├── README.md
├── LICENSE
└── vggish_tf_records.ipynb


/README.md:
--------------------------------------------------------------------------------
1 | # audioset_experiments
2 | Various experiments with the audioset database and tensorflow
3 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2019 Jose Giraldo
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


--------------------------------------------------------------------------------
/vggish_tf_records.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |   "nbformat": 4,
  3 |   "nbformat_minor": 0,
  4 |   "metadata": {
  5 |     "colab": {
  6 |       "name": "vggish_tf_records",
  7 |       "provenance": [],
  8 |       "include_colab_link": true
  9 |     },
 10 |     "kernelspec": {
 11 |       "name": "python3",
 12 |       "display_name": "Python 3"
 13 |     }
 14 |   },
 15 |   "cells": [
 16 |     {
 17 |       "cell_type": "markdown",
 18 |       "metadata": {
 19 |         "id": "view-in-github",
 20 |         "colab_type": "text"
 21 |       },
 22 |       "source": [
 23 |         "<a href=\"https://colab.research.google.com/github/wetdog/audioset_experiments/blob/master/vggish_tf_records.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
 24 |       ]
 25 |     },
 26 |     {
 27 |       "cell_type": "markdown",
 28 |       "metadata": {
 29 |         "id": "KIgCYEtxtjZh"
 30 |       },
 31 |       "source": [
 32 |         "**Reading Audioset database in Tensorflow 2.0  **\n",
 33 |         "\n",
 34 |         "This is an example based on the following tutorial https://www.tensorflow.org/tutorials/load_data/tf_records and adapted to work with the audioset database. The main difference is the use of Sequence example\n",
 35 |         "\n",
 36 |         "\n",
 37 |         "\n"
 38 |       ]
 39 |     },
 40 |     {
 41 |       "cell_type": "code",
 42 |       "metadata": {
 43 |         "id": "r7BmTVx1tn_8"
 44 |       },
 45 |       "source": [
 46 |         "from __future__ import absolute_import, division, print_function, unicode_literals\n",
 47 |         "\n",
 48 |         "\n",
 49 |         "import tensorflow as tf\n",
 50 |         "\n",
 51 |         "import numpy as np\n",
 52 |         "import IPython.display as display"
 53 |       ],
 54 |       "execution_count": 2,
 55 |       "outputs": []
 56 |     },
 57 |     {
 58 |       "cell_type": "markdown",
 59 |       "metadata": {
 60 |         "id": "ZM2EsEbxqV4T"
 61 |       },
 62 |       "source": [
 63 |         "Download the audioset embeddings dataset in  tf records format and the class label mappings"
 64 |       ]
 65 |     },
 66 |     {
 67 |       "cell_type": "code",
 68 |       "metadata": {
 69 |         "id": "Dfm0ylYIbSEE",
 70 |         "outputId": "01b2e419-e7ee-4a87-f46e-4ec28657ab6e",
 71 |         "colab": {
 72 |           "base_uri": "https://localhost:8080/"
 73 |         }
 74 |       },
 75 |       "source": [
 76 |         "!curl -O http://storage.googleapis.com/us_audioset/youtube_corpus/v1/features/features.tar.gz\n",
 77 |         "!curl -O http://storage.googleapis.com/us_audioset/youtube_corpus/v1/csv/class_labels_indices.csv"
 78 |       ],
 79 |       "execution_count": 3,
 80 |       "outputs": [
 81 |         {
 82 |           "output_type": "stream",
 83 |           "name": "stdout",
 84 |           "text": [
 85 |             "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
