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Running
Running
mylibrar
commited on
Commit
·
6713f3f
1
Parent(s):
9868b53
Add help messages to interface
Browse files
app.py
CHANGED
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@@ -16,26 +16,33 @@ with st.sidebar:
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st.markdown(html, unsafe_allow_html=True)
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metric = st.radio(
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"Choose a metric", options=os.listdir(os.path.join(EVAL_DIR))
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)
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n_shot = st.radio(
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"Selece an n-shot number", os.listdir(os.path.join(EVAL_DIR, metric))
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)
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col1, col2 = st.columns(2)
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def render_column(col_label):
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st.header(f"Checkpoint {col_label}")
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ckpt = st.select_slider('Select a checkpoint', sorted(os.listdir(os.path.join(EVAL_DIR, metric, n_shot))), key=col_label + '1')
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st.write(f'Veiwing Evaluation Results for Checkpoint: `{ckpt}`')
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with tarfile.open(os.path.join(EVAL_DIR, metric, n_shot, ckpt, file), "r:gz") as tar:
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f = tar.extractfile(tar.next())
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eval_json = json.load(f)
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if isinstance(eval_json, list):
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doc_id = st.slider("Select a document id", 0, len(eval_json) - 1, 0, 1, key=col_label + '3')
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st.json(eval_json[doc_id])
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else:
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st.json(eval_json)
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st.markdown(html, unsafe_allow_html=True)
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metric = st.radio(
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"Choose a metric", options=os.listdir(os.path.join(EVAL_DIR)),
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help="type of evaluation benchmark task"
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)
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n_shot = st.radio(
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"Selece an n-shot number", os.listdir(os.path.join(EVAL_DIR, metric)),
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help="number of examples included in few-shot prompting"
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)
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col1, col2 = st.columns(2)
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def render_column(col_label):
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st.header(f"Checkpoint {col_label}")
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ckpt = st.select_slider('Select a checkpoint', sorted(os.listdir(os.path.join(EVAL_DIR, metric, n_shot))), key=col_label + '1', help="checkpoint index from 3 to 360")
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st.write(f'Veiwing Evaluation Results for Checkpoint: `{ckpt}`')
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suffix, result_file = ".tar.gz", "results.json"
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file_list: list = sorted(f_name[:-len(suffix)] for f_name in os.listdir(os.path.join(EVAL_DIR, metric, n_shot, ckpt)))
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if result_file in file_list:
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file_list.remove(result_file)
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file_list = [result_file] + file_list
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file = st.selectbox("Select a file", file_list, key=col_label + '2', help="a list of raw output files from evaluation results")
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file += suffix
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with tarfile.open(os.path.join(EVAL_DIR, metric, n_shot, ckpt, file), "r:gz") as tar:
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f = tar.extractfile(tar.next())
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eval_json = json.load(f)
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if isinstance(eval_json, list):
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doc_id = st.slider("Select a document id", 0, len(eval_json) - 1, 0, 1, key=col_label + '3', help="index of a specific question/task in current file")
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st.json(eval_json[doc_id])
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else:
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st.json(eval_json)
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