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<Fix> evaluation dataset, printed samples #836

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<Fix> evaluation dataset, printed samples #836

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22 changes: 13 additions & 9 deletions 08-seq_classification.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -497,7 +497,7 @@
"\n",
" with torch.no_grad():\n",
" for batch_idx in range(len(data_generator)):\n",
" data, target = test_data_gen[batch_idx]\n",
" data, target = data_generator[batch_idx]\n",
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We want to inspect sequences from the test set, no?
I didn't get it.

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Then why are we declaring the "data_generator", with a different seed, and not using it to sample data?

" data, target = torch.from_numpy(data).float().to(device), torch.from_numpy(target).long().to(device)\n",
"\n",
" data_decoded = data_generator.decode_x_batch(data.cpu().numpy())\n",
Expand Down Expand Up @@ -527,18 +527,22 @@
" print(f'{label}: {num_correct} / {count_classes[label]} correct')\n",
"\n",
" # Report some random sequences for examination\n",
" num_sequences_to_print = min(10, len(correct))\n",
" idxs = random.sample(range(len(correct)), num_sequences_to_print)\n",
"\n",
" print('\\nHere are some example sequences:')\n",
" for i in range(10):\n",
" sequence, truth, prediction = correct[random.randrange(0, 10)]\n",
" for i in idxs:\n",
" sequence, truth, prediction = correct[i]\n",
" print(f'{sequence} -> {truth} was labelled {prediction}')\n",
"\n",
" # Report misclassified sequences for investigation\n",
" if incorrect and verbose:\n",
" print('\\nThe following sequences were misclassified:')\n",
" for sequence, truth, prediction in incorrect:\n",
" print(f'{sequence} -> {truth} was labelled {prediction}')\n",
" else:\n",
" print('\\nThere were no misclassified sequences.')"
" if verbose:\n",
" if incorrect:\n",
" print('\\nThe following sequences were misclassified:')\n",
" for sequence, truth, prediction in incorrect:\n",
" print(f'{sequence} -> {truth} was labelled {prediction}')\n",
" else:\n",
" print('\\nThere were no misclassified sequences.')"
]
},
{
Expand Down