From 53691e943a9e17e273be243ac50a74b9602133fe Mon Sep 17 00:00:00 2001 From: jmq19950824 Date: Thu, 11 Aug 2022 20:43:48 +0800 Subject: [PATCH] update to the latest version --- demo.ipynb | 10570 ++++++++++++++++++++------------------------------- 1 file changed, 4097 insertions(+), 6473 deletions(-) diff --git a/demo.ipynb b/demo.ipynb index 3211ff3..82af61a 100644 --- a/demo.ipynb +++ b/demo.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2022-07-08T07:41:53.643140Z", @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2022-07-08T07:41:53.675055Z", @@ -70,16 +70,16 @@ "data": { "text/plain": [ "['10_cover.npz',\n", - " '11_fault.npz',\n", - " '12_glass.npz',\n", - " '13_HeartDisease.npz',\n", - " '14_Hepatitis.npz',\n", - " '15_http.npz',\n", - " '16_imgseg.npz',\n", + " '11_donors.npz',\n", + " '12_fault.npz',\n", + " '13_fraud.npz',\n", + " '14_glass.npz',\n", + " '15_Hepatitis.npz',\n", + " '16_http.npz',\n", " '17_InternetAds.npz',\n", " '18_Ionosphere.npz',\n", " '19_landsat.npz',\n", - " '1_abalone.npz',\n", + " '1_ALOI.npz',\n", " '20_letter.npz',\n", " '21_Lymphography.npz',\n", " '22_magic.gamma.npz',\n", @@ -88,86 +88,48 @@ " '25_musk.npz',\n", " '26_optdigits.npz',\n", " '27_PageBlocks.npz',\n", - " '28_Parkinson.npz',\n", - " '29_pendigits.npz',\n", - " '2_ALOI.npz',\n", - " '30_Pima.npz',\n", - " '31_satellite.npz',\n", - " '32_satimage-2.npz',\n", - " '33_shuttle.npz',\n", - " '34_skin.npz',\n", - " '35_smtp.npz',\n", - " '36_SpamBase.npz',\n", - " '37_speech.npz',\n", - " '38_Stamps.npz',\n", - " '39_thyroid.npz',\n", - " '3_annthyroid.npz',\n", - " '40_vertebral.npz',\n", - " '41_vowels.npz',\n", - " '42_Waveform.npz',\n", - " '43_WBC.npz',\n", - " '44_WDBC.npz',\n", - " '45_Wilt.npz',\n", - " '46_wine.npz',\n", - " '47_WPBC.npz',\n", - " '48_yeast.npz',\n", - " '49_CIFAR10_0.npz',\n", - " '49_CIFAR10_1.npz',\n", - " '49_CIFAR10_2.npz',\n", - " '49_CIFAR10_3.npz',\n", - " '49_CIFAR10_4.npz',\n", - " '49_CIFAR10_5.npz',\n", - " '49_CIFAR10_6.npz',\n", - " '49_CIFAR10_7.npz',\n", - " '49_CIFAR10_8.npz',\n", - " '49_CIFAR10_9.npz',\n", - " '4_Arrhythmia.npz',\n", - " '50_FashionMNIST_0.npz',\n", - " '50_FashionMNIST_1.npz',\n", - " '50_FashionMNIST_2.npz',\n", - " '50_FashionMNIST_3.npz',\n", - " '50_FashionMNIST_4.npz',\n", - " '50_FashionMNIST_5.npz',\n", - " '50_FashionMNIST_6.npz',\n", - " '50_FashionMNIST_7.npz',\n", - " '50_FashionMNIST_8.npz',\n", - " '50_FashionMNIST_9.npz',\n", - " '51_SVHN_0.npz',\n", - " '51_SVHN_1.npz',\n", - " '51_SVHN_2.npz',\n", - " '51_SVHN_3.npz',\n", - " '51_SVHN_4.npz',\n", - " '51_SVHN_5.npz',\n", - " '51_SVHN_6.npz',\n", - " '51_SVHN_7.npz',\n", - " '51_SVHN_8.npz',\n", - " '51_SVHN_9.npz',\n", - " '52_agnews_0.npz',\n", - " '52_agnews_1.npz',\n", - " '52_agnews_2.npz',\n", - " '52_agnews_3.npz',\n", - " '53_amazon.npz',\n", - " '54_imdb.npz',\n", - " '55_yelp.npz',\n", - " '5_breastw.npz',\n", + " '28_pendigits.npz',\n", + " '29_Pima.npz',\n", + " '2_annthyroid.npz',\n", + " '30_satellite.npz',\n", + " '31_satimage-2.npz',\n", + " '32_shuttle.npz',\n", + " '33_skin.npz',\n", + " '34_smtp.npz',\n", + " '35_SpamBase.npz',\n", + " '36_speech.npz',\n", + " '37_Stamps.npz',\n", + " '38_thyroid.npz',\n", + " '39_vertebral.npz',\n", + " '3_backdoor.npz',\n", + " '40_vowels.npz',\n", + " '41_Waveform.npz',\n", + " '42_WBC.npz',\n", + " '43_WDBC.npz',\n", + " '44_Wilt.npz',\n", + " '45_wine.npz',\n", + " '46_WPBC.npz',\n", + " '47_yeast.npz',\n", + " '4_breastw.npz',\n", + " '5_campaign.npz',\n", " '6_cardio.npz',\n", " '7_Cardiotocography.npz',\n", - " '8_comm.and.crime.npz',\n", - " '9_concrete.npz']" + " '8_celeba.npz',\n", + " '9_census.npz']" ] }, - "execution_count": 2, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "os.listdir('datasets')" + "os.listdir('datasets/Classical')" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2022-07-08T07:41:55.627834Z", @@ -184,7 +146,7 @@ "from baseline.Supervised import supervised\n", "\n", "# dataset and model list / dict\n", - "dataset_list = ['6_cardio', '25_musk', '26_optdigits', '37_speech', '41_vowels']\n", + "dataset_list = ['6_cardio', '25_musk', '26_optdigits', '36_speech', '40_vowels']\n", "model_dict = {'IForest': PYOD, 'DeepSVDD': PYOD, 'DevNet': DevNet, 'RF': supervised, 'CatB': supervised}\n", "\n", "# save the results\n", @@ -194,7 +156,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-07-08T07:50:14.507244Z", @@ -213,11 +175,11 @@ "{'Samples': 1831, 'Features': 21, 'Anomalies': 176, 'Anomalies Ratio(%)': 9.61}\n", "best param: None\n", "best param: None\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x0000025690E58D38> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A85DB64F78> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x0000025690E58D38> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A85DB64F78> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", @@ -254,193 +216,187 @@ "_________________________________________________________________\n", "None\n", "Epoch 1/100\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x0000025691080168> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A864D2B948> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x0000025691080168> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A864D2B948> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - " 1/36 [..............................] - ETA: 15s - loss: 5.7001WARNING:tensorflow:AutoGraph could not transform .test_function at 0x000002569106FF78> and will run it as-is.\n", + "26/36 [====================>.........] - ETA: 0s - loss: 3.7731 WARNING:tensorflow:AutoGraph could not transform .test_function at 0x000002A85D984D38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .test_function at 0x000002569106FF78> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .test_function at 0x000002A85D984D38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "36/36 [==============================] - 1s 5ms/step - loss: 3.5793 - val_loss: 2.5642\n", + "36/36 [==============================] - 1s 15ms/step - loss: 3.5793 - val_loss: 2.5642\n", "Epoch 2/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 2.3332 - val_loss: 1.9590\n", "Epoch 3/100\n", "36/36 [==============================] - 0s 2ms/step - loss: 1.8247 - val_loss: 1.5770\n", "Epoch 4/100\n", - "36/36 [==============================] - 0s 2ms/step - loss: 1.4952 - val_loss: 1.3395\n", + "36/36 [==============================] - 0s 3ms/step - loss: 1.4952 - val_loss: 1.3395\n", "Epoch 5/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 1.2543 - val_loss: 1.1465\n", "Epoch 6/100\n", "36/36 [==============================] - 0s 2ms/step - loss: 1.0795 - val_loss: 0.9893\n", "Epoch 7/100\n", - "36/36 [==============================] - 0s 2ms/step - loss: 0.9447 - val_loss: 0.8691\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.9447 - val_loss: 0.8691\n", "Epoch 8/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 0.8356 - val_loss: 0.7674\n", "Epoch 9/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.7454 - val_loss: 0.6875\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.7454 - val_loss: 0.6875\n", "Epoch 10/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.6720 - val_loss: 0.6246\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.6720 - val_loss: 0.6246\n", "Epoch 11/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 0.6102 - val_loss: 0.5674\n", "Epoch 12/100\n", - "36/36 [==============================] - 0s 3ms/step - loss: 0.5600 - val_loss: 0.5262\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.5600 - val_loss: 0.5262\n", "Epoch 13/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.5220 - val_loss: 0.4894\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.5220 - val_loss: 0.4894\n", "Epoch 14/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 0.4907 - val_loss: 0.4613\n", "Epoch 15/100\n", - "36/36 [==============================] - 0s 3ms/step - loss: 0.4636 - val_loss: 0.4324\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.4636 - val_loss: 0.4324\n", "Epoch 16/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.4382 - val_loss: 0.4101\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.4382 - val_loss: 0.4101\n", "Epoch 17/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 0.4174 - val_loss: 0.3914\n", "Epoch 18/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 0.3981 - val_loss: 0.3754\n", "Epoch 19/100\n", - "36/36 [==============================] - 0s 3ms/step - loss: 0.3813 - val_loss: 0.3613\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.3813 - val_loss: 0.3613\n", "Epoch 20/100\n", - "36/36 [==============================] - 0s 6ms/step - loss: 0.3672 - val_loss: 0.3516\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.3672 - val_loss: 0.3516\n", "Epoch 21/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.3537 - val_loss: 0.3365\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.3537 - val_loss: 0.3365\n", "Epoch 22/100\n", - "36/36 [==============================] - 0s 7ms/step - loss: 0.3409 - val_loss: 0.3217\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.3409 - val_loss: 0.3217\n", "Epoch 23/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.3295 - val_loss: 0.3116\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.3295 - val_loss: 0.3116\n", "Epoch 24/100\n", - "36/36 [==============================] - 0s 6ms/step - loss: 0.3186 - val_loss: 0.3050\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.3186 - val_loss: 0.3050\n", "Epoch 25/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.3084 - val_loss: 0.2920\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.3084 - val_loss: 0.2920\n", "Epoch 26/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.3004 - val_loss: 0.2907\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.3004 - val_loss: 0.2907\n", "Epoch 27/100\n", "36/36 [==============================] - 0s 4ms/step - loss: 0.2938 - val_loss: 0.2819\n", "Epoch 28/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2893 - val_loss: 0.2761\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2893 - val_loss: 0.2761\n", "Epoch 29/100\n", "36/36 [==============================] - 0s 3ms/step - loss: 0.2832 - val_loss: 0.2725\n", "Epoch 30/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2783 - val_loss: 0.2691\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2783 - val_loss: 0.2691\n", "Epoch 31/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2747 - val_loss: 0.2694\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2747 - val_loss: 0.2694\n", "Epoch 32/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2704 - val_loss: 0.2648\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2704 - val_loss: 0.2648\n", "Epoch 33/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2670 - val_loss: 0.2610\n", - "Epoch 34/100\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "36/36 [==============================] - 0s 4ms/step - loss: 0.2631 - val_loss: 0.2573\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2670 - val_loss: 0.2610\n", + "Epoch 34/100\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2631 - val_loss: 0.2573\n", "Epoch 35/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2612 - val_loss: 0.2568\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2612 - val_loss: 0.2568\n", "Epoch 36/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2592 - val_loss: 0.2537\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2592 - val_loss: 0.2537\n", "Epoch 37/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2563 - val_loss: 0.2512\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2563 - val_loss: 0.2512\n", "Epoch 38/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2546 - val_loss: 0.2507\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2546 - val_loss: 0.2507\n", "Epoch 39/100\n", - "36/36 [==============================] - 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0s 2ms/step - loss: 0.2388 - val_loss: 0.2376\n", "Epoch 50/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2376 - val_loss: 0.2373\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2376 - val_loss: 0.2373\n", "Epoch 51/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2368 - val_loss: 0.2361\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2368 - val_loss: 0.2361\n", "Epoch 52/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2367 - val_loss: 0.2374\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2367 - val_loss: 0.2374\n", "Epoch 53/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2374 - val_loss: 0.2367\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2374 - val_loss: 0.2367\n", "Epoch 54/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2356 - val_loss: 0.2333\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2356 - val_loss: 0.2333\n", "Epoch 55/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2336 - val_loss: 0.2339\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2336 - val_loss: 0.2339\n", "Epoch 56/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2328 - val_loss: 0.2324\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2328 - val_loss: 0.2324\n", "Epoch 57/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2324 - val_loss: 0.2337\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2324 - val_loss: 0.2337\n", "Epoch 58/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2323 - val_loss: 0.2346\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2323 - val_loss: 0.2346\n", "Epoch 59/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2323 - val_loss: 0.2336\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2323 - val_loss: 0.2336\n", "Epoch 60/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2313 - val_loss: 0.2334\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2313 - val_loss: 0.2334\n", "Epoch 61/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2301 - val_loss: 0.2337\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2301 - val_loss: 0.2337\n", "Epoch 62/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2300 - val_loss: 0.2299\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2300 - val_loss: 0.2299\n", "Epoch 63/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2290 - val_loss: 0.2303\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2290 - val_loss: 0.2303\n", "Epoch 64/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2296 - val_loss: 0.2318\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2296 - val_loss: 0.2318\n", "Epoch 65/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2299 - val_loss: 0.2330\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2299 - val_loss: 0.2330\n", "Epoch 66/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2289 - val_loss: 0.2313\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2289 - val_loss: 0.2313\n", "Epoch 67/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2278 - val_loss: 0.2310\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2278 - val_loss: 0.2310\n", "Epoch 68/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2295 - val_loss: 