diff --git "a/.ipynb_checkpoints/music_generation_with_Variational_AE-checkpoint.ipynb" "b/.ipynb_checkpoints/music_generation_with_Variational_AE-checkpoint.ipynb"
new file mode 100644--- /dev/null
+++ "b/.ipynb_checkpoints/music_generation_with_Variational_AE-checkpoint.ipynb"
@@ -0,0 +1,755 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "dgxD_ljQ23dE"
+ },
+ "source": [
+ "# Music generation with Variational AutoEncoder"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "jRRn77kD4EiT"
+ },
+ "outputs": [],
+ "source": [
+ "!pip install -q git+https://github.com/tensorflow/docs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "jqomLmiK4RY4",
+ "outputId": "f26beba1-c06d-48db-a3cf-df5bc83efcb0"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+ "Requirement already satisfied: tensorflow-addons in /usr/local/lib/python3.7/dist-packages (0.17.0)\n",
+ "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from tensorflow-addons) (21.3)\n",
+ "Requirement already satisfied: typeguard>=2.7 in /usr/local/lib/python3.7/dist-packages (from tensorflow-addons) (2.7.1)\n",
+ "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->tensorflow-addons) (3.0.9)\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install tensorflow-addons"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "7DZkI3Fg2yUQ"
+ },
+ "outputs": [],
+ "source": [
+ "import librosa\n",
+ "\n",
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import os\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import tensorflow_addons as tfa\n",
+ "from tensorflow.keras import layers \n",
+ "\n",
+ "import matplotlib.pyplot as plt\n",
+ "from IPython import display\n",
+ "from IPython.display import clear_output\n",
+ "\n",
+ "import glob\n",
+ "import imageio\n",
+ "import time\n",
+ "import IPython.display as ipd\n",
+ "\n",
+ "AUTOTUNE = tf.data.experimental.AUTOTUNE"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "AWcjKTUD37z-"
+ },
+ "outputs": [],
+ "source": [
+ "seed=123\n",
+ "tf.compat.v1.set_random_seed(seed)\n",
+ "session_conf = tf.compat.v1.ConfigProto(intra_op_parallelism_threads=1, inter_op_parallelism_threads=1)\n",
+ "sess = tf.compat.v1.Session(graph=tf.compat.v1.get_default_graph(), config=session_conf)\n",
+ "tf.compat.v1.keras.backend.set_session(sess)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "hsaYjzBi4BPv"
+ },
+ "outputs": [],
+ "source": [
+ "train_size = 60000\n",
+ "BATCH_SIZE = 10\n",
+ "test_size = 10000\n",
+ "epochs = 20\n",
+ "# set the dimensionality of the latent space to a plane for visualization later\n",
+ "latent_dim = 2\n",
+ "num_examples_to_generate = 10\n",
+ "\n",
+ "BASE_PATH = 'drive/MyDrive/music_generation/auto_encoder/genres_original'"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "PM0_HbJd45tx"
+ },
+ "source": [
+ "Data preprocessing"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "ChJ3XdWt40ap"
+ },
+ "outputs": [],
+ "source": [
+ "def DatasetLoader(class_):\n",
+ " music_list = np.array(sorted(os.listdir(BASE_PATH+'/'+class_)))\n",
+ " train_music_1 = list(music_list[[0,52,19,39,71,12,75,85,3,45,24,46,88]]) #99,10,66,76,41\n",
+ " train_music_2 = list(music_list[[4,43,56,55,45,31,11,13,70,37,21,78]]) #65,32,53,22,19,80,89,\n",
+ " TrackSet_1 = [(BASE_PATH)+'/'+class_+'/%s'%(x) for x in train_music_1]\n",
+ " TrackSet_2 = [(BASE_PATH)+'/'+class_+'/%s'%(x) for x in train_music_2]\n",
+ "\n",
+ " return TrackSet_1, TrackSet_2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "Z1sM3p7h42Af"
+ },
+ "outputs": [],
+ "source": [
+ "def load(file_):\n",
+ " data_, sampling_rate = librosa.load(file_,sr=3000, offset=0.0, duration=30)\n",
+ " data_ = data_.reshape(1,90001)\n",
+ " return data_\n",
+ "map_data = lambda filename: tf.compat.v1.py_func(load, [filename], [tf.float32])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "h6ipB6js43ME"
+ },
+ "outputs": [],
+ "source": [
+ "TrackSet_1, TrackSet_2 = DatasetLoader('jazz')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "6Cglv0Yc472G"
+ },
+ "source": [
+ "sample original music"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 75
+ },
+ "id": "yMbqcybe49YH",
+ "outputId": "7cd4c8e8-0b46-4d86-c1fc-961673e9a44b"
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 33,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "sample = TrackSet_1[1]\n",
+ "sample_, sampling_rate = librosa.load(sample,sr=3000, offset=0.0, duration=30)\n",
+ "ipd.Audio(sample_,rate=3000)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 232
+ },
+ "id": "Z-Nnpz3o4-p_",
+ "outputId": "22194601-ef5d-499a-f4f2-40d3ea8adc82"
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
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+ "