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Tensor Network vs FC Controllability /
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600epochs_3xTNLayers.ipynb
2940 lines (2940 with data), 190.8 kB
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"machine_shape": "hm"
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "8XnVMPBXmtRa"
},
"source": [
"# TensorNetworks in Neural Networks.\n",
"\n",
"Here, we have a small toy example of how to use a TN inside of a fully connected neural network.\n",
"\n",
"First off, let's install tensornetwork"
]
},
{
"cell_type": "code",
"metadata": {
"id": "7HGRsYNAFxME"
},
"source": [
"# !pip install tensornetwork\n",
"\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import tensorflow as tf\n",
"# Import tensornetwork\n",
"import tensornetwork as tn\n",
"import random\n",
"import time\n",
"# Set the backend to tesorflow\n",
"# (default is numpy)\n",
"tn.set_default_backend(\"tensorflow\")\n",
"np.random.seed(42)\n",
"random.seed(42)\n",
"tf.random.set_seed(42)"
],
"execution_count": 146,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "g1OMCo5XmrYu"
},
"source": [
"# TensorNetwork layer definition\n",
"\n",
"Here, we define the TensorNetwork layer we wish to use to replace the fully connected layer. Here, we simply use a 2 node Matrix Product Operator network to replace the normal dense weight matrix.\n",
"\n",
"We TensorNetwork's NCon API to keep the code short."
]
},
{
"cell_type": "code",
"metadata": {
"id": "wvSMKtPufnLp"
},
"source": [
"class TNLayer(tf.keras.layers.Layer):\n",
"\n",
" def __init__(self):\n",
" super(TNLayer, self).__init__()\n",
" # Create the variables for the layer.\n",
" self.a_var = tf.Variable(tf.random.normal(shape=(32, 32, 2),\n",
" stddev=1.0/32.0),\n",
" name=\"a\", trainable=True)\n",
" self.b_var = tf.Variable(tf.random.normal(shape=(32, 32, 2),\n",
" stddev=1.0/32.0),\n",
" name=\"b\", trainable=True)\n",
" self.bias = tf.Variable(tf.zeros(shape=(32, 32)),\n",
" name=\"bias\", trainable=True)\n",
"\n",
" def call(self, inputs):\n",
" # Define the contraction.\n",
" # We break it out so we can parallelize a batch using\n",
" # tf.vectorized_map (see below).\n",
" def f(input_vec, a_var, b_var, bias_var):\n",
" # Reshape to a matrix instead of a vector.\n",
" input_vec = tf.reshape(input_vec, (32, 32))\n",
"\n",
" # Now we create the network.\n",
" a = tn.Node(a_var)\n",
" b = tn.Node(b_var)\n",
" x_node = tn.Node(input_vec)\n",
" a[1] ^ x_node[0]\n",
" b[1] ^ x_node[1]\n",
" a[2] ^ b[2]\n",
"\n",
" # The TN should now look like this\n",
" # | |\n",
" # a --- b\n",
" # \\ /\n",
" # x\n",
"\n",
" # Now we begin the contraction.\n",
" c = a @ x_node\n",
" result = (c @ b).tensor\n",
"\n",
" # To make the code shorter, we also could've used Ncon.\n",
" # The above few lines of code is the same as this:\n",
" # result = tn.ncon([x, a_var, b_var], [[1, 2], [-1, 1, 3], [-2, 2, 3]])\n",
"\n",
" # Finally, add bias.\n",
" return result + bias_var\n",
"\n",
" # To deal with a batch of items, we can use the tf.vectorized_map\n",
" # function.\n",
" # https://www.tensorflow.org/api_docs/python/tf/vectorized_map\n",
" result = tf.vectorized_map(\n",
" lambda vec: f(vec, self.a_var, self.b_var, self.bias), inputs)\n",
" return tf.nn.relu(tf.reshape(result, (-1, 1024)))"
],
"execution_count": 147,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "V-CVqIhPnhY_"
},
"source": [
"# Smaller model\n",
"These two models are effectively the same, but notice how the TN layer has nearly 10x fewer parameters."
]
},
{
"cell_type": "code",
"metadata": {
"id": "XPBvnB95jg4b",
"outputId": "f8a1041d-da41-43d0-b150-fcafbac21917",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
}
},
"source": [
"Dense = tf.keras.layers.Dense\n",
"fc_model = tf.keras.Sequential(\n",
" [\n",
" tf.keras.Input(shape=(2,)),\n",
" Dense(1024, activation=tf.nn.relu),\n",
" Dense(1024, activation=tf.nn.relu),\n",
" Dense(1, activation=None)])\n",
"fc_model.summary()"
],
"execution_count": 148,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Model: \"sequential_24\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param # \n",
"=================================================================\n",
" dense_60 (Dense) (None, 1024) 3072 \n",
" \n",
" dense_61 (Dense) (None, 1024) 1049600 \n",
" \n",
" dense_62 (Dense) (None, 1) 1025 \n",
" \n",
"=================================================================\n",
"Total params: 1053697 (4.02 MB)\n",
"Trainable params: 1053697 (4.02 MB)\n",
"Non-trainable params: 0 (0.00 Byte)\n",
"_________________________________________________________________\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "bbKsmK8wIFTp",
"outputId": "5374cb08-d96c-4e32-e998-9d8fbd93549e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
}
},
"source": [
"tn_model = tf.keras.Sequential(\n",
" [\n",
" tf.keras.Input(shape=(2,)),\n",
" Dense(1024, activation=tf.nn.relu),\n",
" # Here, we replace the dense layer with our MPS.\n",
" TNLayer(),\n",
" TNLayer(),\n",
" TNLayer(),\n",
" Dense(1, activation=None)])\n",
"tn_model.summary()"
],
"execution_count": 149,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Model: \"sequential_25\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param # \n",
"=================================================================\n",
" dense_63 (Dense) (None, 1024) 3072 \n",
" \n",
" tn_layer_36 (TNLayer) (None, 1024) 5120 \n",
" \n",
" tn_layer_37 (TNLayer) (None, 1024) 5120 \n",
" \n",
" tn_layer_38 (TNLayer) (None, 1024) 5120 \n",
" \n",
" dense_64 (Dense) (None, 1) 1025 \n",
" \n",
"=================================================================\n",
"Total params: 19457 (76.00 KB)\n",
"Trainable params: 19457 (76.00 KB)\n",
"Non-trainable params: 0 (0.00 Byte)\n",
"_________________________________________________________________\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "GWwoYp0WnsLA"
},
"source": [
"# Training a model\n",
"\n",
"You can train the TN model just as you would a normal neural network model! Here, we give an example of how to do it in Keras."
]
},
{
"cell_type": "code",
"metadata": {
"id": "qDFzOC7sDBJ-"
},
"source": [
"X = np.concatenate([np.random.randn(20, 2) + np.array([3, 3]),\n",
" np.random.randn(20, 2) + np.array([-3, -3]),\n",
" np.random.randn(20, 2) + np.array([-3, 3]),\n",
" np.random.randn(20, 2) + np.array([3, -3])])\n",
"\n",
"Y = np.concatenate([np.ones((40)), -np.ones((40))])"
],
"execution_count": 150,
"outputs": []
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "19TWP-1eKURB",
"outputId": "46e8e838-43cb-4e2d-c33d-9d793ee1ef44"
},
"execution_count": 151,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1710205498.5181167\n",
"Tue Mar 12 01:04:58 2024\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "crc0q1vbIyTj",
"outputId": "78a3ff46-a107-4f8a-9142-9ec010b3bb53",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
}
},
"source": [
"tn_model.compile(optimizer=\"adam\", loss=\"mean_squared_error\")\n",
"tn_model.fit(X, Y, epochs=600, verbose=2)"
],
"execution_count": 152,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/600\n",
"3/3 - 2s - loss: 1.0018 - 2s/epoch - 688ms/step\n",
"Epoch 2/600\n",
"3/3 - 0s - loss: 1.0018 - 20ms/epoch - 7ms/step\n",
"Epoch 3/600\n",
"3/3 - 0s - loss: 1.0007 - 21ms/epoch - 7ms/step\n",
"Epoch 4/600\n",
"3/3 - 0s - loss: 1.0001 - 19ms/epoch - 6ms/step\n",
"Epoch 5/600\n",
"3/3 - 0s - loss: 1.0006 - 22ms/epoch - 7ms/step\n",
"Epoch 6/600\n",
"3/3 - 0s - loss: 0.9997 - 19ms/epoch - 6ms/step\n",
"Epoch 7/600\n",
"3/3 - 0s - loss: 0.9991 - 20ms/epoch - 7ms/step\n",
"Epoch 8/600\n",
"3/3 - 0s - loss: 0.9978 - 20ms/epoch - 7ms/step\n",
"Epoch 9/600\n",
"3/3 - 0s - loss: 0.9946 - 20ms/epoch - 7ms/step\n",
"Epoch 10/600\n",
"3/3 - 0s - loss: 0.9873 - 17ms/epoch - 6ms/step\n",
"Epoch 11/600\n",
"3/3 - 0s - loss: 0.9702 - 18ms/epoch - 6ms/step\n",
"Epoch 12/600\n",
"3/3 - 0s - loss: 0.9332 - 19ms/epoch - 6ms/step\n",
"Epoch 13/600\n",
"3/3 - 0s - loss: 0.8618 - 17ms/epoch - 6ms/step\n",
"Epoch 14/600\n",
"3/3 - 0s - loss: 0.7187 - 21ms/epoch - 7ms/step\n",
"Epoch 15/600\n",
"3/3 - 0s - loss: 0.4604 - 19ms/epoch - 6ms/step\n",
"Epoch 16/600\n",
"3/3 - 0s - loss: 0.1368 - 17ms/epoch - 6ms/step\n",
"Epoch 17/600\n",
"3/3 - 0s - loss: 0.1065 - 17ms/epoch - 6ms/step\n",
"Epoch 18/600\n",
"3/3 - 0s - loss: 0.0901 - 18ms/epoch - 6ms/step\n",
"Epoch 19/600\n",
"3/3 - 0s - loss: 0.0193 - 18ms/epoch - 6ms/step\n",
"Epoch 20/600\n",
"3/3 - 0s - loss: 0.0450 - 17ms/epoch - 6ms/step\n",
"Epoch 21/600\n",
"3/3 - 0s - loss: 0.0507 - 17ms/epoch - 6ms/step\n",
"Epoch 22/600\n",
"3/3 - 0s - loss: 0.0290 - 18ms/epoch - 6ms/step\n",
"Epoch 23/600\n",
"3/3 - 0s - loss: 0.0136 - 19ms/epoch - 6ms/step\n",
"Epoch 24/600\n",
"3/3 - 0s - loss: 0.0176 - 20ms/epoch - 7ms/step\n",
"Epoch 25/600\n",
"3/3 - 0s - loss: 0.0193 - 19ms/epoch - 6ms/step\n",
"Epoch 26/600\n",
"3/3 - 0s - loss: 0.0116 - 18ms/epoch - 6ms/step\n",
"Epoch 27/600\n",
"3/3 - 0s - loss: 0.0091 - 18ms/epoch - 6ms/step\n",
"Epoch 28/600\n",
"3/3 - 0s - loss: 0.0110 - 17ms/epoch - 6ms/step\n",
"Epoch 29/600\n",
"3/3 - 0s - loss: 0.0104 - 19ms/epoch - 6ms/step\n",
"Epoch 30/600\n",
"3/3 - 0s - loss: 0.0078 - 18ms/epoch - 6ms/step\n",
"Epoch 31/600\n",
"3/3 - 0s - loss: 0.0073 - 18ms/epoch - 6ms/step\n",
"Epoch 32/600\n",
"3/3 - 0s - loss: 0.0076 - 19ms/epoch - 6ms/step\n",
"Epoch 33/600\n",
"3/3 - 0s - loss: 0.0071 - 19ms/epoch - 6ms/step\n",
"Epoch 34/600\n",
"3/3 - 0s - loss: 0.0062 - 17ms/epoch - 6ms/step\n",
"Epoch 35/600\n",
"3/3 - 0s - loss: 0.0061 - 18ms/epoch - 6ms/step\n",
"Epoch 36/600\n",
"3/3 - 0s - loss: 0.0061 - 18ms/epoch - 6ms/step\n",
"Epoch 37/600\n",
"3/3 - 0s - loss: 0.0057 - 18ms/epoch - 6ms/step\n",
"Epoch 38/600\n",
"3/3 - 0s - loss: 0.0053 - 18ms/epoch - 6ms/step\n",
"Epoch 39/600\n",
"3/3 - 0s - loss: 0.0052 - 18ms/epoch - 6ms/step\n",
"Epoch 40/600\n",
"3/3 - 0s - loss: 0.0051 - 17ms/epoch - 6ms/step\n",
"Epoch 41/600\n",
"3/3 - 0s - loss: 0.0048 - 17ms/epoch - 6ms/step\n",
"Epoch 42/600\n",
"3/3 - 0s - loss: 0.0046 - 20ms/epoch - 7ms/step\n",
"Epoch 43/600\n",
"3/3 - 0s - loss: 0.0046 - 18ms/epoch - 6ms/step\n",
"Epoch 44/600\n",
"3/3 - 0s - loss: 0.0044 - 18ms/epoch - 6ms/step\n",
"Epoch 45/600\n",
"3/3 - 0s - loss: 0.0042 - 19ms/epoch - 6ms/step\n",
"Epoch 46/600\n",
"3/3 - 0s - loss: 0.0040 - 18ms/epoch - 6ms/step\n",
"Epoch 47/600\n",
"3/3 - 0s - loss: 0.0040 - 19ms/epoch - 6ms/step\n",
"Epoch 48/600\n",
"3/3 - 0s - loss: 0.0039 - 18ms/epoch - 6ms/step\n",
"Epoch 49/600\n",
"3/3 - 0s - loss: 0.0037 - 18ms/epoch - 6ms/step\n",
"Epoch 50/600\n",
"3/3 - 0s - loss: 0.0036 - 20ms/epoch - 7ms/step\n",
"Epoch 51/600\n",
"3/3 - 0s - loss: 0.0035 - 18ms/epoch - 6ms/step\n",
"Epoch 52/600\n",
"3/3 - 0s - loss: 0.0034 - 18ms/epoch - 6ms/step\n",
"Epoch 53/600\n",
"3/3 - 0s - loss: 0.0033 - 18ms/epoch - 6ms/step\n",
"Epoch 54/600\n",
"3/3 - 0s - loss: 0.0032 - 17ms/epoch - 6ms/step\n",
"Epoch 55/600\n",
"3/3 - 0s - loss: 0.0031 - 19ms/epoch - 6ms/step\n",
"Epoch 56/600\n",
"3/3 - 0s - loss: 0.0031 - 20ms/epoch - 7ms/step\n",
"Epoch 57/600\n",
"3/3 - 0s - loss: 0.0030 - 18ms/epoch - 6ms/step\n",
"Epoch 58/600\n",
"3/3 - 0s - loss: 0.0029 - 19ms/epoch - 6ms/step\n",
"Epoch 59/600\n",
"3/3 - 0s - loss: 0.0028 - 19ms/epoch - 6ms/step\n",
"Epoch 60/600\n",
"3/3 - 0s - loss: 0.0027 - 18ms/epoch - 6ms/step\n",
"Epoch 61/600\n",
"3/3 - 0s - loss: 0.0026 - 17ms/epoch - 6ms/step\n",
"Epoch 62/600\n",
"3/3 - 0s - loss: 0.0025 - 19ms/epoch - 6ms/step\n",
"Epoch 63/600\n",
"3/3 - 0s - loss: 0.0025 - 18ms/epoch - 6ms/step\n",
"Epoch 64/600\n",
"3/3 - 0s - loss: 0.0024 - 20ms/epoch - 7ms/step\n",
"Epoch 65/600\n",
"3/3 - 0s - loss: 0.0024 - 21ms/epoch - 7ms/step\n",
"Epoch 66/600\n",
"3/3 - 0s - loss: 0.0023 - 21ms/epoch - 7ms/step\n",
"Epoch 67/600\n",
"3/3 - 0s - loss: 0.0022 - 19ms/epoch - 6ms/step\n",
"Epoch 68/600\n",
"3/3 - 0s - loss: 0.0022 - 21ms/epoch - 7ms/step\n",
"Epoch 69/600\n",
"3/3 - 0s - loss: 0.0021 - 20ms/epoch - 7ms/step\n",
"Epoch 70/600\n",
"3/3 - 0s - loss: 0.0020 - 20ms/epoch - 7ms/step\n",
"Epoch 71/600\n",
"3/3 - 0s - loss: 0.0020 - 19ms/epoch - 6ms/step\n",
"Epoch 72/600\n",
"3/3 - 0s - loss: 0.0019 - 22ms/epoch - 7ms/step\n",
"Epoch 73/600\n",
"3/3 - 0s - loss: 0.0019 - 20ms/epoch - 7ms/step\n",
"Epoch 74/600\n",
"3/3 - 0s - loss: 0.0018 - 19ms/epoch - 6ms/step\n",
"Epoch 75/600\n",
"3/3 - 0s - loss: 0.0018 - 20ms/epoch - 7ms/step\n",
"Epoch 76/600\n",
"3/3 - 0s - loss: 0.0017 - 19ms/epoch - 6ms/step\n",
"Epoch 77/600\n",
"3/3 - 0s - loss: 0.0017 - 20ms/epoch - 7ms/step\n",
"Epoch 78/600\n",
"3/3 - 0s - loss: 0.0016 - 20ms/epoch - 7ms/step\n",
"Epoch 79/600\n",
"3/3 - 0s - loss: 0.0016 - 21ms/epoch - 7ms/step\n",
"Epoch 80/600\n",
"3/3 - 0s - loss: 0.0016 - 24ms/epoch - 8ms/step\n",
"Epoch 81/600\n",
"3/3 - 0s - loss: 0.0015 - 23ms/epoch - 8ms/step\n",
"Epoch 82/600\n",
"3/3 - 0s - loss: 0.0015 - 20ms/epoch - 7ms/step\n",
"Epoch 83/600\n",
"3/3 - 0s - loss: 0.0014 - 20ms/epoch - 7ms/step\n",
"Epoch 84/600\n",
"3/3 - 0s - loss: 0.0014 - 20ms/epoch - 7ms/step\n",
"Epoch 85/600\n",
"3/3 - 0s - loss: 0.0013 - 21ms/epoch - 7ms/step\n",
"Epoch 86/600\n",
"3/3 - 0s - loss: 0.0013 - 19ms/epoch - 6ms/step\n",
"Epoch 87/600\n",
"3/3 - 0s - loss: 0.0013 - 17ms/epoch - 6ms/step\n",
"Epoch 88/600\n",
"3/3 - 0s - loss: 0.0012 - 17ms/epoch - 6ms/step\n",
"Epoch 89/600\n",
"3/3 - 0s - loss: 0.0012 - 20ms/epoch - 7ms/step\n",
"Epoch 90/600\n",
"3/3 - 0s - loss: 0.0012 - 19ms/epoch - 6ms/step\n",
"Epoch 91/600\n",
"3/3 - 0s - loss: 0.0011 - 20ms/epoch - 7ms/step\n",
"Epoch 92/600\n",
"3/3 - 0s - loss: 0.0011 - 20ms/epoch - 7ms/step\n",
"Epoch 93/600\n",
"3/3 - 0s - loss: 0.0010 - 20ms/epoch - 7ms/step\n",
"Epoch 94/600\n",
"3/3 - 0s - loss: 0.0010 - 20ms/epoch - 7ms/step\n",
"Epoch 95/600\n",
"3/3 - 0s - loss: 9.9175e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 96/600\n",
"3/3 - 0s - loss: 9.7160e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 97/600\n",