 86 |             "                                 Dload  Upload   Total   Spent    Left  Speed\n",
 87 |             "100 2468M  100 2468M    0     0  66.3M      0  0:00:37  0:00:37 --:--:-- 58.6M\n",
 88 |             "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
 89 |             "                                 Dload  Upload   Total   Spent    Left  Speed\n",
 90 |             "100 14675  100 14675    0     0   193k      0 --:--:-- --:--:-- --:--:--  196k\n"
 91 |           ]
 92 |         }
 93 |       ]
 94 |     },
 95 |     {
 96 |       "cell_type": "markdown",
 97 |       "metadata": {
 98 |         "id": "e5w1wXdbq4xr"
 99 |       },
100 |       "source": [
101 |         "Extract the tf recods files"
102 |       ]
103 |     },
104 |     {
105 |       "cell_type": "code",
106 |       "metadata": {
107 |         "id": "1Znps6fkbyLc",
108 |         "outputId": "e0dacae4-6a87-477e-b23f-fffb939ccc1b",
109 |         "colab": {
110 |           "base_uri": "https://localhost:8080/"
111 |         }
112 |       },
113 |       "source": [
114 |         "!tar xvfz features.tar.gz | wc -l"
115 |       ],
116 |       "execution_count": 4,
117 |       "outputs": [
118 |         {
119 |           "output_type": "stream",
120 |           "name": "stdout",
121 |           "text": [
122 |             "12232\n"
123 |           ]
124 |         }
125 |       ]
126 |     },
127 |     {
128 |       "cell_type": "markdown",
129 |       "metadata": {
130 |         "id": "N5-0CCa2vrnH"
131 |       },
132 |       "source": [
133 |         "Parse the csv file with the names of the labels"
134 |       ]
135 |     },
136 |     {
137 |       "cell_type": "code",
138 |       "metadata": {
139 |         "id": "G_mdTCYAv0tl"
140 |       },
141 |       "source": [
142 |         "with open('class_labels_indices.csv') as f:\n",
143 |         "  idx = []\n",
144 |         "  names = []\n",
145 |         "  for line in f:\n",
146 |         "    items = line.strip(\"\").split(',')\n",
147 |         "    idx.append(items[0])\n",
148 |         "    names.append(items[2])\n",
149 |         "\n",
150 |         "labels_dict = {(i): j for i,j in zip(idx,names)}\n"
151 |       ],
152 |       "execution_count": 6,
153 |       "outputs": []
154 |     },
155 |     {
156 |       "cell_type": "markdown",
157 |       "metadata": {
158 |         "id": "UdkjtE0D9FrT"
159 |       },
160 |       "source": [
161 |         "**Read tfrecord File**\n",
162 |         "\n",
163 |         "Use SequenceExample to get the audio embedding, if we use tf.train.Example we only retrieve the metadata asociated with the embedding. We should see 10 tensors of embeddings corresponding to 10 seconds of audio."
164 |       ]
165 |     },
166 |     {
167 |       "cell_type": "code",
168 |       "metadata": {
169 |         "id": "dRUCG2Bls23K",
170 |         "outputId": "0a9f0e56-2a5d-4bd4-af41-c7714a98455b",
171 |         "colab": {
172 |           "base_uri": "https://localhost:8080/"
173 |         }
174 |       },
175 |       "source": [
176 |         "raw_dataset = tf.data.TFRecordDataset('audioset_v1_embeddings/bal_train/mY.tfrecord') # load example file\n",
177 |         "\n",
178 |         "\n",
179 |         "for raw_record in raw_dataset.take(1):\n",
180 |         "  tf_seq_example = tf.train.SequenceExample()\n",
181 |         "  tf_seq_example.ParseFromString(raw_record.numpy())\n",
