1-list数据类型
- 内置方法查看长度
- len（list）
2.array数据类型
查看形状
3.tuple
取出元组
t = (1, 2, 3, 4, 5)
# 取出第一个元素
2first_element = t[0]
3print(first_element) # 输出：1
4
5# 取出第三个元素
6third_element = t[2]
7print(third_element) # 输出：3
self.train_dataset[77]
len( self.train_dataset)
100
self.train_dataset[77]
['p316', array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0.,... 0., 1., 0., 0., 0.],
dtype=float32), (array([[ 0.2622058 , 0.2520623 , 0.22725889, ..., 0.01219749,
0.01633989,... 0.07434033, 0.07480213]], dtype=float32), array([-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000...00000e+10, -1.0000000e+10], dtype=float32)), None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, ...]
special variables:
function variables:
000: 'p316'
001: array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.],
dtype=float32)
002: (array([[ 0.2622058 , 0.2520623 , 0.22725889, ..., 0.01219749,
0.01633989,... 0.07434033, 0.07480213]], dtype=float32), array([-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000...00000e+10, -1.0000000e+10], dtype=float32))
003: None
004: None
005: None
006: None
007: None
008: None
009: None
010: None
011: None
012: None
013: None
014: None
015: None
016: None
017: None
018: None
019: None
020: None
021: None
022: None
023: None
024: None
025: None
026: None
027: None
028: None
029: None
030: None
031: None
032: None
033: None
034: None
035: None
036: None
037: None
038: None
039: None
040: None
041: None
042: None
043: None
044: None
045: None
046: None
047: None
048: None
049: None
050: None
051: None
052: None
053: None
054: None
055: None
056: None
057: None
058: None
059: None
060: None
061: None
062: None
063: None
064: None
065: None
066: None
067: None
068: None
069: None
070: None
071: None
072: None
073: None
074: None
075: None
076: None
077: None
078: None
079: None
080: None
081: None
082: None
083: None
084: None
085: None
086: None
087: None
088: None
089: None
090: None
091: None
092: None
093: None
094: None
095: None
096: None
097: None
098: None
099: None
more: [100:423]
len(): 423
self.train_dataset[0][2]
(array([[ 0.3585394 , 0.3018739 , 0.31105113, ..., 0.11300398,
0.13763978,... 0.19390605, 0.20955321]], dtype=float32), array([-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000...10,
-1.0000000e+10], dtype=float32))
special variables:
function variables:
0: array([[ 0.3585394 , 0.3018739 , 0.31105113, ..., 0.11300398,
0.13763978, 0.1481771 ],
[ 0.39186838, 0.28555837, 0.26440546, ..., 0.05680866,
0.08005004, 0.08875965],
[ 0.4017174 , 0.26269558, 0.2291187 , ..., 0.03097245,
-0.01500634, -0.05946859],
...,
[ 0.31265986, 0.26113972, 0.24987312, ..., 0.00301073,
-0.00385549, -0.05521088],
[ 0.393526 , 0.3625572 , 0.2850872 , ..., 0.1024707 ,
0.10312076, 0.11706395],
[ 0.4812853 , 0.4445946 , 0.38248026, ..., 0.1924281 ,
0.19390605, 0.20955321]], dtype=float32)
1: array([-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, 6.4911819e-01,
6.2345779e-01, 6.4090478e-01, 6.4279598e-01, 6.4552206e-01,
6.4994138e-01, 6.5974551e-01, 6.6462046e-01, 6.7087328e-01,
6.6634196e-01, 6.6224831e-01, 6.6087329e-01, 6.5927708e-01,
6.5056252e-01, 6.3305575e-01, 5.4912585e-01, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, 6.3081306e-01,
5.2999961e-01, 5.0226504e-01, 4.8222768e-01, 4.5869541e-01,
4.3690044e-01, 4.3986464e-01, 4.4301969e-01, 4.4689795e-01,
4.3496856e-01, 4.2702240e-01, 4.1260844e-01, 3.4266099e-01,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, 6.1800110e-01,
4.4760248e-01, 4.0614852e-01, 3.7573645e-01, 3.6150464e-01,
3.5052958e-01, 3.3238921e-01, 3.3283028e-01, 3.4399042e-01,
3.7932014e-01, 3.6280128e-01, 3.4794918e-01, 3.8073543e-01,
3.9630288e-01, 3.8179722e-01, 3.6594597e-01, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10, -1.0000000e+10, -1.0000000e+10, -1.0000000e+10,
-1.0000000e+10], dtype=float32)
len(): 2
导入包的路径问题
import sys
sys.path.append('/home/zjx/CosyVoice-main')
在Python中以绝对路径或者相对路径导入文件的方法_使用绝对路径导包-CSDN博客