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# -*- coding: utf-8 -*-
"""
Author: BigCat
Modifier: KittenCN
"""
import os
ball_name = [
("红球", "red"),
("蓝球", "blue")
]
data_file_name = "data.csv"
data_cq_file_name = "data_cq.csv"
predict_path = "predict/"
name_path = {
"ssq": {
"name": "双色球",
"path": "data/ssq/"
},
"dlt": {
"name": "大乐透",
"path": "data/dlt/"
},
"qxc": {
"name": "七星彩",
"path": "data/qxc/"
},
"pls": {
"name": "排列三",
"path": "data/pls/"
},
"kl8": {
"name": "快乐8",
"path": "data/kl8/"
},
}
model_path = os.getcwd() + "/model/"
model_args = {
"kl8": {
"model_args": {
"windows_size": 3,
"batch_size": 1,
"red_sequence_len": 20,
"sequence_len": 20,
"red_n_class": 80,
"red_epochs": 1,
"red_embedding_size": 20,
"red_hidden_size": 20,
"red_layer_size": 1,
"blue_sequence_len": 1,
"blue_n_class": 0,
"blue_epochs": 0,
"blue_embedding_size": 0,
"blue_hidden_size": 0,
"blue_layer_size": 0,
},
"train_args": {
"red_learning_rate": 0.001,
"red_beta1": 0.9,
"red_beta2": 0.999,
"red_epsilon": 1e-08,
"blue_learning_rate": 0.001,
"blue_beta1": 0.9,
"blue_beta2": 0.999,
"blue_epsilon": 1e-08
},
"path": {
"red": model_path + "/kl8/red_ball_model/",
"blue": model_path + "/kl8/blue_ball_model/"
},
"pathname": {
"name":"/kl8/"
},
"subpath": {
"red": "/red_ball_model/",
"blue": "/blue_ball_model/"
}
},
"pls": {
"model_args": {
"windows_size": 3,
"batch_size": 1,
"red_sequence_len": 3,
"sequence_len": 3,
"red_n_class": 10,
"red_epochs": 1,
"red_embedding_size": 10,
"red_hidden_size": 10,
"red_layer_size": 1,
"blue_sequence_len": 1,
"blue_n_class": 0,
"blue_epochs": 0,
"blue_embedding_size": 0,
"blue_hidden_size": 0,
"blue_layer_size": 0,
},
"train_args": {
"red_learning_rate": 0.001,
"red_beta1": 0.9,
"red_beta2": 0.999,
"red_epsilon": 1e-08,
"blue_learning_rate": 0.001,
"blue_beta1": 0.9,
"blue_beta2": 0.999,
"blue_epsilon": 1e-08
},
"path": {
"red": model_path + "/pls/red_ball_model/",
"blue": model_path + "/pls/blue_ball_model/"
},
"pathname": {
"name":"/pls/"
},
"subpath": {
"red": "/red_ball_model/",
"blue": "/blue_ball_model/"
}
},
"ssq": {
"model_args": {
"windows_size": 3,
"batch_size": 1,
"red_sequence_len": 6,
"sequence_len": 6,
"red_n_class": 33,
"red_epochs": 1,
"red_embedding_size": 32,
"red_hidden_size": 32,
"red_layer_size": 1,
"blue_sequence_len": 1,
"blue_n_class": 16,
"blue_epochs": 1,
"blue_embedding_size": 32,
"blue_hidden_size": 32,
"blue_layer_size": 1,
},
"train_args": {
"red_learning_rate": 0.001,
"red_beta1": 0.9,
"red_beta2": 0.999,
"red_epsilon": 1e-08,
"blue_learning_rate": 0.001,
"blue_beta1": 0.9,
"blue_beta2": 0.999,
"blue_epsilon": 1e-08
},
"path": {
"red": model_path + "/ssq/red_ball_model/",
"blue": model_path + "/ssq/blue_ball_model/"
},
"pathname": {
"name":"/ssq/"
},
"subpath": {
"red": "/red_ball_model/",
"blue": "/blue_ball_model/"
}
},
"dlt": {
"model_args": {
"windows_size": 3,
"batch_size": 1,
"red_sequence_len": 5,
"red_n_class": 35,
"red_epochs": 1,
"red_embedding_size": 32,
"red_hidden_size": 32,
"red_layer_size": 1,
"blue_sequence_len": 2,
"blue_n_class": 12,
"blue_epochs": 1,
"blue_embedding_size": 32,
"blue_hidden_size": 32,
"blue_layer_size": 1
},
"train_args": {
"red_learning_rate": 0.001,
"red_beta1": 0.9,
"red_beta2": 0.999,
"red_epsilon": 1e-08,
"blue_learning_rate": 0.001,
"blue_beta1": 0.9,
"blue_beta2": 0.999,
"blue_epsilon": 1e-08
},
"path": {
"red": model_path + "/dlt/red_ball_model/",
"blue": model_path + "/dlt/blue_ball_model/"
},
"pathname": {
"name":"/dlt/"
},
"subpath": {
"red": "/red_ball_model/",
"blue": "/blue_ball_model/"
}
}
}
# 模型名
pred_key_name = "key_name.json"
red_ball_model_name = "red_ball_model"
blue_ball_model_name = "blue_ball_model"
extension = "ckpt"
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