ssim: 0.9890 - accuracy: 0.7395

Epoch 00051: loss did not improve from 0.19987
Epoch 52/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.6463 - ssim: 0.9790 - accuracy: 0.7255

Epoch 00052: loss did not improve from 0.19987
Epoch 53/1000
969/969 [==============================] - 693s 712ms/step - loss: 0.2685 - ssim: 0.9876 - accuracy: 0.7302

Epoch 00053: loss did not improve from 0.19987
Epoch 54/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.2158 - ssim: 0.9864 - accuracy: 0.7306

Epoch 00054: loss did not improve from 0.19987
Epoch 55/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.2847 - ssim: 0.9871 - accuracy: 0.7270

Epoch 00055: loss did not improve from 0.19987
Epoch 56/1000
969/969 [==============================] - 694s 712ms/step - loss: 0.3182 - ssim: 0.9848 - accuracy: 0.7312

Epoch 00056: loss did not improve from 0.19987
Epoch 57/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.3150 - ssim: 0.9870 - accuracy: 0.7345

Epoch 00057: loss did not improve from 0.19987
Epoch 58/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1769 - ssim: 0.9885 - accuracy: 0.7288

Epoch 00058: loss did not improve from 0.19987
Epoch 59/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2028 - ssim: 0.9883 - accuracy: 0.7326

Epoch 00059: loss did not improve from 0.19987
Epoch 60/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2420 - ssim: 0.9883 - accuracy: 0.7332

Epoch 00060: loss did not improve from 0.19987
Epoch 61/1000
969/969 [==============================] - 696s 715ms/step - loss: 0.4973 - ssim: 0.9835 - accuracy: 0.7271

Epoch 00061: loss did not improve from 0.19987
Epoch 62/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.4091 - ssim: 0.9878 - accuracy: 0.7316

Epoch 00062: loss did not improve from 0.19987
Epoch 63/1000
969/969 [==============================] - 695s 713ms/step - loss: 0.2117 - ssim: 0.9887 - accuracy: 0.7311

Epoch 00063: loss did not improve from 0.19987
Epoch 64/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2114 - ssim: 0.9868 - accuracy: 0.7255

Epoch 00064: loss improved from 0.19987 to 0.18251, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 65/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.3600 - ssim: 0.9856 - accuracy: 0.7270

Epoch 00065: loss did not improve from 0.18251
Epoch 66/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2107 - ssim: 0.9889 - accuracy: 0.7412

Epoch 00066: loss did not improve from 0.18251
Epoch 67/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2347 - ssim: 0.9873 - accuracy: 0.7293

Epoch 00067: loss did not improve from 0.18251
Epoch 68/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.3010 - ssim: 0.9879 - accuracy: 0.7287

Epoch 00068: loss did not improve from 0.18251
Epoch 69/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2173 - ssim: 0.9879 - accuracy: 0.7304

Epoch 00069: loss did not improve from 0.18251
Epoch 70/1000
969/969 [==============================] - 696s 715ms/step - loss: 0.1722 - ssim: 0.9892 - accuracy: 0.7325

Epoch 00070: loss did not improve from 0.18251
Epoch 71/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.2608 - ssim: 0.9864 - accuracy: 0.7356

Epoch 00071: loss did not improve from 0.18251
Epoch 72/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.2013 - ssim: 0.9882 - accuracy: 0.7267

Epoch 00072: loss did not improve from 0.18251
Epoch 73/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1659 - ssim: 0.9902 - accuracy: 0.7322

Epoch 00073: loss improved from 0.18251 to 0.18083, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 74/1000
969/969 [==============================] - 694s 714ms/step - loss: 0.2203 - ssim: 0.9870 - accuracy: 0.7319

Epoch 00074: loss did not improve from 0.18083
Epoch 75/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1719 - ssim: 0.9892 - accuracy: 0.7386

Epoch 00075: loss improved from 0.18083 to 0.17424, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 76/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.2322 - ssim: 0.9866 - accuracy: 0.7305

Epoch 00076: loss did not improve from 0.17424
Epoch 77/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.3399 - ssim: 0.9864 - accuracy: 0.7316

Epoch 00077: loss did not improve from 0.17424
Epoch 78/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2440 - ssim: 0.9848 - accuracy: 0.7295

Epoch 00078: loss did not improve from 0.17424
Epoch 79/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1866 - ssim: 0.9892 - accuracy: 0.7384

Epoch 00079: loss did not improve from 0.17424
Epoch 80/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1917 - ssim: 0.9898 - accuracy: 0.7356

Epoch 00080: loss did not improve from 0.17424
Epoch 81/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1905 - ssim: 0.9899 - accuracy: 0.7366

Epoch 00081: loss did not improve from 0.17424
Epoch 82/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.3733 - ssim: 0.9822 - accuracy: 0.7225

Epoch 00082: loss did not improve from 0.17424
Epoch 83/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1709 - ssim: 0.9896 - accuracy: 0.7320

Epoch 00083: loss improved from 0.17424 to 0.14928, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 84/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.2219 - ssim: 0.9904 - accuracy: 0.7296

Epoch 00084: loss did not improve from 0.14928
Epoch 85/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.2318 - ssim: 0.9886 - accuracy: 0.7268

