text stringlengths 0 93.6k |
|---|
}, |
form_layout=AccordionFormLayout( |
sections=[ |
FormSection(name="General", fields=["name", "age", "mini_bio"], default_open=True), |
FormSection( |
name="HR", |
fields=["office", "joined", "location", "resume_file", "metadata"], |
default_open=True, |
), |
FormSection(name="Other", fields=["pets", "jobs"], default_open=True), |
], |
), |
), |
], |
pt="1rem", |
) |
), |
dmc.AppShellAside( |
dmc.ScrollArea( |
dmc.Text( |
id=ids.form_dependent_id("output", AIO_ID, FORM_ID), |
style={"whiteSpace": "pre-wrap"}, |
p="1rem 0.5rem", |
), |
), |
), |
], |
aside={"width": 350}, |
), |
) |
@callback( |
Output(ids.form_dependent_id("output", MATCH, MATCH), "children"), |
Output(ModelForm.ids.errors(MATCH, MATCH), "data"), |
Input(ModelForm.ids.main(MATCH, MATCH), "data"), |
State(ModelForm.ids.model_store(MATCH, MATCH), "data"), |
prevent_initial_call=True, |
) |
def display(form_data, model_name): |
"""Display form data.""" |
children = dmc.Stack( |
[ |
dmc.Text("Form data", mb="-0.5rem", fw=600), |
dmc.Code( |
json.dumps(form_data, indent=2), |
), |
] |
) |
errors = None |
try: |
model_cls = get_model_cls(model_name) |
item = model_cls.model_validate(form_data) |
children.children[1].children = item.model_dump_json(indent=2) |
except ValidationError as e: |
children.children.extend( |
[ |
dmc.Text("Validation errors", mb="-0.5rem", fw=500, c="red"), |
dmc.List( |
[ |
dmc.ListItem( |
[SEP.join([str(x) for x in error["loc"]]), f" : {error['msg']}, got {error['input']}"], |
) |
for error in e.errors() |
], |
size="sm", |
c="red", |
), |
] |
) |
errors = None |
errors = {SEP.join([str(x) for x in error["loc"]]): error["msg"] for error in e.errors()} |
return children, errors |
clientside_callback( |
"""(isLightMode) => isLightMode ? 'light' : 'dark'""", |
Output("mantine-provider", "forceColorScheme"), |
Input("scheme-switch", "checked"), |
prevent_initial_callback=True, |
) |
if __name__ == "__main__": |
app.run_server(debug=True) |
# <FILESEP> |
import argparse |
import copy |
import pickle |
import numpy as np |
import torch |
from agent.qvpo import QVPO |
from agent.replay_memory import ReplayMemory, DiffusionMemory |
from tensorboardX import SummaryWriter |
import gym |
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