Pytorch之parameters的使用
阿新 • • 發佈：2020-01-08
1.預構建網路
class Net(nn.Module):
def __init__(self):
super(Net,self).__init__()
# 1 input image channel,6 output channels,5*5 square convolution
# kernel
self.conv1 = nn.Conv2d(1,6,5)
self.conv2 = nn.Conv2d(6,16,5)
# an affine operation: y = Wx + b
self.fc1 = nn.Linear(16 * 5 * 5,120)
self.fc2 = nn.Linear(120,84)
self.fc3 = nn.Linear(84,10)
def forward(self,x):
# max pooling over a (2,2) window
x = F.max_pool2d(F.relu(self.conv1(x)),(2,2))
# If size is a square you can only specify a single number
x = F.max_pool2d(F.relu(self.conv2(x)),2)
x = x.view(-1,self.num_flat_features(x))
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
def num_flat_features(self,x):
size = x.size()[1:] # all dimensions except the batch dimension
num_features = 1
for s in size:
num_features *= s
return num_features
net = Net()
網路結構
Net( (conv1): Conv2d(1,kernel_size=(5,5),stride=(1,1)) (conv2): Conv2d(6,1)) (fc1): Linear(in_features=400,out_features=120,bias=True) (fc2): Linear(in_features=120,out_features=84,bias=True) (fc3): Linear(in_features=84,out_features=10,bias=True) )
2.net.parameters()
構建好神經網路後，網路的引數都儲存在parameters()函式當中
print(net.parameters())
輸出 <generator object Module.parameters at 0x0000000003161200>
para = list(net.parameters()) print(para) #len返回列表項個數 print(len(para))
輸出
[Parameter containing: tensor([[[[-0.0596,0.1908,0.1831,0.0542,-0.0283],[-0.0542,-0.1680,0.1566,0.1036,-0.1756],[-0.1437,0.0083,0.0871,0.1549,0.1556],[ 0.1360,0.0171,0.1034,-0.1548,-0.1343],[-0.0978,-0.1803,-0.0701,-0.0377,0.0290]]],[[[-0.1020,0.0862,-0.1227,-0.1742,0.1510],[ 0.0728,0.1725,0.0352,0.1579,0.0367],[ 0.0862,-0.0995,0.1276,-0.1895,-0.1346],[ 0.1938,0.1387,-0.1983,-0.1015,-0.0740],[-0.0248,-0.0546,0.0849,0.1510,-0.0066]]],[[[ 0.1333,0.0300,0.0969,-0.0295,0.0879],[ 0.1216,-0.0864,0.0259,0.0157,-0.1330],[-0.1873,0.1309,0.1947,0.1886,0.1944],[-0.0647,0.0957,0.1592,0.1894,0.1862],[ 0.0896,0.1287,-0.0650,0.0684,0.1182]]],[[[-0.0816,0.0968,0.1259,-0.1124,-0.0864],[-0.0450,0.0737,0.0483,0.1180,-0.0933],[-0.0925,-0.0549,0.1191,0.0165,0.1369],[-0.1771,-0.1937,0.1542,0.1105,0.1572],[ 0.1163,-0.1577,0.1426,0.0431,-0.0362]]],[[[-0.0675,-0.1039,0.0762,-0.1798,0.0071],[-0.1794,0.1942,0.0540,0.1887,0.1413],[ 