0.2297\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2295 - val_loss: 0.2297\n", "Epoch 69/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2271 - val_loss: 0.2297\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2271 - val_loss: 0.2297\n", "Epoch 70/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2268 - val_loss: 0.2306\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2268 - val_loss: 0.2306\n", "Epoch 71/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2271 - val_loss: 0.2304\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2271 - val_loss: 0.2304\n", "Epoch 72/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2264 - val_loss: 0.2272\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2264 - val_loss: 0.2272\n", "Epoch 73/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2254 - val_loss: 0.2293\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2254 - val_loss: 0.2293\n", "Epoch 74/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2261 - val_loss: 0.2300\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2261 - val_loss: 0.2300\n", "Epoch 75/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2269 - val_loss: 0.2290\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2269 - val_loss: 0.2290\n", "Epoch 76/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2262 - val_loss: 0.2284\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2262 - val_loss: 0.2284\n", "Epoch 77/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2248 - val_loss: 0.2257\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2248 - val_loss: 0.2257\n", "Epoch 78/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2238 - val_loss: 0.2263\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2238 - val_loss: 0.2263\n", "Epoch 79/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2240 - val_loss: 0.2266\n", + "36/36 [==============================] - 0s 2ms/step - loss: 0.2240 - val_loss: 0.2266\n", "Epoch 80/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2240 - val_loss: 0.2260\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2240 - val_loss: 0.2260\n", "Epoch 81/100\n", "36/36 [==============================] - 0s 4ms/step - loss: 0.2243 - val_loss: 0.2290\n", "Epoch 82/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2245 - val_loss: 0.2257\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2245 - val_loss: 0.2257\n", "Epoch 83/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2249 - val_loss: 0.2266\n", + "36/36 [==============================] - 0s 4ms/step - loss: 0.2249 - val_loss: 0.2266\n", "Epoch 84/100\n", "36/36 [==============================] - 0s 4ms/step - loss: 0.2235 - val_loss: 0.2274\n", "Epoch 85/100\n", @@ -448,1218 +404,1176 @@ "Epoch 86/100\n", "36/36 [==============================] - 0s 4ms/step - loss: 0.2231 - val_loss: 0.2243\n", "Epoch 87/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2234 - val_loss: 0.2249\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2234 - val_loss: 0.2249\n", "Epoch 88/100\n", - "36/36 [==============================] - 0s 6ms/step - loss: 0.2237 - val_loss: 0.2245\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2237 - val_loss: 0.2245\n", "Epoch 89/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2219 - val_loss: 0.2287\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2219 - val_loss: 0.2287\n", "Epoch 90/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2231 - val_loss: 0.2225\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2231 - val_loss: 0.2225\n", "Epoch 91/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2212 - val_loss: 0.2224\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2212 - val_loss: 0.2224\n", "Epoch 92/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2209 - val_loss: 0.2245\n", + "36/36 [==============================] - 0s 4ms/step - loss: 0.2209 - val_loss: 0.2245\n", "Epoch 93/100\n", - "36/36 [==============================] - 0s 7ms/step - loss: 0.2223 - val_loss: 0.2217\n", + "36/36 [==============================] - 0s 4ms/step - loss: 0.2223 - val_loss: 0.2217\n", "Epoch 94/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2213 - val_loss: 0.2234\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2213 - val_loss: 0.2234\n", "Epoch 95/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2210 - val_loss: 0.2239\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2210 - val_loss: 0.2239\n", "Epoch 96/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2208 - val_loss: 0.2216\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2208 - val_loss: 0.2216\n", "Epoch 97/100\n", - "36/36 [==============================] - 0s 5ms/step - loss: 0.2195 - val_loss: 0.2251\n", + "36/36 [==============================] - 0s 4ms/step - loss: 0.2195 - val_loss: 0.2251\n", "Epoch 98/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2213 - val_loss: 0.2210\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2213 - val_loss: 0.2210\n", "Epoch 99/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2204 - val_loss: 0.2239\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2204 - val_loss: 0.2239\n", "Epoch 100/100\n", - "36/36 [==============================] - 0s 4ms/step - loss: 0.2201 - val_loss: 0.2254\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x0000025690F32DC8> and will run it as-is.\n", + "36/36 [==============================] - 0s 3ms/step - loss: 0.2201 - val_loss: 0.2254\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A85DC31DC8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x0000025690F32DC8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A85DC31DC8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", "Training size: 1281, No. outliers: 12\n", "Epoch 1/50\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x0000025690B2DB88> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A86623A5E8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x0000025690B2DB88> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A86623A5E8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING:tensorflow:AutoGraph could not transform > and will run it as-is.\n", + "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", + "WARNING:tensorflow:AutoGraph could not transform > and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform > and will run it as-is.\n", + "WARNING: AutoGraph could not transform > and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "20/20 [==============================] - 4s 42ms/step - loss: 2.6113\n", + "20/20 [==============================] - 2s 19ms/step - loss: 2.6113\n", "Epoch 2/50\n", - "20/20 [==============================] - 1s 43ms/step - loss: 2.5092\n", + "20/20 [==============================] - 0s 20ms/step - loss: 2.5092\n", "Epoch 3/50\n", - "20/20 [==============================] - 1s 43ms/step - loss: 2.4254\n", + "20/20 [==============================] - 0s 20ms/step - loss: 2.4254\n", "Epoch 4/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 2.3352\n", + "20/20 [==============================] - 0s 20ms/step - loss: 2.3352\n", "Epoch 5/50\n", - "20/20 [==============================] - 1s 44ms/step - loss: 2.2528\n", + "20/20 [==============================] - 0s 22ms/step - loss: 2.2528\n", "Epoch 6/50\n", - "20/20 [==============================] - 1s 46ms/step - loss: 2.1757\n", + "20/20 [==============================] - 0s 24ms/step - loss: 2.1757\n", "Epoch 7/50\n", - "20/20 [==============================] - 1s 46ms/step - loss: 2.0780\n", + "20/20 [==============================] - 0s 25ms/step - loss: 2.0780\n", "Epoch 8/50\n", - "20/20 [==============================] - 1s 44ms/step - loss: 1.9833\n", + "20/20 [==============================] - 0s 23ms/step - loss: 1.9833\n", "Epoch 9/50\n", - "20/20 [==============================] - 1s 48ms/step - loss: 1.8887\n", + "20/20 [==============================] - 0s 23ms/step - loss: 1.8887\n", "Epoch 10/50\n", - "20/20 [==============================] - 1s 43ms/step - loss: 1.7759\n", + "20/20 [==============================] - 0s 24ms/step - loss: 1.7759\n", "Epoch 11/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 1.6884\n", + "20/20 [==============================] - 0s 18ms/step - loss: 1.6884\n", "Epoch 12/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 1.6021\n", + "20/20 [==============================] - 0s 19ms/step - loss: 1.6021\n", "Epoch 13/50\n", - "20/20 [==============================] - 1s 48ms/step - loss: 1.5143\n", + "20/20 [==============================] - 0s 20ms/step - loss: 1.5143\n", "Epoch 14/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 1.4463\n", + "20/20 [==============================] - 0s 20ms/step - loss: 1.4463\n", "Epoch 15/50\n", - "20/20 [==============================] - 1s 46ms/step - loss: 1.3844\n", + "20/20 [==============================] - 0s 24ms/step - loss: 1.3844\n", "Epoch 16/50\n", - "20/20 [==============================] - 1s 47ms/step - loss: 1.3041\n", + "20/20 [==============================] - 0s 18ms/step - loss: 1.3041\n", "Epoch 17/50\n", - "20/20 [==============================] - 1s 48ms/step - loss: 1.2343\n", + "20/20 [==============================] - 0s 17ms/step - loss: 1.2343\n", "Epoch 18/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 1.1601\n", + "20/20 [==============================] - 0s 17ms/step - loss: 1.1601\n", "Epoch 19/50\n", - "20/20 [==============================] - 1s 47ms/step - loss: 1.1050\n", + "20/20 [==============================] - 0s 20ms/step - loss: 1.1050\n", "Epoch 20/50\n", - "20/20 [==============================] - 1s 47ms/step - loss: 1.0670\n", + "20/20 [==============================] - 0s 19ms/step - loss: 1.0670\n", "Epoch 21/50\n", - "20/20 [==============================] - 1s 43ms/step - loss: 1.0465\n", + "20/20 [==============================] - 0s 22ms/step - loss: 1.0465\n", "Epoch 22/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 1.0341\n", + "20/20 [==============================] - 0s 22ms/step - loss: 1.0341\n", "Epoch 23/50\n", - "20/20 [==============================] - 1s 47ms/step - loss: 1.0117\n", + "20/20 [==============================] - 0s 22ms/step - loss: 1.0117\n", "Epoch 24/50\n", - "20/20 [==============================] - 1s 44ms/step - loss: 0.9782\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.9782\n", "Epoch 25/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 0.9769\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.9769\n", "Epoch 26/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.9716\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.9716\n", "Epoch 27/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.9261\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.9261\n", "Epoch 28/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.9384\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.9384\n", "Epoch 29/50\n", - "20/20 [==============================] - 1s 44ms/step - loss: 0.9182\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.9182\n", "Epoch 30/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.9306\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.9306\n", "Epoch 31/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 0.9137\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.9137\n", "Epoch 32/50\n", - "20/20 [==============================] - 1s 47ms/step - loss: 0.9005\n", + "20/20 [==============================] - 0s 25ms/step - loss: 0.9005\n", "Epoch 33/50\n", - "20/20 [==============================] - 1s 43ms/step - loss: 0.9003\n", + "20/20 [==============================] - 0s 25ms/step - loss: 0.9003\n", "Epoch 34/50\n", - "20/20 [==============================] - 1s 43ms/step - loss: 0.8745\n", + "20/20 [==============================] - 1s 32ms/step - loss: 0.8745\n", "Epoch 35/50\n", - "20/20 [==============================] - 1s 46ms/step - loss: 0.8753\n", + "20/20 [==============================] - 1s 28ms/step - loss: 0.8753\n", "Epoch 36/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.8713\n", + "20/20 [==============================] - 1s 30ms/step - loss: 0.8713\n", "Epoch 37/50\n", - "20/20 [==============================] - 1s 50ms/step - loss: 0.8690\n", + "20/20 [==============================] - 1s 30ms/step - loss: 0.8690\n", "Epoch 38/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.8483\n", + "20/20 [==============================] - 1s 30ms/step - loss: 0.8483\n", "Epoch 39/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.8555\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.8555\n", "Epoch 40/50\n", - "20/20 [==============================] - 1s 47ms/step - loss: 0.8416\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.8416\n", "Epoch 41/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.8228\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.8228\n", "Epoch 42/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.8439\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.8439\n", "Epoch 43/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.8245\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.8245\n", "Epoch 44/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.8181\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.8181\n", "Epoch 45/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.8054\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.8054\n", "Epoch 46/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.8058\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.8058\n", "Epoch 47/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.7976\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.7976\n", "Epoch 48/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.7972\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.7972\n", "Epoch 49/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.7974\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.7974\n", "Epoch 50/50\n", - "20/20 [==============================] - 1s 46ms/step - loss: 0.7631\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569AACB4C8> and will run it as-is.\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.7631\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A86628BD38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569AACB4C8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A86628BD38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", "Learning rate set to 0.011451\n", - "0:\tlearn: 0.6660157\ttotal: 146ms\tremaining: 2m 26s\n", - "1:\tlearn: 0.6365578\ttotal: 154ms\tremaining: 1m 16s\n", - "2:\tlearn: 0.6118627\ttotal: 158ms\tremaining: 52.6s\n", - "3:\tlearn: 0.5888814\ttotal: 162ms\tremaining: 40.4s\n", - "4:\tlearn: 0.5661308\ttotal: 168ms\tremaining: 33.4s\n", - "5:\tlearn: 0.5448045\ttotal: 178ms\tremaining: 29.6s\n", - "6:\tlearn: 0.5247282\ttotal: 188ms\tremaining: 26.7s\n", - "7:\tlearn: 0.5033319\ttotal: 198ms\tremaining: 24.5s\n", - "8:\tlearn: 0.4836736\ttotal: 210ms\tremaining: 23.1s\n", - "9:\tlearn: 0.4663022\ttotal: 218ms\tremaining: 21.6s\n", - "10:\tlearn: 0.4496327\ttotal: 223ms\tremaining: 20.1s\n", - "11:\tlearn: 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4.19s\tremaining: 16.8ms\n", + "996:\tlearn: 0.0036031\ttotal: 4.2s\tremaining: 12.6ms\n", + "997:\tlearn: 0.0035998\ttotal: 4.21s\tremaining: 8.44ms\n", + "998:\tlearn: 0.0035980\ttotal: 4.22s\tremaining: 4.22ms\n", + "999:\tlearn: 0.0035922\ttotal: 4.23s\tremaining: 0us\n", "current noise type: None\n", "{'Samples': 3062, 'Features': 166, 'Anomalies': 97, 'Anomalies Ratio(%)': 3.17}\n", "best param: None\n", "best param: None\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569AB2F438> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A8678738B8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569AB2F438> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A8678738B8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", @@ -1682,13 +1596,7 @@ " ambda) \n", " \n", " tf.math.reduce_mean_3 (TFOp () 0 \n", - " Lambda) \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + " Lambda) \n", " \n", " tf.