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Merge branch 'main' into update-autograd-doc-comment
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advanced_source/dynamic_quantization_tutorial.py

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@@ -134,10 +134,18 @@ def tokenize(self, path):
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# -----------------------------
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#
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# This is a tutorial on dynamic quantization, a quantization technique
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# that is applied after a model has been trained. Therefore, we'll simply load some
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# pretrained weights into this model architecture; these weights were obtained
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# by training for five epochs using the default settings in the word language model
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# example.
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# that is applied after a model has been trained. Therefore, we'll simply
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# load some pretrained weights into this model architecture; these
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# weights were obtained by training for five epochs using the default
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# settings in the word language model example.
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#
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# Before running this tutorial, download the required pre-trained model:
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#
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# .. code-block:: bash
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#
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# wget https://s3.amazonaws.com/pytorch-tutorial-assets/word_language_model_quantize.pth
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#
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# Place the downloaded file in the data directory or update the model_data_filepath accordingly.
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ntokens = len(corpus.dictionary)
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