182 |         "  print(tf_seq_example)"
183 |       ],
184 |       "execution_count": 7,
185 |       "outputs": [
186 |         {
187 |           "output_type": "stream",
188 |           "name": "stdout",
189 |           "text": [
190 |             "context {\n",
191 |             "  feature {\n",
192 |             "    key: \"end_time_seconds\"\n",
193 |             "    value {\n",
194 |             "      float_list {\n",
195 |             "        value: 50.0\n",
196 |             "      }\n",
197 |             "    }\n",
198 |             "  }\n",
199 |             "  feature {\n",
200 |             "    key: \"labels\"\n",
201 |             "    value {\n",
202 |             "      int64_list {\n",
203 |             "        value: 114\n",
204 |             "        value: 510\n",
205 |             "      }\n",
206 |             "    }\n",
207 |             "  }\n",
208 |             "  feature {\n",
209 |             "    key: \"start_time_seconds\"\n",
210 |             "    value {\n",
211 |             "      float_list {\n",
212 |             "        value: 40.0\n",
213 |             "      }\n",
214 |             "    }\n",
215 |             "  }\n",
216 |             "  feature {\n",
217 |             "    key: \"video_id\"\n",
218 |             "    value {\n",
219 |             "      bytes_list {\n",
220 |             "        value: \"mYehsuARe6A\"\n",
221 |             "      }\n",
222 |             "    }\n",
223 |             "  }\n",
224 |             "}\n",
225 |             "feature_lists {\n",
226 |             "  feature_list {\n",
227 |             "    key: \"audio_embedding\"\n",
228 |             "    value {\n",
229 |             "      feature {\n",
230 |             "        bytes_list {\n",
231 |             "          value: \"#\\226]\\006(N\\223K\\377\\207\\r\\363\\333\\377\\000Y\\322v9\\351\\303\\000\\377\\311\\375\\215E\\342\\377J\\000\\000_\\000\\370\\222:\\270\\377\\357\\000\\245\\000\\377\\213jd\\267\\353\\377J\\033$\\273\\267\\307\\035\\377\\000\\207\\244Q\\000\\000\\206\\000\\000\\312\\356<R\\325g\\303\\356\\016N\\224\\377\\270\\377\\237\\240\\377\\377\\321\\252j\\357O\\217\\377\\377,\\330\\000\\377|\\246\\000\\013\\034\\000\\377\\357\\212\\267\\300b\\000\\000\\000\\251\\236\\000\\233\\035\\000\\326\\377\\327\\327\\377\\377\\223\\0009{\"\n",
232 |             "        }\n",
233 |             "      }\n",
234 |             "      feature {\n",
235 |             "        bytes_list {\n",
236 |             "          value: \"\\034\\256t\\0004\\224\\250M\\377\\256\\000\\334\\330\\373\\001_\\313c\\322\\361\\310\\000\\366\\233\\272\\256\\006\\342\\377\\000\\000\\000\\236\\000\\377\\214\\000\\001\\377\\220\\000\\000\\000\\377\\307\\034(\\377\\032\\377\\237\\377\\000\\202_\\274\\\"\\377\\000\\000C\\000:\\000F\\000\\026S\\257wa5\\377\\3777\\000\\361\\211\\377\\304\\377\\373\\377\\236\\377\\247\\270\\000\\340\\000l\\377\\377\\005Qu\\377\\366\\315jk\\246V\\377\\377\\373\\321\\252\\000\\000\\214\\033\\000\\000\\000\\377\\356f\\300\\202[\\000\\\\\\017\\377\\000\\261\\377\"\n",
237 |             "        }\n",
238 |             "      }\n",
239 |             "      feature {\n",
240 |             "        bytes_list {\n",