__operators__.add_3 (TFO () 0 \n", " pLambda) \n", @@ -1702,45 +1610,45 @@ "_________________________________________________________________\n", "None\n", "Epoch 1/100\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002569AC11288> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A867C44EE8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x000002569AC11288> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A867C44EE8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "51/61 [========================>.....] - ETA: 0s - loss: 7.8240WARNING:tensorflow:AutoGraph could not transform .test_function at 0x000002569ACFFE58> and will run it as-is.\n", + "31/61 [==============>...............] - ETA: 0s - loss: 9.1377 WARNING:tensorflow:AutoGraph could not transform .test_function at 0x000002A868631D38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .test_function at 0x000002569ACFFE58> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .test_function at 0x000002A868631D38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "61/61 [==============================] - 2s 11ms/step - loss: 7.3430 - val_loss: 4.5381\n", + "61/61 [==============================] - 1s 4ms/step - loss: 7.3430 - val_loss: 4.5381\n", "Epoch 2/100\n", - "61/61 [==============================] - 0s 7ms/step - loss: 3.5348 - val_loss: 2.9142\n", + "61/61 [==============================] - 0s 2ms/step - loss: 3.5348 - val_loss: 2.9142\n", "Epoch 3/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 2.4972 - val_loss: 2.2388\n", + "61/61 [==============================] - 0s 2ms/step - loss: 2.4972 - val_loss: 2.2388\n", "Epoch 4/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 2.0142 - val_loss: 1.8898\n", + "61/61 [==============================] - 0s 2ms/step - loss: 2.0142 - val_loss: 1.8898\n", "Epoch 5/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.7264 - val_loss: 1.6607\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.7264 - val_loss: 1.6607\n", "Epoch 6/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.5529 - val_loss: 1.5061\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.5529 - val_loss: 1.5061\n", "Epoch 7/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 1.4164 - val_loss: 1.4221\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.4164 - val_loss: 1.4221\n", "Epoch 8/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.3415 - val_loss: 1.3473\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.3415 - val_loss: 1.3473\n", "Epoch 9/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.2798 - val_loss: 1.3169\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.2798 - val_loss: 1.3169\n", "Epoch 10/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.2383 - val_loss: 1.2506\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.2383 - val_loss: 1.2506\n", "Epoch 11/100\n", "61/61 [==============================] - 0s 4ms/step - loss: 1.1884 - val_loss: 1.1987\n", "Epoch 12/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.1548 - val_loss: 1.1640\n", + "61/61 [==============================] - 0s 4ms/step - loss: 1.1548 - val_loss: 1.1640\n", "Epoch 13/100\n", "61/61 [==============================] - 0s 4ms/step - loss: 1.1323 - val_loss: 1.1441\n", "Epoch 14/100\n", @@ -1748,1358 +1656,1310 @@ "Epoch 15/100\n", "61/61 [==============================] - 0s 4ms/step - loss: 1.0945 - val_loss: 1.1438\n", "Epoch 16/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.0778 - val_loss: 1.0961\n", + "61/61 [==============================] - 0s 4ms/step - loss: 1.0778 - val_loss: 1.0961\n", "Epoch 17/100\n", "61/61 [==============================] - 0s 4ms/step - loss: 1.0742 - val_loss: 1.1112\n", "Epoch 18/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.0841 - val_loss: 1.1242\n", + "61/61 [==============================] - 0s 4ms/step - loss: 1.0841 - val_loss: 1.1242\n", "Epoch 19/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.0569 - val_loss: 1.0845\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.0569 - val_loss: 1.0845\n", "Epoch 20/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.0465 - val_loss: 1.0588\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.0465 - val_loss: 1.0588\n", "Epoch 21/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.0592 - val_loss: 1.0854\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.0592 - val_loss: 1.0854\n", "Epoch 22/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.0369 - val_loss: 1.0560\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.0369 - val_loss: 1.0560\n", "Epoch 23/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.0146 - val_loss: 1.0421\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.0146 - val_loss: 1.0421\n", "Epoch 24/100\n", - "61/61 [==============================] - 0s 6ms/step - loss: 1.0063 - val_loss: 1.0391\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.0063 - val_loss: 1.0391\n", "Epoch 25/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.0211 - val_loss: 1.0982\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.0211 - val_loss: 1.0982\n", "Epoch 26/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.0717 - val_loss: 1.1014\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.0717 - val_loss: 1.1014\n", "Epoch 27/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.0419 - val_loss: 1.0301\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.0419 - val_loss: 1.0301\n", "Epoch 28/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 1.0257 - val_loss: 1.0376\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.0257 - val_loss: 1.0376\n", "Epoch 29/100\n", "61/61 [==============================] - 0s 4ms/step - loss: 1.1032 - val_loss: 1.1237\n", "Epoch 30/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.0428 - val_loss: 1.0123\n", + "61/61 [==============================] - 0s 3ms/step - loss: 1.0428 - val_loss: 1.0123\n", "Epoch 31/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9827 - val_loss: 1.0054\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9827 - val_loss: 1.0054\n", "Epoch 32/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9798 - val_loss: 1.0104\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9798 - val_loss: 1.0104\n", "Epoch 33/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9676 - val_loss: 0.9793\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9676 - val_loss: 0.9793\n", "Epoch 34/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9577 - val_loss: 0.9804\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9577 - val_loss: 0.9804\n", "Epoch 35/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9664 - val_loss: 1.0045\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9664 - val_loss: 1.0045\n", "Epoch 36/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9832 - val_loss: 1.0272\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9832 - val_loss: 1.0272\n", "Epoch 37/100\n", "61/61 [==============================] - 0s 4ms/step - loss: 1.0178 - val_loss: 1.0454\n", "Epoch 38/100\n", - "61/61 [==============================] - 0s 6ms/step - loss: 0.9934 - val_loss: 0.9906\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9934 - val_loss: 0.9906\n", "Epoch 39/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9998 - val_loss: 0.9643\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9998 - val_loss: 0.9643\n", "Epoch 40/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9568 - val_loss: 0.9843\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9568 - val_loss: 0.9843\n", "Epoch 41/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9828 - val_loss: 0.9986\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9828 - val_loss: 0.9986\n", "Epoch 42/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9866 - val_loss: 1.0020\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9866 - val_loss: 1.0020\n", "Epoch 43/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9863 - val_loss: 0.9834\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9863 - val_loss: 0.9834\n", "Epoch 44/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9541 - val_loss: 1.1236\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9541 - val_loss: 1.1236\n", "Epoch 45/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9623 - val_loss: 0.9612\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9623 - val_loss: 0.9612\n", "Epoch 46/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9585 - val_loss: 0.9885\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9585 - val_loss: 0.9885\n", "Epoch 47/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9754 - val_loss: 1.0569\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9754 - val_loss: 1.0569\n", "Epoch 48/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 1.0243 - val_loss: 1.0181\n", + "61/61 [==============================] - 0s 2ms/step - loss: 1.0243 - val_loss: 1.0181\n", "Epoch 49/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9979 - val_loss: 1.0629\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9979 - val_loss: 1.0629\n", "Epoch 50/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9641 - val_loss: 0.9533\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9641 - val_loss: 0.9533\n", "Epoch 51/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9367 - val_loss: 0.9571\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9367 - val_loss: 0.9571\n", "Epoch 52/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9318 - val_loss: 0.9465\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9318 - val_loss: 0.9465\n", "Epoch 53/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9336 - val_loss: 0.9719\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9336 - val_loss: 0.9719\n", "Epoch 54/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9759 - val_loss: 0.9958\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9759 - val_loss: 0.9958\n", "Epoch 55/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9536 - val_loss: 0.9588\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9536 - val_loss: 0.9588\n", "Epoch 56/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9326 - val_loss: 0.9630\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9326 - val_loss: 0.9630\n", "Epoch 57/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9860 - val_loss: 1.0026\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "61/61 [==============================] - 0s 2ms/step - loss: 0.9860 - val_loss: 1.0026\n", "Epoch 58/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9372 - val_loss: 0.9441\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9372 - val_loss: 0.9441\n", "Epoch 59/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9292 - val_loss: 0.9503\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9292 - val_loss: 0.9503\n", "Epoch 60/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9453 - val_loss: 1.0259\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9453 - val_loss: 1.0259\n", "Epoch 61/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9903 - val_loss: 1.0764\n", + "61/61 [==============================] - 0s 3ms/step - loss: 0.9903 - val_loss: 1.0764\n", "Epoch 62/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9826 - val_loss: 0.9982\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9826 - val_loss: 0.9982\n", "Epoch 63/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9299 - val_loss: 0.9224\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9299 - val_loss: 0.9224\n", "Epoch 64/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9298 - val_loss: 0.9307\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9298 - val_loss: 0.9307\n", "Epoch 65/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9531 - val_loss: 0.9755\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9531 - val_loss: 0.9755\n", "Epoch 66/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9402 - val_loss: 0.9479\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9402 - val_loss: 0.9479\n", "Epoch 67/100\n", - "61/61 [==============================] - 0s 6ms/step - loss: 0.9510 - val_loss: 0.9945\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9510 - val_loss: 0.9945\n", "Epoch 68/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9907 - val_loss: 1.0216\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9907 - val_loss: 1.0216\n", "Epoch 69/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9867 - val_loss: 0.9697\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9867 - val_loss: 0.9697\n", "Epoch 70/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9294 - val_loss: 0.9218\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9294 - val_loss: 0.9218\n", "Epoch 71/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9130 - val_loss: 0.9152\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9130 - val_loss: 0.9152\n", "Epoch 72/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9033 - val_loss: 0.9012\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9033 - val_loss: 0.9012\n", "Epoch 73/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9158 - val_loss: 0.9185\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9158 - val_loss: 0.9185\n", "Epoch 74/100\n", - "61/61 [==============================] - 0s 6ms/step - loss: 0.9397 - val_loss: 0.9508\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9397 - val_loss: 0.9508\n", "Epoch 75/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9327 - val_loss: 0.9242\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9327 - val_loss: 0.9242\n", "Epoch 76/100\n", - "61/61 [==============================] - 0s 5ms/step - loss: 0.9578 - val_loss: 0.9641\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9578 - val_loss: 0.9641\n", "Epoch 77/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9847 - val_loss: 0.9523\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9847 - val_loss: 0.9523\n", "Epoch 78/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9605 - val_loss: 0.9749\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9605 - val_loss: 0.9749\n", "Epoch 