importtorchimporttorch.nnasnnimporttorch.optimasoptimimportnumpyasnpimportpandasaspdimportmatplotlib.pyplotaspltfromsklearn.model_selectionimporttrain_test_split, KFoldfromsklearn.metricsimportmean_squared_error, r2_scorefromsklearn.preprocessingimpor...
from_numpy(x_train).requires_grad_()).data.numpy() # 模型的保存 torch.save(model.state_dict(), 'model.pkl') # 模型读取 model.load_state_dict(torch.load('model.pkl')) 实例二:手写线性回归 import random import torch from d2l import torch as d2l def synthetic_data(w, b, num_...
2.6 从numpy创建Tensor# Torch code: x = torch.from_numpy(x).float() # PaddlePaddle code x = paddle.to_tensor(x).astype(np.float32) In [7] import paddle x=paddle.to_tensor([1,2,3,4,5,6,7,8,9,10,11,12]) sample_lst=[0,5,7,11] x[sample_lst] Tensor(shape=[4], dtype...
importnumpy as np#线性回归#求loss#loss = (wx +b - y) ** 2defcompute_error_for_line_given_point(b, w, points): totalError=0foriinrange(0, len(points)): x=points[i, 0] y= points[i, 1] totalError= totalError + (y - (w * x + b)) ** 2returntotalError /float(len(poi...
x=torch.tensor([1.],requires_grad=True)# 需要设置tensor的requires_grad属性为True,才会进行梯度反传 ret=Exp.apply(x)# 使用apply方法调用自定义autogradfunctionprint(ret)#tensor([2.7183],grad_fn=<ExpBackward>)ret.backward()# 反传梯度print(x.grad)#tensor([2.7183]) ...
from numpy.random import RandomState # 假设我们要最小化函数 y=x^2 , 选择初始点 x0=5 TRAINING_STEPS = 100 LEARNING_RATE = 1 x = tf.Variable(tf.constant(5, dtype=tf.float32), name="x") y = tf.square(x) train_op = tf.train.GradientDescentOptimizer(LEARNING_RATE).minimize(y) ...
import scipy def f3(x): x = x * 2 x = scipy.fft.dct(x.numpy()) x = torch.from_numpy(x) x = x * 2 return x TorchScript 跟踪将非 PyTorch 函数调用的结果视为常量,因此结果可能是无声的错误。 inp1 = torch.randn(5, 5) inp2 = torch.randn(5, 5) traced_f3 = torch.jit.tra...
1.4 Numpy和Torch Torch自称为神经网络界的Numpy,因为它能将torch产生的tensor放在GPU中加速运算,就像Numpy会把array放在CPU中加速运算。Torch和Numpy有着很好的兼容性,可以自由的转换numpy的array和torch的tensor。 (1)格式转换 import torch import numpy as np ...
torch中from_numpy的等效keras函数是什么? 、、 我在torch中发现了一个代码,我必须将其更改为keras,但我找不到与其中一些相同的代码。例如,我更改了其中一些,如下所示,但我不确定它们是真是假: `torch.tensor` to `K.variable` ( `K` is `from keras import backend asK`) torch.empty((3,) + request...
import os import numpy as np import torch import torch.nn as nn from torch.utils.data import Dataset, DataLoader import torch.optim as optimizer 1. 2. 3. 4. 5. 6. 超参数配置: batch size 初始学习率(初始) 训练次数(max_epochs) GPU配置 batch_size = 16 # 批次的大小 lr = 1e-4 # ...