Delete app.py

app.py

@@ -1,68 +0,0 @@
-# A3C++ a modified version of Asynchronous Advantage actor critic algorithm
-# -----------------------------------
-#
-# A3C paper: https://arxiv.org/abs/1602.01783
-#
-# The A3C implementation is available at:
-# https://jaromiru.com/2017/02/16/lets-make-an-a3c-theory/
-# by: Jaromir Janisch, 2017
-
-# Two variations are implemented: A memory replay and a deterministic search following argmax(pi) instead of pi as a probability distribution
-# Every action selection is made following the action with the highest probability pi
-
-# Author: Taha Nakabi
-
-# Args: 'train' for training the model anything else will skip the training and try to use already saved models
-
-# import tensorflow as tf
-# import numpy as np
-# import gym, time, random, threading
-# from keras.callbacks import TensorBoard
-# from keras.models import *
-# from keras.layers import *
-# from keras import backend as K
-
-# from tcl_env_dqn_1 import *
-
-# import os
-import gradio as gr
-from gradio.components import *
-
-
-
-def main(use_default, file):
-    # if __name__ == '__main__':
-
-
-    # subprocess.run(['python', './A3C_plusplus.py'])
-
-
-    base = r'./RESULT/'
-    img_path = []
-    for i in range(1, 11):
-        temp_path = base + 'Day' + str(i) + '.png'
-        img_path.append(temp_path)
-    # else:
-    # 根据上传的文件执行相应的逻辑
-    # 请根据您的实际需求自行编写代码
-
-    return [img for img in img_path]
-
-# 创建一个复选框来表示是否选择默认文件
-default_checkbox = gr.inputs.Checkbox(label="使用默认文件", default=False)
-
-inputs = [
-    default_checkbox,
-    File(label="上传文件", optional=True)
-]
-outputs = [
-    Image(label="DAY" + str(day + 1), type='filepath') for
- day in range(10)
-]
-
-iface = gr.Interface(fn=main, inputs=inputs, outputs=outputs)
-
-iface.launch()
-
-
-