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import gradio as gr
from widgets.widget_base import Widget
from data_measurements.dataset_statistics import DatasetStatisticsCacheClass as dmt_cls
import utils
logs = utils.prepare_logging(__file__)
## possibyl looking for update()--> return output
class TextLengths(Widget):
def __init__(self):
self.text_length_distribution_plot = gr.Image(render=False)
self.text_length_explainer = gr.Markdown(render=False)
self.text_length_drop_down = gr.Dropdown(render=False)
self.text_length_df = gr.DataFrame(render=False)
def update_text_length_df(self, length, dstats):
return dstats.length_obj.lengths_df[
dstats.length_obj.lengths_df["length"] == length
].set_index("length")
def render(self):
with gr.TabItem("Text Lengths"):
gr.Markdown(
"Use this widget to identify outliers, particularly suspiciously long outliers."
)
gr.Markdown(
"Below, you can see how the lengths of the text instances in your "
"dataset are distributed."
)
gr.Markdown(
"Any unexpected peaks or valleys in the distribution may help to "
"identify instances you want to remove or augment."
)
gr.Markdown(
"### Here is the count of different text lengths in " "your dataset:"
)
# When matplotlib first creates this, it's a Figure.
# Once it's saved, then read back in,
# it's an ndarray that must be displayed using st.image
# (I know, lame).
self.text_length_distribution_plot.render()
self.text_length_explainer.render()
self.text_length_drop_down.render()
self.text_length_df.render()
def update(self, dstats: dmt_cls):
explainer_text = (
"The average length of text instances is **"
+ str(round(dstats.length_obj.avg_length, 2))
+ " words**, with a standard deviation of **"
+ str(round(dstats.length_obj.std_length, 2))
+ "**."
)
# TODO: Add text on choosing the length you want to the dropdown.
output = {
self.text_length_distribution_plot: dstats.length_obj.fig_lengths,
self.text_length_explainer: explainer_text,
}
if dstats.length_obj.lengths_df is not None:
import numpy as np
choices = np.sort(dstats.length_obj.lengths_df["length"].unique())[
::-1
].tolist()
output[self.text_length_drop_down] = gr.Dropdown.update(
choices=choices, value=choices[0]
)
output[self.text_length_df] = self.update_text_length_df(choices[0], dstats)
else:
output[self.text_length_df] = gr.update(visible=False)
output[self.text_length_drop_down] = gr.update(visible=False)
return output
@property
def output_components(self):
return [
self.text_length_distribution_plot,
self.text_length_explainer,
self.text_length_drop_down,
self.text_length_df,
]
def add_events(self, state: gr.State):
self.text_length_drop_down.change(
self.update_text_length_df,
inputs=[self.text_length_drop_down, state],
outputs=[self.text_length_df],
)
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