0.1366,0.0682,0.1230,0.0184,-0.0980],[-0.1613,0.1225,-0.0734,0.1938,0.1919],[ 0.1745,-0.1550,0.0663,0.0044,-0.0538]]],[[[-0.0926,0.1146,0.1008,0.1644,0.1046],[-0.1230,0.0080,0.0198,-0.1216,-0.1942],[ 0.0327,0.0205,-0.1714,0.0955],[ 0.0358,-0.1350,-0.1365,-0.1600],[ 0.0368,-0.1323,-0.0127,0.0917,-0.1892]]]],requires_grad=True),Parameter containing: tensor([-0.0229,-0.1387,-0.1571,-0.0381,-0.1559,0.0946],Parameter containing: tensor([[[[-0.0497,-0.0356,-0.0272,-0.0519,0.0451],[-0.0247,0.0228,0.0705,-0.0341,-0.0454],[ 0.0129,-0.0385,-0.0613,0.0497],[-0.0394,0.0218,-0.0056,0.0204,-0.0668],[ 0.0469,0.0649,-0.0470,0.0138,-0.0686]],[[ 0.0647,0.0554,-0.0220,-0.0145],[ 0.0500,-0.0026,0.0545,0.0415,0.0020],[-0.0802,0.0742,-0.0291,0.0679,-0.0657],[ 0.0309,0.0729,-0.0158,-0.0495,-0.0220],[-0.0433,0.0440,-0.0485,0.0478,0.0618]],[[ 0.0523,-0.0072,-0.0786,0.0569,0.0334],[-0.0254,-0.0043,-0.0113,0.0755,-0.0590],[ 0.0113,-0.0170,0.0318,-0.0764,-0.0210],[-0.0203,-0.0273,0.0634,0.0380,0.0014],[-0.0112,0.0555,-0.0129,-0.0395,0.0624]],[[ 0.0387,0.0189,-0.0007,-0.0604,0.0114],[ 0.0481,0.0551,0.0182,0.0474,0.0390],[ 0.0152,-0.0106,-0.0630,-0.0645],[ 0.0092,-0.0616,0.0571,0.0562],[ 0.0418,-0.0372,0.0269,0.0109,-0.0758]],[[-0.0751,-0.0610,-0.0331,-0.0193],[ 0.0577,0.0430,-0.0201,-0.0017,-0.0408],[-0.0590,-0.0148,0.0790,0.0575,-0.0786],[ 0.0168,0.0335,0.0170,-0.0792,0.0344],[-0.0738,0.0193,-0.0732,-0.0666,-0.0734]],[[ 0.0154,0.0712,-0.0429,0.0573],[-0.0423,0.0424,-0.0488,0.0317,0.0808],[ 0.0605,0.0324,-0.0020,-0.0538,0.0664],[ 0.0243,-0.0452,0.0070,-0.0287,-0.0476],[ 0.0087,0.0561,-0.0076,-0.0391,0.0795]]],[[[ 0.0773,0.0748,-0.0133,0.0651,0.0659],[ 0.0254,0.0222,0.0017,-0.0722,0.0667],[ 0.0357,-0.0677,0.0085,-0.0005,-0.0313],[ 0.0672,-0.0359,-0.0243,-0.0811,-0.0726],[ 0.0011,0.0226,0.0278,-0.0615,-0.0410]],[[ 0.0202,0.0519,0.0527,-0.0086,-0.0683],[ 0.0694,0.0434,0.0746,0.0754,0.0073],[ 0.0036,-0.0692,-0.0250,-0.0470],[-0.0669,0.0609,0.0189],[-0.0564,0.0370,0.0464,-0.0530,0.0487]],[[ 0.0068,0.0722,0.0629,-0.0214,0.0673],[-0.0384,0.0799,-0.0350,0.0816,0.0586],[-0.0111,0.0696,0.0145,-0.0397,-0.0784],[-0.0120,0.0021,-0.0494,-0.0344],[-0.0335,0.0502,-0.0490,0.0135]],[[-0.0365,0.0733,0.0610,0.0028,0.0292],[ 