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摘要: hardsigmoid torch.nn.functional.hardsigmoid(input) → Tensor[SOURCE] Applies the element-wise function \text{Hardsigmoid}(x) = \begin{cases} 0 & \text{ 阅读全文
posted @ 2020-12-01 09:59 说分手后还能做炮友? 阅读(591) 评论(0) 推荐(0)
摘要: criteria = nn.CrossEntropyLoss() loss = criteria(output, target) loss = torch.nn.functional.cross_entropy(output, target) import torch import torchvis 阅读全文
posted @ 2020-11-30 21:20 说分手后还能做炮友? 阅读(370) 评论(0) 推荐(0)
摘要: 检查运行文件名称与模块名称是否重复。如果重复,需要将文件名称重新命名。 阅读全文
posted @ 2020-11-30 12:09 说分手后还能做炮友? 阅读(87) 评论(0) 推荐(0)
摘要: a = np.r_[1:4,0,4] print(a) [1 2 3 0 4] 阅读全文
posted @ 2020-11-17 16:57 说分手后还能做炮友? 阅读(137) 评论(0) 推荐(0)
摘要: import tensorflow as tf inputs = tf.random.normal([32, 10, 8]) lstm = tf.keras.layers.LSTM(4) output = lstm(inputs) print(output.shape) lstm = tf.kera 阅读全文
posted @ 2020-11-09 14:30 说分手后还能做炮友? 阅读(337) 评论(0) 推荐(0)
摘要: import numpy as np # from tensorflow import keras X = np.random.randint(100, size=10*1000).reshape(1000, 10) Y = np.random.randint(100, size=15*1000). 阅读全文
posted @ 2020-11-05 14:55 说分手后还能做炮友? 阅读(201) 评论(0) 推荐(0)
摘要: import torch from torch import nn from torch.utils.tensorboard import SummaryWriter '''https://zhuanlan.zhihu.com/p/242086547''' a = torch.Tensor([[1, 阅读全文
posted @ 2020-11-03 16:14 说分手后还能做炮友? 阅读(362) 评论(0) 推荐(0)
摘要: import tensorflow as tf import numpy as np # a = tf.random.uniform([2, 1, 2, 3]) # b = tf.random.uniform([1, 3, 3, 2]) # c = tf.matmul(a, b) '''https: 阅读全文
posted @ 2020-11-03 14:21 说分手后还能做炮友? 阅读(276) 评论(0) 推荐(0)
摘要: class a: @property def x(self): return 1 @x.setter def x(self,value): pass a1= a() y = a1.x print(y) a1.x = 2 print(y) 1 1 阅读全文
posted @ 2020-10-29 11:11 说分手后还能做炮友? 阅读(91) 评论(0) 推荐(0)
摘要: See Also asanyarray : Similar function which passes through subclasses. ascontiguousarray : Convert input to a contiguous array. asfarray : Convert in 阅读全文
posted @ 2020-10-29 10:30 说分手后还能做炮友? 阅读(145) 评论(0) 推荐(0)
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