241 |             "          value: \"2rp:\\\"/\\205\\000\\377\\234\\000i\\332\\362\\000c\\310X\\356\\376R\\000\\335_\\216\\276E\\237\\377\\274\\000\\000\\005\\000\\355\\304\\000\\\"\\377\\225\\000\\004\\000\\377\\377h\\213\\377V\\377w\\177\\000Z\\264\\276\\200\\377\\000\\3770TN\\000\\024\\000\\013\\377\\250\\002\\377\\017\\377\\342\\202,\\213\\000O\\273d\\377\\375\\377\\377\\001\\377!\\267\\000\\245\\377\\377b\\201\\000\\377\\000\\260\\000\\000,\\000\\377`\\345\\020,\\000\\000\\022\\000*\\000\\000\\274\\000\\030W\\000\\000\\377\\377\\377\\312\\000\\377\\000\"\n",
242 |             "        }\n",
243 |             "      }\n",
244 |             "      feature {\n",
245 |             "        bytes_list {\n",
246 |             "          value: \"DV};k\\200[\\013\\377~\\000;\\350\\343\\002~\\207+\\344\\215\\226<\\304b\\230\\232\\232e\\377V\\000\\000c\\000\\363\\205@\\016\\337j\\000\\0371\\377\\357i\\266\\377j\\377~\\377\\000\\017Z\\210\\036n\\n\\255Bh%u\\234\\000F\\377\\213\\025\\346(\\364\\334\\000u\\000\\013:\\3124\\320\\360W\\377\\n\\357\\201\\266\\000o\\322\\377a\\000\\263\\315\\312\\236\\\\\\004E\\000\\3778\\377\\000\\213\\000\\202r#\\000\\200\\000\\324\\r\\377N\\034\\013@\\377\\211xq\\377A\"\n",
247 |             "        }\n",
248 |             "      }\n",
249 |             "      feature {\n",
250 |             "        bytes_list {\n",
251 |             "          value: \"#zs\\013\\031A\\211\\027\\377\\222\\000<\\350\\325\\000D\\310g\\250\\377e\\n\\377B\\222=\\000\\236\\377f\\000L\\003\\000\\364\\377\\0006\\377\\277\\000\\000\\000\\377\\3635^\\377\\210\\377\\275[\\030\\214\\224\\377\\177\\377\\000\\3226\\273\\020\\026\\013\\000p\\202\\377:c\\000\\377\\377\\000A5Q\\233\\357\\217\\330\\377\\377\\377\\217\\377^\\346C\\226\\377\\377\\005>\\000\\3779\\030\\000\\000H\\000\\377V\\377=\\000\\000\\000\\000p\\0005\\000\\377\\000\\000\\232\\377\\000\\377\\377\\377\\377\\000\\377\\030\"\n",
252 |             "        }\n",
253 |             "      }\n",
254 |             "      feature {\n",
255 |             "        bytes_list {\n",
256 |             "          value: \"n\\211x:?\\205a&\\377\\315\\030e\\215\\260\\030K\\242t\\211\\307h\\000\\377{\\204\\213h\\212\\377r\\000\\036\\365\\000\\345\\034\\026\\000\\377{\\000\\000\\000\\377\\322\\317\\276\\377\\321\\377i\\377)\\207\\377\\271\\036\\323\\000\\242<\\000ih\\000\\000\\202}\\263L\\366\\207\\375\\33422\\254\\256\\377b\\277\\024\\377\\276\\377\\205\\200\\000\\273\\037&\\377\\377\\000\\000\\230\\314\\233\\000\\000\\020w\\240\\245\\304\\3457^\\000\\000\\016\\000\\000b\\000\\364\\000\\007\\334\\334E\\000\\345\\377\\377\\036\\351\\322\"\n",
257 |             "        }\n",
258 |             "      }\n",
259 |             "      feature {\n",
260 |             "        bytes_list {\n",
261 |             "          value: \"Z\\206\\2078\\026w\\226&\\377\\207\\000{\\200\\326;V\\215B\\256\\306\\230.\\377\\324\\007\\203\\036\\225\\377\\000\\000\\000\\377*\\345\\217\\000\\n\\377\\213%\\000\\000\\377\\261\\377V\\377\\271\\377\\327\\345\\000\\027t\\243\\346~W~W\\t\\320\\211}\\000\\001{\\317\\000qKj\\377\\377\\233\\377\\203\\377\\000]\\377\\360\\000\\314\\254c\\220\\031\\000I\\377\\273\\0107\\\"\\233\\377P\\000`\\316\\277\\266\\351\\205cs\\036\\367\\377\\033\\003f\\000\\377\\357\\204K\\211Hj3\\013\\271s\\000M\"\n",
262 |             "        }\n",
263 |             "      }\n",
264 |             "      feature {\n",
265 |             "        bytes_list {\n",