79/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9520 - val_loss: 0.9704\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9520 - val_loss: 0.9704\n", "Epoch 80/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9311 - val_loss: 0.9219\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9311 - val_loss: 0.9219\n", "Epoch 81/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9069 - val_loss: 0.9272\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9069 - val_loss: 0.9272\n", "Epoch 82/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9024 - val_loss: 0.9209\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9024 - val_loss: 0.9209\n", "Epoch 83/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9135 - val_loss: 0.9219\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9135 - val_loss: 0.9219\n", "Epoch 84/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9208 - val_loss: 0.9444\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9208 - val_loss: 0.9444\n", "Epoch 85/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9283 - val_loss: 0.9526\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9283 - val_loss: 0.9526\n", "Epoch 86/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9629 - val_loss: 0.9561\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9629 - val_loss: 0.9561\n", "Epoch 87/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9693 - val_loss: 0.9242\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9693 - val_loss: 0.9242\n", "Epoch 88/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9173 - val_loss: 0.9445\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9173 - val_loss: 0.9445\n", "Epoch 89/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9071 - val_loss: 0.9127\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9071 - val_loss: 0.9127\n", "Epoch 90/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9093 - val_loss: 0.9188\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9093 - val_loss: 0.9188\n", "Epoch 91/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9230 - val_loss: 0.9890\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9230 - val_loss: 0.9890\n", "Epoch 92/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9426 - val_loss: 0.9365\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9426 - val_loss: 0.9365\n", "Epoch 93/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9113 - val_loss: 0.9079\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9113 - val_loss: 0.9079\n", "Epoch 94/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9152 - val_loss: 0.9133\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9152 - val_loss: 0.9133\n", "Epoch 95/100\n", - "61/61 [==============================] - 0s 4ms/step - loss: 0.9020 - val_loss: 0.9143\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9020 - val_loss: 0.9143\n", "Epoch 96/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9466 - val_loss: 0.9412\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9466 - val_loss: 0.9412\n", "Epoch 97/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9639 - val_loss: 0.9513\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9639 - val_loss: 0.9513\n", "Epoch 98/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9192 - val_loss: 0.9432\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9192 - val_loss: 0.9432\n", "Epoch 99/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9044 - val_loss: 0.9352\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9044 - val_loss: 0.9352\n", "Epoch 100/100\n", - "61/61 [==============================] - 0s 3ms/step - loss: 0.9381 - val_loss: 0.9360\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569CB565E8> and will run it as-is.\n", + "61/61 [==============================] - 0s 2ms/step - loss: 0.9381 - val_loss: 0.9360\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A868779EE8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569CB565E8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A868779EE8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", "Training size: 2143, No. outliers: 6\n", "Epoch 1/50\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002569AF88828> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A867B9D1F8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x000002569AF88828> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A867B9D1F8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "20/20 [==============================] - 3s 35ms/step - loss: 1.8955\n", + "20/20 [==============================] - 1s 19ms/step - loss: 1.8955\n", "Epoch 2/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.8923\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.8923\n", "Epoch 3/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.6108\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.6108\n", "Epoch 4/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.5346\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.5346\n", "Epoch 5/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.4875\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.4875\n", "Epoch 6/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.4527\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.4527\n", "Epoch 7/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.4334\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.4334\n", "Epoch 8/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.4186\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.4186\n", "Epoch 9/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.4163\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.4163\n", "Epoch 10/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.3969\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3969\n", "Epoch 11/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.3735\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3735\n", "Epoch 12/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.3723\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3723\n", "Epoch 13/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.3701\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3701\n", "Epoch 14/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.3588\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3588\n", "Epoch 15/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 0.3657\n", + "20/20 [==============================] - 0s 16ms/step - loss: 0.3657\n", "Epoch 16/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.3378\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3378\n", "Epoch 17/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.3374\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3374\n", "Epoch 18/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.3329\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.3329\n", "Epoch 19/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.3283\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3283\n", "Epoch 20/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.3247\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3247\n", "Epoch 21/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 0.3220\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3220\n", "Epoch 22/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.3075\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3075\n", "Epoch 23/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 0.3104\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.3104\n", "Epoch 24/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 0.3123\n", - "Epoch 25/50\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "20/20 [==============================] - 1s 30ms/step - loss: 0.2949\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.3123\n", + "Epoch 25/50\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.2949\n", "Epoch 26/50\n", - "20/20 [==============================] - 1s 28ms/step - loss: 0.2951\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.2951\n", "Epoch 27/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.2940\n", + "20/20 [==============================] - 1s 25ms/step - loss: 0.2940\n", "Epoch 28/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.2898\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.2898\n", "Epoch 29/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.2802\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.2802\n", "Epoch 30/50\n", - "20/20 [==============================] - 1s 29ms/step - loss: 0.2794\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.2794\n", "Epoch 31/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.2720\n", + "20/20 [==============================] - 1s 26ms/step - loss: 0.2720\n", "Epoch 32/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.2749\n", + "20/20 [==============================] - 1s 25ms/step - loss: 0.2749\n", "Epoch 33/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.2591\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.2591\n", "Epoch 34/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.2615\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.2615\n", "Epoch 35/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.2547\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.2547\n", "Epoch 36/50\n", - "20/20 [==============================] - 1s 40ms/step - loss: 0.2599\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.2599\n", "Epoch 37/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.2574\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.2574\n", "Epoch 38/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.2573\n", + "20/20 [==============================] - 0s 16ms/step - loss: 0.2573\n", "Epoch 39/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.2499\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.2499\n", "Epoch 40/50\n", - "20/20 [==============================] - 1s 40ms/step - loss: 0.2463\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.2463\n", "Epoch 41/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.2441\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.2441\n", "Epoch 42/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.2425\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.2425\n", "Epoch 43/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.2394\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.2394\n", "Epoch 44/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.2404\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.2404\n", "Epoch 45/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.2384\n", + "20/20 [==============================] - 0s 16ms/step - loss: 0.2384\n", "Epoch 46/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.2255\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.2255\n", "Epoch 47/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.2279\n", + "20/20 [==============================] - 0s 17ms/step - loss: 0.2279\n", "Epoch 48/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.2291\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.2291\n", "Epoch 49/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.2181\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.2181\n", "Epoch 50/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.2172\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569CFC4EE8> and will run it as-is.\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.2172\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A869E08D38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569CFC4EE8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A869E08D38> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", "Learning rate set to 0.014265\n", - "0:\tlearn: 0.6553672\ttotal: 43.3ms\tremaining: 43.2s\n", - "1:\tlearn: 0.6146052\ttotal: 79.3ms\tremaining: 39.6s\n", - "2:\tlearn: 0.5831875\ttotal: 117ms\tremaining: 38.8s\n", - "3:\tlearn: 0.5503776\ttotal: 156ms\tremaining: 38.9s\n", - "4:\tlearn: 0.5173647\ttotal: 207ms\tremaining: 41.2s\n", - "5:\tlearn: 0.4902149\ttotal: 252ms\tremaining: 41.8s\n", - "6:\tlearn: 0.4615770\ttotal: 280ms\tremaining: 39.7s\n", - "7:\tlearn: 0.4375522\ttotal: 307ms\tremaining: 38s\n", - "8:\tlearn: 0.4133432\ttotal: 343ms\tremaining: 37.8s\n", - "9:\tlearn: 0.3864447\ttotal: 376ms\tremaining: 37.3s\n", - "10:\tlearn: 0.3646034\ttotal: 412ms\tremaining: 37.1s\n", - "11:\tlearn: 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Ratio(%)': 2.88}\n", "best param: None\n", "best param: None\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569B107048> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A86AF1E168> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569B107048> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A86AF1E168> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", @@ -3136,1410 +2996,1356 @@ "_________________________________________________________________\n", "None\n", "Epoch 1/100\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002569B1ED318> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A86AF1EDC8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING: AutoGraph could not transform .train_function at 0x000002569B1ED318> and will run it as-is.\n", + "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A86AF1EDC8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - " 99/103 [===========================>..] - ETA: 0s - loss: 6.7534WARNING:tensorflow:AutoGraph could not transform .test_function at 0x00000256995475E8> and will run it as-is.