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rasbt 2024-05-06 07:40:09 -05:00
parent 78829f28e9
commit 0448162fdc
2 changed files with 31 additions and 14 deletions
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1
.gitignore vendored
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@ -13,6 +13,7 @@ ch05/02_alternative_weight_loading/checkpoints
ch05/01_main-chapter-code/model.pth ch05/01_main-chapter-code/model.pth
ch05/01_main-chapter-code/model_and_optimizer.pth ch05/01_main-chapter-code/model_and_optimizer.pth
ch05/03_bonus_pretraining_on_gutenberg/model_checkpoints ch05/03_bonus_pretraining_on_gutenberg/model_checkpoints
ch06/01_main-chapter-code/gpt2
# Datasets # Datasets
ch02/01_main-chapter-code/number-data.txt ch02/01_main-chapter-code/number-data.txt

44
ch06/01_main-chapter-code/ch06.ipynb
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@ -628,7 +628,10 @@
" def __getitem__(self, index):\n", " def __getitem__(self, index):\n",
" encoded = self.encoded_texts[index]\n", " encoded = self.encoded_texts[index]\n",
" label = self.data.iloc[index][\"Label\"]\n", " label = self.data.iloc[index][\"Label\"]\n",
" return torch.tensor(encoded, dtype=torch.long), torch.tensor(label, dtype=torch.long)\n", " return (\n",
" torch.tensor(encoded, dtype=torch.long),\n",
" torch.tensor(label, dtype=torch.long)\n",
" )\n",
"\n", "\n",
" def __len__(self):\n", " def __len__(self):\n",
" return len(self.data)\n", " return len(self.data)\n",
@ -663,7 +666,12 @@
} }
], ],
"source": [ "source": [
"train_dataset = SpamDataset(\"train.csv\", max_length=None, tokenizer=tokenizer)\n", "train_dataset = SpamDataset(\n",
" csv_file=\"train.csv\",\n",
" max_length=None,\n",
" tokenizer=tokenizer\n",
")\n",
"\n",
"print(train_dataset.max_length)" "print(train_dataset.max_length)"
] ]
}, },
@ -686,8 +694,16 @@
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"val_dataset = SpamDataset(\"validation.csv\", max_length=train_dataset.max_length, tokenizer=tokenizer)\n", "val_dataset = SpamDataset(\n",
"test_dataset = SpamDataset(\"test.csv\", max_length=train_dataset.max_length, tokenizer=tokenizer)" " csv_file=\"validation.csv\",\n",
" max_length=train_dataset.max_length,\n",
" tokenizer=tokenizer\n",
")\n",
"test_dataset = SpamDataset(\n",
" csv_file=\"test.csv\",\n",
" max_length=train_dataset.max_length,\n",
" tokenizer=tokenizer\n",
")"
] ]
}, },
{ {
@ -695,7 +711,7 @@
"id": "20170d89-85a0-4844-9887-832f5d23432a", "id": "20170d89-85a0-4844-9887-832f5d23432a",
"metadata": {}, "metadata": {},
"source": [ "source": [
"- Next, we use the dataset to instantiate the data loaders, which is similar to creating the data loaders in previous chapters:" "- Next, we use the dataset to instantiate the data loaders, which is similar to creating the data loaders in previous chapters"
] ]
}, },
{ {
@ -787,7 +803,7 @@
"id": "5cdd7947-7039-49bf-8a5e-c0a2f4281ca1", "id": "5cdd7947-7039-49bf-8a5e-c0a2f4281ca1",
"metadata": {}, "metadata": {},
"source": [ "source": [
"- Lastly, let's print the total number of batches in each dataset:" "- Lastly, let's print the total number of batches in each dataset"
] ]
}, },
{ {
@ -880,16 +896,16 @@
}, },
"outputs": [ "outputs": [
{ {
"name": "stdout", "name": "stderr",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"File already exists and is up-to-date: gpt2/124M/checkpoint\n", "checkpoint: 100%|███████████████████████████| 77.0/77.0 [00:00<00:00, 39.7kiB/s]\n",
"File already exists and is up-to-date: gpt2/124M/encoder.json\n", "encoder.json: 100%|███████████████████████| 1.04M/1.04M [00:00<00:00, 3.25MiB/s]\n",
"File already exists and is up-to-date: gpt2/124M/hparams.json\n", "hparams.json: 100%|█████████████████████████| 90.0/90.0 [00:00<00:00, 51.4kiB/s]\n",
"File already exists and is up-to-date: gpt2/124M/model.ckpt.data-00000-of-00001\n", "model.ckpt.data-00000-of-00001: 100%|███████| 498M/498M [01:00<00:00, 8.20MiB/s]\n",
"File already exists and is up-to-date: gpt2/124M/model.ckpt.index\n", "model.ckpt.index: 100%|███████████████████| 5.21k/5.21k [00:00<00:00, 2.34MiB/s]\n",
"File already exists and is up-to-date: gpt2/124M/model.ckpt.meta\n", "model.ckpt.meta: 100%|██████████████████████| 471k/471k [00:00<00:00, 2.26MiB/s]\n",
"File already exists and is up-to-date: gpt2/124M/vocab.bpe\n" "vocab.bpe: 100%|████████████████████████████| 456k/456k [00:00<00:00, 2.62MiB/s]\n"
] ]
} }
], ],