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optuna-dashboard/optuna_dashboard/streamlit/_streamlit_helper.py
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2023-07-07 17:12:45 +09:00

179 lines
6.1 KiB
Python

from __future__ import annotations
from typing import TYPE_CHECKING
import optuna
from optuna.trial import FrozenTrial
import streamlit as st
from .._form_widget import get_form_widgets_json
from .._note import get_note_from_system_attrs
if TYPE_CHECKING:
from typing import Callable
from typing import Optional
from typing import Sequence
from typing import Union
from .._form_widget import ChoiceWidgetJSON
from .._form_widget import SliderWidgetJSON
from .._form_widget import TextInputWidgetJSON
from .._form_widget import UserAttrRefJSON
def render_trial_note(study: optuna.Study, trial: FrozenTrial) -> None:
"""Write a trial note to UI with streamlit as a markdown format.
Args:
study: The optuna study object.
trial: The optuna trial object to get note.
"""
note = get_note_from_system_attrs(study.system_attrs, trial._trial_id)
st.markdown(note["body"], unsafe_allow_html=True)
def _format_choice(choice: float, widget: ChoiceWidgetJSON) -> str:
return widget["choices"][widget["values"].index(choice)]
def _format_description(description: Optional[str]) -> str:
return "" if description is None else description
def _render_widgets(
widgets: Sequence[
Union[ChoiceWidgetJSON, SliderWidgetJSON, TextInputWidgetJSON, UserAttrRefJSON]
],
trial: FrozenTrial,
) -> tuple[bool, list[Optional[Union[str, float]]]]:
values: list[Optional[Union[str, float]]] = []
with st.form("user_input", clear_on_submit=False):
for i, widget in enumerate(widgets):
if widget["type"] == "choice":
value = st.radio(
_format_description(widget["description"]),
widget["values"],
format_func=lambda choice, widget=widget: _format_choice( # type: ignore
choice, widget
),
horizontal=True,
key=f"radio_{i}",
)
elif widget["type"] == "slider":
# NOTE: It is difficult to reflect "labels".
value = st.slider(
_format_description(widget["description"]),
min_value=widget["min"],
max_value=widget["max"],
step=widget["step"],
key=f"slider_{i}",
)
elif widget["type"] == "text":
# NOTE: Current implementation ignores "optional".
value = st.text_input(
_format_description(widget["description"]), key=f"text_{i}"
) # type: ignore
elif widget["type"] == "user_attr":
value = trial.user_attrs[widget["key"]]
else:
raise ValueError(
"Widget type should be 'choice', 'slider', 'text', or 'user_attr'."
)
values.append(value)
submitted = st.form_submit_button("Submit")
return submitted, values
def render_user_attr_form_widgets(
study: optuna.Study,
trial: FrozenTrial,
on_success_callback: Optional[Callable[[], None]] = None,
) -> None:
"""Render user input widgets to UI with streamlit.
Submitted values to the forms are registered as each trial's user_attrs.
Args:
study: The optuna study object to get widget specification.
trial: The optuna trial object to save user feedbacks.
on_success_callback: The callback function which will be executed
when feedback submission is succeeded.
Raises:
ValueError: If No form widgets registered.
ValueError: If 'output_type' of form widgets is not 'user_attr'.
"""
form_widgets_dict = get_form_widgets_json(study.system_attrs)
if form_widgets_dict is None:
raise ValueError("No form widgets registered.")
if form_widgets_dict["output_type"] != "user_attr":
raise ValueError("'output_type' should be 'user_attr'.")
widgets = form_widgets_dict["widgets"]
submitted, values = _render_widgets(widgets, trial)
if submitted:
for widget, value in zip(widgets, values):
if "user_attr_key" in widget.keys():
study._storage.set_trial_user_attr(
trial._trial_id, key=widget["user_attr_key"], value=value # type: ignore
)
if on_success_callback is None:
st.success("Submitted!")
else:
on_success_callback()
def render_objective_form_widgets(
study: optuna.Study,
trial: FrozenTrial,
on_success_callback: Optional[Callable[[], None]] = None,
) -> None:
"""Render user input widgets to UI with streamlit.
Submitted values to the forms are telled to optuna trial object.
All submitted values should be float.
Multiple widgets correspond to multi-objective optimization.
Args:
study: The optuna study object to get widget specification.
trial: The optuna trial object to tell user feedbacks.
on_success_callback: The callback function which will be executed
when feedback submission is succeeded.
Raises:
ValueError: If No form widgets registered.
ValueError: If 'output_type' of form widgets is not 'objective'.
ValueError: If any submitted values cannot be converted to float.
"""
form_widgets_dict = get_form_widgets_json(study.system_attrs)
if form_widgets_dict is None:
raise ValueError("No form widgets registered.")
if form_widgets_dict["output_type"] != "objective":
raise ValueError("'output_type' should be 'objective'.")
submitted, values = _render_widgets(form_widgets_dict["widgets"], trial)
if submitted:
values_float = []
try:
for value in values:
values_float.append(float(value)) # type: ignore
study.tell(trial.number, values_float)
if on_success_callback is None:
st.success("Submitted!")
else:
on_success_callback()
except ValueError:
st.error("Please enter float values.")