"3/3 - 0s - loss: 9.1934e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 98/600\n",
"3/3 - 0s - loss: 9.1939e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 99/600\n",
"3/3 - 0s - loss: 8.9917e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 100/600\n",
"3/3 - 0s - loss: 8.5670e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 101/600\n",
"3/3 - 0s - loss: 8.2558e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 102/600\n",
"3/3 - 0s - loss: 8.0836e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 103/600\n",
"3/3 - 0s - loss: 7.7820e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 104/600\n",
"3/3 - 0s - loss: 7.4222e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 105/600\n",
"3/3 - 0s - loss: 7.2910e-04 - 17ms/epoch - 6ms/step\n",
"Epoch 106/600\n",
"3/3 - 0s - loss: 7.1327e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 107/600\n",
"3/3 - 0s - loss: 6.7226e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 108/600\n",
"3/3 - 0s - loss: 6.5387e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 109/600\n",
"3/3 - 0s - loss: 6.3478e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 110/600\n",
"3/3 - 0s - loss: 6.0961e-04 - 21ms/epoch - 7ms/step\n",
"Epoch 111/600\n",
"3/3 - 0s - loss: 5.8166e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 112/600\n",
"3/3 - 0s - loss: 5.8480e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 113/600\n",
"3/3 - 0s - loss: 5.4503e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 114/600\n",
"3/3 - 0s - loss: 5.3062e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 115/600\n",
"3/3 - 0s - loss: 5.2946e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 116/600\n",
"3/3 - 0s - loss: 4.7874e-04 - 21ms/epoch - 7ms/step\n",
"Epoch 117/600\n",
"3/3 - 0s - loss: 4.7114e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 118/600\n",
"3/3 - 0s - loss: 4.5269e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 119/600\n",
"3/3 - 0s - loss: 4.5380e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 120/600\n",
"3/3 - 0s - loss: 4.2536e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 121/600\n",
"3/3 - 0s - loss: 3.9441e-04 - 17ms/epoch - 6ms/step\n",
"Epoch 122/600\n",
"3/3 - 0s - loss: 3.8316e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 123/600\n",
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"Epoch 124/600\n",
"3/3 - 0s - loss: 3.6512e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 125/600\n",
"3/3 - 0s - loss: 3.3016e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 126/600\n",
"3/3 - 0s - loss: 3.1494e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 127/600\n",
"3/3 - 0s - loss: 3.1160e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 128/600\n",
"3/3 - 0s - loss: 2.8627e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 129/600\n",
"3/3 - 0s - loss: 2.6777e-04 - 17ms/epoch - 6ms/step\n",
"Epoch 130/600\n",
"3/3 - 0s - loss: 2.6258e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 131/600\n",
"3/3 - 0s - loss: 2.4426e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 132/600\n",
"3/3 - 0s - loss: 2.4068e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 133/600\n",
"3/3 - 0s - loss: 2.2655e-04 - 17ms/epoch - 6ms/step\n",
"Epoch 134/600\n",
"3/3 - 0s - loss: 2.1242e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 135/600\n",
"3/3 - 0s - loss: 2.0196e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 136/600\n",
"3/3 - 0s - loss: 1.9252e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 137/600\n",
"3/3 - 0s - loss: 1.8062e-04 - 17ms/epoch - 6ms/step\n",
"Epoch 138/600\n",
"3/3 - 0s - loss: 1.7509e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 139/600\n",
"3/3 - 0s - loss: 1.6781e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 140/600\n",
"3/3 - 0s - loss: 1.5383e-04 - 18ms/epoch - 6ms/step\n",
"Epoch 141/600\n",
"3/3 - 0s - loss: 1.4289e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 142/600\n",
"3/3 - 0s - loss: 1.3294e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 143/600\n",
"3/3 - 0s - loss: 1.2580e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 144/600\n",
"3/3 - 0s - loss: 1.1927e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 145/600\n",
"3/3 - 0s - loss: 1.1094e-04 - 19ms/epoch - 6ms/step\n",
"Epoch 146/600\n",
"3/3 - 0s - loss: 1.1226e-04 - 20ms/epoch - 7ms/step\n",
"Epoch 147/600\n",
"3/3 - 0s - loss: 9.7595e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 148/600\n",
"3/3 - 0s - loss: 9.3520e-05 - 20ms/epoch - 7ms/step\n",
"Epoch 149/600\n",
"3/3 - 0s - loss: 8.7133e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 150/600\n",
"3/3 - 0s - loss: 8.2338e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 151/600\n",
"3/3 - 0s - loss: 8.4051e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 152/600\n",
"3/3 - 0s - loss: 7.1404e-05 - 21ms/epoch - 7ms/step\n",
"Epoch 153/600\n",
"3/3 - 0s - loss: 6.8557e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 154/600\n",
"3/3 - 0s - loss: 6.2511e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 155/600\n",
"3/3 - 0s - loss: 6.0561e-05 - 20ms/epoch - 7ms/step\n",
"Epoch 156/600\n",
"3/3 - 0s - loss: 5.4933e-05 - 20ms/epoch - 7ms/step\n",
"Epoch 157/600\n",
"3/3 - 0s - loss: 5.1755e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 158/600\n",
"3/3 - 0s - loss: 4.7015e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 159/600\n",
"3/3 - 0s - loss: 4.2376e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 160/600\n",
"3/3 - 0s - loss: 4.2349e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 161/600\n",
"3/3 - 0s - loss: 4.1130e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 162/600\n",
"3/3 - 0s - loss: 3.6309e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 163/600\n",
"3/3 - 0s - loss: 3.4193e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 164/600\n",
"3/3 - 0s - loss: 3.4451e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 165/600\n",
"3/3 - 0s - loss: 2.9192e-05 - 20ms/epoch - 7ms/step\n",
"Epoch 166/600\n",
"3/3 - 0s - loss: 2.7077e-05 - 20ms/epoch - 7ms/step\n",
"Epoch 167/600\n",
"3/3 - 0s - loss: 2.3977e-05 - 17ms/epoch - 6ms/step\n",
"Epoch 168/600\n",
"3/3 - 0s - loss: 2.3505e-05 - 20ms/epoch - 7ms/step\n",
"Epoch 169/600\n",
"3/3 - 0s - loss: 2.1494e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 170/600\n",
"3/3 - 0s - loss: 1.9601e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 171/600\n",
"3/3 - 0s - loss: 1.8738e-05 - 21ms/epoch - 7ms/step\n",
"Epoch 172/600\n",
"3/3 - 0s - loss: 1.7222e-05 - 19ms/epoch - 6ms/step\n",
"Epoch 173/600\n",
"3/3 - 0s - loss: 1.6006e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 174/600\n",
"3/3 - 0s - loss: 1.5306e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 175/600\n",
"3/3 - 0s - loss: 1.4319e-05 - 17ms/epoch - 6ms/step\n",
"Epoch 176/600\n",
"3/3 - 0s - loss: 1.3512e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 177/600\n",
"3/3 - 0s - loss: 1.3253e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 178/600\n",
"3/3 - 0s - loss: 1.0599e-05 - 18ms/epoch - 6ms/step\n",
"Epoch 179/600\n",
"3/3 - 0s - loss: 1.1178e-05 - 17ms/epoch - 6ms/step\n",
"Epoch 180/600\n",
"3/3 - 0s - loss: 9.1475e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 181/600\n",
"3/3 - 0s - loss: 9.3396e-06 - 19ms/epoch - 6ms/step\n",
"Epoch 182/600\n",
"3/3 - 0s - loss: 8.2424e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 183/600\n",
"3/3 - 0s - loss: 7.5882e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 184/600\n",
"3/3 - 0s - loss: 7.2334e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 185/600\n",
"3/3 - 0s - loss: 6.5040e-06 - 19ms/epoch - 6ms/step\n",
"Epoch 186/600\n",
"3/3 - 0s - loss: 6.0464e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 187/600\n",
"3/3 - 0s - loss: 5.6838e-06 - 19ms/epoch - 6ms/step\n",
"Epoch 188/600\n",
"3/3 - 0s - loss: 5.6350e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 189/600\n",
"3/3 - 0s - loss: 4.8108e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 190/600\n",
"3/3 - 0s - loss: 4.7074e-06 - 21ms/epoch - 7ms/step\n",
"Epoch 191/600\n",
"3/3 - 0s - loss: 4.3411e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 192/600\n",
"3/3 - 0s - loss: 3.8214e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 193/600\n",
"3/3 - 0s - loss: 3.8367e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 194/600\n",
"3/3 - 0s - loss: 3.3282e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 195/600\n",
"3/3 - 0s - loss: 3.1114e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 196/600\n",
"3/3 - 0s - loss: 3.0487e-06 - 19ms/epoch - 6ms/step\n",
"Epoch 197/600\n",
"3/3 - 0s - loss: 2.6585e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 198/600\n",
"3/3 - 0s - loss: 2.6784e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 199/600\n",
"3/3 - 0s - loss: 2.4610e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 200/600\n",
"3/3 - 0s - loss: 2.2299e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 201/600\n",
"3/3 - 0s - loss: 2.3534e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 202/600\n",
"3/3 - 0s - loss: 2.0683e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 203/600\n",
"3/3 - 0s - loss: 1.8921e-06 - 19ms/epoch - 6ms/step\n",
"Epoch 204/600\n",
"3/3 - 0s - loss: 1.9061e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 205/600\n",
"3/3 - 0s - loss: 1.6377e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 206/600\n",
"3/3 - 0s - loss: 1.5557e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 207/600\n",
"3/3 - 0s - loss: 1.4975e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 208/600\n",
"3/3 - 0s - loss: 1.4472e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 209/600\n",
"3/3 - 0s - loss: 1.3231e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 210/600\n",
"3/3 - 0s - loss: 1.2137e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 211/600\n",
"3/3 - 0s - loss: 1.0814e-06 - 19ms/epoch - 6ms/step\n",
"Epoch 212/600\n",
"3/3 - 0s - loss: 1.1012e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 213/600\n",
"3/3 - 0s - loss: 1.0367e-06 - 18ms/epoch - 6ms/step\n",
"Epoch 214/600\n",
"3/3 - 0s - loss: 1.0579e-06 - 17ms/epoch - 6ms/step\n",
"Epoch 215/600\n",
"3/3 - 0s - loss: 8.6901e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 216/600\n",
"3/3 - 0s - loss: 9.2759e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 217/600\n",
"3/3 - 0s - loss: 7.7820e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 218/600\n",
"3/3 - 0s - loss: 7.5039e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 219/600\n",
"3/3 - 0s - loss: 6.8642e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 220/600\n",
"3/3 - 0s - loss: 6.7417e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 221/600\n",
"3/3 - 0s - loss: 6.2442e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 222/600\n",
"3/3 - 0s - loss: 6.4821e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 223/600\n",
"3/3 - 0s - loss: 6.0551e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 224/600\n",
"3/3 - 0s - loss: 5.7419e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 225/600\n",
"3/3 - 0s - loss: 5.5595e-07 - 20ms/epoch - 7ms/step\n",
"Epoch 226/600\n",
"3/3 - 0s - loss: 5.1922e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 227/600\n",
"3/3 - 0s - loss: 5.5299e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 228/600\n",
"3/3 - 0s - loss: 5.0953e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 229/600\n",
"3/3 - 0s - loss: 5.3831e-07 - 20ms/epoch - 7ms/step\n",
"Epoch 230/600\n",
"3/3 - 0s - loss: 4.5238e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 231/600\n",
"3/3 - 0s - loss: 5.3890e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 232/600\n",
"3/3 - 0s - loss: 4.1443e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 233/600\n",
"3/3 - 0s - loss: 5.0137e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 234/600\n",
"3/3 - 0s - loss: 4.2846e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 235/600\n",
"3/3 - 0s - loss: 4.2069e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 236/600\n",
"3/3 - 0s - loss: 5.2210e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 237/600\n",
"3/3 - 0s - loss: 4.9140e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 238/600\n",
"3/3 - 0s - loss: 4.2449e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 239/600\n",
"3/3 - 0s - loss: 4.8237e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 240/600\n",
"3/3 - 0s - loss: 4.1727e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 241/600\n",
"3/3 - 0s - loss: 3.8011e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 242/600\n",
"3/3 - 0s - loss: 4.0372e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 243/600\n",
"3/3 - 0s - loss: 3.6880e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 244/600\n",
"3/3 - 0s - loss: 3.5867e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 245/600\n",
"3/3 - 0s - loss: 3.5779e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 246/600\n",
"3/3 - 0s - loss: 3.3445e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 247/600\n",
"3/3 - 0s - loss: 3.2059e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 248/600\n",
"3/3 - 0s - loss: 3.1275e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 249/600\n",
"3/3 - 0s - loss: 3.0808e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 250/600\n",
"3/3 - 0s - loss: 3.0408e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 251/600\n",
"3/3 - 0s - loss: 2.9309e-07 - 21ms/epoch - 7ms/step\n",
"Epoch 252/600\n",
"3/3 - 0s - loss: 3.4348e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 253/600\n",
"3/3 - 0s - loss: 3.1357e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 254/600\n",
"3/3 - 0s - loss: 2.8772e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 255/600\n",
"3/3 - 0s - loss: 3.0372e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 256/600\n",
"3/3 - 0s - loss: 2.7702e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 257/600\n",
