Spaces:
Runtime error
Runtime error
First commit.
Browse files- .gitignore +2 -0
- download.py +3 -0
- logo.png +0 -0
- requirements.txt +1 -0
- run.py +313 -0
.gitignore
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venv/
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.idea/
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download.py
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import thermostat
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data = thermostat.load("imdb-bert-lig", cache_dir="~/datasets")
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logo.png
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requirements.txt
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thermostat-datasets==1.0.1
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run.py
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import datasets
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import glob
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import json
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import pandas as pd
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import streamlit as st
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import sys
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import textwrap
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from thermostat import load
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from thermostat.data.thermostat_configs import builder_configs
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nlp = datasets
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HTML_WRAPPER = """<div>{}</div>"""
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#HTML_WRAPPER = """<div style="overflow-x: auto; border: 1px solid #e6e9ef; border-radius: 0.25rem; padding: 1rem;
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# margin-bottom: 2.5rem">{}</div>"""
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MAX_SIZE = 40000000000
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if len(sys.argv) > 1:
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path_to_datasets = sys.argv[1]
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else:
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path_to_datasets = None
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# Hack to extend the width of the main pane.
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def _max_width_():
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max_width_str = f"max-width: 1000px;"
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st.markdown(
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f"""
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<style>
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.reportview-container .main .block-container{{
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{max_width_str}
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}}
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th {{
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text-align: left;
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font-size: 110%;
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}}
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tr:hover {{
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background-color: #ffff99;
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}}
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</style>
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""",
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unsafe_allow_html=True,
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)
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_max_width_()
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def render_features(features):
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if isinstance(features, dict):
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return {k: render_features(v) for k, v in features.items()}
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if isinstance(features, nlp.features.ClassLabel):
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return features.names
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if isinstance(features, nlp.features.Value):
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return features.dtype
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if isinstance(features, nlp.features.Sequence):
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return {"[]": render_features(features.feature)}
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return features
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app_state = st.experimental_get_query_params()
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start = True
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loaded = True
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INITIAL_SELECTION = ""
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app_state.setdefault("dataset", "glue")
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if len(app_state.get("dataset", [])) == 1:
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app_state["dataset"] = app_state["dataset"][0]
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INITIAL_SELECTION = app_state["dataset"]
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#print(INITIAL_SELECTION)
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if start:
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# Logo and sidebar decoration.
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st.sidebar.markdown(
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"""<center>
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<a href="https://github.com/DFKI-NLP/thermostat">
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</a>
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</center>""",
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unsafe_allow_html=True,
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)
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st.sidebar.image("logo.png", width=300)
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st.sidebar.markdown(
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"<center><h2><a href='https://github.com/DFKI-NLP/thermostat'>github/DFKI-NLP/thermostat</h2></a></center>",
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unsafe_allow_html=True,
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)
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st.sidebar.markdown(
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"""
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<center>
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<a target="_blank" href="https://huggingface.co/docs/datasets/">datasets Docs</a>
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</center>""",
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unsafe_allow_html=True,
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)
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st.sidebar.subheader("")
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# Interaction with the nlp libary.
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# @st.cache
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def get_confs():
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""" Get the list of confs for a dataset. """
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confs = builder_configs
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if confs and len(confs) > 1:
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return confs
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else:
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return []
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# @st.cache(allow_output_mutation=True)
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def get(conf):
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""" Get a dataset from name and conf """
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ds = load(conf, cache_dir=path_to_datasets)
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return ds, False
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# Dataset select box.
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datasets = []
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selection = None
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if path_to_datasets is None:
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list_of_datasets = nlp.list_datasets(with_community_datasets=False)
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else:
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list_of_datasets = sorted(glob.glob(path_to_datasets + "*"))
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for i, dataset in enumerate(list_of_datasets):
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dataset = dataset.split("/")[-1]
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if INITIAL_SELECTION and dataset == INITIAL_SELECTION:
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selection = i
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datasets.append(dataset)
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st.experimental_set_query_params(**app_state)
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# Side bar Configurations.
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configs = get_confs()
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conf_avail = len(configs) > 0
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conf_option = None
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if conf_avail:
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start = 0
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for i, conf in enumerate(configs):
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if conf.name == app_state.get("config", None):
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start = i
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conf_option = st.sidebar.selectbox(
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"Thermostat configuration", configs, index=start, format_func=lambda a: a.name
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)
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app_state["config"] = conf_option.name
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else:
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if "config" in app_state:
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del app_state["config"]
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st.experimental_set_query_params(**app_state)
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dts, fail = get(str(conf_option.name) if conf_option else None)
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# Main panel setup.