\n", + " 77/103 [=====================>........] - ETA: 0s - loss: 7.1901 WARNING:tensorflow:AutoGraph could not transform .test_function at 0x000002A86B180AF8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .test_function at 0x00000256995475E8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .test_function at 0x000002A86B180AF8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "103/103 [==============================] - 3s 8ms/step - loss: 6.6618 - val_loss: 6.2838\n", + "103/103 [==============================] - 1s 3ms/step - loss: 6.6618 - val_loss: 6.2838\n", "Epoch 2/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 3.9578 - val_loss: 4.6408\n", + "103/103 [==============================] - 0s 2ms/step - loss: 3.9578 - val_loss: 4.6408\n", "Epoch 3/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 2.7172 - val_loss: 3.4605\n", + "103/103 [==============================] - 0s 2ms/step - loss: 2.7172 - val_loss: 3.4605\n", "Epoch 4/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 2.0354 - val_loss: 2.8097\n", + "103/103 [==============================] - 0s 2ms/step - loss: 2.0354 - val_loss: 2.8097\n", "Epoch 5/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 1.6453 - val_loss: 2.2201\n", + "103/103 [==============================] - 0s 2ms/step - loss: 1.6453 - val_loss: 2.2201\n", "Epoch 6/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 1.3968 - val_loss: 1.9453\n", + "103/103 [==============================] - 0s 2ms/step - loss: 1.3968 - val_loss: 1.9453\n", "Epoch 7/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 1.2235 - val_loss: 1.6787\n", + "103/103 [==============================] - 0s 2ms/step - loss: 1.2235 - val_loss: 1.6787\n", "Epoch 8/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 1.0915 - val_loss: 1.5269\n", + "103/103 [==============================] - 0s 2ms/step - loss: 1.0915 - val_loss: 1.5269\n", "Epoch 9/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.9925 - val_loss: 1.3620\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.9925 - val_loss: 1.3620\n", "Epoch 10/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.9097 - val_loss: 1.1940\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.9097 - val_loss: 1.1940\n", "Epoch 11/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.8422 - val_loss: 1.1115\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.8422 - val_loss: 1.1115\n", "Epoch 12/100\n", - "103/103 [==============================] - 0s 5ms/step - loss: 0.7851 - val_loss: 1.0448\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.7851 - val_loss: 1.0448\n", "Epoch 13/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.7372 - val_loss: 0.9879\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.7372 - val_loss: 0.9879\n", "Epoch 14/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.7002 - val_loss: 0.8722\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.7002 - val_loss: 0.8722\n", "Epoch 15/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.6659 - val_loss: 0.8237\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.6659 - val_loss: 0.8237\n", "Epoch 16/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.6395 - val_loss: 0.7899\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.6395 - val_loss: 0.7899\n", "Epoch 17/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.6178 - val_loss: 0.7777\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.6178 - val_loss: 0.7777\n", "Epoch 18/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5967 - val_loss: 0.7385\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5967 - val_loss: 0.7385\n", "Epoch 19/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5815 - val_loss: 0.6845\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5815 - val_loss: 0.6845\n", "Epoch 20/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5654 - val_loss: 0.6761\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5654 - val_loss: 0.6761\n", "Epoch 21/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.5501 - val_loss: 0.6804\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5501 - val_loss: 0.6804\n", "Epoch 22/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5381 - val_loss: 0.6566\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5381 - val_loss: 0.6566\n", "Epoch 23/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5296 - val_loss: 0.6152\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5296 - val_loss: 0.6152\n", "Epoch 24/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.5235 - val_loss: 0.6039\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5235 - val_loss: 0.6039\n", "Epoch 25/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.5165 - val_loss: 0.6442\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5165 - val_loss: 0.6442\n", "Epoch 26/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.5125 - val_loss: 0.5685\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5125 - val_loss: 0.5685\n", "Epoch 27/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5071 - val_loss: 0.6032\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5071 - val_loss: 0.6032\n", "Epoch 28/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5045 - val_loss: 0.5841\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5045 - val_loss: 0.5841\n", "Epoch 29/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4988 - val_loss: 0.5594\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4988 - val_loss: 0.5594\n", "Epoch 30/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4983 - val_loss: 0.5560\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4983 - val_loss: 0.5560\n", "Epoch 31/100\n", "103/103 [==============================] - 0s 3ms/step - loss: 0.4922 - val_loss: 0.5165\n", "Epoch 32/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4930 - val_loss: 0.5981\n", + "103/103 [==============================] - 0s 3ms/step - loss: 0.4930 - val_loss: 0.5981\n", "Epoch 33/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4919 - val_loss: 0.5759\n", + "103/103 [==============================] - 0s 3ms/step - loss: 0.4919 - val_loss: 0.5759\n", "Epoch 34/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4914 - val_loss: 0.5597\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4914 - val_loss: 0.5597\n", "Epoch 35/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.5011 - val_loss: 0.5291\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.5011 - val_loss: 0.5291\n", "Epoch 36/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4877 - val_loss: 0.5185\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4877 - val_loss: 0.5185\n", "Epoch 37/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4795 - val_loss: 0.4970\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4795 - val_loss: 0.4970\n", "Epoch 38/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4802 - val_loss: 0.4966\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4802 - val_loss: 0.4966\n", "Epoch 39/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4783 - val_loss: 0.5672\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4783 - val_loss: 0.5672\n", "Epoch 40/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4780 - val_loss: 0.5264\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4780 - val_loss: 0.5264\n", "Epoch 41/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4730 - val_loss: 0.5367\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4730 - val_loss: 0.5367\n", "Epoch 42/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.4773 - val_loss: 0.5446\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4773 - val_loss: 0.5446\n", "Epoch 43/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4790 - val_loss: 0.4969\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4790 - val_loss: 0.4969\n", "Epoch 44/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4721 - val_loss: 0.4985\n", + "103/103 [==============================] - 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0s 2ms/step - loss: 0.4705 - val_loss: 0.5197\n", "Epoch 50/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4815 - val_loss: 0.5588\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4815 - val_loss: 0.5588\n", "Epoch 51/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4742 - val_loss: 0.5842\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4742 - val_loss: 0.5842\n", "Epoch 52/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4765 - val_loss: 0.5105\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4765 - val_loss: 0.5105\n", "Epoch 53/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4643 - val_loss: 0.4867\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4643 - val_loss: 0.4867\n", "Epoch 54/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4643 - val_loss: 0.5298\n", + "103/103 [==============================] - 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0s 2ms/step - loss: 0.4661 - val_loss: 0.4971\n", "Epoch 60/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4694 - val_loss: 0.5532\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4694 - val_loss: 0.5532\n", "Epoch 61/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4693 - val_loss: 0.5487\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4693 - val_loss: 0.5487\n", "Epoch 62/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.4618 - val_loss: 0.4902\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4618 - val_loss: 0.4902\n", "Epoch 63/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4635 - val_loss: 0.5233\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4635 - val_loss: 0.5233\n", "Epoch 64/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4649 - val_loss: 0.5477\n", + "103/103 [==============================] - 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0s 2ms/step - loss: 0.4586 - val_loss: 0.5016\n", "Epoch 96/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.4590 - val_loss: 0.4919\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4590 - val_loss: 0.4919\n", "Epoch 97/100\n", "103/103 [==============================] - 0s 3ms/step - loss: 0.4614 - val_loss: 0.5165\n", "Epoch 98/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.4560 - val_loss: 0.4975\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4560 - val_loss: 0.4975\n", "Epoch 99/100\n", - "103/103 [==============================] - 0s 4ms/step - loss: 0.4554 - val_loss: 0.4901\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4554 - val_loss: 0.4901\n", "Epoch 100/100\n", - "103/103 [==============================] - 0s 3ms/step - loss: 0.4586 - val_loss: 0.5843\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569AEE9168> and will run it as-is.\n", + "103/103 [==============================] - 0s 2ms/step - loss: 0.4586 - val_loss: 0.5843\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A86B1801F8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569AEE9168> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A86B1801F8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", "Training size: 3651, No. outliers: 10\n", "Epoch 1/50\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x0000025699364A68> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A859A66048> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x0000025699364A68> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A859A66048> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "20/20 [==============================] - 3s 35ms/step - loss: 2.6008\n", + "20/20 [==============================] - 2s 25ms/step - loss: 2.6008\n", "Epoch 2/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 2.2897\n", + "20/20 [==============================] - 0s 23ms/step - loss: 2.2897\n", "Epoch 3/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 1.9644\n", + "20/20 [==============================] - 0s 22ms/step - loss: 1.9644\n", "Epoch 4/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 1.5778\n", + "20/20 [==============================] - 0s 19ms/step - loss: 1.5778\n", "Epoch 5/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 1.1767\n", + "20/20 [==============================] - 0s 19ms/step - loss: 1.1767\n", "Epoch 6/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.9690\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.9690\n", "Epoch 7/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.8805\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.8805\n", "Epoch 8/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.7858\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.7858\n", "Epoch 9/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.6960\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.6960\n", "Epoch 10/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.6357\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.6357\n", "Epoch 11/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.5969\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.5969\n", "Epoch 12/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.5560\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.5560\n", "Epoch 13/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.5505\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.5505\n", "Epoch 14/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.5423\n", + "20/20 [==============================] - 1s 28ms/step - loss: 0.5423\n", "Epoch 15/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.5254\n", + "20/20 [==============================] - 1s 26ms/step - loss: 0.5254\n", "Epoch 16/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.5066\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.5066\n", "Epoch 17/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.5031\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.5031\n", "Epoch 18/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.4925\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.4925\n", "Epoch 19/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.4754\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.4754\n", "Epoch 20/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.4643\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.4643\n", "Epoch 21/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.4396\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.4396\n", "Epoch 22/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.4415\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.4415\n", "Epoch 23/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.4354\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.4354\n", "Epoch 24/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.4150\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.4150\n", "Epoch 25/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.4143\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.4143\n", "Epoch 26/50\n", - "20/20 [==============================] - 1s 28ms/step - loss: 0.4077\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.4077\n", "Epoch 27/50\n", - "20/20 [==============================] - 0s 24ms/step - loss: 0.3924\n", + "20/20 [==============================] - 1s 26ms/step - loss: 0.3924\n", "Epoch 28/50\n", "20/20 [==============================] - 0s 21ms/step - loss: 0.4030\n", "Epoch 29/50\n", - "20/20 [==============================] - 0s 21ms/step - loss: 0.3783\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.3783\n", "Epoch 30/50\n", - "20/20 [==============================] - 0s 17ms/step - loss: 0.3744\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3744\n", "Epoch 31/50\n", "20/20 [==============================] - 0s 19ms/step - loss: 0.3702\n", "Epoch 32/50\n", - "20/20 [==============================] - 0s 24ms/step - loss: 0.3450\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3450\n", "Epoch 33/50\n", - "20/20 [==============================] - 0s 24ms/step - loss: 0.3633\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3633\n", "Epoch 34/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 0.3449\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.3449\n", "Epoch 35/50\n", - "20/20 [==============================] - 0s 25ms/step - loss: 0.3409\n", - "Epoch 36/50\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "20/20 [==============================] - 0s 21ms/step - loss: 0.3336\n", + "20/20 [==============================] - 1s 32ms/step - loss: 0.3409\n", + "Epoch 36/50\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.3336\n", "Epoch 37/50\n", - "20/20 [==============================] - 0s 16ms/step - loss: 0.3308\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.3308\n", "Epoch 38/50\n", - "20/20 [==============================] - 0s 15ms/step - loss: 0.3202\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.3202\n", "Epoch 39/50\n", - "20/20 [==============================] - 0s 15ms/step - loss: 0.3117\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3117\n", "Epoch 40/50\n", - "20/20 [==============================] - 0s 14ms/step - loss: 0.3044\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.3044\n", "Epoch 41/50\n", - "20/20 [==============================] - 0s 13ms/step - loss: 0.3094\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.3094\n", "Epoch 42/50\n", - "20/20 [==============================] - 0s 14ms/step - loss: 0.3066\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.3066\n", "Epoch 43/50\n", - "20/20 [==============================] - 0s 15ms/step - loss: 0.3007\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.3007\n", "Epoch 44/50\n", - "20/20 [==============================] - 0s 14ms/step - loss: 0.2862\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.2862\n", "Epoch 45/50\n", - "20/20 [==============================] - 0s 14ms/step - loss: 0.2930\n", + "20/20 [==============================] - 0s 18ms/step - loss: 0.2930\n", "Epoch 46/50\n", - "20/20 [==============================] - 0s 15ms/step - loss: 0.2925\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.2925\n", "Epoch 47/50\n", - "20/20 [==============================] - 0s 25ms/step - loss: 0.2806\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.2806\n", "Epoch 48/50\n", - "20/20 [==============================] - 1s 29ms/step - loss: 0.2818\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.2818\n", "Epoch 49/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.2646\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.2646\n", "Epoch 50/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 0.2661\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569E29CE58> and will run it as-is.