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{
"cells": [
{
"cell_type": "markdown",
"id": "adadfc62",
"metadata": {},
"source": [
"<!--- Licensed to the Apache Software Foundation (ASF) under one -->\n",
"<!--- or more contributor license agreements. See the NOTICE file -->\n",
"<!--- distributed with this work for additional information -->\n",
"<!--- regarding copyright ownership. The ASF licenses this file -->\n",
"<!--- to you under the Apache License, Version 2.0 (the -->\n",
"<!--- \"License\"); you may not use this file except in compliance -->\n",
"<!--- with the License. You may obtain a copy of the License at -->\n",
"\n",
"<!--- http://www.apache.org/licenses/LICENSE-2.0 -->\n",
"\n",
"<!--- Unless required by applicable law or agreed to in writing, -->\n",
"<!--- software distributed under the License is distributed on an -->\n",
"<!--- \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -->\n",
"<!--- KIND, either express or implied. See the License for the -->\n",
"<!--- specific language governing permissions and limitations -->\n",
"<!--- under the License. -->\n",
"\n",
"\n",
"# Gluon `Dataset`s and `DataLoader`\n",
"\n",
"One of the most critical steps for model training and inference is loading the data: without data you can't do Machine Learning! In this tutorial we use the Gluon API to define a [Dataset](../../../../api/gluon/data/index.rst#datasets) and use a [DataLoader](../../../../api/gluon/data/index.rst#dataloader) to iterate through the dataset in mini-batches.\n",
"\n",
"## Introduction to `Dataset`s\n",
"\n",
"[Dataset](../../../../api/gluon/data/index.rst#datasets) objects are used to represent collections of data, and include methods to load and parse the data (that is often stored on disk). Gluon has a number of different `Dataset` classes for working with image data straight out-of-the-box, but we'll use the [ArrayDataset](../../../../api/gluon/data/index.rst#mxnet.gluon.data.ArrayDataset) to introduce the idea of a `Dataset`.\n",
"\n",
"We first start by generating random data `X` (with 3 variables) and corresponding random labels `y` to simulate a typical supervised learning task. We generate 10 samples and we pass them all to the `ArrayDataset`."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "f6aec9c9",
"metadata": {},
"outputs": [],
"source": [
"import mxnet as mx\n",
"import os\n",
"import tarfile\n",
"\n",
"mx.np.random.seed(42) # Fix the seed for reproducibility\n",
"X = mx.np.random.uniform(size=(10, 3))\n",
"y = mx.np.random.uniform(size=(10, 1))\n",
"dataset = mx.gluon.data.dataset.ArrayDataset(X, y)"
]
},
{
"cell_type": "markdown",
"id": "c1cd826a",
"metadata": {},
"source": [
"A key feature of a `Dataset` is the __*ability to retrieve a single sample given an index*__. Our random data and labels were generated in memory, so this `ArrayDataset` doesn't have to load anything from disk, but the interface is the same for all `Dataset`'s."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "088bbac1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(array([0.74707687, 0.37641123, 0.46362457]), array([0.35440788]))\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"[04:46:52] /work/mxnet/src/storage/storage.cc:202: Using Pooled (Naive) StorageManager for CPU\n"
]
}
],
"source": [
"sample_idx = 4\n",
"sample = dataset[sample_idx]\n",
"\n",
"assert len(sample) == 2\n",
"assert sample[0].shape == (3, )\n",
"assert sample[1].shape == (1, )\n",
"print(sample)"
]
},
{
"cell_type": "markdown",
"id": "b59bd84b",
"metadata": {},
"source": [
"We get a tuple of a data sample and its corresponding label, which makes sense because we passed the data `X` and the labels `y` in that order when we instantiated the `ArrayDataset`. We don't usually retrieve individual samples from `Dataset` objects though (unless we're quality checking the output samples). Instead we use a `DataLoader`.\n",
"\n",
"## Introduction to `DataLoader`\n",
"\n",
"A [DataLoader](../../../../api/gluon/data/index.rst#dataloader) is used to create mini-batches of samples from a [Dataset](../../../../api/gluon/data/index.rst#datasets), and provides a convenient iterator interface for looping these batches. It's typically much more efficient to pass a mini-batch of data through a neural network than a single sample at a time, because the computation can be performed in parallel. A required parameter of `DataLoader` is the size of the mini-batches you want to create, called `batch_size`.\n",
"\n",
