我试着用Pytorch训练我自己的目标检测模型。但我总是犯这个错误。我试图改变火炬版本,但这没有帮助。
我的包裹:火炬-0.11.1和火炬-1.10.0
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-10-9e52b782b448> in <module>()
4 for e
我遵循一个代码来学习图像分类。但是,此代码在compile函数中使用带有优化器的结构: optimizer=optimizers.Adam(lr=lr) 但是我得到了一个错误: File "C:\Users\jucar\PycharmProjects\AIRecProject\Scode.py", line 69, in <module>
optimizer=optimizers.Adam(lr=lr),NameError: name 'optimizers' is not defined 我按照这个问题的类似解决方案更改了结构: optimize
在尝试将RMSProp优化器与PyTorch一起使用时,将获得以下错误:
AttributeError: module 'torch.optim' has no attribute 'RMSProp'
代码:
import torch as T
import torch.nn as nn
import torch.optim as optim
class DeepQNetwork(nn.Module):
def __init__(self, alpha, ...):
super(DeepQNetwork, self).__init__()
尝试将Twisted包从20.3.0升级到21.2.0。
升级后,在运行Mypy时,我在访问反应器(从twisted.internet导入反应器)时遇到以下错误:
error: Module has no attribute "run" [attr-defined]
error: Module has no attribute "running" [attr-defined]
error: Module has no attribute "running" [attr-defined]
error: Module has no
我正在使用python3.9,tensorflow 2.7.0和一个改版的Mask )。我正在使用tensorflow .keras并专门导入
import tensorflow as tf
from tensorflow.python import keras
from tensorflow.python.keras import backend as K
from tensorflow.python.keras import layers as KL
from tensorflow.python.keras import utils as KU
from tensorflow.pytho
例如,我试图编写一个应该在列表上执行一次的任务:
- name: Create something that has an attribute with more than one values
some_module:
some_attribute: "{{ item }}"
run_once: true
loop:
- a
- b
但是像这样编写的任务将执行两次,比如
- name: Create something that has an attribute with more than one values
some_module
我只是安装了替罪羊的文件(在Windows 7上)。但是,当我试图从cmd运行命令“scapy”时,它会给出一个错误:
C:\Users\THOMAS>scapy
Traceback (most recent call last):
File "C:\Python26\Scripts\\scapy", line 23, in <module>
from scapy.main import interact
ImportError: No module named 'scapy'
模块似乎也不起作用,它给我带来了以下错误:
WARNI
我正试着把keras.initializers引入我的网络,
import keras
from keras.optimizers import RMSprop, Adam
from keras.layers import Input, Embedding, LSTM, Dense, merge, Activation
from keras.models import Model, Sequential
model = Sequential()
model.add(Dense(100, init='lecun_uniform', input_shape=(6,)))
mode
%reset -f
import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
import numpy as np
import matplotlib.pyplot as plt
import torch.utils.data as data_utils
import torch.nn as nn
import torch.nn.functional as F
num_epochs = 20
x1 = np.array([0,0])
x2 = np.
import keras
from keras.layers import Input, Dense
from keras.models import Model
from keras_adamw import AdamW
mlp = Model([
Dense(10, activation='relu', input_shape=trainX_scaled.shape), #input shape
Dense(10, activation='relu'), #Hiddin layer
Dense(10, a
下面是代码片段:
merged_model = Sequential()
merged_model = concatenate([model1.output, model2.output, model3.output, model4.output, model5.output])
x = BatchNormalization()(merged_model)
x = Dense(300)(x)
x = PReLU()(x)
x = Dropout(0.2)(x)
x = BatchNormalization()(x)
x = D
我正在尝试在keras图中执行matmul,并在编译模型时获得AttributeError: 'NoneType' object has no attribute '_inbound_nodes' error from keras import backend as K
from keras.layers import Input, Dense, Reshape
mainInput = Input(shape=(10*10,))
x = Dense(10*10, activation='relu')(x)
x1 = Reshape((10,
面对一个奇怪的问题。导入pygal成功。但不能使用它。下面是一个Ubuntu。同样的事情也适用于我的mac电脑。
感谢您的帮助!
Python 2.7.6 (default, Jun 22 2015, 18:00:18)
[GCC 4.8.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import pygal
>>>
>>> pygal.Line()
我目前正在参加Coursera-人工智能、机器学习和深度学习的TensorFlow入门课程。我在下面的代码中遇到一个错误。
这是我的python代码,
# y = 2x - 1
import tensorflow as tf
# helps us to represent our data as lists easily and quickly
import numpy as np
# framework for defining a neural network as a set of Sequential layers
from tensorflow import keras
# Th
我想在Firebase Cloud Firestore中追加数组中的数据。为此,我使用FieldValue.arrayUnion。
我试用了这些导入工具,但它们都不起作用
from firebase_admin import firestore
firebase_admin.firestore.FieldValue.arrayUnion()
AttributeError: module 'firebase_admin.firestore' has no attribute 'FieldValue'
from google.cloud import firest