0.0552,-0.0674,0.0176,-0.0131,0.0688],[ 0.0147,-0.0432,0.0473,-0.0231,-0.0314],[-0.0194,0.0508,-0.0475,0.0599,0.0286],[ 0.0055,0.0287,-0.0543,0.0778]],[[-0.0241,-0.0322,0.0704,-0.0758,-0.0562],[-0.0675,-0.0265,-0.0444,-0.0370,0.0581],[-0.0577,0.0462,0.0146,-0.0317],[ 0.0047,0.0666,-0.0365,0.0749,0.0677],[ 0.0557,0.0098,0.0451,0.0306,-0.0628]],[[ 0.0529,0.0167,0.0501,0.0505],[-0.0006,-0.0128,0.0794,-0.0794],[ 0.0016,-0.0504,-0.0252,0.0266,0.0635],[ 0.0305,-0.0807,-0.0236,-0.0810,-0.0010],-0.0285,-0.0559,0.0560,0.0796]]],[[[-0.0504,0.0504,-0.0440,0.0425],[ 0.0517,-0.0268,-0.0517,0.0646,0.0693],[ 0.0566,0.0194,0.0426,-0.0787,0.0163],[-0.0661,-0.0457,0.0691,-0.0058,-0.0073],[ 0.0794,0.0645,0.0367,-0.0625,-0.0731]],[[ 0.0190,0.0393,-0.0073,0.0478],[ 0.0405,0.0038,-0.0349,-0.0022,0.0202],[ 0.0346,-0.0622,-0.0151,0.0220],[ 0.0002,-0.0663,0.0730,-0.0462,-0.0182],[ 0.0311,-0.0079,0.0720,0.0517,-0.0601]],[[-0.0039,-0.0102,-0.0599,-0.0467],[-0.0495,0.0484,0.0497,0.0090],[-0.0260,0.0256,0.0476,-0.0585,0.0411],[-0.0505,-0.0447,-0.0002,-0.0121,-0.0170],[ 0.0400,0.0457,0.0709,0.0195,0.0762]],[[ 0.0732,-0.0100,0.0115,-0.0046,-0.0133],[ 0.0333,-0.0065,0.0057,0.0370],[ 0.0328,-0.0513,0.0648,0.0588,0.0230],[ 0.0154,0.0261,0.0579,0.0118,0.0050],[ 0.0089,0.0468,-0.0763,-0.0314,0.0676]],[[ 0.0428,-0.0646,-0.0339,0.0185,-0.0042],[-0.0480,0.0639,-0.0366,-0.0537,0.0241],[-0.0572,0.0309,-0.0761,0.0227,-0.0385],[-0.0546,-0.0338,0.0277,-0.0081],[ 0.0690,-0.0083,0.0295,0.0088,0.0360]],[[ 0.0514,0.0622,-0.0556,-0.0048,-0.0279],[ 0.0112,-0.0413,-0.0483,0.0166,0.0690],0.0410,-0.0335,-0.0458,-0.0055],[ 0.0229,0.0289,0.0695,0.0574,0.0075],[ 0.0651,-0.0337,-0.0130,0.0272]]],...,[[[-0.0538,0.0321,0.0302,-0.0062],[ 0.0050,-0.0461,0.0084,-0.0448,-0.0604],[-0.0457,0.0455,-0.0773,-0.0437,0.0446],[ 0.0691,0.0390,-0.0040,0.0035,[ 0.0545,-0.0067,0.0314,-0.0448]],[[ 0.0029,-0.0675,-0.0254,-0.0168,-0.0563],[ 0.0163,-0.0621,-0.0561,-0.0306],[-0.0021,0.0389,0.0778,[-0.0578,0.0123,0.0049,-0.0728,[ 0.0722,0.0388,0.0177,0.0526,-0.0291]],[[ 0.0369,-0.0091],[ 0.0066,0.0114,0.0243,-0.0455],[ 0.0494,0.0495,-0.0257,-0.0024],[-0.0476,-0.0552,0.0029,-0.0813,0.0698],[-0.0704,-0.0590,-0.0641,0.0284,0.0578]],[[ 