"Another benefit of using `DataLoader` is the ability to easily load data in parallel using [multiprocessing](https://docs.python.org/3.6/library/multiprocessing.html). You can set the `num_workers` parameter to the number of CPUs available on your machine for maximum performance, or limit it to a lower number to spare resources."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c67ce5f5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"X_batch has shape (5, 3), and y_batch has shape (5, 1)\n",
"X_batch has shape (5, 3), and y_batch has shape (5, 1)\n"
]
}
],
"source": [
"from multiprocessing import cpu_count\n",
"CPU_COUNT = cpu_count()\n",
"\n",
"data_loader = mx.gluon.data.DataLoader(dataset, batch_size=5, num_workers=CPU_COUNT)\n",
"\n",
"for X_batch, y_batch in data_loader:\n",
" print(\"X_batch has shape {}, and y_batch has shape {}\".format(X_batch.shape, y_batch.shape))"
]
},
{
"cell_type": "markdown",
"id": "dfadd6e6",
"metadata": {},
"source": [
"`X_batch has shape (5, 3), and y_batch has shape (5, 1)` <!--notebook-skip-line-->\n",
"\n",
"`X_batch has shape (5, 3), and y_batch has shape (5, 1)` <!--notebook-skip-line-->\n",
"\n",
"\n",
"We can see 2 mini-batches of data (and labels), each with 5 samples, which makes sense given we started with a dataset of 10 samples. When comparing the shape of the batches to the samples returned by the `Dataset`, we've gained an extra dimension at the start which is sometimes called the batch axis.\n",
"\n",
"Our `data_loader` loop will stop when every sample of `dataset` has been returned as part of a batch. Sometimes the dataset length isn't divisible by the mini-batch size, leaving a final batch with a smaller number of samples. `DataLoader`'s default behavior is to return this smaller mini-batch, but this can be changed by setting the `last_batch` parameter to `discard` (which ignores the last batch) or `rollover` (which starts the next epoch with the remaining samples).\n",
"\n",
"## Machine learning with `Dataset`s and `DataLoader`s\n",
"\n",
"You will often use a few different `Dataset` objects in your Machine Learning project. It's essential to separate your training dataset from testing dataset, and it's also good practice to have validation dataset (a.k.a. development dataset) that can be used for optimising hyperparameters.\n",
"\n",
"Using Gluon `Dataset` objects, we define the data to be included in each of these separate datasets. Common use cases for loading data are covered already (e.g. [mxnet.gluon.data.vision.datasets.ImageFolderDataset](../../../../api/gluon/data/vision/datasets/index.rst#mxnet.gluon.data.vision.datasets.ImageFolderDataset)), but it's simple to create your own custom `Dataset` classes for other types of data. You can even use included `Dataset` objects for common datasets if you want to experiment quickly; they download and parse the data for you! In this example we use the [Fashion MNIST](https://github.com/zalandoresearch/fashion-mnist) dataset from Zalando Research.\n",
"\n",
"Many of the image `Dataset`'s accept a function (via the optional `transform` parameter) which is applied to each sample returned by the `Dataset`. It's useful for performing data augmentation, but can also be used for more simple data type conversion and pixel value scaling as seen below."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e2f9fe27",
"metadata": {},
"outputs": [],
"source": [
"def transform(data, label):\n",
" data = data.astype('float32')/255\n",
" return data, label\n",
"\n",
"train_dataset = mx.gluon.data.vision.datasets.FashionMNIST(train=True).transform(transform)\n",
"valid_dataset = mx.gluon.data.vision.datasets.FashionMNIST(train=False).transform(transform)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "769f8ae7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data type: float32\n",
"Label: 8\n",
"Label description: Bag\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"from matplotlib.pylab import imshow\n",
"\n",
"sample_idx = 234\n",
"sample = train_dataset[sample_idx]\n",
"data = sample[0]\n",
"label = sample[1]\n",
"label_desc = {0:'T-shirt/top', 1:'Trouser', 2:'Pullover', 3:'Dress', 4:'Coat', 5:'Sandal', 6:'Shirt', 7:'Sneaker', 8:'Bag', 9:'Ankle boot'}\n",
"\n",
"imshow(data[:,:,0].asnumpy(), cmap='gray')\n",
"print(\"Data type: {}\".format(data.dtype))\n",
"print(\"Label: {}\".format(label))\n",
"print(\"Label description: {}\".format(label_desc[label.item()]))"
]
},
{
"cell_type": "markdown",
"id": "ab2d89ec",
"metadata": {},
"source": [
"`Data type: <class 'numpy.float32'>`<!--notebook-skip-line-->\n",
