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11 | 11 | },
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12 | 12 | {
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13 | 13 | "cell_type": "code",
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14 |
| - "execution_count": null, |
| 14 | + "execution_count": 1, |
15 | 15 | "metadata": {
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16 | 16 | "cellView": "form",
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17 | 17 | "id": "AJs7HHFmg1M9"
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|
104 | 104 | },
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105 | 105 | {
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106 | 106 | "cell_type": "code",
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107 |
| - "execution_count": null, |
| 107 | + "execution_count": 2, |
108 | 108 | "metadata": {
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109 | 109 | "id": "dzLKpmZICaWN"
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110 | 110 | },
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111 |
| - "outputs": [], |
| 111 | + "outputs": [ |
| 112 | + { |
| 113 | + "name": "stderr", |
| 114 | + "output_type": "stream", |
| 115 | + "text": [ |
| 116 | + "2023-02-21 23:30:16.927226: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA\n", |
| 117 | + "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", |
| 118 | + "2023-02-21 23:30:22.964311: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n", |
| 119 | + "2023-02-21 23:30:25.215418: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n", |
| 120 | + "2023-02-21 23:30:25.215454: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n", |
| 121 | + "2023-02-21 23:30:46.622463: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n", |
| 122 | + "2023-02-21 23:30:46.622808: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n", |
| 123 | + "2023-02-21 23:30:46.622837: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n" |
| 124 | + ] |
| 125 | + } |
| 126 | + ], |
112 | 127 | "source": [
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113 | 128 | "import os\n",
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114 | 129 | "import pathlib\n",
|
|
143 | 158 | },
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144 | 159 | {
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145 | 160 | "cell_type": "code",
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146 |
| - "execution_count": null, |
| 161 | + "execution_count": 3, |
147 | 162 | "metadata": {
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148 | 163 | "id": "2-rayb7-3Y0I"
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149 | 164 | },
|
150 |
| - "outputs": [], |
| 165 | + "outputs": [ |
| 166 | + { |
| 167 | + "name": "stdout", |
| 168 | + "output_type": "stream", |
| 169 | + "text": [ |
| 170 | + "Downloading data from http://storage.googleapis.com/download.tensorflow.org/data/mini_speech_commands.zip\n", |
| 171 | + "112967680/182082353 [=================>............] - ETA: 1:08" |
| 172 | + ] |
| 173 | + }, |
| 174 | + { |
| 175 | + "name": "stderr", |
| 176 | + "output_type": "stream", |
| 177 | + "text": [ |
| 178 | + "\n", |
| 179 | + "KeyboardInterrupt\n", |
| 180 | + "\n" |
| 181 | + ] |
| 182 | + } |
| 183 | + ], |
151 | 184 | "source": [
|
152 | 185 | "DATASET_PATH = 'data/mini_speech_commands'\n",
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153 | 186 | "\n",
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|
322 | 355 | },
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323 | 356 | "outputs": [],
|
324 | 357 | "source": [
|
325 |
| - "plt.figure(figsize=(16,10))\n", |
326 |
| - "for i in range(9):\n", |
327 |
| - " plt.subplot(3,3,i+1)\n", |
328 |
| - " audio_signal = example_audio.numpy()[i]\n", |
| 358 | + "plt.figure(figsize=(16, 10))\n", |
| 359 | + "rows = 3\n", |
| 360 | + "cols = 3\n", |
| 361 | + "n = rows * cols\n", |
| 362 | + "for i in range(n):\n", |
| 363 | + " plt.subplot(3, 3, i+1)\n", |
| 364 | + " audio_signal = example_audio[i]\n", |
329 | 365 | " plt.plot(audio_signal)\n",
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330 | 366 | " plt.title(label_names[example_labels[i]])\n",
|
331 | 367 | " plt.yticks(np.arange(-1.2, 1.2, 0.2))\n",
|
332 |
| - " plt.ylim([-1.1,1.1])" |
| 368 | + " plt.ylim([-1.1, 1.1])" |
333 | 369 | ]
|
334 | 370 | },
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335 | 371 | {
|
|
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