小编Rob*_*cia的帖子

我的项目需要生成大量(例如,大约10 ^ 7)的正态分布的随机数,并且该步骤需要大量的计算资源.

有没有比rnorm生成此类数据更有效的方法？

我有一个全新安装的Ubuntu Server 14.04,我正在尝试安装我的Laravel项目.

我已将整个存储库移动到所需的文件夹中,但是当我运行该命令时

php artisan

在该目录中,终端返回错误说明

[InvalidArgumentException]

The "" directory does not exist.

有谁知道我可以做些什么来解决这个问题？

我刚刚开始使用JavaFX,我正在尝试使用标签,文本字段和按钮构建一个简单的应用程序,单击该按钮时,将标签的值设置为文本字段的值.一切顺利,直到我将控制器连接到主文件.这是我的代码:

Main.java

package application;

import java.io.IOException;

import javafx.application.Application;
import javafx.fxml.FXMLLoader;
import javafx.stage.Stage;
import javafx.scene.Scene;
import javafx.scene.layout.AnchorPane;


public class Main extends Application {

    private Stage primaryStage;

    @Override
    public void start(Stage primaryStage) {
        this.primaryStage = primaryStage; // connect primary stage
        mainWindow();
    }

    // main window
    public void mainWindow() {
        try {
            // view
            FXMLLoader loader = new FXMLLoader(Main.class.getResource("/MainWindowView.fxml"));
            AnchorPane pane = loader.load();

            // controller
            MainWindowController mainWindowController = loader.getController();
            mainWindowController.setMain(this);

            // scene on stage
            Scene scene = new Scene(pane);
            primaryStage.setScene(scene);
            primaryStage.show();

        } catch …

When I try load training data from an HDF5 file using fit_generator and generator functions, I get a ValueError, which results from a PointSelectionError with HDF5:

Epoch 1/10
Exception in thread Thread-1:
Traceback (most recent call last):
  File "/usr/lib/python2.7/threading.py", line 810, in __bootstrap_inner
    self.run()
  File "/usr/lib/python2.7/threading.py", line 763, in run
    self.__target(*self.__args, **self.__kwargs)
  File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 429, in data_generator_task
    generator_output = next(self._generator)
  File "osr.py", line 108, in generate_training_sequences
    X = training_save_file["X"][batch_idxs]
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper (/tmp/pip-4rPeHA-build/h5py/_objects.c:2684)
  File "h5py/_objects.pyx", line …

该模型的目标是对视频序列进行分类分类,其中每个输入是灰度,45帧,100x150视频序列(1,45,100,150),对应于3的一个热门编码分类输出类,例如[0,0,1].以下是用于训练模型的脚本:

from keras import backend as K
from keras.callbacks import Callback
from keras.constraints import maxnorm
from keras.models import Sequential, load_model
from keras.layers import Dense
from keras.layers import Dropout
from keras.layers import Flatten
from keras.layers.convolutional import Convolution3D
from keras.layers.convolutional import MaxPooling3D
from keras.layers.normalization import BatchNormalization
from keras.optimizers import Nadam
from keras.preprocessing.image import random_rotation, random_shift, random_shear, random_zoom
from keras.regularizers import WeightRegularizer
from keras.utils import np_utils
from keras.utils.io_utils import HDF5Matrix
from pprint import pprint
from random import shuffle
from sklearn.utils import shuffle
K.set_image_dim_ordering("th") …