"\n",
"`Label: 8`<!--notebook-skip-line-->\n",
"\n",
"`Label description: Bag`<!--notebook-skip-line-->\n",
"\n",
"\n",
"![datasets fashion mnist bag](https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/doc/tutorials/gluon/datasets/fashion_mnist_bag.png)<!--notebook-skip-line-->\n",
"\n",
"\n",
"When training machine learning models it is important to shuffle the training samples every time you pass through the dataset (i.e. each epoch). Sometimes the order of your samples will have a spurious relationship with the target variable, and shuffling the samples helps remove this. With [DataLoader](../../../../api/gluon/data/index.rst#dataloader) it's as simple as adding `shuffle=True`. You don't need to shuffle the validation and testing data though.\n",
"\n",
"If you have more complex shuffling requirements (e.g. when handling sequential data), take a look at [mxnet.gluon.data.BatchSampler](../../../../api/gluon/data/index.rst#mxnet.gluon.data.BatchSampler) and pass this to your `DataLoader` instead."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "db5efe6e",
"metadata": {},
"outputs": [],
"source": [
"batch_size = 32\n",
"train_data_loader = mx.gluon.data.DataLoader(train_dataset, batch_size, shuffle=True, num_workers=CPU_COUNT)\n",
"valid_data_loader = mx.gluon.data.DataLoader(valid_dataset, batch_size, num_workers=CPU_COUNT)"
]
},
{
"cell_type": "markdown",
"id": "1c173b3c",
"metadata": {},
"source": [
"With both `DataLoader`s defined, we can now train a model to classify each image and evaluate the validation loss at each epoch. Our Fashion MNIST dataset has 10 classes including shirt, dress, sneakers, etc. We define a simple fully connected network with a softmax output and use cross entropy as our loss."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c67a9cf7",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[04:46:56] /work/mxnet/src/storage/storage.cc:202: Using Pooled (Naive) StorageManager for GPU\n"
]
}
],
"source": [
"from mxnet import gluon, autograd, ndarray\n",
"\n",
"def construct_net():\n",
" net = gluon.nn.HybridSequential()\n",
" net.add(gluon.nn.Dense(128, activation=\"relu\"))\n",
" net.add(gluon.nn.Dense(64, activation=\"relu\"))\n",
" net.add(gluon.nn.Dense(10))\n",
" return net\n",
"\n",
"# construct and initialize network.\n",
"device = mx.gpu() if mx.device.num_gpus() else mx.cpu()\n",
"\n",
"net = construct_net()\n",
"net.hybridize()\n",
"net.initialize(mx.init.Xavier(), device=device)\n",
"# define loss and trainer.\n",
"criterion = gluon.loss.SoftmaxCrossEntropyLoss()\n",
"trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': 0.1})"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "23ed2cf0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 0, training loss: 0.54, validation loss: 0.42\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1, training loss: 0.40, validation loss: 0.36\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2, training loss: 0.36, validation loss: 0.35\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3, training loss: 0.33, validation loss: 0.33\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 4, training loss: 0.31, validation loss: 0.33\n"
]
}
],
"source": [
"\n",
"\n",
"epochs = 5\n",
"for epoch in range(epochs):\n",
" # training loop (with autograd and trainer steps, etc.)\n",
" cumulative_train_loss = mx.np.zeros(1, device=device)\n",
" training_samples = 0\n",
" for batch_idx, (data, label) in enumerate(train_data_loader):\n",
" data = data.to_device(device).reshape((-1, 784)) # 28*28=784\n",
" label = label.to_device(device)\n",
" with autograd.record():\n",
" output = net(data)\n",
" loss = criterion(output, label)\n",
" loss.backward()\n",
" trainer.step(data.shape[0])\n",
" cumulative_train_loss += mx.np.sum(loss)\n",
" training_samples += data.shape[0]\n",
" train_loss = cumulative_train_loss.item()/training_samples\n",
"\n",
" # validation loop\n",
" cumulative_valid_loss = mx.np.zeros(1, device=device)\n",
" valid_samples = 0\n",
" for batch_idx, (data, label) in enumerate(valid_data_loader):\n",
" data = data.to_device(device).reshape((-1, 784)) # 28*28=784\n",
" label = label.to_device(device)\n",
" output = net(data)\n",
" loss = criterion(output, label)\n",
" cumulative_valid_loss += mx.np.sum(loss)\n",
" valid_samples += data.shape[0]\n",
" valid_loss = cumulative_valid_loss.item()/valid_samples\n",
"\n",
" print(\"Epoch {}, training loss: {:.2f}, validation loss: {:.2f}\".format(epoch, train_loss, valid_loss))"
]
},
{