"3/3 - 0s - loss: 2.8394e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 258/600\n",
"3/3 - 0s - loss: 2.6677e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 259/600\n",
"3/3 - 0s - loss: 2.8928e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 260/600\n",
"3/3 - 0s - loss: 2.7944e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 261/600\n",
"3/3 - 0s - loss: 3.1606e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 262/600\n",
"3/3 - 0s - loss: 2.5433e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 263/600\n",
"3/3 - 0s - loss: 2.6045e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 264/600\n",
"3/3 - 0s - loss: 2.6014e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 265/600\n",
"3/3 - 0s - loss: 2.4268e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 266/600\n",
"3/3 - 0s - loss: 2.4573e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 267/600\n",
"3/3 - 0s - loss: 2.4149e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 268/600\n",
"3/3 - 0s - loss: 2.4068e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 269/600\n",
"3/3 - 0s - loss: 2.3706e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 270/600\n",
"3/3 - 0s - loss: 2.3918e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 271/600\n",
"3/3 - 0s - loss: 2.4026e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 272/600\n",
"3/3 - 0s - loss: 2.2306e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 273/600\n",
"3/3 - 0s - loss: 2.3760e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 274/600\n",
"3/3 - 0s - loss: 2.4834e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 275/600\n",
"3/3 - 0s - loss: 2.4366e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 276/600\n",
"3/3 - 0s - loss: 2.2627e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 277/600\n",
"3/3 - 0s - loss: 2.5376e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 278/600\n",
"3/3 - 0s - loss: 2.3523e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 279/600\n",
"3/3 - 0s - loss: 2.1522e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 280/600\n",
"3/3 - 0s - loss: 2.2154e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 281/600\n",
"3/3 - 0s - loss: 2.0595e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 282/600\n",
"3/3 - 0s - loss: 2.0932e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 283/600\n",
"3/3 - 0s - loss: 2.1318e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 284/600\n",
"3/3 - 0s - loss: 2.0770e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 285/600\n",
"3/3 - 0s - loss: 2.3224e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 286/600\n",
"3/3 - 0s - loss: 2.0743e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 287/600\n",
"3/3 - 0s - loss: 1.9832e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 288/600\n",
"3/3 - 0s - loss: 2.3544e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 289/600\n",
"3/3 - 0s - loss: 2.0329e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 290/600\n",
"3/3 - 0s - loss: 1.8422e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 291/600\n",
"3/3 - 0s - loss: 2.1591e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 292/600\n",
"3/3 - 0s - loss: 1.8602e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 293/600\n",
"3/3 - 0s - loss: 1.8403e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 294/600\n",
"3/3 - 0s - loss: 1.8101e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 295/600\n",
"3/3 - 0s - loss: 1.7758e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 296/600\n",
"3/3 - 0s - loss: 1.8401e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 297/600\n",
"3/3 - 0s - loss: 1.9147e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 298/600\n",
"3/3 - 0s - loss: 1.7183e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 299/600\n",
"3/3 - 0s - loss: 2.1222e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 300/600\n",
"3/3 - 0s - loss: 1.9317e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 301/600\n",
"3/3 - 0s - loss: 1.8375e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 302/600\n",
"3/3 - 0s - loss: 1.9362e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 303/600\n",
"3/3 - 0s - loss: 2.1317e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 304/600\n",
"3/3 - 0s - loss: 2.1440e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 305/600\n",
"3/3 - 0s - loss: 2.1560e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 306/600\n",
"3/3 - 0s - loss: 2.0397e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 307/600\n",
"3/3 - 0s - loss: 1.9984e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 308/600\n",
"3/3 - 0s - loss: 2.2129e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 309/600\n",
"3/3 - 0s - loss: 2.3031e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 310/600\n",
"3/3 - 0s - loss: 1.7201e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 311/600\n",
"3/3 - 0s - loss: 1.9411e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 312/600\n",
"3/3 - 0s - loss: 1.9448e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 313/600\n",
"3/3 - 0s - loss: 1.6600e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 314/600\n",
"3/3 - 0s - loss: 1.5323e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 315/600\n",
"3/3 - 0s - loss: 1.6354e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 316/600\n",
"3/3 - 0s - loss: 1.5027e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 317/600\n",
"3/3 - 0s - loss: 1.5395e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 318/600\n",
"3/3 - 0s - loss: 1.4699e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 319/600\n",
"3/3 - 0s - loss: 1.4190e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 320/600\n",
"3/3 - 0s - loss: 1.4405e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 321/600\n",
"3/3 - 0s - loss: 1.4744e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 322/600\n",
"3/3 - 0s - loss: 1.4585e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 323/600\n",
"3/3 - 0s - loss: 1.5841e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 324/600\n",
"3/3 - 0s - loss: 1.5570e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 325/600\n",
"3/3 - 0s - loss: 1.4753e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 326/600\n",
"3/3 - 0s - loss: 1.4586e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 327/600\n",
"3/3 - 0s - loss: 1.3731e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 328/600\n",
"3/3 - 0s - loss: 1.4161e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 329/600\n",
"3/3 - 0s - loss: 1.3163e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 330/600\n",
"3/3 - 0s - loss: 1.7134e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 331/600\n",
"3/3 - 0s - loss: 1.9550e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 332/600\n",
"3/3 - 0s - loss: 1.4891e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 333/600\n",
"3/3 - 0s - loss: 1.6563e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 334/600\n",
"3/3 - 0s - loss: 1.4941e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 335/600\n",
"3/3 - 0s - loss: 1.6838e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 336/600\n",
"3/3 - 0s - loss: 1.9736e-07 - 20ms/epoch - 7ms/step\n",
"Epoch 337/600\n",
"3/3 - 0s - loss: 1.1688e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 338/600\n",
"3/3 - 0s - loss: 1.5850e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 339/600\n",
"3/3 - 0s - loss: 1.4288e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 340/600\n",
"3/3 - 0s - loss: 1.3207e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 341/600\n",
"3/3 - 0s - loss: 1.4376e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 342/600\n",
"3/3 - 0s - loss: 1.6759e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 343/600\n",
"3/3 - 0s - loss: 1.4996e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 344/600\n",
"3/3 - 0s - loss: 1.5474e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 345/600\n",
"3/3 - 0s - loss: 1.5305e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 346/600\n",
"3/3 - 0s - loss: 1.5095e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 347/600\n",
"3/3 - 0s - loss: 1.4360e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 348/600\n",
"3/3 - 0s - loss: 1.0976e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 349/600\n",
"3/3 - 0s - loss: 1.2650e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 350/600\n",
"3/3 - 0s - loss: 1.3316e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 351/600\n",
"3/3 - 0s - loss: 1.1045e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 352/600\n",
"3/3 - 0s - loss: 1.1529e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 353/600\n",
"3/3 - 0s - loss: 1.1211e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 354/600\n",
"3/3 - 0s - loss: 1.0878e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 355/600\n",
"3/3 - 0s - loss: 1.1071e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 356/600\n",
"3/3 - 0s - loss: 9.9950e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 357/600\n",
"3/3 - 0s - loss: 1.1369e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 358/600\n",
"3/3 - 0s - loss: 1.2189e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 359/600\n",
"3/3 - 0s - loss: 1.0373e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 360/600\n",
"3/3 - 0s - loss: 1.2454e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 361/600\n",
"3/3 - 0s - loss: 1.3100e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 362/600\n",
"3/3 - 0s - loss: 1.1431e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 363/600\n",
"3/3 - 0s - loss: 1.1297e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 364/600\n",
"3/3 - 0s - loss: 1.3847e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 365/600\n",
"3/3 - 0s - loss: 1.1059e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 366/600\n",
"3/3 - 0s - loss: 1.0736e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 367/600\n",
"3/3 - 0s - loss: 1.1491e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 368/600\n",
"3/3 - 0s - loss: 1.1969e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 369/600\n",
"3/3 - 0s - loss: 9.6771e-08 - 21ms/epoch - 7ms/step\n",
"Epoch 370/600\n",
"3/3 - 0s - loss: 1.1021e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 371/600\n",
"3/3 - 0s - loss: 1.0336e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 372/600\n",
"3/3 - 0s - loss: 1.1251e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 373/600\n",
"3/3 - 0s - loss: 1.1028e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 374/600\n",
"3/3 - 0s - loss: 9.5262e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 375/600\n",
"3/3 - 0s - loss: 1.0350e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 376/600\n",
"3/3 - 0s - loss: 9.3561e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 377/600\n",
"3/3 - 0s - loss: 1.0377e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 378/600\n",
"3/3 - 0s - loss: 9.5911e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 379/600\n",
"3/3 - 0s - loss: 1.0765e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 380/600\n",
"3/3 - 0s - loss: 9.6007e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 381/600\n",
"3/3 - 0s - loss: 1.0157e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 382/600\n",
"3/3 - 0s - loss: 9.6630e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 383/600\n",
"3/3 - 0s - loss: 9.2116e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 384/600\n",
"3/3 - 0s - loss: 9.2046e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 385/600\n",
"3/3 - 0s - loss: 9.8998e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 386/600\n",
"3/3 - 0s - loss: 9.5565e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 387/600\n",
"3/3 - 0s - loss: 1.2183e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 388/600\n",
"3/3 - 0s - loss: 1.1153e-07 - 16ms/epoch - 5ms/step\n",
"Epoch 389/600\n",
"3/3 - 0s - loss: 9.0460e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 390/600\n",
"3/3 - 0s - loss: 9.9698e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 391/600\n",
"3/3 - 0s - loss: 8.3681e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 392/600\n",
"3/3 - 0s - loss: 1.1799e-07 - 17ms/epoch - 6ms/step\n",
"Epoch 393/600\n",
"3/3 - 0s - loss: 8.8952e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 394/600\n",
"3/3 - 0s - loss: 1.0968e-07 - 19ms/epoch - 6ms/step\n",
"Epoch 395/600\n",
"3/3 - 0s - loss: 1.2105e-07 - 18ms/epoch - 6ms/step\n",
"Epoch 396/600\n",
"3/3 - 0s - loss: 7.4285e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 397/600\n",
"3/3 - 0s - loss: 9.1431e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 398/600\n",
"3/3 - 0s - loss: 7.5279e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 399/600\n",
"3/3 - 0s - loss: 8.7076e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 400/600\n",
"3/3 - 0s - loss: 7.7606e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 401/600\n",
"3/3 - 0s - loss: 8.0799e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 402/600\n",
"3/3 - 0s - loss: 7.7469e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 403/600\n",
"3/3 - 0s - loss: 7.4221e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 404/600\n",
"3/3 - 0s - loss: 7.2481e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 405/600\n",
"3/3 - 0s - loss: 7.8779e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 406/600\n",
"3/3 - 0s - loss: 8.1153e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 407/600\n",
"3/3 - 0s - loss: 8.4900e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 408/600\n",
"3/3 - 0s - loss: 9.6151e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 409/600\n",
"3/3 - 0s - loss: 7.7901e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 410/600\n",
"3/3 - 0s - loss: 8.9594e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 411/600\n",
"3/3 - 0s - loss: 7.2830e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 412/600\n",
