Question

我有多个使用joblib导入的sklearn模型。他们可以完美地独立工作。我现在正在尝试围绕它创建一个Dash应用，以便非编码器可以传递输入并获取4个预测值。

这是我的代码：

import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import numpy as np
import pandas as pd
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets = external_stylesheets)
def label_input(ls, tag = 'sample'):
    ls.append(html.Label(tag))
    ls.append(dcc.Input(value = 0, type = 'number', id = tag))
inputs_list = []
features_list = *list of 25 features*
for i in features_list:
    label_input(inputs_list, i)
inputs_list.append(
    html.Table([
        html.Tr([html.Td([*Output variable name*]), html.Td(id = *output variable name in lower case)]),
    *repeated 3 more times
    ])
)
app.layout = html.Div(inputs_list)
import joblib
model_1 = joblib.load(*filename*)
*repeated 3 more times*
def output_generator(ls, tag, val):
    ls.append(Output(tag, val))

def input_generator(ls, tag, val):
    ls.append(Input(tag, val))
input_list = []
for i in features_list:
    input_generator(input_list, i, 'value')

targets = *list of 4 outputs*
output_list = []
for i in targets:
    output_generator(output_list, i.lower(), 'children')
@app.callback(output_list, input_list)
def predictor(a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y):
    df = pd.DataFrame(dict(zip(features_list, [a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y])),
                      index = [0])
    return model1.predict(df), *repeated 3 times*
if __name__ == '__main__':
    app.run_server(debug = False)

一切正常，直到我尝试在任何文本框中键入任何内容。我每次都会收到以下错误：靠后的并行循环不能嵌套在线程下，设置n_jobs = 1

我知道很多，但是我被困住了。任何帮助将不胜感激。

使用Dash部署sklearn模型会导致并行循环不能嵌套在线程警告下方

0 个答案: