-
Notifications
You must be signed in to change notification settings - Fork 1
/
config.py
115 lines (85 loc) · 2.74 KB
/
config.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
# -*- coding: utf-8 -*-
# @Author: Aastha Gupta
# @Date: 2017-04-19 08:23:18
# @Last Modified by: Aastha Gupta
# @Last Modified time: 2017-05-19 09:40:21
import pickle
import os
# Artists list and File name
ARTISTS = ["rihanna","ed sheeran","beatles","coldplay","elvis presley"]
FILE_NAME = "mashup"
BASE_URL = "http://www.metrolyrics.com/"
RESOURCE_PATH = "resources/"
PATH = os.path.join(RESOURCE_PATH,FILE_NAME)
# make directory for artist if doesn't exist
if not os.path.exists(PATH):
os.makedirs(PATH)
LYRICS_FILE = os.path.join(PATH,"lyrics.txt")
DATA_FILE = os.path.join(PATH,"dataset.txt")
MODEL_FILE = os.path.join(PATH,"model.h5")
OUTPUT_FILE = os.path.join(PATH,"fun.txt")
ANALYSIS_FILE = os.path.join(PATH,"analysis.txt")
# directory of checkpoints
CHKPT_PATH = os.path.join(PATH,"checkpoints/")
if not os.path.exists(CHKPT_PATH):
os.makedirs(CHKPT_PATH)
# get this data from file if exists
pkl_filename = os.path.join(PATH,"config_data.pkl")
if os.path.exists(pkl_filename):
with open(pkl_filename,"rb") as f:
VOCAB_SIZE, DATA_SIZE, NUM_SEQ = pickle.load(f)
else:
VOCAB_SIZE = 0
DATA_SIZE = 0
NUM_SEQ = 0 # number of sequences = DATA_SIZE/SEQ_LENGTH
SEED = 7
# number of layers in the network
LAYER_NUM = 3
# number of units of LSTM
HIDDEN_DIM = 256
# batch size
BATCH_SIZE = 150
SEQ_LENGTH = 26
# Initial learning rate
LR = 0.0001
# number of epochs for training
NUM_EPOCHS = 1000
# length of characters to generate
LEN_TO_GEN = 700
# length of characters to generate (for analysis.py)
LEN_TO_GEN_2 = 250
#############################################################
#############################################################
# #
# FLOYD CONFIGURATIONS #
# #
#############################################################
#############################################################
FLOYD = False
# to train network on floyd
if FLOYD:
DATA_FILE = "dataset.txt"
LYRICS_FILE = "lyrics.txt"
RESOURCE_PATH = "/output/"
PATH = os.path.join(RESOURCE_PATH,FILE_NAME)
# make directory for artist if doesn't exist
if not os.path.exists(PATH):
os.makedirs(PATH)
MODEL_FILE = os.path.join(PATH,"model.h5")
OUTPUT_FILE = os.path.join(PATH,"fun.txt")
ANALYSIS_FILE = os.path.join(PATH,"analysis.txt")
# directory of checkpoints
CHKPT_PATH = os.path.join(PATH,"checkpoints/")
if not os.path.exists(CHKPT_PATH):
os.makedirs(CHKPT_PATH)
# get this data from file if exists
pkl_filename = os.path.join(PATH,"config_data.pkl")
if os.path.exists(pkl_filename):
with open(pkl_filename,"rb") as f:
VOCAB_SIZE, DATA_SIZE, NUM_SEQ = pickle.load(f)
else:
VOCAB_SIZE = 0
DATA_SIZE = 0
NUM_SEQ = 0 # number of sequences = DATA_SIZE/SEQ_LENGTH
BATCH_SIZE = 100
NUM_EPOCHS = 50