\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.2661\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A867756168> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569E29CE58> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A867756168> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", "Learning rate set to 0.01791\n", - "0:\tlearn: 0.6461217\ttotal: 3.99ms\tremaining: 3.99s\n", - "1:\tlearn: 0.5950066\ttotal: 7.79ms\tremaining: 3.89s\n", - "2:\tlearn: 0.5548099\ttotal: 11.3ms\tremaining: 3.77s\n", - "3:\tlearn: 0.5161424\ttotal: 14.9ms\tremaining: 3.7s\n", - "4:\tlearn: 0.4802768\ttotal: 18.8ms\tremaining: 3.75s\n", - "5:\tlearn: 0.4444653\ttotal: 22.7ms\tremaining: 3.75s\n", - "6:\tlearn: 0.4134718\ttotal: 26.2ms\tremaining: 3.72s\n", - "7:\tlearn: 0.3821667\ttotal: 29.3ms\tremaining: 3.63s\n", - "8:\tlearn: 0.3554573\ttotal: 32.8ms\tremaining: 3.62s\n", - "9:\tlearn: 0.3288207\ttotal: 36.6ms\tremaining: 3.63s\n", - "10:\tlearn: 0.3058822\ttotal: 39.7ms\tremaining: 3.57s\n", - 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36.3ms\n", + "991:\tlearn: 0.0008177\ttotal: 4s\tremaining: 32.2ms\n", + "992:\tlearn: 0.0008175\ttotal: 4s\tremaining: 28.2ms\n", + "993:\tlearn: 0.0008172\ttotal: 4s\tremaining: 24.2ms\n", + "994:\tlearn: 0.0008167\ttotal: 4.01s\tremaining: 20.1ms\n", + "995:\tlearn: 0.0008165\ttotal: 4.01s\tremaining: 16.1ms\n", + "996:\tlearn: 0.0008162\ttotal: 4.01s\tremaining: 12.1ms\n", + "997:\tlearn: 0.0008158\ttotal: 4.01s\tremaining: 8.05ms\n", + "998:\tlearn: 0.0008154\ttotal: 4.02s\tremaining: 4.02ms\n", + "999:\tlearn: 0.0008151\ttotal: 4.02s\tremaining: 0us\n", "current noise type: None\n", "{'Samples': 3686, 'Features': 400, 'Anomalies': 61, 'Anomalies Ratio(%)': 1.65}\n", "best param: None\n", "best param: None\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569E2240D8> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A8678735E8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING: AutoGraph could not transform .predict_function at 0x000002569E2240D8> and will run it as-is.\n", + "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A8678735E8> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", @@ -4576,71 +4382,71 @@ "_________________________________________________________________\n", "None\n", "Epoch 1/100\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x00000256990D18B8> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A85DC31A68> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x00000256990D18B8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A85DC31A68> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "65/73 [=========================>....] - ETA: 0s - loss: 14.0531WARNING:tensorflow:AutoGraph could not transform .test_function at 0x000002569CA36DC8> and will run it as-is.\n", + "62/73 [========================>.....] - ETA: 0s - loss: 14.1699WARNING:tensorflow:AutoGraph could not transform .test_function at 0x000002A85D984F78> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .test_function at 0x000002569CA36DC8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .test_function at 0x000002A85D984F78> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "73/73 [==============================] - 1s 7ms/step - loss: 13.7096 - val_loss: 10.7606\n", + "73/73 [==============================] - 1s 5ms/step - loss: 13.7096 - val_loss: 10.7606\n", "Epoch 2/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 8.8029 - val_loss: 8.2734\n", + "73/73 [==============================] - 0s 2ms/step - loss: 8.8029 - val_loss: 8.2734\n", "Epoch 3/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 6.3712 - val_loss: 6.3979\n", + "73/73 [==============================] - 0s 2ms/step - loss: 6.3712 - val_loss: 6.3979\n", "Epoch 4/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 4.6723 - val_loss: 5.0698\n", + "73/73 [==============================] - 0s 2ms/step - loss: 4.6723 - val_loss: 5.0698\n", "Epoch 5/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 3.5562 - val_loss: 4.0794\n", + "73/73 [==============================] - 0s 2ms/step - loss: 3.5562 - val_loss: 4.0794\n", "Epoch 6/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 2.8334 - val_loss: 3.4363\n", + "73/73 [==============================] - 0s 2ms/step - loss: 2.8334 - val_loss: 3.4363\n", "Epoch 7/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 2.3737 - val_loss: 2.9787\n", + "73/73 [==============================] - 0s 2ms/step - loss: 2.3737 - val_loss: 2.9787\n", "Epoch 8/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 2.0557 - val_loss: 2.6802\n", + "73/73 [==============================] - 0s 3ms/step - loss: 2.0557 - val_loss: 2.6802\n", "Epoch 9/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.8331 - val_loss: 2.4538\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.8331 - val_loss: 2.4538\n", "Epoch 10/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.6703 - val_loss: 2.2506\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.6703 - val_loss: 2.2506\n", "Epoch 11/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.5635 - val_loss: 2.1735\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.5635 - val_loss: 2.1735\n", "Epoch 12/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.5063 - val_loss: 2.0811\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.5063 - val_loss: 2.0811\n", "Epoch 13/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.5180 - val_loss: 2.0496\n", "Epoch 14/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.6399 - val_loss: 2.1277\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.6399 - val_loss: 2.1277\n", "Epoch 15/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.7435 - val_loss: 1.9969\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.7435 - val_loss: 1.9969\n", "Epoch 16/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.7084 - val_loss: 1.9978\n", "Epoch 17/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.6801 - val_loss: 2.0267\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.6801 - val_loss: 2.0267\n", "Epoch 18/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.6146 - val_loss: 1.8896\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.6146 - val_loss: 1.8896\n", "Epoch 19/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.5570 - val_loss: 1.8790\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.5570 - val_loss: 1.8790\n", "Epoch 20/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.5507 - val_loss: 1.8148\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.5507 - val_loss: 1.8148\n", "Epoch 21/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.5324 - val_loss: 1.8493\n", "Epoch 22/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.5418 - val_loss: 1.8900\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.5418 - val_loss: 1.8900\n", "Epoch 23/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.5640 - val_loss: 1.8532\n", "Epoch 24/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.5463 - val_loss: 1.8154\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.5463 - val_loss: 1.8154\n", "Epoch 25/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.5441 - val_loss: 1.8160\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.5441 - val_loss: 1.8160\n", "Epoch 26/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.5388 - val_loss: 1.6682\n", "Epoch 27/100\n", @@ -4650,51 +4456,45 @@ "Epoch 29/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.4537 - val_loss: 1.7828\n", "Epoch 30/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.4357 - val_loss: 1.7725\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.4357 - val_loss: 1.7725\n", "Epoch 31/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.4487 - val_loss: 1.7560\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.4487 - val_loss: 1.7560\n", "Epoch 32/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.4586 - val_loss: 1.8040\n", + "73/73 [==============================] - 0s 4ms/step - loss: 1.4586 - val_loss: 1.8040\n", "Epoch 33/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.4599 - val_loss: 1.7603\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.4599 - val_loss: 1.7603\n", "Epoch 34/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.4531 - val_loss: 1.7134\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.4531 - val_loss: 1.7134\n", "Epoch 35/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.4352 - val_loss: 1.7624\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.4352 - val_loss: 1.7624\n", "Epoch 36/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.3956 - val_loss: 1.7228\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.3956 - val_loss: 1.7228\n", "Epoch 37/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.3903 - val_loss: 1.6817\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.3903 - val_loss: 1.6817\n", "Epoch 38/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.3735 - val_loss: 1.7670\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.3735 - val_loss: 1.7670\n", "Epoch 39/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.3768 - val_loss: 1.7332\n", - "Epoch 40/100\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "73/73 [==============================] - 0s 3ms/step - loss: 1.3768 - val_loss: 1.7332\n", + "Epoch 40/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.3592 - val_loss: 1.6484\n", "Epoch 41/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.3614 - val_loss: 1.7747\n", "Epoch 42/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.3772 - val_loss: 1.7110\n", "Epoch 43/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.3777 - val_loss: 1.6485\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.3777 - val_loss: 1.6485\n", "Epoch 44/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.3511 - val_loss: 1.7285\n", "Epoch 45/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.3398 - val_loss: 1.6650\n", "Epoch 46/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.3302 - val_loss: 1.7032\n", + "73/73 [==============================] - 0s 4ms/step - loss: 1.3302 - val_loss: 1.7032\n", "Epoch 47/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.3146 - val_loss: 1.6655\n", + "73/73 [==============================] - 0s 4ms/step - loss: 1.3146 - val_loss: 1.6655\n", "Epoch 48/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.3066 - val_loss: 1.6923\n", + "73/73 [==============================] - 0s 4ms/step - loss: 1.3066 - val_loss: 1.6923\n", "Epoch 49/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.3444 - val_loss: 1.7287\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.3444 - val_loss: 1.7287\n", "Epoch 50/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.3346 - val_loss: 1.6857\n", "Epoch 51/100\n", @@ -4710,37 +4510,37 @@ "Epoch 56/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.2706 - val_loss: 1.6875\n", "Epoch 57/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.2773 - val_loss: 1.7262\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2773 - val_loss: 1.7262\n", "Epoch 58/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.2734 - val_loss: 1.8204\n", "Epoch 59/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.2769 - val_loss: 1.7243\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2769 - val_loss: 1.7243\n", "Epoch 60/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.2673 - val_loss: 1.7526\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2673 - val_loss: 1.7526\n", "Epoch 61/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.2488 - val_loss: 1.7065\n", "Epoch 62/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.2272 - val_loss: 1.7067\n", "Epoch 63/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.2177 - val_loss: 1.7384\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2177 - val_loss: 1.7384\n", "Epoch 64/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.2167 - val_loss: 1.7301\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.2167 - val_loss: 1.7301\n", "Epoch 65/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.2173 - val_loss: 1.7222\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2173 - val_loss: 1.7222\n", "Epoch 66/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.2370 - val_loss: 1.7242\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2370 - val_loss: 1.7242\n", "Epoch 67/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.2442 - val_loss: 1.7574\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2442 - val_loss: 1.7574\n", "Epoch 68/100\n", - "73/73 [==============================] - 0s 4ms/step - loss: 1.2402 - val_loss: 1.7249\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.2402 - val_loss: 1.7249\n", "Epoch 69/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.2239 - val_loss: 1.7383\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2239 - val_loss: 1.7383\n", "Epoch 70/100\n", "73/73 [==============================] - 0s 3ms/step - loss: 1.2051 - val_loss: 1.7034\n", "Epoch 71/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.2046 - val_loss: 1.6765\n", "Epoch 72/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.2032 - val_loss: 