"cell_type": "markdown",
"id": "cb2e8baf",
"metadata": {},
"source": [
"`Epoch 0, training loss: 0.54, validation loss: 0.45`<!--notebook-skip-line-->\n",
"\n",
"`...`<!--notebook-skip-line-->\n",
"\n",
"`Epoch 4, training loss: 0.32, validation loss: 0.33`<!--notebook-skip-line-->\n",
"\n",
"\n",
"# Using own data with included `Dataset`s\n",
"\n",
"Gluon has a number of different [Dataset](../../../../api/gluon/data/index.rst#mxnet.gluon.data.Dataset) classes for working with your own image data straight out-of-the-box. You can get started quickly using the [mxnet.gluon.data.vision.datasets.ImageFolderDataset](../../../../api/gluon/data/vision/datasets/index.rst#mxnet.gluon.data.vision.datasets.ImageFolderDataset) which loads images directly from a user-defined folder, and infers the label (i.e. class) from the folders.\n",
"\n",
"We will run through an example for image classification, but a similar process applies for other vision tasks. If you already have your own collection of images to work with you should partition your data into training and test sets, and place all objects of the same class into seperate folders. Similar to:"
]
},
{
"cell_type": "markdown",
"id": "1e27d17b",
"metadata": {},
"source": [
"```\n",
" ./images/train/car/abc.jpg\n",
" ./images/train/car/efg.jpg\n",
" ./images/train/bus/hij.jpg\n",
" ./images/train/bus/klm.jpg\n",
" ./images/test/car/xyz.jpg\n",
" ./images/test/bus/uvw.jpg\n",
"```\n"
]
},
{
"cell_type": "markdown",
"id": "bf54a418",
"metadata": {},
"source": [
"You can download the Caltech 101 dataset if you don't already have images to work with for this example, but please note the download is 126MB."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "970af891",
"metadata": {},
"outputs": [],
"source": [
"\n",
"data_folder = \"data\"\n",
"dataset_name = \"101_ObjectCategories\"\n",
"archive_file = \"{}.tar.gz\".format(dataset_name)\n",
"archive_path = os.path.join(data_folder, archive_file)\n",
"data_url = \"https://s3.us-east-2.amazonaws.com/mxnet-public/\"\n",
"\n",
"if not os.path.isfile(archive_path):\n",
" mx.test_utils.download(\"{}{}\".format(data_url, archive_file), dirname = data_folder)\n",
" print('Extracting {} in {}...'.format(archive_file, data_folder))\n",
" tar = tarfile.open(archive_path, \"r:gz\")\n",
" tar.extractall(data_folder)\n",
" tar.close()\n",
" print('Data extracted.')"
]
},
{
"cell_type": "markdown",
"id": "625858d8",
"metadata": {},
"source": [
"After downloading and extracting the data archive, we have two folders: `data/101_ObjectCategories` and `data/101_ObjectCategories_test`. We load the data into separate training and testing [ImageFolderDataset](../../../../api/gluon/data/vision/datasets/index.rst#mxnet.gluon.data.vision.datasets.ImageFolderDataset)s."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "031d4fc7",
"metadata": {},
"outputs": [],
"source": [
"training_path = os.path.join(data_folder, dataset_name)\n",
"testing_path = os.path.join(data_folder, \"{}_test\".format(dataset_name))"
]
},
{
"cell_type": "markdown",
"id": "acb87269",
"metadata": {},
"source": [
"We instantiate the [ImageFolderDataset](../../../../api/gluon/data/vision/datasets/index.rst#mxnet.gluon.data.vision.datasets.ImageFolderDataset)s by providing the path to the data, and the folder structure will be traversed to determine which image classes are available and which images correspond to each class. You must take care to ensure the same classes are both the training and testing datasets, otherwise the label encodings can get muddled.\n",
"\n",
"Optionally, you can pass a `transform` parameter to these `Dataset`'s as we've seen before."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "5baa25a7",
"metadata": {},
"outputs": [],
"source": [
"train_dataset = mx.gluon.data.vision.datasets.ImageFolderDataset(training_path)\n",
"test_dataset = mx.gluon.data.vision.datasets.ImageFolderDataset(testing_path)"
]
},
{
"cell_type": "markdown",
"id": "e13fa4f1",
"metadata": {},
"source": [
"Samples from these datasets are tuples of data and label. Images are loaded from disk, decoded and optionally transformed when the `__getitem__(i)` method is called (equivalent to `train_dataset[i]`).\n",
"\n",
"As with the Fashion MNIST dataset the labels will be integer encoded. You can use the `synsets` property of the [ImageFolderDataset](../../../../api/gluon/data/vision/datasets/index.rst#mxnet.gluon.data.vision.datasets.ImageFolderDataset)s to retrieve the original descriptions (e.g. `train_dataset.synsets[i]`)."