266 |             "          value: \"2\\237\\214\\010\\031z\\3111\\377\\205\\000\\213\\212\\342$h\\212:\\227\\277\\263\\000\\377\\253C\\216\\020\\246\\377\\000\\000\\000\\377#\\377m\\000\\005\\376\\325\\024Q\\000\\357a\\313B\\377\\220\\377\\303\\300\\000\\232\\211\\2535\\360\\000\\000\\035\\017\\324\\200\\205$\\001\\243\\335\\037W\\000\\261\\226\\305}\\340w\\377{n\\377\\377\\000|y\\371\\251v\\000`\\377\\377^41\\377\\276\\235\\0002\\252\\306\\256\\377\\272\\345v\\000\\275\\377{\\000\\210\\000\\272\\031\\2729I\\033\\000\\3018\\377\\000\\206\\214\"\n",
267 |             "        }\n",
268 |             "      }\n",
269 |             "      feature {\n",
270 |             "        bytes_list {\n",
271 |             "          value: \"Sz\\203(U]\\217@\\377\\276\\000\\226\\311\\364\\000G\\303F\\221\\326g\\010\\377\\205~\\231A\\331\\377&\\000\\000\\335\\000\\300\\250\\000\\004\\377S\\000v\\000\\377\\235\\324\\270\\377\\315\\377\\210\\250\\000\\217\\256sG\\374\\000\\301\\037\\000\\207\\000\\000\\000o\\260\\240:\\305p\\331\\327\\264o\\220\\000\\377\\213Lu\\377\\326\\377h\\377r\\303\\036\\220\\377\\377\\002|=\\305\\250\\000\\000XZ\\205\\313\\377\\242\\177\\377U\\000&B\\000\\312\\000\\234\\000\\021\\237AEZ\\353\\373\\361d\\000w\"\n",
272 |             "        }\n",
273 |             "      }\n",
274 |             "      feature {\n",
275 |             "        bytes_list {\n",
276 |             "          value: \"@uy\\031d^qE\\377\\313\\000\\234\\311\\372\\001Z\\237\\240i\\370\\211\\000\\377j\\215\\255<\\351\\377J\\000\\000|\\000\\266\\214\\023+\\377\\233\\000X\\000\\377\\262\\250\\205\\377\\253\\377\\244\\315\\006_\\360l8\\362\\000\\326b\\0008\\000b\\000#\\277\\365G\\337\\215\\201\\300\\203#T\\214\\377tf1\\375\\336\\377\\215\\372U\\347\\000[\\377\\377\\000M\\261\\377\\377G\\000[f\\025\\271\\377\\2573\\324\\033\\203\\000I\\022\\354\\\"\\262l\\000)\\376\\007w\\275\\377\\207U4\\377\"\n",
277 |             "        }\n",
278 |             "      }\n",
279 |             "    }\n",
280 |             "  }\n",
281 |             "}\n",
282 |             "\n"
283 |           ]
284 |         }
285 |       ]
286 |     },
287 |     {
288 |       "cell_type": "code",
289 |       "metadata": {
290 |         "id": "Mc6BplBmtXL9",
291 |         "outputId": "e632e5cb-3c0f-4dbe-c4f5-0e0dde0e13d8",
292 |         "colab": {
293 |           "base_uri": "https://localhost:8080/"
294 |         }
295 |       },
296 |       "source": [
297 |         "# print raw representation of the fields\n",
298 |         "for raw_record in raw_dataset.take(1):\n",
299 |         "  print(repr(raw_record))"
300 |       ],
301 |       "execution_count": 8,
302 |       "outputs": [
303 |         {
304 |           "output_type": "stream",
305 |           "name": "stdout",
306 |           "text": [
307 |             "<tf.Tensor: shape=(), dtype=string, numpy=b'\\nn\\n\\x1b\\n\\x08video_id\\x12\\x0f\\n\\r\\n\\x0bmYehsuARe6A\\n\\x1e\\n\\x12start_time_seconds\\x12\\x08\\x12\\x06\\n\\x04\\x00\\x00 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308 |           ]
309 |         }
310 |       ]
311 |     },
312 |     {
313 |       "cell_type": "markdown",
314 |       "metadata": {
315 |         "id": "NoyioUq8v4p-"
316 |       },
317 |       "source": [
318 |         "In order to parse the tensors we have to create a description of the features, note that the label field is a VarLenFeature beacuse each example is labeled with a multi-class tag without a fixed size of labels."