1.7824\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.2032 - val_loss: 1.7824\n", "Epoch 73/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1966 - val_loss: 1.7929\n", "Epoch 74/100\n", @@ -4754,33 +4554,33 @@ "Epoch 78/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.2136 - val_loss: 1.7719\n", "Epoch 79/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.1926 - val_loss: 1.8415\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.1926 - val_loss: 1.8415\n", "Epoch 80/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1773 - val_loss: 1.7112\n", "Epoch 81/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1775 - val_loss: 1.8018\n", "Epoch 82/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.1715 - val_loss: 1.9076\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.1715 - val_loss: 1.9076\n", "Epoch 83/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.1893 - val_loss: 1.8441\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.1893 - val_loss: 1.8441\n", "Epoch 84/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1950 - val_loss: 1.8157\n", "Epoch 85/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.2133 - val_loss: 1.7801\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.2133 - val_loss: 1.7801\n", "Epoch 86/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.2015 - val_loss: 1.8572\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.2015 - val_loss: 1.8572\n", "Epoch 87/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1823 - val_loss: 1.8624\n", "Epoch 88/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.1747 - val_loss: 1.7853\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.1747 - val_loss: 1.7853\n", "Epoch 89/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.1930 - val_loss: 1.8346\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.1930 - val_loss: 1.8346\n", "Epoch 90/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1861 - val_loss: 1.8728\n", "Epoch 91/100\n", - "73/73 [==============================] - 0s 1ms/step - loss: 1.1812 - val_loss: 1.8321\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.1812 - val_loss: 1.8321\n", "Epoch 92/100\n", - "73/73 [==============================] - 0s 2ms/step - loss: 1.1951 - val_loss: 1.8438\n", + "73/73 [==============================] - 0s 3ms/step - loss: 1.1951 - val_loss: 1.8438\n", "Epoch 93/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1806 - val_loss: 1.8027\n", "Epoch 94/100\n", @@ -4790,2621 +4590,618 @@ "Epoch 96/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1738 - val_loss: 1.9128\n", "Epoch 97/100\n", - "73/73 [==============================] - 0s 3ms/step - loss: 1.1787 - val_loss: 1.9168\n", + "73/73 [==============================] - 0s 2ms/step - loss: 1.1787 - val_loss: 1.9168\n", "Epoch 98/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1752 - val_loss: 2.0141\n", "Epoch 99/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1698 - val_loss: 1.9576\n", "Epoch 100/100\n", "73/73 [==============================] - 0s 2ms/step - loss: 1.1648 - val_loss: 1.9099\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569B0A5CA8> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A864C9E048> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569B0A5CA8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A864C9E048> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", "Training size: 2580, No. outliers: 4\n", "Epoch 1/50\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002569B444288> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x000002569B444288> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "20/20 [==============================] - 2s 30ms/step - loss: 2.4112\n", - "Epoch 2/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 1.5985\n", - "Epoch 3/50\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "20/20 [==============================] - 1s 32ms/step - loss: 1.0839\n", - "Epoch 4/50\n", - "20/20 [==============================] - 1s 25ms/step - loss: 0.8287\n", - "Epoch 5/50\n", - "20/20 [==============================] - 1s 26ms/step - loss: 0.7233\n", - "Epoch 6/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.6716\n", - "Epoch 7/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.6518\n", - "Epoch 8/50\n", - "20/20 [==============================] - 1s 26ms/step - loss: 0.6228\n", - "Epoch 9/50\n", - "20/20 [==============================] - 0s 18ms/step - loss: 0.6249\n", - "Epoch 10/50\n", - "20/20 [==============================] - 0s 16ms/step - loss: 0.5914\n", - "Epoch 11/50\n", - "20/20 [==============================] - 0s 22ms/step - loss: 0.5713\n", - "Epoch 12/50\n", - "20/20 [==============================] - 1s 26ms/step - loss: 0.5510\n", - "Epoch 13/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.5421\n", - "Epoch 14/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.5277\n", - "Epoch 15/50\n", - "20/20 [==============================] - 1s 49ms/step - loss: 0.5157\n", - "Epoch 16/50\n", - "20/20 [==============================] - 1s 49ms/step - loss: 0.5187\n", - "Epoch 17/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 0.5126\n", - "Epoch 18/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.4980\n", - "Epoch 19/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.5011\n", - "Epoch 20/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.4903\n", - "Epoch 21/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.4827\n", - "Epoch 22/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.4823\n", - "Epoch 23/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.4765\n", - "Epoch 24/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.4764\n", - "Epoch 25/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.4912\n", - "Epoch 26/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.4841\n", - "Epoch 27/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.4792\n", - "Epoch 28/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.4815\n", - "Epoch 29/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.4751\n", - "Epoch 30/50\n", - "20/20 [==============================] - 1s 33ms/step - loss: 0.4771\n", - "Epoch 31/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.4736\n", - "Epoch 32/50\n", - "20/20 [==============================] - 1s 40ms/step - loss: 0.4649\n", - "Epoch 33/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.4649\n", - "Epoch 34/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 0.4589\n", - "Epoch 35/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 0.4524\n", - "Epoch 36/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.4490\n", - "Epoch 37/50\n", - "20/20 [==============================] - 1s 40ms/step - loss: 0.4369\n", - "Epoch 38/50\n", - "20/20 [==============================] - 1s 44ms/step - loss: 0.4330\n", - "Epoch 39/50\n", - "20/20 [==============================] - 1s 48ms/step - loss: 0.4274\n", - "Epoch 40/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 0.4208\n", - "Epoch 41/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.4146\n", - "Epoch 42/50\n", - "20/20 [==============================] - 1s 45ms/step - loss: 0.3983\n", - "Epoch 43/50\n", - "20/20 [==============================] - 1s 47ms/step - loss: 0.3803\n", - "Epoch 44/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.3673\n", - "Epoch 45/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.3607\n", - "Epoch 46/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.3580\n", - "Epoch 47/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.3516\n", - "Epoch 48/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.3486\n", - "Epoch 49/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.3446\n", - "Epoch 50/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 0.3364\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569B4A9F78> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569B4A9F78> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "Learning rate set to 0.015442\n", - "0:\tlearn: 0.6519800\ttotal: 101ms\tremaining: 1m 40s\n", - "1:\tlearn: 0.6141763\ttotal: 183ms\tremaining: 1m 31s\n", - "2:\tlearn: 0.5793682\ttotal: 253ms\tremaining: 1m 24s\n", - "3:\tlearn: 0.5469453\ttotal: 313ms\tremaining: 1m 17s\n", - "4:\tlearn: 0.5135033\ttotal: 395ms\tremaining: 1m 18s\n", - "5:\tlearn: 0.4836202\ttotal: 470ms\tremaining: 1m 17s\n", - "6:\tlearn: 0.4572832\ttotal: 548ms\tremaining: 1m 17s\n", - "7:\tlearn: 0.4309952\ttotal: 645ms\tremaining: 1m 19s\n", - "8:\tlearn: 0.4068804\ttotal: 799ms\tremaining: 1m 27s\n", - "9:\tlearn: 0.3838344\ttotal: 920ms\tremaining: 1m 31s\n", - "10:\tlearn: 0.3636639\ttotal: 1.04s\tremaining: 1m 33s\n", - "11:\tlearn: 0.3425565\ttotal: 1.13s\tremaining: 1m 32s\n", - 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"best param: None\n", - "best param: None\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569E37DAF8> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569E37DAF8> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model: \"model_26\"\n", - "_________________________________________________________________\n", - " Layer (type) Output Shape Param # \n", - "=================================================================\n", - " input_18 (InputLayer) [(None, 12)] 0 \n", - " \n", - " dense_9 (Dense) (None, 64) 768 \n", - " \n", - " net_output (Dense) (None, 32) 2048 \n", - " \n", - " tf.math.subtract_9 (TFOpLam (None, 32) 0 \n", - " bda) \n", - " \n", - " tf.math.pow_9 (TFOpLambda) (None, 32) 0 \n", - " \n", - " tf.math.reduce_sum_9 (TFOpL (None,) 0 \n", - " ambda) \n", - " \n", - " tf.math.reduce_mean_9 (TFOp () 0 \n", - " Lambda) \n", - " \n", - " tf.__operators__.add_9 (TFO () 0 \n", - " pLambda) \n", - " \n", - " add_loss_9 (AddLoss) () 0 \n", - " \n", - "=================================================================\n", - "Total params: 2,816\n", - "Trainable params: 2,816\n", - "Non-trainable params: 0\n", - "_________________________________________________________________\n", - "None\n", - "Epoch 1/100\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x00000256A03205E8> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x00000256A03205E8> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "19/29 [==================>...........] - ETA: 0s - loss: 3.2295 WARNING:tensorflow:AutoGraph could not transform .test_function at 0x00000256A04D1318> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .test_function at 0x00000256A04D1318> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "29/29 [==============================] - 2s 23ms/step - loss: 2.8862 - val_loss: 2.0160\n", - "Epoch 2/100\n", - "29/29 [==============================] - 0s 10ms/step - loss: 1.8580 - val_loss: 1.5632\n", - "Epoch 3/100\n", - "29/29 [==============================] - 0s 8ms/step - loss: 1.4668 - val_loss: 1.2597\n", - "Epoch 4/100\n", - "29/29 [==============================] - 0s 10ms/step - loss: 1.1964 - val_loss: 1.0309\n", - "Epoch 5/100\n", - "29/29 [==============================] - 0s 10ms/step - loss: 0.9955 - val_loss: 0.8653\n", - "Epoch 6/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.8526 - val_loss: 0.7561\n", - "Epoch 7/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.7439 - val_loss: 0.6646\n", - "Epoch 8/100\n", - "29/29 [==============================] - 0s 12ms/step - loss: 0.6550 - val_loss: 0.5900\n", - "Epoch 9/100\n", - "29/29 [==============================] - 0s 8ms/step - loss: 0.5860 - val_loss: 0.5326\n", - "Epoch 10/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.5324 - val_loss: 0.4908\n", - "Epoch 11/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.4901 - val_loss: 0.4578\n", - "Epoch 12/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.4553 - val_loss: 0.4265\n", - "Epoch 13/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.4276 - val_loss: 0.4037\n", - "Epoch 14/100\n", - "29/29 [==============================] - 0s 8ms/step - loss: 0.4030 - val_loss: 0.3862\n", - "Epoch 15/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.3810 - val_loss: 0.3650\n", - "Epoch 16/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.3626 - val_loss: 0.3492\n", - "Epoch 17/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.3467 - val_loss: 0.3372\n", - "Epoch 18/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.3340 - val_loss: 0.3297\n", - "Epoch 19/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.3232 - val_loss: 0.3191\n", - "Epoch 20/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.3134 - val_loss: 0.3103\n", - "Epoch 21/100\n", - "29/29 [==============================] - 0s 8ms/step - loss: 0.3055 - val_loss: 0.3040\n", - "Epoch 22/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2982 - val_loss: 0.2955\n", - "Epoch 23/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2912 - val_loss: 0.2898\n", - "Epoch 24/100\n", - "29/29 [==============================] - 0s 8ms/step - loss: 0.2848 - val_loss: 0.2853\n", - "Epoch 25/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2789 - val_loss: 0.2765\n", - "Epoch 26/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2729 - val_loss: 0.2715\n", - "Epoch 27/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2677 - val_loss: 0.2677\n", - "Epoch 28/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2628 - val_loss: 0.2630\n", - "Epoch 29/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2594 - val_loss: 0.2635\n", - "Epoch 30/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2558 - val_loss: 0.2548\n", - "Epoch 31/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.2532 - val_loss: 0.2545\n", - "Epoch 32/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2505 - val_loss: 0.2515\n", - "Epoch 33/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2483 - val_loss: 0.2494\n", - "Epoch 34/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2461 - val_loss: 0.2471\n", - "Epoch 35/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2443 - val_loss: 0.2463\n", - "Epoch 36/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2423 - val_loss: 0.2434\n", - "Epoch 37/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2409 - val_loss: 0.2397\n", - "Epoch 38/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.2386 - val_loss: 0.2393\n", - "Epoch 39/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.2373 - val_loss: 0.2380\n", - "Epoch 40/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.2351 - val_loss: 0.2372\n", - "Epoch 41/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2343 - val_loss: 0.2351\n", - "Epoch 42/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.2328 - val_loss: 0.2337\n", - "Epoch 43/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2321 - val_loss: 0.2337\n", - "Epoch 44/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2310 - val_loss: 0.2331\n", - "Epoch 45/100\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "29/29 [==============================] - 0s 6ms/step - loss: 0.2297 - val_loss: 0.2302\n", - "Epoch 46/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2289 - val_loss: 0.2336\n", - "Epoch 47/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2281 - val_loss: 