Spaces:
Running
on
T4
Running
on
T4
Update app.py
Browse files
app.py
CHANGED
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@@ -35,6 +35,7 @@ STYLE = """
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padding-right: 2px;
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padding-top: 0;
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padding-bottom: 0;
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}
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.tree {
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padding: 0px;
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@@ -137,10 +138,10 @@ a:before {
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text-decoration-line: none;
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border-radius: 5px;
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transition: .5s;
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width: 280px;
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display: flex;
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align-items: center;
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justify-content: space-
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}
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.tree li a span {
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padding: 5px;
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@@ -157,13 +158,19 @@ a:before {
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}
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.end-of-text, .chosen {
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background-color: #ea580c;
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width:auto!important;
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}
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"""
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def clean(s):
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return s.replace("\n", r"\n").replace("\t", r"\t")
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def generate_markdown_table(
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@@ -197,10 +204,10 @@ def generate_nodes(token_ix, node, step):
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token = tokenizer.decode([token_ix])
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if node.is_final:
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return f"<li> <a href='#' class='end-of-text'> <span> <b>{
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html_content = (
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f"<li> <a href='#'> <span> <b>{
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)
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if node.table is not None:
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html_content += node.table
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@@ -265,8 +272,6 @@ def generate_beams(start_sentence, scores, sequences, length_penalty):
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n_beams = len(scores[0])
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beam_trees = [original_tree] * n_beams
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candidate_nodes = []
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-
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for step, step_scores in enumerate(scores):
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(
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top_token_indexes,
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@@ -359,16 +364,6 @@ def generate_beams(start_sentence, scores, sequences, length_penalty):
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),
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)
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# Check this child should be selected as a top beam.
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# Is it a final step or an EOS token?
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if (
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step == len(scores) - 1
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or current_token_choice_ix == tokenizer.eos_token_id
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):
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candidate_nodes.append(
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beam_trees[source_beam_ix].children[current_token_choice_ix]
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)
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# Reassign all beams at once
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beam_trees = [
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beam_trees[int(top_df_selected.iloc[beam_ix]["beam_index"])]
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padding-right: 2px;
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padding-top: 0;
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padding-bottom: 0;
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text-wrap:nowrap;
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}
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.tree {
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padding: 0px;
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text-decoration-line: none;
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border-radius: 5px;
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transition: .5s;
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display: flex;
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align-items: center;
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justify-content: space-between;
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overflow: hidden;
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}
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.tree li a span {
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padding: 5px;
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}
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.end-of-text, .chosen {
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background-color: #ea580c;
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}
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.end-of-text {
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width:auto!important;
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}
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.nonfinal {
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width:280px;
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min-width: 280px;
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}
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"""
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def clean(s):
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return s.replace("\n", r"\n").replace("\t", r"\t").strip()
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def generate_markdown_table(
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token = tokenizer.decode([token_ix])
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if node.is_final:
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return f"<li> <a href='#' class='end-of-text'> <span> <b>{clean(token)}</b> <br>Total score: {node.total_score:.2f}</span> </a> </li>"
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html_content = (
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f"<li> <a href='#' class='nonfinal'> <span> <b>{clean(token)}</b> </span>"
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)
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if node.table is not None:
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html_content += node.table
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n_beams = len(scores[0])
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beam_trees = [original_tree] * n_beams
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for step, step_scores in enumerate(scores):
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(
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top_token_indexes,
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),
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)
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# Reassign all beams at once
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beam_trees = [
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beam_trees[int(top_df_selected.iloc[beam_ix]["beam_index"])]
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