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if fail:
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st.markdown(
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"Dataset is too large to browse or requires manual download. Check it out in the datasets library! \n\n "
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"Size: "
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+ str(dts.info.size_in_bytes)
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+ "\n\n Instructions: "
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+ str(dts.manual_download_instructions)
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)
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else:
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d = dts
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keys = list(d[0].__dict__.keys())
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st.header(
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"Thermostat configuration: "
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+ (conf_option.name if conf_option else "")
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)
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st.markdown(
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"*Homepage*: "
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+ d.info.homepage
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)
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md = """
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%s
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""" % (
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d.info.description.replace("\\", " ")
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)
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st.markdown(md)
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step = 50
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offset = st.sidebar.number_input(
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"Offset (Size: %d)" % len(d),
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min_value=0,
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max_value=int(len(d)) - step,
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value=0,
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step=step,
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)
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citation = None #st.sidebar.checkbox("Show Citations", False)
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table = not st.sidebar.checkbox("Show List View", False)
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show_features = st.sidebar.checkbox("Show Features", True)
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show_atts = st.sidebar.checkbox("Show Attribution Scores", False)
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md = """
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```
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%s
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```
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""" % (
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d.info.citation.replace("\\", "").replace("}", " }").replace("{", "{ "),
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)
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if citation:
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st.markdown(md)
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# st.text("Features:")
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#if show_features:
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# on_keys = st.multiselect("Features", keys, keys)
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# #st.write(render_features(d.features))
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#else:
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on_keys = keys
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# Remove some keys
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on_keys = [k for k in on_keys if k in ['predictions', 'true_label', 'predicted_label']]
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if not table:
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# Full view.
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for item in range(offset, offset + step):
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st.text(" ")
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st.text(" ---- #" + str(item))
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st.text(" ")
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# Use st to write out.
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for k in on_keys:
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v = getattr(d[item], k)
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st.subheader(k)
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if isinstance(v, str):
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out = v
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st.text(textwrap.fill(out, width=120))
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elif (
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isinstance(v, bool)
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or isinstance(v, int)
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or isinstance(v, float)
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):
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st.text(v)
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else:
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st.write(v)
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else:
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# Table view. Use Pandas.
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df, heatmap_htmls = [], []
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for item in range(offset, offset + step):
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df_item = {}
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df_item["_number"] = item
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for k in on_keys:
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v = getattr(d[item], k)
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# Remove [PAD] tokens from attributions and input_ids
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if k in ['attributions', 'input_ids']:
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v = [vi for vi in v if vi != 0 or vi != 0.0]
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if isinstance(v, str):
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out = v
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df_item[k] = textwrap.fill(out, width=50)
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elif (
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isinstance(v, bool)
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or isinstance(v, int)
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or isinstance(v, float)
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):
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df_item[k] = v
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else:
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out = json.dumps(v, indent=2, sort_keys=True)
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df_item[k] = out
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# Add heatmap viz
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html = getattr(d[item], 'heatmap').render(labels=show_atts)
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html = html.replace("\n", " ")
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heatmap_htmls.append(HTML_WRAPPER.format(html))
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df.append(df_item)
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df2 = df
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df = pd.DataFrame(df).set_index("_number")
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def hover(hover_color="#ffff99"):
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return dict(
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selector="tr:hover",
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props=[("background-color", "%s" % hover_color)],
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)
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styles = [
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hover(),
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dict(
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selector="th",
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props=[("font-size", "150%"), ("text-align", "center")],
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),
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dict(selector="caption", props=[("caption-side", "bottom")]),
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]
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# Table view. Use pands styling.
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style = df.style.set_properties(
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**{"text-align": "left", "white-space": "pre"}
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).set_table_styles([dict(selector="th", props=[("text-align", "left")])])
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style = style.set_table_styles(styles) # Setting the style appears to be broken for streamlit+pandas
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for i, heatmap_html in enumerate(heatmap_htmls):
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st.write(HTML_WRAPPER.format(heatmap_html), unsafe_allow_html=True)
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st.table(df.iloc[[i]])
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st.markdown(""" --- """)
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# Additional dataset installation and sidebar properties.
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md = """
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301 |
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### Code
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302 |
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303 |
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```python
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!pip install thermostat_datasets
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from thermostat import load
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dataset = load(
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'%s)
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```
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309 |
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""" % (
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(conf_option.name + "'") if conf_option else "",
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)
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st.sidebar.markdown(md)
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