"3/3 - 0s - loss: 7.7258e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 413/600\n",
"3/3 - 0s - loss: 7.3764e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 414/600\n",
"3/3 - 0s - loss: 6.9179e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 415/600\n",
"3/3 - 0s - loss: 6.9631e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 416/600\n",
"3/3 - 0s - loss: 6.8140e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 417/600\n",
"3/3 - 0s - loss: 7.6016e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 418/600\n",
"3/3 - 0s - loss: 7.2604e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 419/600\n",
"3/3 - 0s - loss: 7.0878e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 420/600\n",
"3/3 - 0s - loss: 7.3099e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 421/600\n",
"3/3 - 0s - loss: 7.0737e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 422/600\n",
"3/3 - 0s - loss: 7.0299e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 423/600\n",
"3/3 - 0s - loss: 7.4157e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 424/600\n",
"3/3 - 0s - loss: 8.0799e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 425/600\n",
"3/3 - 0s - loss: 8.6588e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 426/600\n",
"3/3 - 0s - loss: 7.2217e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 427/600\n",
"3/3 - 0s - loss: 7.0006e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 428/600\n",
"3/3 - 0s - loss: 8.4730e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 429/600\n",
"3/3 - 0s - loss: 8.4061e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 430/600\n",
"3/3 - 0s - loss: 7.0861e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 431/600\n",
"3/3 - 0s - loss: 6.2573e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 432/600\n",
"3/3 - 0s - loss: 7.9075e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 433/600\n",
"3/3 - 0s - loss: 6.6627e-08 - 23ms/epoch - 8ms/step\n",
"Epoch 434/600\n",
"3/3 - 0s - loss: 6.9767e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 435/600\n",
"3/3 - 0s - loss: 8.2181e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 436/600\n",
"3/3 - 0s - loss: 7.3544e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 437/600\n",
"3/3 - 0s - loss: 6.1450e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 438/600\n",
"3/3 - 0s - loss: 6.2898e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 439/600\n",
"3/3 - 0s - loss: 6.3277e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 440/600\n",
"3/3 - 0s - loss: 5.9180e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 441/600\n",
"3/3 - 0s - loss: 6.7579e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 442/600\n",
"3/3 - 0s - loss: 8.3768e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 443/600\n",
"3/3 - 0s - loss: 6.7668e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 444/600\n",
"3/3 - 0s - loss: 6.1503e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 445/600\n",
"3/3 - 0s - loss: 5.7124e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 446/600\n",
"3/3 - 0s - loss: 5.9290e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 447/600\n",
"3/3 - 0s - loss: 6.0694e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 448/600\n",
"3/3 - 0s - loss: 5.8756e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 449/600\n",
"3/3 - 0s - loss: 5.7755e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 450/600\n",
"3/3 - 0s - loss: 5.9693e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 451/600\n",
"3/3 - 0s - loss: 5.2393e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 452/600\n",
"3/3 - 0s - loss: 7.4925e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 453/600\n",
"3/3 - 0s - loss: 5.8268e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 454/600\n",
"3/3 - 0s - loss: 5.9728e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 455/600\n",
"3/3 - 0s - loss: 5.5067e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 456/600\n",
"3/3 - 0s - loss: 5.6427e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 457/600\n",
"3/3 - 0s - loss: 5.0045e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 458/600\n",
"3/3 - 0s - loss: 5.6459e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 459/600\n",
"3/3 - 0s - loss: 6.9810e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 460/600\n",
"3/3 - 0s - loss: 8.4879e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 461/600\n",
"3/3 - 0s - loss: 7.8481e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 462/600\n",
"3/3 - 0s - loss: 5.7484e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 463/600\n",
"3/3 - 0s - loss: 5.6489e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 464/600\n",
"3/3 - 0s - loss: 6.4932e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 465/600\n",
"3/3 - 0s - loss: 6.4632e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 466/600\n",
"3/3 - 0s - loss: 5.4950e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 467/600\n",
"3/3 - 0s - loss: 6.7931e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 468/600\n",
"3/3 - 0s - loss: 6.3551e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 469/600\n",
"3/3 - 0s - loss: 5.1181e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 470/600\n",
"3/3 - 0s - loss: 4.8830e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 471/600\n",
"3/3 - 0s - loss: 5.4158e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 472/600\n",
"3/3 - 0s - loss: 5.3932e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 473/600\n",
"3/3 - 0s - loss: 5.1400e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 474/600\n",
"3/3 - 0s - loss: 5.0049e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 475/600\n",
"3/3 - 0s - loss: 4.7968e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 476/600\n",
"3/3 - 0s - loss: 5.0733e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 477/600\n",
"3/3 - 0s - loss: 4.8479e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 478/600\n",
"3/3 - 0s - loss: 4.5347e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 479/600\n",
"3/3 - 0s - loss: 4.5587e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 480/600\n",
"3/3 - 0s - loss: 4.7967e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 481/600\n",
"3/3 - 0s - loss: 4.5294e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 482/600\n",
"3/3 - 0s - loss: 4.9768e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 483/600\n",
"3/3 - 0s - loss: 6.2928e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 484/600\n",
"3/3 - 0s - loss: 5.7928e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 485/600\n",
"3/3 - 0s - loss: 5.8018e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 486/600\n",
"3/3 - 0s - loss: 7.2048e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 487/600\n",
"3/3 - 0s - loss: 6.8709e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 488/600\n",
"3/3 - 0s - loss: 5.8280e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 489/600\n",
"3/3 - 0s - loss: 7.0236e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 490/600\n",
"3/3 - 0s - loss: 6.5742e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 491/600\n",
"3/3 - 0s - loss: 6.5217e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 492/600\n",
"3/3 - 0s - loss: 7.9026e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 493/600\n",
"3/3 - 0s - loss: 6.6774e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 494/600\n",
"3/3 - 0s - loss: 4.7015e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 495/600\n",
"3/3 - 0s - loss: 5.3433e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 496/600\n",
"3/3 - 0s - loss: 5.1338e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 497/600\n",
"3/3 - 0s - loss: 4.5060e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 498/600\n",
"3/3 - 0s - loss: 4.7938e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 499/600\n",
"3/3 - 0s - loss: 4.4799e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 500/600\n",
"3/3 - 0s - loss: 5.0362e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 501/600\n",
"3/3 - 0s - loss: 4.4256e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 502/600\n",
"3/3 - 0s - loss: 4.0775e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 503/600\n",
"3/3 - 0s - loss: 4.0000e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 504/600\n",
"3/3 - 0s - loss: 3.9693e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 505/600\n",
"3/3 - 0s - loss: 3.7061e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 506/600\n",
"3/3 - 0s - loss: 3.9355e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 507/600\n",
"3/3 - 0s - loss: 3.9811e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 508/600\n",
"3/3 - 0s - loss: 3.7174e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 509/600\n",
"3/3 - 0s - loss: 3.7193e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 510/600\n",
"3/3 - 0s - loss: 3.7218e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 511/600\n",
"3/3 - 0s - loss: 4.1305e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 512/600\n",
"3/3 - 0s - loss: 3.5842e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 513/600\n",
"3/3 - 0s - loss: 3.5438e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 514/600\n",
"3/3 - 0s - loss: 4.2435e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 515/600\n",
"3/3 - 0s - loss: 4.6417e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 516/600\n",
"3/3 - 0s - loss: 3.9056e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 517/600\n",
"3/3 - 0s - loss: 4.7542e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 518/600\n",
"3/3 - 0s - loss: 4.1235e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 519/600\n",
"3/3 - 0s - loss: 3.7268e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 520/600\n",
"3/3 - 0s - loss: 4.0164e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 521/600\n",
"3/3 - 0s - loss: 3.4524e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 522/600\n",
"3/3 - 0s - loss: 4.1617e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 523/600\n",
"3/3 - 0s - loss: 4.0596e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 524/600\n",
"3/3 - 0s - loss: 4.4117e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 525/600\n",
"3/3 - 0s - loss: 3.3849e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 526/600\n",
"3/3 - 0s - loss: 3.5670e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 527/600\n",
"3/3 - 0s - loss: 3.8044e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 528/600\n",
"3/3 - 0s - loss: 3.9683e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 529/600\n",
"3/3 - 0s - loss: 3.4610e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 530/600\n",
"3/3 - 0s - loss: 3.8500e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 531/600\n",
"3/3 - 0s - loss: 3.8916e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 532/600\n",
"3/3 - 0s - loss: 3.9176e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 533/600\n",
"3/3 - 0s - loss: 3.1848e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 534/600\n",
"3/3 - 0s - loss: 3.4688e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 535/600\n",
"3/3 - 0s - loss: 3.3907e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 536/600\n",
"3/3 - 0s - loss: 4.0806e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 537/600\n",
"3/3 - 0s - loss: 3.8817e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 538/600\n",
"3/3 - 0s - loss: 3.5881e-08 - 21ms/epoch - 7ms/step\n",
"Epoch 539/600\n",
"3/3 - 0s - loss: 4.2593e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 540/600\n",
"3/3 - 0s - loss: 3.5349e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 541/600\n",
"3/3 - 0s - loss: 3.1435e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 542/600\n",
"3/3 - 0s - loss: 3.5932e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 543/600\n",
"3/3 - 0s - loss: 3.6199e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 544/600\n",
"3/3 - 0s - loss: 3.3507e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 545/600\n",
"3/3 - 0s - loss: 3.6200e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 546/600\n",
"3/3 - 0s - loss: 4.0353e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 547/600\n",
"3/3 - 0s - loss: 3.6099e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 548/600\n",
"3/3 - 0s - loss: 3.9779e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 549/600\n",
"3/3 - 0s - loss: 3.2686e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 550/600\n",
"3/3 - 0s - loss: 3.3786e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 551/600\n",
"3/3 - 0s - loss: 4.6635e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 552/600\n",
"3/3 - 0s - loss: 3.2934e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 553/600\n",
"3/3 - 0s - loss: 3.3727e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 554/600\n",
"3/3 - 0s - loss: 5.2191e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 555/600\n",
"3/3 - 0s - loss: 3.6277e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 556/600\n",
"3/3 - 0s - loss: 4.3152e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 557/600\n",
"3/3 - 0s - loss: 3.4447e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 558/600\n",
"3/3 - 0s - loss: 3.8308e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 559/600\n",
"3/3 - 0s - loss: 3.4180e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 560/600\n",
"3/3 - 0s - loss: 3.2723e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 561/600\n",
"3/3 - 0s - loss: 3.3313e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 562/600\n",
"3/3 - 0s - loss: 4.0636e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 563/600\n",
"3/3 - 0s - loss: 3.9440e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 564/600\n",
"3/3 - 0s - loss: 2.9614e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 565/600\n",
"3/3 - 0s - loss: 3.5028e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 566/600\n",
