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2022-07-29 11:07:11 +00:00
parent 8a093ac9d2
commit d430336c47
11 changed files with 741 additions and 722 deletions
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examples/scibert/deploy/index.html
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@ -2238,9 +2238,8 @@ def get_tokenizer_and_model(
<span class="n">positive_likelihood</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Softmax</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)(</span><span class="n">result</span><span class="o">.</span><span class="n">logits</span><span class="p">)[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span>
<span class="n">tokens</span> <span class="o">=</span> <span class="n">tensors</span><span class="p">[</span><span class="s2">&quot;input_ids&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="n">attentions</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">result</span><span class="o">.</span><span class="n">attentions</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">numpy</span><span class="p">()[</span><span class="mi">0</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)[</span><span class="mi">0</span><span class="p">][</span>
<span class="mi">1</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span>
<span class="p">]</span> <span class="c1"># Tuple of `torch.FloatTensor` (one for each layer) of shape</span>
<span class="n">attentions</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">result</span><span class="o">.</span><span class="n">attentions</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">numpy</span><span class="p">()[</span><span class="mi">0</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
<span class="c1"># Tuple of `torch.FloatTensor` (one for each layer) of shape</span>
<span class="c1"># `(batch_size, num_heads, sequence_length, sequence_length)`.</span>
<span class="n">explanation</span> <span class="o">=</span> <span class="p">[]</span>
@ -2302,9 +2301,8 @@ def find_highlights(sentence: str) -> EvaluatedSentence:
positive_likelihood = torch.nn.Softmax(dim=1)(result.logits)[0][1]
tokens = tensors["input_ids"][0]
attentions = np.sum(result.attentions[-1].numpy()[0], axis=0)[0][
1:-1
] # Tuple of `torch.FloatTensor` (one for each layer) of shape
attentions = np.sum(result.attentions[-1].numpy()[0], axis=0)[0][1:-1]
# Tuple of `torch.FloatTensor` (one for each layer) of shape
# `(batch_size, num_heads, sequence_length, sequence_length)`.
explanation = []
@ -2480,7 +2478,7 @@ To check out the Dockerimage, go to <a href="/examples/scibert/additional-files"
<small>
Last update:
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 17, 2022</span>
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 29, 2022</span>
</small>