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "e027e91b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data type: uint8\n",
"Label: 1\n",
"Label description: Faces_easy\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sample_idx = 539\n",
"sample = train_dataset[sample_idx]\n",
"data = sample[0]\n",
"label = sample[1]\n",
"\n",
"imshow(data.asnumpy(), cmap='gray')\n",
"print(\"Data type: {}\".format(data.dtype))\n",
"print(\"Label: {}\".format(label))\n",
"print(\"Label description: {}\".format(train_dataset.synsets[label]))\n",
"assert label == 1"
]
},
{
"cell_type": "markdown",
"id": "245cb62a",
"metadata": {},
"source": [
"`Data type: <class 'numpy.uint8'>`<!--notebook-skip-line-->\n",
"\n",
"`Label: 1`<!--notebook-skip-line-->\n",
"\n",
"`Label description: Faces_easy` <!--notebook-skip-line-->\n",
"\n",
"\n",
"![datasets caltech101 face](https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/doc/tutorials/gluon/datasets/caltech101_face.png)<!--notebook-skip-line-->\n",
"\n",
"\n",
"# Using own data with custom `Dataset`s\n",
"\n",
"Sometimes you have data that doesn't quite fit the format expected by the included [Dataset](../../../../api/gluon/data/index.rst#mxnet.gluon.data.Dataset)s. You might be able to preprocess your data to fit the expected format, but it is easy to create your own dataset to do this.\n",
"\n",
"All you need to do is create a class that implements a `__getitem__` method, that returns a sample (i.e. a tuple of [mx.np.ndarray](../../../../api/np/arrays.ndarray.rst#the-n-dimensional-array-ndarray)'s).\n",
"\n",
"# Appendix: Upgrading from Module `DataIter` to Gluon `DataLoader`\n",
"\n",
"Before Gluon's [DataLoader](../../../../api/gluon/data/index.rst#Dataloader), MXNet used [DataIter](../../../../api/legacy/io/index.rst#mxnet.io.DataIter) objects for loading data for training and testing. `DataIter` has a similar interface for iterating through data, but it isn't directly compatible with typical Gluon `DataLoader` loops. Unlike Gluon `DataLoader` which often returns a tuple of `(data, label)`, a `DataIter` returns a [DataBatch](../../../../api/legacy/io/index.rst#mxnet.io.DataBatch) object that has `data` and `label` properties. Switching to `DataLoader`'s is highly recommended when using Gluon, but you'll need to take care of pre-processing steps such as augmentations in a `transform` function.\n",
"\n",
"So you can get up and running with Gluon quicker if you have already implemented complex pre-processing steps using `DataIter`, we have provided a simple class to wrap existing `DataIter` objects so they can be used in a typical Gluon training loop. You can use this class for `DataIter`s such as [mxnet.image.ImageIter](../../../../api/legacy/image/index.rst#mxnet.image.ImageIter) and [mxnet.io.ImageRecordIter](../../../../api/legacy/io/index.rst#mxnet.io.ImageDetRecordIter) that have single data and label arrays."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "ec9b60d3",
"metadata": {},
"outputs": [],
"source": [
"class DataIterLoader():\n",
" def __init__(self, data_iter):\n",
" self.data_iter = data_iter\n",
"\n",
" def __iter__(self):\n",
" self.data_iter.reset()\n",
" return self\n",
"\n",
" def __next__(self):\n",
" batch = self.data_iter.__next__()\n",
" assert len(batch.data) == len(batch.label) == 1\n",
" data = batch.data[0]\n",
" label = batch.label[0]\n",
" return data, label\n",
"\n",
" def next(self):\n",
" return self.__next__() # for Python 2"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "654bf6ca",
"metadata": {},
"outputs": [],
"source": [
"data_iter = mx.io.NDArrayIter(data=X, label=y, batch_size=5)\n",
"data_iter_loader = DataIterLoader(data_iter)\n",
"for X_batch, y_batch in data_iter_loader:\n",
" assert X_batch.shape == (5, 3)\n",
" assert y_batch.shape == (5, 1)"
]
},
{
"cell_type": "markdown",
"id": "dc4def57",
"metadata": {},
"source": [
"<!-- INSERT SOURCE DOWNLOAD BUTTONS -->"
]
}
],
"metadata": {
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 5
}