"3/3 - 0s - loss: 3.1181e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 567/600\n",
"3/3 - 0s - loss: 3.8115e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 568/600\n",
"3/3 - 0s - loss: 4.8947e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 569/600\n",
"3/3 - 0s - loss: 5.4386e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 570/600\n",
"3/3 - 0s - loss: 4.6262e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 571/600\n",
"3/3 - 0s - loss: 3.1405e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 572/600\n",
"3/3 - 0s - loss: 3.4291e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 573/600\n",
"3/3 - 0s - loss: 3.0647e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 574/600\n",
"3/3 - 0s - loss: 3.7326e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 575/600\n",
"3/3 - 0s - loss: 2.9520e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 576/600\n",
"3/3 - 0s - loss: 2.7857e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 577/600\n",
"3/3 - 0s - loss: 2.4016e-08 - 21ms/epoch - 7ms/step\n",
"Epoch 578/600\n",
"3/3 - 0s - loss: 2.6693e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 579/600\n",
"3/3 - 0s - loss: 2.5403e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 580/600\n",
"3/3 - 0s - loss: 2.7897e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 581/600\n",
"3/3 - 0s - loss: 2.8217e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 582/600\n",
"3/3 - 0s - loss: 3.1185e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 583/600\n",
"3/3 - 0s - loss: 2.7439e-08 - 16ms/epoch - 5ms/step\n",
"Epoch 584/600\n",
"3/3 - 0s - loss: 3.8568e-08 - 20ms/epoch - 7ms/step\n",
"Epoch 585/600\n",
"3/3 - 0s - loss: 3.6706e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 586/600\n",
"3/3 - 0s - loss: 3.4904e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 587/600\n",
"3/3 - 0s - loss: 3.2432e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 588/600\n",
"3/3 - 0s - loss: 3.6042e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 589/600\n",
"3/3 - 0s - loss: 2.9780e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 590/600\n",
"3/3 - 0s - loss: 3.1562e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 591/600\n",
"3/3 - 0s - loss: 2.7406e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 592/600\n",
"3/3 - 0s - loss: 3.2185e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 593/600\n",
"3/3 - 0s - loss: 2.7582e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 594/600\n",
"3/3 - 0s - loss: 3.4031e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 595/600\n",
"3/3 - 0s - loss: 2.7156e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 596/600\n",
"3/3 - 0s - loss: 2.7635e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 597/600\n",
"3/3 - 0s - loss: 2.8050e-08 - 17ms/epoch - 6ms/step\n",
"Epoch 598/600\n",
"3/3 - 0s - loss: 3.8239e-08 - 18ms/epoch - 6ms/step\n",
"Epoch 599/600\n",
"3/3 - 0s - loss: 2.6142e-08 - 19ms/epoch - 6ms/step\n",
"Epoch 600/600\n",
"3/3 - 0s - loss: 2.7255e-08 - 19ms/epoch - 6ms/step\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<keras.src.callbacks.History at 0x7ec198594130>"
]
},
"metadata": {},
"execution_count": 152
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "n-aNP4n3sqG_",
"outputId": "2e59e8b8-d088-4935-f192-cc68fbbcb93f",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 443
}
},
"source": [
"# Plotting code, feel free to ignore.\n",
"h = 1.0\n",
"x_min, x_max = X[:, 0].min() - 5, X[:, 0].max() + 5\n",
"y_min, y_max = X[:, 1].min() - 5, X[:, 1].max() + 5\n",
"xx, yy = np.meshgrid(np.arange(x_min, x_max, h),\n",
" np.arange(y_min, y_max, h))\n",
"\n",
"# here \"model\" is your model's prediction (classification) function\n",
"Z = tn_model.predict(np.c_[xx.ravel(), yy.ravel()])\n",
"\n",
"# Put the result into a color plot\n",
"Z = Z.reshape(xx.shape)\n",
"plt.contourf(xx, yy, Z)\n",
"plt.axis('off')\n",
"\n",
"# Plot also the training points\n",
"plt.scatter(X[:, 0], X[:, 1], c=Y, cmap=plt.cm.Paired)"
],
"execution_count": 153,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"14/14 [==============================] - 0s 4ms/step\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7ec1802114e0>"
]
},
"metadata": {},
"execution_count": 153
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since end of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "wfZCzuq9KY9b",
"outputId": "5fe901e2-d0c1-4cb5-fe41-41ef9f6a38b3"
},
"execution_count": 154,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1710205513.8816519\n",
"Tue Mar 12 01:05:13 2024\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "Ft6S13x6KuEQ",
"outputId": "2422ef6a-4715-48d2-a8ac-51af2d71f9b6"
},
"execution_count": 155,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1710205513.891752\n",
"Tue Mar 12 01:05:13 2024\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "BMxSJo5gtOmQ"
},
"source": [
"# VS Fully Connected"
]
},
{
"cell_type": "code",
"metadata": {
"id": "NKQx7stYswzU",
"outputId": "35f84cc4-6ffa-4a31-ee35-52fc5d03516a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 22474
}
},
"source": [
"fc_model.compile(optimizer=\"adam\", loss=\"mean_squared_error\")\n",
"fc_model.fit(X, Y, epochs=600, verbose=2)\n",
"# Plotting code, feel free to ignore.\n",
"h = 1.0\n",
"x_min, x_max = X[:, 0].min() - 5, X[:, 0].max() + 5\n",
"y_min, y_max = X[:, 1].min() - 5, X[:, 1].max() + 5\n",
"xx, yy = np.meshgrid(np.arange(x_min, x_max, h),\n",
" np.arange(y_min, y_max, h))\n",
"\n",
"# here \"model\" is your model's prediction (classification) function\n",
"Z = fc_model.predict(np.c_[xx.ravel(), yy.ravel()])\n",
"\n",
"# Put the result into a color plot\n",
"Z = Z.reshape(xx.shape)\n",
"plt.contourf(xx, yy, Z)\n",
"plt.axis('off')\n",
"\n",
"# Plot also the training points\n",
"plt.scatter(X[:, 0], X[:, 1], c=Y, cmap=plt.cm.Paired)"
],
"execution_count": 156,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/600\n",
"3/3 - 1s - loss: 0.5656 - 652ms/epoch - 217ms/step\n",
"Epoch 2/600\n",
"3/3 - 0s - loss: 0.1959 - 23ms/epoch - 8ms/step\n",
"Epoch 3/600\n",
"3/3 - 0s - loss: 0.1423 - 25ms/epoch - 8ms/step\n",
"Epoch 4/600\n",
"3/3 - 0s - loss: 0.0917 - 26ms/epoch - 9ms/step\n",
"Epoch 5/600\n",
"3/3 - 0s - loss: 0.0828 - 25ms/epoch - 8ms/step\n",
"Epoch 6/600\n",
"3/3 - 0s - loss: 0.0827 - 24ms/epoch - 8ms/step\n",
"Epoch 7/600\n",
"3/3 - 0s - loss: 0.0680 - 28ms/epoch - 9ms/step\n",
"Epoch 8/600\n",
"3/3 - 0s - loss: 0.0680 - 26ms/epoch - 9ms/step\n",
"Epoch 9/600\n",
"3/3 - 0s - loss: 0.0605 - 23ms/epoch - 8ms/step\n",
"Epoch 10/600\n",
"3/3 - 0s - loss: 0.0632 - 25ms/epoch - 8ms/step\n",
"Epoch 11/600\n",
"3/3 - 0s - loss: 0.0537 - 23ms/epoch - 8ms/step\n",
"Epoch 12/600\n",
"3/3 - 0s - loss: 0.0523 - 25ms/epoch - 8ms/step\n",
"Epoch 13/600\n",
"3/3 - 0s - loss: 0.0522 - 23ms/epoch - 8ms/step\n",
"Epoch 14/600\n",
"3/3 - 0s - loss: 0.0483 - 24ms/epoch - 8ms/step\n",
"Epoch 15/600\n",
"3/3 - 0s - loss: 0.0498 - 26ms/epoch - 9ms/step\n",
"Epoch 16/600\n",
"3/3 - 0s - loss: 0.0444 - 28ms/epoch - 9ms/step\n",
"Epoch 17/600\n",
"3/3 - 0s - loss: 0.0487 - 26ms/epoch - 9ms/step\n",
"Epoch 18/600\n",
"3/3 - 0s - loss: 0.0467 - 26ms/epoch - 9ms/step\n",
"Epoch 19/600\n",
"3/3 - 0s - loss: 0.0419 - 22ms/epoch - 7ms/step\n",
"Epoch 20/600\n",
"3/3 - 0s - loss: 0.0439 - 23ms/epoch - 8ms/step\n",
"Epoch 21/600\n",
"3/3 - 0s - loss: 0.0406 - 27ms/epoch - 9ms/step\n",
"Epoch 22/600\n",
"3/3 - 0s - loss: 0.0414 - 24ms/epoch - 8ms/step\n",
"Epoch 23/600\n",
"3/3 - 0s - loss: 0.0421 - 23ms/epoch - 8ms/step\n",
"Epoch 24/600\n",
"3/3 - 0s - loss: 0.0378 - 25ms/epoch - 8ms/step\n",
"Epoch 25/600\n",
"3/3 - 0s - loss: 0.0382 - 23ms/epoch - 8ms/step\n",
"Epoch 26/600\n",
"3/3 - 0s - loss: 0.0425 - 22ms/epoch - 7ms/step\n",
"Epoch 27/600\n",
"3/3 - 0s - loss: 0.0505 - 24ms/epoch - 8ms/step\n",
"Epoch 28/600\n",
"3/3 - 0s - loss: 0.0423 - 23ms/epoch - 8ms/step\n",
"Epoch 29/600\n",
"3/3 - 0s - loss: 0.0513 - 25ms/epoch - 8ms/step\n",
"Epoch 30/600\n",
"3/3 - 0s - loss: 0.0385 - 25ms/epoch - 8ms/step\n",
"Epoch 31/600\n",
"3/3 - 0s - loss: 0.0392 - 26ms/epoch - 9ms/step\n",
"Epoch 32/600\n",
"3/3 - 0s - loss: 0.0417 - 24ms/epoch - 8ms/step\n",
"Epoch 33/600\n",
"3/3 - 0s - loss: 0.0414 - 24ms/epoch - 8ms/step\n",
"Epoch 34/600\n",
"3/3 - 0s - loss: 0.0374 - 23ms/epoch - 8ms/step\n",
"Epoch 35/600\n",
"3/3 - 0s - loss: 0.0348 - 27ms/epoch - 9ms/step\n",
"Epoch 36/600\n",
"3/3 - 0s - loss: 0.0319 - 24ms/epoch - 8ms/step\n",
"Epoch 37/600\n",
"3/3 - 0s - loss: 0.0429 - 24ms/epoch - 8ms/step\n",
"Epoch 38/600\n",
"3/3 - 0s - loss: 0.0382 - 27ms/epoch - 9ms/step\n",
"Epoch 39/600\n",
"3/3 - 0s - loss: 0.0266 - 25ms/epoch - 8ms/step\n",
"Epoch 40/600\n",
"3/3 - 0s - loss: 0.0399 - 25ms/epoch - 8ms/step\n",
"Epoch 41/600\n",
"3/3 - 0s - loss: 0.0336 - 24ms/epoch - 8ms/step\n",
"Epoch 42/600\n",
"3/3 - 0s - loss: 0.0293 - 24ms/epoch - 8ms/step\n",
"Epoch 43/600\n",
"3/3 - 0s - loss: 0.0304 - 26ms/epoch - 9ms/step\n",
"Epoch 44/600\n",
"3/3 - 0s - loss: 0.0370 - 24ms/epoch - 8ms/step\n",
"Epoch 45/600\n",
"3/3 - 0s - loss: 0.0295 - 27ms/epoch - 9ms/step\n",
"Epoch 46/600\n",
"3/3 - 0s - loss: 0.0278 - 26ms/epoch - 9ms/step\n",
"Epoch 47/600\n",
"3/3 - 0s - loss: 0.0298 - 25ms/epoch - 8ms/step\n",
"Epoch 48/600\n",
"3/3 - 0s - loss: 0.0244 - 28ms/epoch - 9ms/step\n",
"Epoch 49/600\n",
"3/3 - 0s - loss: 0.0270 - 23ms/epoch - 8ms/step\n",
"Epoch 50/600\n",
"3/3 - 0s - loss: 0.0191 - 24ms/epoch - 8ms/step\n",
"Epoch 51/600\n",
"3/3 - 0s - loss: 0.0257 - 23ms/epoch - 8ms/step\n",
"Epoch 52/600\n",
"3/3 - 0s - loss: 0.0229 - 26ms/epoch - 9ms/step\n",
"Epoch 53/600\n",
"3/3 - 0s - loss: 0.0226 - 23ms/epoch - 8ms/step\n",
"Epoch 54/600\n",
"3/3 - 0s - loss: 0.0251 - 22ms/epoch - 7ms/step\n",
"Epoch 55/600\n",
"3/3 - 0s - loss: 0.0231 - 24ms/epoch - 8ms/step\n",
"Epoch 56/600\n",
"3/3 - 0s - loss: 0.0268 - 23ms/epoch - 8ms/step\n",
"Epoch 57/600\n",
"3/3 - 0s - loss: 0.0274 - 24ms/epoch - 8ms/step\n",
"Epoch 58/600\n",
"3/3 - 0s - loss: 0.0182 - 21ms/epoch - 7ms/step\n",
"Epoch 59/600\n",
"3/3 - 0s - loss: 0.0233 - 23ms/epoch - 8ms/step\n",
"Epoch 60/600\n",
"3/3 - 0s - loss: 0.0189 - 24ms/epoch - 8ms/step\n",
"Epoch 61/600\n",
"3/3 - 0s - loss: 0.0133 - 23ms/epoch - 8ms/step\n",
"Epoch 62/600\n",
"3/3 - 0s - loss: 0.0144 - 23ms/epoch - 8ms/step\n",
"Epoch 63/600\n",
"3/3 - 0s - loss: 0.0157 - 23ms/epoch - 8ms/step\n",
"Epoch 64/600\n",
"3/3 - 0s - loss: 0.0119 - 22ms/epoch - 7ms/step\n",
"Epoch 65/600\n",
"3/3 - 0s - loss: 0.0188 - 25ms/epoch - 8ms/step\n",
"Epoch 66/600\n",
"3/3 - 0s - loss: 0.0130 - 24ms/epoch - 8ms/step\n",
"Epoch 67/600\n",
"3/3 - 0s - loss: 0.0116 - 23ms/epoch - 8ms/step\n",
"Epoch 68/600\n",
"3/3 - 0s - loss: 0.0110 - 22ms/epoch - 7ms/step\n",
"Epoch 69/600\n",
"3/3 - 0s - loss: 0.0073 - 22ms/epoch - 7ms/step\n",
"Epoch 70/600\n",
"3/3 - 0s - loss: 0.0097 - 23ms/epoch - 8ms/step\n",
"Epoch 71/600\n",
"3/3 - 0s - loss: 0.0088 - 23ms/epoch - 8ms/step\n",
"Epoch 72/600\n",
"3/3 - 0s - loss: 0.0063 - 22ms/epoch - 7ms/step\n",
"Epoch 73/600\n",
"3/3 - 0s - loss: 0.0058 - 21ms/epoch - 7ms/step\n",
"Epoch 74/600\n",
"3/3 - 0s - loss: 0.0060 - 24ms/epoch - 8ms/step\n",
"Epoch 75/600\n",
"3/3 - 0s - loss: 0.0094 - 23ms/epoch - 8ms/step\n",
"Epoch 76/600\n",
"3/3 - 0s - loss: 0.0106 - 29ms/epoch - 10ms/step\n",
"Epoch 77/600\n",
"3/3 - 0s - loss: 0.0083 - 24ms/epoch - 8ms/step\n",
"Epoch 78/600\n",
"3/3 - 0s - loss: 0.0048 - 24ms/epoch - 8ms/step\n",
"Epoch 79/600\n",
"3/3 - 0s - loss: 0.0048 - 27ms/epoch - 9ms/step\n",
"Epoch 80/600\n",
"3/3 - 0s - loss: 0.0046 - 23ms/epoch - 8ms/step\n",
"Epoch 81/600\n",
"3/3 - 0s - loss: 0.0029 - 23ms/epoch - 8ms/step\n",
"Epoch 82/600\n",
"3/3 - 0s - loss: 0.0026 - 24ms/epoch - 8ms/step\n",
"Epoch 83/600\n",
"3/3 - 0s - loss: 0.0030 - 27ms/epoch - 9ms/step\n",
"Epoch 84/600\n",
"3/3 - 0s - loss: 0.0032 - 22ms/epoch - 7ms/step\n",
"Epoch 85/600\n",
"3/3 - 0s - loss: 0.0040 - 27ms/epoch - 9ms/step\n",
"Epoch 86/600\n",
"3/3 - 0s - loss: 0.0045 - 24ms/epoch - 8ms/step\n",
"Epoch 87/600\n",
"3/3 - 0s - loss: 0.0047 - 25ms/epoch - 8ms/step\n",
"Epoch 88/600\n",
"3/3 - 0s - loss: 0.0033 - 24ms/epoch - 8ms/step\n",
"Epoch 89/600\n",
"3/3 - 0s - loss: 0.0034 - 26ms/epoch - 9ms/step\n",
"Epoch 90/600\n",
"3/3 - 0s - loss: 0.0083 - 27ms/epoch - 9ms/step\n",
"Epoch 91/600\n",
"3/3 - 0s - loss: 0.0109 - 25ms/epoch - 8ms/step\n",
"Epoch 92/600\n",
"3/3 - 0s - loss: 0.0065 - 25ms/epoch - 8ms/step\n",
"Epoch 93/600\n",
"3/3 - 0s - loss: 0.0046 - 23ms/epoch - 8ms/step\n",
"Epoch 94/600\n",
"3/3 - 0s - loss: 0.0068 - 24ms/epoch - 8ms/step\n",
"Epoch 95/600\n",
"3/3 - 0s - loss: 0.0096 - 22ms/epoch - 7ms/step\n",
"Epoch 96/600\n",
"3/3 - 0s - loss: 0.0103 - 22ms/epoch - 7ms/step\n",
"Epoch 97/600\n",
"3/3 - 0s - loss: 0.0119 - 23ms/epoch - 8ms/step\n",
"Epoch 98/600\n",
"3/3 - 0s - loss: 0.0069 - 23ms/epoch - 8ms/step\n",
"Epoch 99/600\n",
"3/3 - 0s - loss: 0.0075 - 24ms/epoch - 8ms/step\n",
"Epoch 100/600\n",
"3/3 - 0s - loss: 0.0057 - 25ms/epoch - 8ms/step\n",
"Epoch 101/600\n",
"3/3 - 0s - loss: 0.0032 - 23ms/epoch - 8ms/step\n",
"Epoch 102/600\n",
"3/3 - 0s - loss: 0.0039 - 21ms/epoch - 7ms/step\n",
"Epoch 103/600\n",
"3/3 - 0s - loss: 0.0029 - 24ms/epoch - 8ms/step\n",
"Epoch 104/600\n",
"3/3 - 0s - loss: 0.0031 - 26ms/epoch - 9ms/step\n",
"Epoch 105/600\n",
"3/3 - 0s - loss: 0.0021 - 25ms/epoch - 8ms/step\n",
"Epoch 106/600\n",
"3/3 - 0s - loss: 0.0015 - 22ms/epoch - 7ms/step\n",
"Epoch 107/600\n",
"3/3 - 0s - loss: 0.0014 - 24ms/epoch - 8ms/step\n",
"Epoch 108/600\n",
"3/3 - 0s - loss: 0.0013 - 28ms/epoch - 9ms/step\n",
"Epoch 109/600\n",
"3/3 - 0s - loss: 0.0022 - 26ms/epoch - 9ms/step\n",
"Epoch 110/600\n",
"3/3 - 0s - loss: 0.0019 - 26ms/epoch - 9ms/step\n",
"Epoch 111/600\n",
"3/3 - 0s - loss: 0.0020 - 23ms/epoch - 8ms/step\n",
"Epoch 112/600\n",
"3/3 - 0s - loss: 6.9314e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 113/600\n",
"3/3 - 0s - loss: 9.3566e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 114/600\n",