319 |       ]
320 |     },
321 |     {
322 |       "cell_type": "code",
323 |       "metadata": {
324 |         "id": "RWzi66sYtdmY"
325 |       },
326 |       "source": [
327 |         "# Create a description of the features.\n",
328 |         "context = {\n",
329 |         "    'start_time_seconds': tf.io.FixedLenFeature([], tf.float32, default_value=0.0),\n",
330 |         "    'video_id': tf.io.FixedLenFeature([], tf.string, default_value=''),\n",
331 |         "    'start_time_seconds': tf.io.FixedLenFeature([], tf.float32, default_value=0.0),\n",
332 |         "    'labels': tf.io.VarLenFeature(tf.int64),\n",
333 |         "}\n",
334 |         "\n",
335 |         "sequence = {\n",
336 |         "    'audio_embedding': tf.io.FixedLenSequenceFeature([], tf.string, default_value=None ,allow_missing=True)\n",
337 |         "}\n",
338 |         "\n",
339 |         "def _parse_function(example_proto):\n",
340 |         "  # Parse the input tf.Example proto using the dictionary above.\n",
341 |         "  return tf.io.parse_single_sequence_example(example_proto, context_features=context, sequence_features=sequence)\n"
342 |       ],
343 |       "execution_count": 9,
344 |       "outputs": []
345 |     },
346 |     {
347 |       "cell_type": "code",
348 |       "metadata": {
349 |         "id": "_3dVZteExWXJ"
350 |       },
351 |       "source": [
352 |         "parsed_dataset = raw_dataset.map(_parse_function)"
353 |       ],
354 |       "execution_count": 10,
355 |       "outputs": []
356 |     },
357 |     {
358 |       "cell_type": "markdown",
359 |       "metadata": {
360 |         "id": "-rNUfWHCwwTh"
361 |       },
362 |       "source": [
363 |         "Finally we can display some of the embeddings present in the tfrecords file"
364 |       ]
365 |     },
366 |     {
367 |       "cell_type": "code",
368 |       "metadata": {
369 |         "id": "DoH0H2VlxpRz",
370 |         "outputId": "ebac373d-51a5-4c5b-b0e7-01b1fab2692a",
371 |         "colab": {
372 |           "base_uri": "https://localhost:8080/",
373 |           "height": 1000
374 |         }
375 |       },
376 |       "source": [
377 |         "import matplotlib.pyplot as plt\n",
378 |         "\n",
379 |         "count = 0\n",
380 |         "for example in parsed_dataset:\n",
381 |         "  context, sequence = example\n",
382 |         "  embedding = sequence['audio_embedding'].numpy()\n",
383 |         "  label = context['labels']\n",
384 |         "  e = tf.io.decode_raw(embedding, tf.int8)\n",
385 |         "  labels_str = [\"\".join(labels_dict[str(i)] for i in label.values.numpy())]\n",
386 |         "  plt.title(labels_str)\n",
387 |         "  plt.imshow(e,cmap='gray')\n",
388 |         "  plt.show()\n",
389 |         "  count+=1\n",
390 |         "  print(count)\n",
391 |         ""
392 |       ],
393 |       "execution_count": 23,
394 |       "outputs": [
395 |         {
396 |           "output_type": "display_data",
397 |           "data": {
398 |             "text/plain": [
399 |               "<Figure size 640x480 with 1 Axes>"
400 |             ],
401 |             "image/png": 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\n"
402 |           },
403 |           "metadata": {}
404 |         },
405 |         {
406 |           "output_type": "stream",
407 |           "name": "stdout",
408 |           "text": [
409 |             "1\n"
410 |           ]
411 |         },
412 |         {
413 |           "output_type": "display_data",
414 |           "data": {
415 |             "text/plain": [
416 |               "<Figure size 640x480 with 1 Axes>"
417 |             ],
418 |             "image/png": 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\n"
419 |           },
420 |           "metadata": {}
421 |         },
422 |         {
423 |           "output_type": "stream",
424 |           "name": "stdout",
425 |           "text": [
426 |             "2\n"
427 |           ]
428 |         },
429 |         {
430 |           "output_type": "display_data",
431 |           "data": {
432 |             "text/plain": [
433 |               "<Figure size 640x480 with 1 Axes>"
434 |             ],
435 |             "image/png": 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\n"
436 |           },
437 |           "metadata": {}
438 |         },
439 |         {
440 |           "output_type": "stream",
441 |           "name": "stdout",
442 |           "text": [
443 |             "3\n"
444 |           ]
445 |         },
446 |         {
447 |           "output_type": "display_data",
448 |           "data": {
449 |             "text/plain": [
450 |               "<Figure size 640x480 with 1 Axes>"
451 |             ],