0.0180,-0.0090,-0.0081,0.0570],[-0.0529,0.0045,-0.0580,-0.0192],[-0.0289,0.0107,0.0180,[-0.0162,0.0607,0.0154,0.0450,0.0694],[ 0.0324,0.0418,-0.0199,-0.0357,0.0104]],[[ 0.0525,-0.0401,0.0803,-0.0453,-0.0534],[ 0.0628,0.0120,0.0147,0.0294,-0.0351],[ 0.0773,-0.0587,-0.0713,0.0125,-0.0125],[-0.0288,-0.0623,0.0547,-0.0603],[ 0.0105,-0.0003,0.0386]],[[ 0.0721,-0.0047,0.0238,0.0489,0.0183],[-0.0127,-0.0588,0.0641,0.0460],-0.0753,0.0186,0.0156],[ 0.0248,-0.0801,-0.0794,0.0811,0.0644],[-0.0415,0.0127,-0.0120,-0.0724,-0.0800]]],[[[-0.0781,0.0279,0.0056,-0.0164,-0.0423],[ 0.0446,0.0030,0.0590,0.0276,-0.0720],[ 0.0647,-0.0414,-0.0306,-0.0477,0.0041],0.0124,-0.0592,0.0164],[ 0.0789,-0.0673,-0.0583,0.0493,0.0306]],[[-0.0105,0.0707,-0.0790,-0.0334,0.0620],[ 0.0095,0.0763,0.0055,-0.0716,-0.0078],[ 0.0141,-0.0645,-0.0282,-0.0557],[ 0.0489,0.0073,0.0203,0.0568,-0.0352],[-0.0299,0.0681,-0.0300,0.0178,-0.0101]],[[ 0.0401,-0.0572,0.0219,0.0427,0.0276],[-0.0683,0.0192,0.0689,0.0217,-0.0365],[-0.0140,-0.0361,-0.0562,0.0528,0.0029],[ 0.0213,0.0525,-0.0804,0.0599],[ 0.0770,-0.0657,0.0655,0.0741,0.0462]],[[ 0.0479,-0.0050,0.0530,-0.0746],[-0.0671,0.0635,0.0360,-0.0642,-0.0573],[ 0.0176,-0.0783,-0.0781,-0.0027,0.0405],[ 0.0057,-0.0685,0.0673,0.0697,-0.0792],[-0.0449,-0.0756,-0.0524,0.0378]],[[ 0.0201,0.0407,-0.0442,-0.0174],[-0.0779,0.0032,0.0172,[ 0.0796,-0.0364,0.0141,-0.0198],[ 0.0270,-0.0578,-0.0515,0.0225],[ 0.0212,0.0231,0.0071,0.0190,0.0285]],[[ 0.0311,0.0148,0.0181,0.0617,0.0037],[ 0.0754,-0.0596,-0.0498,-0.0612],[ 0.0318,-0.0068,-0.0725,-0.0671,-0.0531],0.0793,0.0033,-0.0685],[ 0.0426,0.0477,0.0556,0.0341]]],[[[ 0.0264,0.0640,0.0658,-0.0286,0.0150],[-0.0585,0.0341,0.0521],[ 0.0732,0.0577,-0.0740,0.0150,0.0718],[-0.0311,-0.0343,0.0234,-0.0110,[ 0.0698,-0.0400,0.0735]],[[-0.0569,0.0414,0.0089,-0.0155],-0.0245,0.0417,0.0205],[-0.0235,-0.0624,-0.0798],[ 0.0679,0.0494,-0.0063,0.0646],[-0.0303,-0.0782,0.0025,0.0761,-0.0034]],[[ 0.0738,0.0397,-0.0492],[ 0.0518,0.0812,0.0331,0.0802],[-0.0672,-0.0441,-0.0760,-0.0191],[ 0.0746,0.0753,0.0669,-0.0648],[-0.0325,0.0273,-0.0089,0.0195]],[[-0.0117,0.0272,0.0785,0.0456,-0.0539],[ 0.0032,0.0351,0.0479,0.0014,-0.0471],[ 0.0423,0.0394,-0.0310,-0.0511,0.0784],[-0.0053,-0.0030],[ 