"3/3 - 0s - loss: 0.0015 - 23ms/epoch - 8ms/step\n",
"Epoch 115/600\n",
"3/3 - 0s - loss: 0.0017 - 23ms/epoch - 8ms/step\n",
"Epoch 116/600\n",
"3/3 - 0s - loss: 0.0020 - 22ms/epoch - 7ms/step\n",
"Epoch 117/600\n",
"3/3 - 0s - loss: 0.0018 - 26ms/epoch - 9ms/step\n",
"Epoch 118/600\n",
"3/3 - 0s - loss: 0.0010 - 23ms/epoch - 8ms/step\n",
"Epoch 119/600\n",
"3/3 - 0s - loss: 8.8028e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 120/600\n",
"3/3 - 0s - loss: 7.2462e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 121/600\n",
"3/3 - 0s - loss: 8.0890e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 122/600\n",
"3/3 - 0s - loss: 9.8991e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 123/600\n",
"3/3 - 0s - loss: 7.1008e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 124/600\n",
"3/3 - 0s - loss: 4.9597e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 125/600\n",
"3/3 - 0s - loss: 4.7966e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 126/600\n",
"3/3 - 0s - loss: 3.0518e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 127/600\n",
"3/3 - 0s - loss: 2.7030e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 128/600\n",
"3/3 - 0s - loss: 3.4302e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 129/600\n",
"3/3 - 0s - loss: 3.2476e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 130/600\n",
"3/3 - 0s - loss: 1.6305e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 131/600\n",
"3/3 - 0s - loss: 1.8642e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 132/600\n",
"3/3 - 0s - loss: 8.2074e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 133/600\n",
"3/3 - 0s - loss: 6.5955e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 134/600\n",
"3/3 - 0s - loss: 6.8692e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 135/600\n",
"3/3 - 0s - loss: 1.1016e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 136/600\n",
"3/3 - 0s - loss: 1.4056e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 137/600\n",
"3/3 - 0s - loss: 1.0764e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 138/600\n",
"3/3 - 0s - loss: 9.8001e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 139/600\n",
"3/3 - 0s - loss: 2.1907e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 140/600\n",
"3/3 - 0s - loss: 2.4921e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 141/600\n",
"3/3 - 0s - loss: 4.0704e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 142/600\n",
"3/3 - 0s - loss: 5.5095e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 143/600\n",
"3/3 - 0s - loss: 8.7078e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 144/600\n",
"3/3 - 0s - loss: 9.0852e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 145/600\n",
"3/3 - 0s - loss: 0.0014 - 25ms/epoch - 8ms/step\n",
"Epoch 146/600\n",
"3/3 - 0s - loss: 0.0021 - 24ms/epoch - 8ms/step\n",
"Epoch 147/600\n",
"3/3 - 0s - loss: 0.0012 - 22ms/epoch - 7ms/step\n",
"Epoch 148/600\n",
"3/3 - 0s - loss: 0.0011 - 23ms/epoch - 8ms/step\n",
"Epoch 149/600\n",
"3/3 - 0s - loss: 0.0014 - 22ms/epoch - 7ms/step\n",
"Epoch 150/600\n",
"3/3 - 0s - loss: 0.0013 - 22ms/epoch - 7ms/step\n",
"Epoch 151/600\n",
"3/3 - 0s - loss: 0.0012 - 27ms/epoch - 9ms/step\n",
"Epoch 152/600\n",
"3/3 - 0s - loss: 0.0011 - 25ms/epoch - 8ms/step\n",
"Epoch 153/600\n",
"3/3 - 0s - loss: 8.8283e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 154/600\n",
"3/3 - 0s - loss: 5.0875e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 155/600\n",
"3/3 - 0s - loss: 4.6452e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 156/600\n",
"3/3 - 0s - loss: 4.4445e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 157/600\n",
"3/3 - 0s - loss: 4.5507e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 158/600\n",
"3/3 - 0s - loss: 5.0221e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 159/600\n",
"3/3 - 0s - loss: 7.1127e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 160/600\n",
"3/3 - 0s - loss: 5.3585e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 161/600\n",
"3/3 - 0s - loss: 3.0625e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 162/600\n",
"3/3 - 0s - loss: 3.6777e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 163/600\n",
"3/3 - 0s - loss: 2.5530e-04 - 21ms/epoch - 7ms/step\n",
"Epoch 164/600\n",
"3/3 - 0s - loss: 1.7076e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 165/600\n",
"3/3 - 0s - loss: 2.1320e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 166/600\n",
"3/3 - 0s - loss: 2.7991e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 167/600\n",
"3/3 - 0s - loss: 3.3069e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 168/600\n",
"3/3 - 0s - loss: 2.9444e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 169/600\n",
"3/3 - 0s - loss: 4.0663e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 170/600\n",
"3/3 - 0s - loss: 3.3016e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 171/600\n",
"3/3 - 0s - loss: 2.0864e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 172/600\n",
"3/3 - 0s - loss: 3.1231e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 173/600\n",
"3/3 - 0s - loss: 2.9278e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 174/600\n",
"3/3 - 0s - loss: 3.0427e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 175/600\n",
"3/3 - 0s - loss: 4.5326e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 176/600\n",
"3/3 - 0s - loss: 3.3629e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 177/600\n",
"3/3 - 0s - loss: 2.4525e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 178/600\n",
"3/3 - 0s - loss: 2.5538e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 179/600\n",
"3/3 - 0s - loss: 3.3784e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 180/600\n",
"3/3 - 0s - loss: 1.9497e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 181/600\n",
"3/3 - 0s - loss: 1.9737e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 182/600\n",
"3/3 - 0s - loss: 2.2758e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 183/600\n",
"3/3 - 0s - loss: 2.9136e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 184/600\n",
"3/3 - 0s - loss: 1.1060e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 185/600\n",
"3/3 - 0s - loss: 5.0481e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 186/600\n",
"3/3 - 0s - loss: 4.0821e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 187/600\n",
"3/3 - 0s - loss: 5.7687e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 188/600\n",
"3/3 - 0s - loss: 5.1819e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 189/600\n",
"3/3 - 0s - loss: 4.4923e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 190/600\n",
"3/3 - 0s - loss: 5.0681e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 191/600\n",
"3/3 - 0s - loss: 3.9062e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 192/600\n",
"3/3 - 0s - loss: 3.1511e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 193/600\n",
"3/3 - 0s - loss: 3.9896e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 194/600\n",
"3/3 - 0s - loss: 3.6009e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 195/600\n",
"3/3 - 0s - loss: 3.8435e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 196/600\n",
"3/3 - 0s - loss: 6.6916e-05 - 28ms/epoch - 9ms/step\n",
"Epoch 197/600\n",
"3/3 - 0s - loss: 1.2784e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 198/600\n",
"3/3 - 0s - loss: 8.5005e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 199/600\n",
"3/3 - 0s - loss: 6.0588e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 200/600\n",
"3/3 - 0s - loss: 6.8180e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 201/600\n",
"3/3 - 0s - loss: 4.7230e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 202/600\n",
"3/3 - 0s - loss: 3.8133e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 203/600\n",
"3/3 - 0s - loss: 7.4671e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 204/600\n",
"3/3 - 0s - loss: 8.1094e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 205/600\n",
"3/3 - 0s - loss: 7.8872e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 206/600\n",
"3/3 - 0s - loss: 8.7357e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 207/600\n",
"3/3 - 0s - loss: 4.8380e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 208/600\n",
"3/3 - 0s - loss: 7.0697e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 209/600\n",
"3/3 - 0s - loss: 5.2098e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 210/600\n",
"3/3 - 0s - loss: 5.4029e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 211/600\n",
"3/3 - 0s - loss: 2.8489e-05 - 28ms/epoch - 9ms/step\n",
"Epoch 212/600\n",
"3/3 - 0s - loss: 3.3961e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 213/600\n",
"3/3 - 0s - loss: 4.1667e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 214/600\n",
"3/3 - 0s - loss: 3.7597e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 215/600\n",
"3/3 - 0s - loss: 2.7004e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 216/600\n",
"3/3 - 0s - loss: 2.9110e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 217/600\n",
"3/3 - 0s - loss: 3.6687e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 218/600\n",
"3/3 - 0s - loss: 7.2615e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 219/600\n",
"3/3 - 0s - loss: 1.0681e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 220/600\n",
"3/3 - 0s - loss: 1.9565e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 221/600\n",
"3/3 - 0s - loss: 1.9595e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 222/600\n",
"3/3 - 0s - loss: 1.7055e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 223/600\n",
"3/3 - 0s - loss: 1.4371e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 224/600\n",
"3/3 - 0s - loss: 1.0054e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 225/600\n",
"3/3 - 0s - loss: 7.8233e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 226/600\n",
"3/3 - 0s - loss: 2.0859e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 227/600\n",
"3/3 - 0s - loss: 2.3248e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 228/600\n",
"3/3 - 0s - loss: 3.5742e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 229/600\n",
"3/3 - 0s - loss: 3.2267e-04 - 30ms/epoch - 10ms/step\n",
"Epoch 230/600\n",
"3/3 - 0s - loss: 2.6533e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 231/600\n",
"3/3 - 0s - loss: 3.3579e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 232/600\n",
"3/3 - 0s - loss: 2.2141e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 233/600\n",
"3/3 - 0s - loss: 1.3816e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 234/600\n",
"3/3 - 0s - loss: 1.2997e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 235/600\n",
"3/3 - 0s - loss: 1.2696e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 236/600\n",
"3/3 - 0s - loss: 7.3166e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 237/600\n",
"3/3 - 0s - loss: 4.9531e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 238/600\n",
"3/3 - 0s - loss: 5.9576e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 239/600\n",
"3/3 - 0s - loss: 6.9014e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 240/600\n",
"3/3 - 0s - loss: 1.2079e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 241/600\n",
"3/3 - 0s - loss: 1.0165e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 242/600\n",
"3/3 - 0s - loss: 1.1189e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 243/600\n",
"3/3 - 0s - loss: 1.2715e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 244/600\n",
"3/3 - 0s - loss: 2.3746e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 245/600\n",
"3/3 - 0s - loss: 7.2393e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 246/600\n",
"3/3 - 0s - loss: 8.1162e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 247/600\n",
"3/3 - 0s - loss: 6.6941e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 248/600\n",
"3/3 - 0s - loss: 6.1267e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 249/600\n",
"3/3 - 0s - loss: 5.4795e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 250/600\n",
"3/3 - 0s - loss: 8.4581e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 251/600\n",
"3/3 - 0s - loss: 4.3189e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 252/600\n",
"3/3 - 0s - loss: 6.3720e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 253/600\n",
"3/3 - 0s - loss: 8.4664e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 254/600\n",
"3/3 - 0s - loss: 0.0025 - 23ms/epoch - 8ms/step\n",
"Epoch 255/600\n",
"3/3 - 0s - loss: 0.0032 - 24ms/epoch - 8ms/step\n",
"Epoch 256/600\n",
"3/3 - 0s - loss: 0.0040 - 25ms/epoch - 8ms/step\n",
"Epoch 257/600\n",
"3/3 - 0s - loss: 0.0021 - 23ms/epoch - 8ms/step\n",
"Epoch 258/600\n",
"3/3 - 0s - loss: 0.0023 - 24ms/epoch - 8ms/step\n",
"Epoch 259/600\n",
"3/3 - 0s - loss: 0.0034 - 25ms/epoch - 8ms/step\n",
"Epoch 260/600\n",
"3/3 - 0s - loss: 0.0045 - 25ms/epoch - 8ms/step\n",
"Epoch 261/600\n",
"3/3 - 0s - loss: 0.0064 - 23ms/epoch - 8ms/step\n",
"Epoch 262/600\n",
"3/3 - 0s - loss: 0.0050 - 24ms/epoch - 8ms/step\n",
"Epoch 263/600\n",
"3/3 - 0s - loss: 0.0068 - 27ms/epoch - 9ms/step\n",
"Epoch 264/600\n",
"3/3 - 0s - loss: 0.0042 - 26ms/epoch - 9ms/step\n",
"Epoch 265/600\n",
"3/3 - 0s - loss: 0.0047 - 24ms/epoch - 8ms/step\n",
"Epoch 266/600\n",
"3/3 - 0s - loss: 0.0045 - 25ms/epoch - 8ms/step\n",
"Epoch 267/600\n",
"3/3 - 0s - loss: 0.0046 - 23ms/epoch - 8ms/step\n",
"Epoch 268/600\n",
"3/3 - 0s - loss: 0.0032 - 23ms/epoch - 8ms/step\n",
"Epoch 269/600\n",
"3/3 - 0s - loss: 0.0031 - 24ms/epoch - 8ms/step\n",
"Epoch 270/600\n",
"3/3 - 0s - loss: 0.0041 - 23ms/epoch - 8ms/step\n",
"Epoch 271/600\n",
"3/3 - 0s - loss: 0.0034 - 23ms/epoch - 8ms/step\n",
"Epoch 272/600\n",
"3/3 - 0s - loss: 0.0043 - 23ms/epoch - 8ms/step\n",
"Epoch 273/600\n",
"3/3 - 0s - loss: 0.0034 - 25ms/epoch - 8ms/step\n",
"Epoch 274/600\n",
"3/3 - 0s - loss: 0.0036 - 25ms/epoch - 8ms/step\n",
"Epoch 275/600\n",
"3/3 - 0s - loss: 0.0030 - 26ms/epoch - 9ms/step\n",
"Epoch 276/600\n",