0.2287\n", - "Epoch 48/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2266 - val_loss: 0.2276\n", - "Epoch 49/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2256 - val_loss: 0.2300\n", - "Epoch 50/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2261 - val_loss: 0.2261\n", - "Epoch 51/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2249 - val_loss: 0.2245\n", - "Epoch 52/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2245 - val_loss: 0.2258\n", - "Epoch 53/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2241 - val_loss: 0.2239\n", - "Epoch 54/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2230 - val_loss: 0.2250\n", - "Epoch 55/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2231 - val_loss: 0.2231\n", - "Epoch 56/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2206 - val_loss: 0.2211\n", - "Epoch 57/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2211 - val_loss: 0.2242\n", - "Epoch 58/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2209 - val_loss: 0.2218\n", - "Epoch 59/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2203 - val_loss: 0.2199\n", - "Epoch 60/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2194 - val_loss: 0.2189\n", - "Epoch 61/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2186 - val_loss: 0.2186\n", - "Epoch 62/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2181 - val_loss: 0.2208\n", - "Epoch 63/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2174 - val_loss: 0.2206\n", - "Epoch 64/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2186 - val_loss: 0.2172\n", - "Epoch 65/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2170 - val_loss: 0.2181\n", - "Epoch 66/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2166 - val_loss: 0.2191\n", - "Epoch 67/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2164 - val_loss: 0.2168\n", - "Epoch 68/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2164 - val_loss: 0.2178\n", - "Epoch 69/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2149 - val_loss: 0.2173\n", - "Epoch 70/100\n", - "29/29 [==============================] - 0s 7ms/step - loss: 0.2155 - val_loss: 0.2204\n", - "Epoch 71/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2158 - val_loss: 0.2147\n", - "Epoch 72/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2142 - val_loss: 0.2161\n", - "Epoch 73/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2132 - val_loss: 0.2155\n", - "Epoch 74/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2137 - val_loss: 0.2167\n", - "Epoch 75/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2140 - val_loss: 0.2146\n", - "Epoch 76/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2140 - val_loss: 0.2139\n", - "Epoch 77/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2132 - val_loss: 0.2133\n", - "Epoch 78/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2124 - val_loss: 0.2177\n", - "Epoch 79/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2121 - val_loss: 0.2132\n", - "Epoch 80/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2112 - val_loss: 0.2127\n", - "Epoch 81/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2116 - val_loss: 0.2140\n", - "Epoch 82/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2121 - val_loss: 0.2136\n", - "Epoch 83/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2112 - val_loss: 0.2138\n", - "Epoch 84/100\n", - "29/29 [==============================] - 0s 6ms/step - loss: 0.2118 - val_loss: 0.2114\n", - "Epoch 85/100\n", - "29/29 [==============================] - 0s 5ms/step - loss: 0.2111 - val_loss: 0.2143\n", - "Epoch 86/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2109 - val_loss: 0.2103\n", - "Epoch 87/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2102 - val_loss: 0.2131\n", - "Epoch 88/100\n", - "29/29 [==============================] - 0s 4ms/step - loss: 0.2100 - val_loss: 0.2133\n", - "Epoch 89/100\n", - "29/29 [==============================] - 0s 3ms/step - loss: 0.2096 - val_loss: 0.2104\n", - "Epoch 90/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2100 - val_loss: 0.2118\n", - "Epoch 91/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2096 - val_loss: 0.2095\n", - "Epoch 92/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2089 - val_loss: 0.2101\n", - "Epoch 93/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2092 - val_loss: 0.2099\n", - "Epoch 94/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2093 - val_loss: 0.2124\n", - "Epoch 95/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2092 - val_loss: 0.2110\n", - "Epoch 96/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2083 - val_loss: 0.2112\n", - "Epoch 97/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2088 - val_loss: 0.2094\n", - "Epoch 98/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2088 - val_loss: 0.2104\n", - "Epoch 99/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2080 - val_loss: 0.2117\n", - "Epoch 100/100\n", - "29/29 [==============================] - 0s 2ms/step - loss: 0.2077 - val_loss: 0.2141\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x00000256A0651828> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x00000256A0651828> and will run it as-is.\n", - "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", - "Cause: 'arguments' object has no attribute 'posonlyargs'\n", - "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "Training size: 1019, No. outliers: 3\n", - "Epoch 1/50\n", - "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x00000256A077B4C8> and will run it as-is.\n", + "WARNING:tensorflow:AutoGraph could not transform .train_function at 0x000002A86876DF78> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .train_function at 0x00000256A077B4C8> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .train_function at 0x000002A86876DF78> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "20/20 [==============================] - 2s 29ms/step - loss: 2.5970\n", + "20/20 [==============================] - 1s 21ms/step - loss: 2.4112\n", "Epoch 2/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 2.5302\n", + "20/20 [==============================] - 0s 21ms/step - loss: 1.5985\n", "Epoch 3/50\n", - "20/20 [==============================] - 1s 42ms/step - loss: 2.4772\n", + "20/20 [==============================] - 0s 21ms/step - loss: 1.0839\n", "Epoch 4/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 2.4202\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.8287\n", "Epoch 5/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 2.3580\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.7233\n", "Epoch 6/50\n", - "20/20 [==============================] - 0s 25ms/step - loss: 2.2957\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.6716\n", "Epoch 7/50\n", - "20/20 [==============================] - 0s 18ms/step - loss: 2.2295\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.6518\n", "Epoch 8/50\n", - "20/20 [==============================] - 0s 21ms/step - loss: 2.1531\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.6228\n", "Epoch 9/50\n", - "20/20 [==============================] - 0s 24ms/step - loss: 2.0724\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "20/20 [==============================] - 0s 21ms/step - loss: 0.6249\n", "Epoch 10/50\n", - "20/20 [==============================] - 1s 27ms/step - loss: 1.9780\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.5914\n", "Epoch 11/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 1.8807\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.5713\n", "Epoch 12/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 1.7777\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.5510\n", "Epoch 13/50\n", - "20/20 [==============================] - 1s 35ms/step - loss: 1.6789\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.5421\n", "Epoch 14/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 1.5542\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.5277\n", "Epoch 15/50\n", - "20/20 [==============================] - 1s 39ms/step - loss: 1.4175\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.5157\n", "Epoch 16/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 1.3098\n", + "20/20 [==============================] - 0s 19ms/step - loss: 0.5187\n", "Epoch 17/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 1.2187\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.5126\n", "Epoch 18/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 1.1719\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.4980\n", "Epoch 19/50\n", - "20/20 [==============================] - 1s 31ms/step - loss: 1.1113\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.5011\n", "Epoch 20/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 1.0366\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.4903\n", "Epoch 21/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.9870\n", + "20/20 [==============================] - 0s 21ms/step - loss: 0.4827\n", "Epoch 22/50\n", - "20/20 [==============================] - 1s 38ms/step - loss: 0.9427\n", + "20/20 [==============================] - 0s 20ms/step - loss: 0.4823\n", "Epoch 23/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.9053\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.4765\n", "Epoch 24/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.8968\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.4764\n", "Epoch 25/50\n", - "20/20 [==============================] - 1s 36ms/step - loss: 0.8685\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.4912\n", "Epoch 26/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.8415\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.4841\n", "Epoch 27/50\n", - "20/20 [==============================] - 1s 37ms/step - loss: 0.8235\n", + "20/20 [==============================] - 0s 22ms/step - loss: 0.4792\n", "Epoch 28/50\n", - "20/20 [==============================] - 1s 41ms/step - loss: 0.8125\n", + "20/20 [==============================] - 1s 31ms/step - loss: 0.4815\n", "Epoch 29/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 0.7855\n", + "20/20 [==============================] - 1s 30ms/step - loss: 0.4751\n", "Epoch 30/50\n", - "20/20 [==============================] - 0s 19ms/step - loss: 0.7631\n", + "20/20 [==============================] - 1s 27ms/step - loss: 0.4771\n", "Epoch 31/50\n", - "20/20 [==============================] - 0s 18ms/step - loss: 0.7348\n", + "20/20 [==============================] - 1s 35ms/step - loss: 0.4736\n", "Epoch 32/50\n", - "20/20 [==============================] - 0s 23ms/step - loss: 0.7292\n", + "20/20 [==============================] - 1s 28ms/step - loss: 0.4649\n", "Epoch 33/50\n", - "20/20 [==============================] - 0s 22ms/step - loss: 0.7120\n", + "20/20 [==============================] - 1s 40ms/step - loss: 0.4649\n", "Epoch 34/50\n", - "20/20 [==============================] - 1s 30ms/step - loss: 0.6891\n", + "20/20 [==============================] - 1s 33ms/step - loss: 0.4589\n", "Epoch 35/50\n", - "20/20 [==============================] - 1s 29ms/step - loss: 0.6854\n", + "20/20 [==============================] - 1s 31ms/step - loss: 0.4524\n", "Epoch 36/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.6796\n", + "20/20 [==============================] - 1s 29ms/step - loss: 0.4490\n", "Epoch 37/50\n", - "20/20 [==============================] - 1s 34ms/step - loss: 0.6722\n", + "20/20 [==============================] - 1s 31ms/step - loss: 0.4369\n", "Epoch 38/50\n", - "20/20 [==============================] - 1s 26ms/step - loss: 0.6874\n", + "20/20 [==============================] - 1s 29ms/step - loss: 0.4330\n", "Epoch 39/50\n", - "20/20 [==============================] - 0s 18ms/step - loss: 0.6738\n", + "20/20 [==============================] - 1s 32ms/step - loss: 0.4274\n", "Epoch 40/50\n", - "20/20 [==============================] - 0s 17ms/step - loss: 0.6599\n", + "20/20 [==============================] - 1s 28ms/step - loss: 0.4208\n", "Epoch 41/50\n", - "20/20 [==============================] - 0s 21ms/step - loss: 0.6647\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.4146\n", "Epoch 42/50\n", - "20/20 [==============================] - 0s 25ms/step - loss: 0.6519\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.3983\n", "Epoch 43/50\n", - "20/20 [==============================] - 1s 28ms/step - loss: 0.6561\n", + "20/20 [==============================] - 1s 26ms/step - loss: 0.3803\n", "Epoch 44/50\n", - "20/20 [==============================] - 1s 29ms/step - loss: 0.6506\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.3673\n", "Epoch 45/50\n", - "20/20 [==============================] - 1s 27ms/step - loss: 0.6421\n", + "20/20 [==============================] - 1s 26ms/step - loss: 0.3607\n", "Epoch 46/50\n", - "20/20 [==============================] - 1s 28ms/step - loss: 0.6408\n", + "20/20 [==============================] - 0s 24ms/step - loss: 0.3580\n", "Epoch 47/50\n", - "20/20 [==============================] - 1s 28ms/step - loss: 0.6522\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.3516\n", "Epoch 48/50\n", - "20/20 [==============================] - 1s 32ms/step - loss: 0.6371\n", + "20/20 [==============================] - 1s 30ms/step - loss: 0.3486\n", "Epoch 49/50\n", - "20/20 [==============================] - 0s 25ms/step - loss: 0.6475\n", + "20/20 [==============================] - 1s 26ms/step - loss: 0.3446\n", "Epoch 50/50\n", - "20/20 [==============================] - 0s 20ms/step - loss: 0.6293\n", - "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002569B3E2318> and will run it as-is.\n", + "20/20 [==============================] - 0s 23ms/step - loss: 0.3364\n", + "WARNING:tensorflow:AutoGraph could not transform .predict_function at 0x000002A867F7A708> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "WARNING: AutoGraph could not transform .predict_function at 0x000002569B3E2318> and will run it as-is.\n", + "WARNING: AutoGraph could not transform .predict_function at 0x000002A867F7A708> and will run it as-is.\n", "Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.\n", "Cause: 'arguments' object has no attribute 'posonlyargs'\n", "To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert\n", - "Learning rate set to 0.010385\n", - "0:\tlearn: 0.6681998\ttotal: 2.95ms\tremaining: 2.94s\n", - "1:\tlearn: 0.6423718\ttotal: 5.43ms\tremaining: 2.71s\n", - "2:\tlearn: 0.6194451\ttotal: 7.68ms\tremaining: 2.55s\n", - "3:\tlearn: 0.5977659\ttotal: 9.83ms\tremaining: 2.45s\n", - "4:\tlearn: 0.5744795\ttotal: 11.9ms\tremaining: 2.38s\n", - "5:\tlearn: 0.5546212\ttotal: 14ms\tremaining: 2.31s\n", - "6:\tlearn: 0.5334639\ttotal: 16.5ms\tremaining: 2.35s\n", - "7:\tlearn: 0.5150649\ttotal: 18.7ms\tremaining: 2.32s\n", - "8:\tlearn: 0.4989972\ttotal: 20.9ms\tremaining: 2.3s\n", - "9:\tlearn: 0.4807838\ttotal: 23ms\tremaining: 2.27s\n", - "10:\tlearn: 0.4638908\ttotal: 25ms\tremaining: 2.25s\n", - "11:\tlearn: 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