0.0415,0.0264,0.0010,0.0069]],[[ 0.0320,-0.0181,-0.0439,[ 0.0479,0.0018,-0.0336,0.0605],[-0.0263,-0.0145,0.0242],[ 0.0662,0.0128,0.0656],[-0.0760,0.0179,0.0657,-0.0070,-0.0182]],[[-0.0080,0.0249,-0.0293,-0.0743],0.0067,0.0361,0.0340],[ 0.0071,-0.0689,-0.0633,-0.0101,0.0191,-0.0481,0.0536,-0.0312]]]],Parameter containing: tensor([ 0.0811,0.0688,0.0037,0.0488,0.0750,0.0471,-0.0719,-0.0324,0.0586,-0.0008,0.0676,-0.0628],Parameter containing: tensor([[-0.0475,-0.0082,-0.0330,0.0490,0.0475],[-0.0275,-0.0029,0.0100,-0.0315],[-0.0226,-0.0392,-0.0472,-0.0402,-0.0432],[-0.0246,0.0447,0.0406,-0.0298,-0.0262],[ 0.0467,0.0372,0.0408,-0.0421,-0.0001,-0.0135],[-0.0282,0.0223,-0.0097,-0.0319,0.0396]],Parameter containing: tensor([ 0.0312,0.0236,-0.0012,-0.0042,0.0425,0.0405,0.0208,-0.0116,-0.0051,0.0387,-0.0304,0.0043,0.0364,0.0444,-0.0117,0.0066,0.0009,-0.0232,0.0040,-0.0159,0.0313,0.0298,-0.0172,-0.0153,0.0011,-0.0480,-0.0373,0.0373,-0.0390,0.0039,-0.0410,-0.0379,-0.0024,0.0319,-0.0204,0.0499,0.0245,-0.0188,0.0363,-0.0162,0.0027,-0.0312,-0.0237,0.0016,0.0022,-0.0360,-0.0160,0.0078,-0.0434,0.0435,0.0065,0.0092,-0.0196,-0.0032,-0.0253,0.0439,0.0008,-0.0006,0.0498,-0.0476,0.0132,0.0282,-0.0258,0.0244,-0.0256,0.0442,0.0345,-0.0403,0.0404,0.0330,0.0240,-0.0060,-0.0173,0.0332,0.0438,0.0324],Parameter containing: tensor([[ 0.0682,0.0024,0.0675],[-0.0736,0.0328,0.0723,0.0668,0.0532],[ 0.0756,0.0187,-0.0489,0.0413,0.0911],[ 0.0413,0.0286,-0.0861,0.0363],[-0.0617,-0.0420,-0.0753],[-0.0725,-0.0901,-0.0083]],Parameter containing: tensor([-0.0349,-0.0911,-0.0866,-0.0378,0.0630,0.0241,-0.0474,-0.0521,0.0237,-0.0527,-0.0368,-0.0609,0.0420,-0.0536,0.0297,-0.0591,0.0113,-0.0748,0.0677,0.0161,-0.0137,0.0421,-0.0099,0.0771,-0.0909,0.0134,0.0267,0.0064,-0.0422,-0.0399,0.0850,-0.0752,0.0048,-0.0739,-0.0775,0.0242,-0.0077,0.0587,0.0817,0.0253,-0.0416,0.0209,-0.0443,-0.0393,0.0637,-0.0822,-0.0534,0.0409,0.0747,0.0825],Parameter containing: tensor([[ 