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171 | 171 | " untar=True, cache_dir='.',\n",
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172 | 172 | " cache_subdir='')\n",
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173 | 173 | "\n",
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174 |
| - "dataset_dir = os.path.join(os.path.dirname(dataset), 'aclImdb')" |
| 174 | + "dataset_dir = os.path.join(os.path.dirname(dataset), 'aclImdb_v1')" |
175 | 175 | ]
|
176 | 176 | },
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177 | 177 | {
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193 | 193 | },
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194 | 194 | "outputs": [],
|
195 | 195 | "source": [
|
196 |
| - "train_dir = os.path.join(dataset_dir, 'train')\n", |
| 196 | + "train_dir = os.path.join(dataset_dir, 'aclImdb', 'train')\n", |
| 197 | + "test_dir = os.path.join(dataset_dir, 'aclImdb', 'test')\n", |
197 | 198 | "os.listdir(train_dir)"
|
198 | 199 | ]
|
199 | 200 | },
|
|
214 | 215 | },
|
215 | 216 | "outputs": [],
|
216 | 217 | "source": [
|
217 |
| - "sample_file = os.path.join(train_dir, 'pos/1181_9.txt')\n", |
| 218 | + "sample_file = os.path.join(train_dir, 'pos', '1181_9.txt')\n", |
218 | 219 | "with open(sample_file) as f:\n",
|
219 | 220 | " print(f.read())"
|
220 | 221 | ]
|
|
286 | 287 | "seed = 42\n",
|
287 | 288 | "\n",
|
288 | 289 | "raw_train_ds = tf.keras.utils.text_dataset_from_directory(\n",
|
289 |
| - " 'aclImdb/train',\n", |
| 290 | + " train_dir,\n", |
290 | 291 | " batch_size=batch_size,\n",
|
291 | 292 | " validation_split=0.2,\n",
|
292 | 293 | " subset='training',\n",
|
|
366 | 367 | "outputs": [],
|
367 | 368 | "source": [
|
368 | 369 | "raw_val_ds = tf.keras.utils.text_dataset_from_directory(\n",
|
369 |
| - " 'aclImdb/train',\n", |
| 370 | + " train_dir,\n", |
370 | 371 | " batch_size=batch_size,\n",
|
371 | 372 | " validation_split=0.2,\n",
|
372 | 373 | " subset='validation',\n",
|
|
382 | 383 | "outputs": [],
|
383 | 384 | "source": [
|
384 | 385 | "raw_test_ds = tf.keras.utils.text_dataset_from_directory(\n",
|
385 |
| - " 'aclImdb/test',\n", |
| 386 | + " test_dir,\n", |
386 | 387 | " batch_size=batch_size)"
|
387 | 388 | ]
|
388 | 389 | },
|
|
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