"""Prep gradio API."""
# pylint: diable=invalid-name
from typing import List, Optional, Union

import os
from pathlib import Path
import multiprocessing as mp
import numpy as np
import psutil
import ray

import gradio as gr
# import joblib
import more_itertools as mit
import numpy as np
import psutil
import ray
from about_time import about_time
from logzero import logger

from radio_embed import radio_embed

num_cpus_m = mp.cpu_count()
num_cpus = psutil.cpu_count(logical=False)

filename = "fangfang-en.txt"
lines = Path(filename).read_text("utf8").splitlines()
lst = [_.strip() for _ in lines if _.strip()]

args_m = ["\n".join(elm) for elm in mit.divide(num_cpus_m, lst)]
args = ["\n".join(elm) for elm in mit.divide(num_cpus, lst)]


os.environ["TOKENIZERS_PARALLELISM"] = "false"

if not ray.is_initialized():
    ray.init(num_cpus=num_cpus)


@ray.remote
def ray_embed(text):
    """Embed text to d-512."""
    return radio_embed(text)


def test_pool(func, args_, num_procs=None):
    """Test mp.Pool."""
    if num_procs is None:
        num_procs = num_cpus_m
    elif num_procs < 1:
        num_procs = num_cpus_m
    with mp.Pool(num_procs) as pool:
        ret = pool.map(func, args_)
    return ret

def fn(type_, num_cpus):
    if type_ in ["mp_pool"]:
        with about_time() as dur:
            _ = test_pool(radio_embed, args, num_procs=num_cpus)

        return dur.duration_human



with gr.Blocks() as blocks:
    with gr.Row():
        type_ = gr.Radio(
            label="type",
            choices=[
                "mp_pool",
                "joblib(loky)",
                "joblib(mp)",
                "ray",
            ],
            value="mp_pool",
            interactive=False,
        )
        num_cpus_ = gr.Slider(
            label="num_procs",
            value=num_cpus_m,
            minimum=1,
            maximum=2 * num_cpus_m,
            step=1,
        )
        btn = gr.Button("Go")
        out = gr.Textbox(
            label="time elapsed",
            value="",
        )
    btn.click(
        fn=fn,
        inputs=[type_, num_cpus_],
        outputs=out,
        api_name="time",
    )
    # gr.Markdown(f"{description}")

blocks.launch(enable_queue=True)