Epoch 00085: loss did not improve from 0.14928
Epoch 86/1000
969/969 [==============================] - 696s 715ms/step - loss: 0.1662 - ssim: 0.9893 - accuracy: 0.7264

Epoch 00086: loss did not improve from 0.14928
Epoch 87/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1488 - ssim: 0.9906 - accuracy: 0.7331

Epoch 00087: loss did not improve from 0.14928
Epoch 88/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1744 - ssim: 0.9906 - accuracy: 0.7319

Epoch 00088: loss did not improve from 0.14928
Epoch 89/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1862 - ssim: 0.9884 - accuracy: 0.7311

Epoch 00089: loss did not improve from 0.14928
Epoch 90/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1558 - ssim: 0.9904 - accuracy: 0.7296

Epoch 00090: loss did not improve from 0.14928
Epoch 91/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1526 - ssim: 0.9910 - accuracy: 0.7292

Epoch 00091: loss did not improve from 0.14928
Epoch 92/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.2015 - ssim: 0.9881 - accuracy: 0.7327

Epoch 00092: loss did not improve from 0.14928
Epoch 93/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1717 - ssim: 0.9904 - accuracy: 0.7340

Epoch 00093: loss did not improve from 0.14928
Epoch 94/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1962 - ssim: 0.9903 - accuracy: 0.7314

Epoch 00094: loss did not improve from 0.14928
Epoch 95/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1934 - ssim: 0.9881 - accuracy: 0.7323

Epoch 00095: loss did not improve from 0.14928
Epoch 96/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.6348 - ssim: 0.9800 - accuracy: 0.7251

Epoch 00096: loss did not improve from 0.14928
Epoch 97/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1914 - ssim: 0.9884 - accuracy: 0.7277

Epoch 00097: loss did not improve from 0.14928
Epoch 98/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1793 - ssim: 0.9902 - accuracy: 0.7385

Epoch 00098: loss did not improve from 0.14928
Epoch 99/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2025 - ssim: 0.9883 - accuracy: 0.7258

Epoch 00099: loss did not improve from 0.14928
Epoch 100/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1571 - ssim: 0.9909 - accuracy: 0.7342

Epoch 00100: loss did not improve from 0.14928
Epoch 101/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1738 - ssim: 0.9901 - accuracy: 0.7306

Epoch 00101: loss did not improve from 0.14928
Epoch 102/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1911 - ssim: 0.9874 - accuracy: 0.7292

Epoch 00102: loss did not improve from 0.14928
Epoch 103/1000
969/969 [==============================] - 695s 713ms/step - loss: 0.1518 - ssim: 0.9913 - accuracy: 0.7387

Epoch 00103: loss did not improve from 0.14928
Epoch 104/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1650 - ssim: 0.9892 - accuracy: 0.7304

Epoch 00104: loss improved from 0.14928 to 0.14763, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 105/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1715 - ssim: 0.9896 - accuracy: 0.7302

Epoch 00105: loss did not improve from 0.14763
Epoch 106/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1850 - ssim: 0.9877 - accuracy: 0.7364

Epoch 00106: loss did not improve from 0.14763
Epoch 107/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2168 - ssim: 0.9908 - accuracy: 0.7246

Epoch 00107: loss did not improve from 0.14763
Epoch 108/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.2845 - ssim: 0.9882 - accuracy: 0.7276

Epoch 00108: loss did not improve from 0.14763
Epoch 109/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1745 - ssim: 0.9889 - accuracy: 0.7255

Epoch 00109: loss did not improve from 0.14763
Epoch 110/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1381 - ssim: 0.9915 - accuracy: 0.7338

Epoch 00110: loss did not improve from 0.14763
Epoch 111/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2768 - ssim: 0.9887 - accuracy: 0.7289

Epoch 00111: loss did not improve from 0.14763
Epoch 112/1000
969/969 [==============================] - 695s 713ms/step - loss: 0.5161 - ssim: 0.9842 - accuracy: 0.7267

Epoch 00112: loss did not improve from 0.14763
Epoch 113/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2437 - ssim: 0.9899 - accuracy: 0.7324

Epoch 00113: loss did not improve from 0.14763
Epoch 114/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.1344 - ssim: 0.9922 - accuracy: 0.7311

Epoch 00114: loss improved from 0.14763 to 0.14319, saving model to ./model/model_8_mse_relu_v2.hdf5
Epoch 115/1000
969/969 [==============================] - 695s 714ms/step - loss: 0.1627 - ssim: 0.9904 - accuracy: 0.7351

Epoch 00115: loss did not improve from 0.14319
Epoch 116/1000
969/969 [==============================] - 696s 715ms/step - loss: 0.1282 - ssim: 0.9914 - accuracy: 0.7367

Epoch 00116: loss did not improve from 0.14319
Epoch 117/1000
969/969 [==============================] - 696s 714ms/step - loss: 0.2049 - ssim: 0.9896 - accuracy: 0.7285

Epoch 00117: loss did not improve from 0.14319
Epoch 118/1000
969/969 [==============================] - 687s 705ms/step - loss: 0.2049 - ssim: 0.9893 - accuracy: 0.7289