452 |             "image/png": 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\n"
453 |           },
454 |           "metadata": {}
455 |         },
456 |         {
457 |           "output_type": "stream",
458 |           "name": "stdout",
459 |           "text": [
460 |             "4\n"
461 |           ]
462 |         },
463 |         {
464 |           "output_type": "display_data",
465 |           "data": {
466 |             "text/plain": [
467 |               "<Figure size 640x480 with 1 Axes>"
468 |             ],
469 |             "image/png": 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\n"
470 |           },
471 |           "metadata": {}
472 |         },
473 |         {
474 |           "output_type": "stream",
475 |           "name": "stdout",
476 |           "text": [
477 |             "5\n"
478 |           ]
479 |         },
480 |         {
481 |           "output_type": "display_data",
482 |           "data": {
483 |             "text/plain": [
484 |               "<Figure size 640x480 with 1 Axes>"
485 |             ],
486 |             "image/png": 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\n"
487 |           },
488 |           "metadata": {}
489 |         },
490 |         {
491 |           "output_type": "stream",
492 |           "name": "stdout",
493 |           "text": [
494 |             "6\n"
495 |           ]
496 |         },
497 |         {
498 |           "output_type": "display_data",
499 |           "data": {
500 |             "text/plain": [
501 |               "<Figure size 640x480 with 1 Axes>"
502 |             ],
503 |             "image/png": 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\n"
504 |           },
505 |           "metadata": {}
506 |         },
507 |         {
508 |           "output_type": "stream",
509 |           "name": "stdout",
510 |           "text": [
511 |             "7\n"
512 |           ]
513 |         },
514 |         {
515 |           "output_type": "display_data",
516 |           "data": {
517 |             "text/plain": [
518 |               "<Figure size 640x480 with 1 Axes>"
519 |             ],
520 |             "image/png": 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\n"
521 |           },
522 |           "metadata": {}
523 |         },
524 |         {
525 |           "output_type": "stream",
526 |           "name": "stdout",
527 |           "text": [
528 |             "8\n"
529 |           ]
530 |         },
531 |         {
532 |           "output_type": "display_data",
533 |           "data": {
534 |             "text/plain": [
535 |               "<Figure size 640x480 with 1 Axes>"
536 |             ],
537 |             "image/png": 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\n"
538 |           },
539 |           "metadata": {}
540 |         },
541 |         {
542 |           "output_type": "stream",
543 |           "name": "stdout",
544 |           "text": [
545 |             "9\n"
546 |           ]
547 |         },
548 |         {
549 |           "output_type": "display_data",
550 |           "data": {
551 |             "text/plain": [
552 |               "<Figure size 640x480 with 1 Axes>"
553 |             ],
554 |             "image/png": 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\n"
555 |           },
556 |           "metadata": {}
557 |         },
558 |         {
559 |           "output_type": "stream",
560 |           "name": "stdout",
561 |           "text": [
562 |             "10\n"
563 |           ]
564 |         },
565 |         {
566 |           "output_type": "display_data",
567 |           "data": {
568 |             "text/plain": [
569 |               "<Figure size 640x480 with 1 Axes>"
570 |             ],
571 |             "image/png": 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\n"
572 |           },
573 |           "metadata": {}
574 |         },
575 |         {
576 |           "output_type": "stream",
577 |           "name": "stdout",
578 |           "text": [
579 |             "11\n"
580 |           ]
581 |         },
582 |         {
583 |           "output_type": "display_data",
584 |           "data": {
585 |             "text/plain": [
586 |               "<Figure size 640x480 with 1 Axes>"
587 |             ],
588 |             "image/png": 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\n"
589 |           },
590 |           "metadata": {}
591 |         },
592 |         {
593 |           "output_type": "stream",
594 |           "name": "stdout",
595 |           "text": [
596 |             "12\n"
597 |           ]
598 |         }
599 |       ]
600 |     }
601 |   ]
602 | }


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