0.0933,-0.0207,0.0699,-0.0832,0.0625,-0.1056,-0.0030,-0.0944,0.0860,0.0847,0.0142,-0.0269,0.0735,-0.0080,-0.0654,0.0801,-0.0691,0.0459,-0.0854,0.0158,-0.0010,-0.0982,0.1022,0.0983,-0.0577,-0.0862,0.0950,0.0595,-0.0567,-0.0346,-0.0157,-0.0865,0.0600,0.0583,-0.0653,0.0962,-0.0919,-0.0094,-0.0529,0.0105,-0.0262,-0.0430,-0.0617,0.0215,-0.0279,-0.0643,0.0924,-0.0948,0.0948,0.1033,-0.0855,0.0897,-0.0881,-0.0235,0.0202,0.0642,0.0931,-0.0185,-0.0069,-0.0505,0.0262,0.0494],0.0659,0.0350,-0.0190,0.0848,0.0323,-0.0729,-0.0899,0.0368,0.0960,-0.0329,-0.0825,-0.0920,-0.0124,-0.0553,-0.1004,0.0774,-0.0640,-0.0858,-0.0961,-0.0628,0.1069,-0.0934,-0.0328,0.0601,0.0520,-0.1076,0.0327,0.0708,0.0961,-0.0425,-0.1044,-0.0531,-0.1091,0.0852,0.0506,-0.0759,0.0647,0.0838,0.0565,-0.0191,-0.0427,-0.0582,0.0391,-0.0757,0.0503,-0.0566,-0.0428,0.0544,[ 0.0067,-0.0176,-0.0715,0.0355,-0.0906,0.0023,-0.0993,0.0541,-0.0550,0.0248,-0.0932,-0.0260,0.1029,-0.0964,-0.0891,-0.0211,0.0446,0.0500,-0.1061,-0.0997,0.0623,0.0050,-0.0658,0.1083,-0.0975,-0.0847,0.0578,0.0997,-0.0887,0.0487,-0.0873,-0.0942,0.0594,-0.0690,0.0987,0.0836,-0.0318,0.0591,0.0820,-0.0838,0.0104,-0.0150,0.0686,-0.0508,0.0454,0.0869,0.0133,0.0598,0.0614,-0.0297,0.0652,-0.0774,-0.0156,-0.0226,0.0355],[ 0.0012,-0.0315,0.0325,0.0805,-0.0054,-0.0746,-0.0037,-0.0950,-0.1013,0.0301,-0.0776,0.0938,0.0627,0.0888,-0.0217,0.1007,-0.0174,0.0552,0.0784,0.1001,0.0386,0.0802,-0.0714,0.0509,-0.0348,-0.0464,0.0685,-0.0985,0.0432,-0.0987,-0.0563,0.0582,-0.0138,0.0392,0.0908,0.0376,-0.0579,0.0461,-0.0510,0.0745,-0.1040,-0.0600,-0.0639,-0.0812,-0.0342,0.0274,0.0212,-0.0570,-0.0320,-0.0152,0.0199,-0.0973,0.0210,-0.0125,0.1074],[ 0.1063,-0.0271,-0.0071,0.0985,-0.0283,-0.0548,0.0047,-0.0903,-0.0945,0.0833,-0.1055,-0.0940,-0.0198,-0.0241,-0.0299,0.0725,0.0081,0.0422,0.0854,-0.0751,-0.0767,0.0197,0.0932,0.0818,-0.1081,0.1002,0.0007,0.0829,-0.0354,-0.0034,0.0529,-0.0712,0.0826,-0.0883,-0.0738,0.0713,-0.0088,0.1027,0.0437,-0.0988,-0.0122,0.1037,-0.0672,0.0365,-0.0655,-0.0897,-0.0060],[ 0.0624,-0.1046,-0.1060,-0.0777,-0.1024,-0.0598,-0.0248,0.0670,-0.0736,0.0003,0.0255,-0.0868,0.0522,-0.0999,0.0567,0.0954,0.0333,-0.0247,0.1058,0.0855,-0.0132,-0.0682,-0.0004,0.0740,0.0549,0.0606,-0.0344,-0.0984,-0.0976,-0.0726,-0.0398,0.0096,0.0385,-0.0697,0.0772,-0.1068,0.0097,-0.0927,0.0767,0.0889,-0.0755,0.0978,-0.0471,-0.0240,-0.0996,0.0211,-0.0500,-0.0496],[-0.0850,-0.0064,0.0650,0.0075,-0.0627,-0.0123,0.1041,-0.0837,-0.0620,0.0620,0.0814,-0.0696,-0.0535