"3/3 - 0s - loss: 0.0027 - 24ms/epoch - 8ms/step\n",
"Epoch 277/600\n",
"3/3 - 0s - loss: 0.0033 - 23ms/epoch - 8ms/step\n",
"Epoch 278/600\n",
"3/3 - 0s - loss: 0.0024 - 23ms/epoch - 8ms/step\n",
"Epoch 279/600\n",
"3/3 - 0s - loss: 0.0017 - 24ms/epoch - 8ms/step\n",
"Epoch 280/600\n",
"3/3 - 0s - loss: 0.0017 - 22ms/epoch - 7ms/step\n",
"Epoch 281/600\n",
"3/3 - 0s - loss: 0.0015 - 24ms/epoch - 8ms/step\n",
"Epoch 282/600\n",
"3/3 - 0s - loss: 0.0015 - 25ms/epoch - 8ms/step\n",
"Epoch 283/600\n",
"3/3 - 0s - loss: 0.0019 - 25ms/epoch - 8ms/step\n",
"Epoch 284/600\n",
"3/3 - 0s - loss: 0.0042 - 23ms/epoch - 8ms/step\n",
"Epoch 285/600\n",
"3/3 - 0s - loss: 0.0026 - 21ms/epoch - 7ms/step\n",
"Epoch 286/600\n",
"3/3 - 0s - loss: 0.0035 - 23ms/epoch - 8ms/step\n",
"Epoch 287/600\n",
"3/3 - 0s - loss: 0.0033 - 27ms/epoch - 9ms/step\n",
"Epoch 288/600\n",
"3/3 - 0s - loss: 0.0059 - 25ms/epoch - 8ms/step\n",
"Epoch 289/600\n",
"3/3 - 0s - loss: 0.0073 - 26ms/epoch - 9ms/step\n",
"Epoch 290/600\n",
"3/3 - 0s - loss: 0.0060 - 23ms/epoch - 8ms/step\n",
"Epoch 291/600\n",
"3/3 - 0s - loss: 0.0032 - 22ms/epoch - 7ms/step\n",
"Epoch 292/600\n",
"3/3 - 0s - loss: 0.0022 - 22ms/epoch - 7ms/step\n",
"Epoch 293/600\n",
"3/3 - 0s - loss: 0.0021 - 24ms/epoch - 8ms/step\n",
"Epoch 294/600\n",
"3/3 - 0s - loss: 0.0025 - 22ms/epoch - 7ms/step\n",
"Epoch 295/600\n",
"3/3 - 0s - loss: 0.0011 - 23ms/epoch - 8ms/step\n",
"Epoch 296/600\n",
"3/3 - 0s - loss: 6.3007e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 297/600\n",
"3/3 - 0s - loss: 4.8764e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 298/600\n",
"3/3 - 0s - loss: 5.1926e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 299/600\n",
"3/3 - 0s - loss: 7.6698e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 300/600\n",
"3/3 - 0s - loss: 7.6851e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 301/600\n",
"3/3 - 0s - loss: 7.3852e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 302/600\n",
"3/3 - 0s - loss: 5.9093e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 303/600\n",
"3/3 - 0s - loss: 5.2005e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 304/600\n",
"3/3 - 0s - loss: 8.6820e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 305/600\n",
"3/3 - 0s - loss: 0.0014 - 24ms/epoch - 8ms/step\n",
"Epoch 306/600\n",
"3/3 - 0s - loss: 0.0011 - 23ms/epoch - 8ms/step\n",
"Epoch 307/600\n",
"3/3 - 0s - loss: 0.0016 - 24ms/epoch - 8ms/step\n",
"Epoch 308/600\n",
"3/3 - 0s - loss: 0.0018 - 25ms/epoch - 8ms/step\n",
"Epoch 309/600\n",
"3/3 - 0s - loss: 0.0013 - 23ms/epoch - 8ms/step\n",
"Epoch 310/600\n",
"3/3 - 0s - loss: 0.0011 - 30ms/epoch - 10ms/step\n",
"Epoch 311/600\n",
"3/3 - 0s - loss: 0.0011 - 23ms/epoch - 8ms/step\n",
"Epoch 312/600\n",
"3/3 - 0s - loss: 8.0266e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 313/600\n",
"3/3 - 0s - loss: 4.5370e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 314/600\n",
"3/3 - 0s - loss: 3.2661e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 315/600\n",
"3/3 - 0s - loss: 3.7869e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 316/600\n",
"3/3 - 0s - loss: 3.3854e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 317/600\n",
"3/3 - 0s - loss: 2.9576e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 318/600\n",
"3/3 - 0s - loss: 3.2977e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 319/600\n",
"3/3 - 0s - loss: 5.7998e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 320/600\n",
"3/3 - 0s - loss: 5.9026e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 321/600\n",
"3/3 - 0s - loss: 8.3968e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 322/600\n",
"3/3 - 0s - loss: 0.0012 - 23ms/epoch - 8ms/step\n",
"Epoch 323/600\n",
"3/3 - 0s - loss: 0.0010 - 24ms/epoch - 8ms/step\n",
"Epoch 324/600\n",
"3/3 - 0s - loss: 0.0012 - 28ms/epoch - 9ms/step\n",
"Epoch 325/600\n",
"3/3 - 0s - loss: 9.7469e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 326/600\n",
"3/3 - 0s - loss: 6.8606e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 327/600\n",
"3/3 - 0s - loss: 7.5367e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 328/600\n",
"3/3 - 0s - loss: 9.4139e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 329/600\n",
"3/3 - 0s - loss: 9.8434e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 330/600\n",
"3/3 - 0s - loss: 7.6078e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 331/600\n",
"3/3 - 0s - loss: 4.7059e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 332/600\n",
"3/3 - 0s - loss: 4.6208e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 333/600\n",
"3/3 - 0s - loss: 9.0345e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 334/600\n",
"3/3 - 0s - loss: 4.2509e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 335/600\n",
"3/3 - 0s - loss: 4.0639e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 336/600\n",
"3/3 - 0s - loss: 2.0134e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 337/600\n",
"3/3 - 0s - loss: 1.6695e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 338/600\n",
"3/3 - 0s - loss: 1.7412e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 339/600\n",
"3/3 - 0s - loss: 1.8951e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 340/600\n",
"3/3 - 0s - loss: 2.1406e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 341/600\n",
"3/3 - 0s - loss: 4.2900e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 342/600\n",
"3/3 - 0s - loss: 2.8856e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 343/600\n",
"3/3 - 0s - loss: 2.6222e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 344/600\n",
"3/3 - 0s - loss: 2.6918e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 345/600\n",
"3/3 - 0s - loss: 2.1942e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 346/600\n",
"3/3 - 0s - loss: 4.9804e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 347/600\n",
"3/3 - 0s - loss: 2.5419e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 348/600\n",
"3/3 - 0s - loss: 2.1331e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 349/600\n",
"3/3 - 0s - loss: 2.8852e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 350/600\n",
"3/3 - 0s - loss: 1.8820e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 351/600\n",
"3/3 - 0s - loss: 1.9960e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 352/600\n",
"3/3 - 0s - loss: 5.1399e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 353/600\n",
"3/3 - 0s - loss: 6.0275e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 354/600\n",
"3/3 - 0s - loss: 6.9778e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 355/600\n",
"3/3 - 0s - loss: 6.6073e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 356/600\n",
"3/3 - 0s - loss: 3.8012e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 357/600\n",
"3/3 - 0s - loss: 3.9308e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 358/600\n",
"3/3 - 0s - loss: 2.4925e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 359/600\n",
"3/3 - 0s - loss: 2.4841e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 360/600\n",
"3/3 - 0s - loss: 1.9365e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 361/600\n",
"3/3 - 0s - loss: 1.5913e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 362/600\n",
"3/3 - 0s - loss: 8.7261e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 363/600\n",
"3/3 - 0s - loss: 1.3214e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 364/600\n",
"3/3 - 0s - loss: 1.1200e-04 - 28ms/epoch - 9ms/step\n",
"Epoch 365/600\n",
"3/3 - 0s - loss: 8.5997e-05 - 21ms/epoch - 7ms/step\n",
"Epoch 366/600\n",
"3/3 - 0s - loss: 1.0082e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 367/600\n",
"3/3 - 0s - loss: 8.8290e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 368/600\n",
"3/3 - 0s - loss: 6.7684e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 369/600\n",
"3/3 - 0s - loss: 8.7257e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 370/600\n",
"3/3 - 0s - loss: 6.2689e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 371/600\n",
"3/3 - 0s - loss: 4.3639e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 372/600\n",
"3/3 - 0s - loss: 4.0352e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 373/600\n",
"3/3 - 0s - loss: 5.7696e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 374/600\n",
"3/3 - 0s - loss: 1.5787e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 375/600\n",
"3/3 - 0s - loss: 1.8431e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 376/600\n",
"3/3 - 0s - loss: 3.0870e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 377/600\n",
"3/3 - 0s - loss: 4.0863e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 378/600\n",
"3/3 - 0s - loss: 3.3507e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 379/600\n",
"3/3 - 0s - loss: 3.6209e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 380/600\n",
"3/3 - 0s - loss: 2.1990e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 381/600\n",
"3/3 - 0s - loss: 3.2797e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 382/600\n",
"3/3 - 0s - loss: 2.7877e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 383/600\n",
"3/3 - 0s - loss: 2.8406e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 384/600\n",
"3/3 - 0s - loss: 2.3757e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 385/600\n",
"3/3 - 0s - loss: 3.9205e-04 - 29ms/epoch - 10ms/step\n",
"Epoch 386/600\n",
"3/3 - 0s - loss: 1.2536e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 387/600\n",
"3/3 - 0s - loss: 1.0487e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 388/600\n",
"3/3 - 0s - loss: 8.6785e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 389/600\n",
"3/3 - 0s - loss: 7.2290e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 390/600\n",
"3/3 - 0s - loss: 1.0353e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 391/600\n",
"3/3 - 0s - loss: 6.3309e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 392/600\n",
"3/3 - 0s - loss: 5.1257e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 393/600\n",
"3/3 - 0s - loss: 9.1437e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 394/600\n",
"3/3 - 0s - loss: 6.5759e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 395/600\n",
"3/3 - 0s - loss: 4.8281e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 396/600\n",
"3/3 - 0s - loss: 1.0294e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 397/600\n",
"3/3 - 0s - loss: 5.3189e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 398/600\n",
"3/3 - 0s - loss: 3.6427e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 399/600\n",
"3/3 - 0s - loss: 5.4985e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 400/600\n",
"3/3 - 0s - loss: 4.5614e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 401/600\n",
"3/3 - 0s - loss: 3.4821e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 402/600\n",
"3/3 - 0s - loss: 4.4809e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 403/600\n",
"3/3 - 0s - loss: 5.5315e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 404/600\n",
"3/3 - 0s - loss: 3.5791e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 405/600\n",
"3/3 - 0s - loss: 4.4281e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 406/600\n",
"3/3 - 0s - loss: 3.8300e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 407/600\n",
"3/3 - 0s - loss: 5.8476e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 408/600\n",
"3/3 - 0s - loss: 7.9609e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 409/600\n",
"3/3 - 0s - loss: 3.1058e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 410/600\n",
"3/3 - 0s - loss: 2.5080e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 411/600\n",
"3/3 - 0s - loss: 4.1401e-04 - 22ms/epoch - 7ms/step\n",
"Epoch 412/600\n",
"3/3 - 0s - loss: 0.0010 - 24ms/epoch - 8ms/step\n",
"Epoch 413/600\n",
"3/3 - 0s - loss: 4.5596e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 414/600\n",
"3/3 - 0s - loss: 0.0013 - 24ms/epoch - 8ms/step\n",
"Epoch 415/600\n",
"3/3 - 0s - loss: 0.0015 - 25ms/epoch - 8ms/step\n",
"Epoch 416/600\n",
"3/3 - 0s - loss: 0.0010 - 24ms/epoch - 8ms/step\n",
"Epoch 417/600\n",
"3/3 - 0s - loss: 0.0018 - 22ms/epoch - 7ms/step\n",
"Epoch 418/600\n",
"3/3 - 0s - loss: 0.0025 - 22ms/epoch - 7ms/step\n",
"Epoch 419/600\n",
"3/3 - 0s - loss: 0.0033 - 22ms/epoch - 7ms/step\n",
"Epoch 420/600\n",
"3/3 - 0s - loss: 0.0171 - 23ms/epoch - 8ms/step\n",
"Epoch 421/600\n",
"3/3 - 0s - loss: 0.0179 - 25ms/epoch - 8ms/step\n",
"Epoch 422/600\n",
"3/3 - 0s - loss: 0.0362 - 25ms/epoch - 8ms/step\n",
"Epoch 423/600\n",
"3/3 - 0s - loss: 0.0421 - 24ms/epoch - 8ms/step\n",
"Epoch 424/600\n",
"3/3 - 0s - loss: 0.0694 - 25ms/epoch - 8ms/step\n",
"Epoch 425/600\n",
"3/3 - 0s - loss: 0.0641 - 25ms/epoch - 8ms/step\n",
"Epoch 426/600\n",
"3/3 - 0s - loss: 0.0499 - 28ms/epoch - 9ms/step\n",
"Epoch 427/600\n",
"3/3 - 0s - loss: 0.0507 - 24ms/epoch - 8ms/step\n",
"Epoch 428/600\n",
"3/3 - 0s - loss: 0.0464 - 26ms/epoch - 9ms/step\n",
"Epoch 429/600\n",
"3/3 - 0s - loss: 0.0284 - 29ms/epoch - 10ms/step\n",
"Epoch 430/600\n",
"3/3 - 0s - loss: 0.0232 - 25ms/epoch - 8ms/step\n",
"Epoch 431/600\n",
"3/3 - 0s - loss: 0.0324 - 28ms/epoch - 9ms/step\n",
"Epoch 432/600\n",
"3/3 - 0s - loss: 0.0193 - 25ms/epoch - 8ms/step\n",
"Epoch 433/600\n",
"3/3 - 0s - loss: 0.0096 - 25ms/epoch - 8ms/step\n",
"Epoch 434/600\n",
"3/3 - 0s - loss: 0.0138 - 23ms/epoch - 8ms/step\n",
"Epoch 435/600\n",
"3/3 - 0s - loss: 0.0067 - 23ms/epoch - 8ms/step\n",
"Epoch 436/600\n",
"3/3 - 0s - loss: 0.0071 - 26ms/epoch - 9ms/step\n",
"Epoch 437/600\n",
"3/3 - 0s - loss: 0.0046 - 24ms/epoch - 8ms/step\n",
"Epoch 438/600\n",
"3/3 - 0s - loss: 0.0030 - 24ms/epoch - 8ms/step\n",
"Epoch 439/600\n",
"3/3 - 0s - loss: 0.0043 - 26ms/epoch - 9ms/step\n",
"Epoch 440/600\n",
"3/3 - 0s - loss: 0.0032 - 27ms/epoch - 9ms/step\n",
"Epoch 441/600\n",
"3/3 - 0s - loss: 0.0037 - 28ms/epoch - 9ms/step\n",
"Epoch 442/600\n",
"3/3 - 0s - loss: 0.0029 - 26ms/epoch - 9ms/step\n",
"Epoch 443/600\n",
"3/3 - 0s - loss: 0.0019 - 26ms/epoch - 9ms/step\n",
"Epoch 444/600\n",
"3/3 - 0s - loss: 0.0022 - 24ms/epoch - 8ms/step\n",
"Epoch 445/600\n",
"3/3 - 0s - loss: 0.0020 - 26ms/epoch - 9ms/step\n",
"Epoch 446/600\n",
"3/3 - 0s - loss: 0.0014 - 26ms/epoch - 9ms/step\n",
"Epoch 447/600\n",
"3/3 - 0s - loss: 0.0017 - 25ms/epoch - 8ms/step\n",
"Epoch 448/600\n",
"3/3 - 0s - loss: 0.0014 - 27ms/epoch - 9ms/step\n",
"Epoch 449/600\n",
"3/3 - 0s - loss: 0.0013 - 26ms/epoch - 9ms/step\n",
"Epoch 450/600\n",
"3/3 - 0s - loss: 0.0011 - 27ms/epoch - 9ms/step\n",
"Epoch 451/600\n",
"3/3 - 0s - loss: 0.0011 - 24ms/epoch - 8ms/step\n",
"Epoch 452/600\n",
"3/3 - 0s - loss: 0.0011 - 28ms/epoch - 9ms/step\n",
"Epoch 453/600\n",
"3/3 - 0s - loss: 9.8960e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 454/600\n",
"3/3 - 0s - loss: 0.0011 - 24ms/epoch - 8ms/step\n",
"Epoch 455/600\n",
"3/3 - 0s - loss: 0.0010 - 26ms/epoch - 9ms/step\n",
"Epoch 456/600\n",
"3/3 - 0s - loss: 6.7690e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 457/600\n",
"3/3 - 0s - loss: 7.4283e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 458/600\n",
"3/3 - 0s - loss: 4.8506e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 459/600\n",
"3/3 - 0s - loss: 4.3200e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 460/600\n",
"3/3 - 0s - loss: 3.4006e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 461/600\n",
"3/3 - 0s - loss: 2.3637e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 462/600\n",
"3/3 - 0s - loss: 2.6243e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 463/600\n",
"3/3 - 0s - loss: 2.1565e-04 - 28ms/epoch - 9ms/step\n",
"Epoch 464/600\n",
"3/3 - 0s - loss: 2.2652e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 465/600\n",
"3/3 - 0s - loss: 1.4571e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 466/600\n",
"3/3 - 0s - loss: 1.0692e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 467/600\n",
"3/3 - 0s - loss: 1.2521e-04 - 25ms/epoch - 8ms/step\n",
"Epoch 468/600\n",
"3/3 - 0s - loss: 1.1410e-04 - 24ms/epoch - 8ms/step\n",
"Epoch 469/600\n",
"3/3 - 0s - loss: 9.9680e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 470/600\n",
"3/3 - 0s - loss: 8.0550e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 471/600\n",
"3/3 - 0s - loss: 7.7929e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 472/600\n",
"3/3 - 0s - loss: 8.0573e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 473/600\n",
"3/3 - 0s - loss: 9.0820e-05 - 43ms/epoch - 14ms/step\n",
"Epoch 474/600\n",
"3/3 - 0s - loss: 9.9753e-05 - 29ms/epoch - 10ms/step\n",
"Epoch 475/600\n",
"3/3 - 0s - loss: 9.5174e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 476/600\n",
"3/3 - 0s - loss: 7.7605e-05 - 28ms/epoch - 9ms/step\n",
"Epoch 477/600\n",
"3/3 - 0s - loss: 1.0790e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 478/600\n",
"3/3 - 0s - loss: 7.8259e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 479/600\n",
"3/3 - 0s - loss: 9.2448e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 480/600\n",
"3/3 - 0s - loss: 8.8744e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 481/600\n",
"3/3 - 0s - loss: 7.9199e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 482/600\n",
"3/3 - 0s - loss: 5.2364e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 483/600\n",
"3/3 - 0s - loss: 6.0705e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 484/600\n",
"3/3 - 0s - loss: 9.1279e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 485/600\n",
"3/3 - 0s - loss: 1.7429e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 486/600\n",
"3/3 - 0s - loss: 2.3553e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 487/600\n",
"3/3 - 0s - loss: 1.7582e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 488/600\n",
"3/3 - 0s - loss: 1.3630e-04 - 27ms/epoch - 9ms/step\n",
"Epoch 489/600\n",
"3/3 - 0s - loss: 1.2006e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 490/600\n",
"3/3 - 0s - loss: 1.3694e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 491/600\n",
"3/3 - 0s - loss: 1.7018e-04 - 29ms/epoch - 10ms/step\n",
"Epoch 492/600\n",
"3/3 - 0s - loss: 1.7374e-04 - 26ms/epoch - 9ms/step\n",
"Epoch 493/600\n",
"3/3 - 0s - loss: 1.0515e-04 - 23ms/epoch - 8ms/step\n",
"Epoch 494/600\n",
"3/3 - 0s - loss: 5.7228e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 495/600\n",
"3/3 - 0s - loss: 8.8101e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 496/600\n",
"3/3 - 0s - loss: 6.1029e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 497/600\n",
"3/3 - 0s - loss: 9.8694e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 498/600\n",
"3/3 - 0s - loss: 8.7701e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 499/600\n",
"3/3 - 0s - loss: 5.5231e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 500/600\n",
"3/3 - 0s - loss: 3.7914e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 501/600\n",
"3/3 - 0s - loss: 3.2689e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 502/600\n",
"3/3 - 0s - loss: 2.9137e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 503/600\n",
"3/3 - 0s - loss: 3.3903e-05 - 28ms/epoch - 9ms/step\n",
"Epoch 504/600\n",
"3/3 - 0s - loss: 3.3639e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 505/600\n",
"3/3 - 0s - loss: 3.2738e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 506/600\n",
"3/3 - 0s - loss: 2.5508e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 507/600\n",
"3/3 - 0s - loss: 2.1105e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 508/600\n",
"3/3 - 0s - loss: 2.0365e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 509/600\n",
"3/3 - 0s - loss: 2.2524e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 510/600\n",
"3/3 - 0s - loss: 2.6952e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 511/600\n",
"3/3 - 0s - loss: 2.4668e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 512/600\n",
"3/3 - 0s - loss: 2.7025e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 513/600\n",
"3/3 - 0s - loss: 1.9352e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 514/600\n",
"3/3 - 0s - loss: 2.3263e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 515/600\n",
"3/3 - 0s - loss: 2.0678e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 516/600\n",
"3/3 - 0s - loss: 2.1186e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 517/600\n",
"3/3 - 0s - loss: 2.0710e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 518/600\n",
"3/3 - 0s - loss: 1.9802e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 519/600\n",
"3/3 - 0s - loss: 1.9410e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 520/600\n",
"3/3 - 0s - loss: 2.3382e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 521/600\n",
"3/3 - 0s - loss: 2.0962e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 522/600\n",
"3/3 - 0s - loss: 2.0404e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 523/600\n",
"3/3 - 0s - loss: 1.7501e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 524/600\n",
"3/3 - 0s - loss: 2.0837e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 525/600\n",
"3/3 - 0s - loss: 2.3776e-05 - 21ms/epoch - 7ms/step\n",
"Epoch 526/600\n",
"3/3 - 0s - loss: 2.0251e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 527/600\n",
"3/3 - 0s - loss: 2.1635e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 528/600\n",
"3/3 - 0s - loss: 1.9761e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 529/600\n",
"3/3 - 0s - loss: 1.7155e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 530/600\n",
"3/3 - 0s - loss: 1.5702e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 531/600\n",
"3/3 - 0s - loss: 1.2652e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 532/600\n",
"3/3 - 0s - loss: 1.4052e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 533/600\n",
"3/3 - 0s - loss: 1.0785e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 534/600\n",
"3/3 - 0s - loss: 1.0768e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 535/600\n",
"3/3 - 0s - loss: 1.1230e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 536/600\n",
"3/3 - 0s - loss: 1.1170e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 537/600\n",
"3/3 - 0s - loss: 1.2886e-05 - 28ms/epoch - 9ms/step\n",
"Epoch 538/600\n",
"3/3 - 0s - loss: 1.2974e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 539/600\n",
"3/3 - 0s - loss: 1.6123e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 540/600\n",
"3/3 - 0s - loss: 1.0273e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 541/600\n",
"3/3 - 0s - loss: 1.3104e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 542/600\n",
"3/3 - 0s - loss: 1.0011e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 543/600\n",
"3/3 - 0s - loss: 9.9656e-06 - 29ms/epoch - 10ms/step\n",
"Epoch 544/600\n",
"3/3 - 0s - loss: 1.2303e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 545/600\n",
"3/3 - 0s - loss: 1.3487e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 546/600\n",
"3/3 - 0s - loss: 1.2662e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 547/600\n",
"3/3 - 0s - loss: 1.8767e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 548/600\n",
"3/3 - 0s - loss: 1.8105e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 549/600\n",
"3/3 - 0s - loss: 2.1670e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 550/600\n",
"3/3 - 0s - loss: 4.1998e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 551/600\n",
"3/3 - 0s - loss: 1.6688e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 552/600\n",
"3/3 - 0s - loss: 9.7002e-06 - 23ms/epoch - 8ms/step\n",
"Epoch 553/600\n",
"3/3 - 0s - loss: 1.0949e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 554/600\n",
"3/3 - 0s - loss: 9.3828e-06 - 28ms/epoch - 9ms/step\n",
"Epoch 555/600\n",
"3/3 - 0s - loss: 8.5191e-06 - 28ms/epoch - 9ms/step\n",
"Epoch 556/600\n",
"3/3 - 0s - loss: 8.6126e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 557/600\n",
"3/3 - 0s - loss: 9.2425e-06 - 24ms/epoch - 8ms/step\n",
"Epoch 558/600\n",
"3/3 - 0s - loss: 1.0452e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 559/600\n",
"3/3 - 0s - loss: 8.6116e-06 - 24ms/epoch - 8ms/step\n",
"Epoch 560/600\n",
"3/3 - 0s - loss: 1.0119e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 561/600\n",
"3/3 - 0s - loss: 9.0311e-06 - 29ms/epoch - 10ms/step\n",
"Epoch 562/600\n",
"3/3 - 0s - loss: 1.5132e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 563/600\n",
"3/3 - 0s - loss: 1.1472e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 564/600\n",
"3/3 - 0s - loss: 6.1006e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 565/600\n",
"3/3 - 0s - loss: 9.0098e-06 - 24ms/epoch - 8ms/step\n",
"Epoch 566/600\n",
"3/3 - 0s - loss: 7.5672e-06 - 22ms/epoch - 7ms/step\n",
"Epoch 567/600\n",
"3/3 - 0s - loss: 8.4777e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 568/600\n",
"3/3 - 0s - loss: 9.0207e-06 - 27ms/epoch - 9ms/step\n",
"Epoch 569/600\n",
"3/3 - 0s - loss: 1.0824e-05 - 27ms/epoch - 9ms/step\n",
"Epoch 570/600\n",
"3/3 - 0s - loss: 7.5615e-06 - 23ms/epoch - 8ms/step\n",
"Epoch 571/600\n",
"3/3 - 0s - loss: 7.1497e-06 - 27ms/epoch - 9ms/step\n",
"Epoch 572/600\n",
"3/3 - 0s - loss: 7.1619e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 573/600\n",
"3/3 - 0s - loss: 5.9869e-06 - 24ms/epoch - 8ms/step\n",
"Epoch 574/600\n",
"3/3 - 0s - loss: 5.9745e-06 - 24ms/epoch - 8ms/step\n",
"Epoch 575/600\n",
"3/3 - 0s - loss: 8.0464e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 576/600\n",
"3/3 - 0s - loss: 7.2107e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 577/600\n",
"3/3 - 0s - loss: 6.2528e-06 - 26ms/epoch - 9ms/step\n",
"Epoch 578/600\n",
"3/3 - 0s - loss: 6.1893e-06 - 26ms/epoch - 9ms/step\n",
"Epoch 579/600\n",
"3/3 - 0s - loss: 5.3146e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 580/600\n",
"3/3 - 0s - loss: 7.6463e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 581/600\n",
"3/3 - 0s - loss: 7.7579e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 582/600\n",
"3/3 - 0s - loss: 9.6108e-06 - 25ms/epoch - 8ms/step\n",
"Epoch 583/600\n",
"3/3 - 0s - loss: 1.2547e-05 - 23ms/epoch - 8ms/step\n",
"Epoch 584/600\n",
"3/3 - 0s - loss: 1.6049e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 585/600\n",
"3/3 - 0s - loss: 1.8587e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 586/600\n",
"3/3 - 0s - loss: 1.6573e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 587/600\n",
"3/3 - 0s - loss: 1.7321e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 588/600\n",
"3/3 - 0s - loss: 1.2758e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 589/600\n",
"3/3 - 0s - loss: 2.1822e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 590/600\n",
"3/3 - 0s - loss: 1.0393e-05 - 22ms/epoch - 7ms/step\n",
"Epoch 591/600\n",
"3/3 - 0s - loss: 1.1617e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 592/600\n",
"3/3 - 0s - loss: 1.2258e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 593/600\n",
"3/3 - 0s - loss: 9.3363e-06 - 23ms/epoch - 8ms/step\n",
"Epoch 594/600\n",
"3/3 - 0s - loss: 1.1190e-05 - 25ms/epoch - 8ms/step\n",
"Epoch 595/600\n",
"3/3 - 0s - loss: 1.2491e-05 - 26ms/epoch - 9ms/step\n",
"Epoch 596/600\n",
"3/3 - 0s - loss: 1.3760e-05 - 24ms/epoch - 8ms/step\n",
"Epoch 597/600\n",
"3/3 - 0s - loss: 1.2583e-05 - 21ms/epoch - 7ms/step\n",
"Epoch 598/600\n",
"3/3 - 0s - loss: 8.4294e-06 - 22ms/epoch - 7ms/step\n",
"Epoch 599/600\n",
"3/3 - 0s - loss: 7.6945e-06 - 22ms/epoch - 7ms/step\n",
"Epoch 600/600\n",
"3/3 - 0s - loss: 9.1345e-06 - 22ms/epoch - 7ms/step\n",
"14/14 [==============================] - 0s 3ms/step\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7ec1985d60b0>"
]
},
"metadata": {},
"execution_count": 156
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since end of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "YyOarWssKyjN",
"outputId": "3fc5ae3d-4fa6-4a6d-e26f-825cbf6bd8ca"
},
"execution_count": 157,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1710205531.162508\n",
"Tue Mar 12 01:05:31 2024\n"
]
}
]
}
]
}