,0.0680,-0.0468,-0.0347,-0.0560,-0.0118,0.0160,-0.0800,0.0152,0.0780,0.0692,-0.0857,0.0379,0.0358,-0.0882,-0.0409,0.0734,-0.0147,-0.0638,-0.0831,0.0770,0.0570,-0.0376,-0.0075,-0.0501,0.0724,0.0453,-0.0479,0.0638,-0.0136,0.0710,0.0281,-0.0595,-0.1032,0.0891,0.0308,0.0624,0.0935,-0.0290],[-0.0420,-0.0954,0.0239,0.0656,0.0359,0.0162,-0.0720,-0.0424,-0.0066,0.0443,-0.0192,-0.1064,-0.0928,-0.0114,-0.0520,0.0953,-0.0619,0.0366,-0.0255,-0.0933,-0.1080,-0.1062,0.0589,0.0721,-0.0768,0.0621,0.0233,-0.0806,-0.0826,0.0383,-0.0808,-0.0836,-0.1047,-0.1059,0.0810,-0.1090,0.0539,0.0472,0.0756,0.0827],[-0.0824,-0.0877,0.1064,-0.0750,0.0401,0.0102,-0.0275,0.0511,0.1013,-0.0493,-0.0197,0.0263,-0.0693,0.0910,-0.0355,-0.0917,0.1026,-0.1053,-0.0651,-0.0820,0.0002,0.0001,-0.1021,-0.1002,0.0693,-0.0405,-0.0484,-0.0259,0.0777,-0.0317,0.1077,0.0079,-0.0981,-0.0223,0.0144,0.0137,-0.0451,0.0913,0.0558,0.0918,-0.0629,-0.0514,-0.0731,-0.0570],[ 0.1043,0.1052,0.0250,0.0986,-0.0078,-0.0091,0.0758,0.0934,-0.0542,-0.0845,-0.0085,-0.0098,-0.0303,0.0304,-0.0351,0.0445,0.0989,-0.0436,0.0580,-0.0860,0.1046,0.0981,0.1066,-0.0814,-0.0362,-0.0863,-0.0438,0.0252,0.0200,-0.1074,0.0858,-0.0384,-0.0569,0.0093,0.1086,-0.0765,-0.0221,-0.0706,0.0766,0.0773,-0.0219]],Parameter containing: tensor([-0.1061,-0.0962,0.0518,-0.0951,-0.0218,-0.0068],requires_grad=True)] 10
逐列表項輸出列表元素和index
利用enumerate函式實現
#逐列表項輸出引數和當前引數位於列表的第幾項
for num,temp in enumerate(para):
print('number:',num)
print(temp)
輸出
number: 0 Parameter containing: tensor([[[[-0.0596,requires_grad=True) number: 1 Parameter containing: tensor([-0.0229,requires_grad=True) number: 2 Parameter containing: tensor([[[[-0.0497,requires_grad=True) number: 3 Parameter containing: tensor([ 0.0811,requires_grad=True) number: 4 Parameter containing: tensor([[-0.0475,requires_grad=True) number: 5 Parameter containing: tensor([ 0.0312,requires_grad=True) number: 6 Parameter containing: tensor([[ 0.0682,requires_grad=True) number: 7 Parameter containing: tensor([-0.0349,requires_grad=True) number: 8 Parameter containing: tensor([[ 0.0933,requires_grad=True) number: 9 Parameter containing: tensor([-0.1061,requires_grad=True)
以上這篇Pytorch之parameters的使用就是小編分享給大家的全部內容了，希望能給大家一個參考，也希望大家多多支援我們。