seed

问题 I'ved been developing in Django and was wondering if there is a way to seed data into the database in Django. In ruby on rails, I use seed.rb and then run "rake db:seed" in command line. Main reason I want to seed some data on statuses, types, etc for the project initialization. Is there something similar ? 回答1: Similar to Rails, we also have option to seed the database. It is done using management commands. In one of your apps, use the following folder structure <project>/<app>/management

问题 I'ved been developing in Django and was wondering if there is a way to seed data into the database in Django. In ruby on rails, I use seed.rb and then run "rake db:seed" in command line. Main reason I want to seed some data on statuses, types, etc for the project initialization. Is there something similar ? 回答1: Similar to Rails, we also have option to seed the database. It is done using management commands. In one of your apps, use the following folder structure <project>/<app>/management

问题 I use the following code. I would like to get the same results for the same random seed. I use the same random seed (1 in this case) and get different results. Here is the code: import pandas as pd import numpy as np from random import seed # Load scikit's random forest classifier library from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split seed(1) ### <----- file_path = 'https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented

问题 I use the following code. I would like to get the same results for the same random seed. I use the same random seed (1 in this case) and get different results. Here is the code: import pandas as pd import numpy as np from random import seed # Load scikit's random forest classifier library from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split seed(1) ### <----- file_path = 'https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented

问题 I'm using a random.seed() to try and keep the random.sample() the same as I sample more values from a list and at some point the numbers change.....where I thought the one purpose of the seed() function was to keep the numbers the same. Heres a test I did to prove it doesn't keep the same numbers. import random a=range(0,100) random.seed(1) a = random.sample(a,10) print a then change the sample much higher and the sequence will change(at least for me they always do): a = random.sample(a,40)

问题 I'm using a random.seed() to try and keep the random.sample() the same as I sample more values from a list and at some point the numbers change.....where I thought the one purpose of the seed() function was to keep the numbers the same. Heres a test I did to prove it doesn't keep the same numbers. import random a=range(0,100) random.seed(1) a = random.sample(a,10) print a then change the sample much higher and the sequence will change(at least for me they always do): a = random.sample(a,40)

问题 I'm using a random.seed() to try and keep the random.sample() the same as I sample more values from a list and at some point the numbers change.....where I thought the one purpose of the seed() function was to keep the numbers the same. Heres a test I did to prove it doesn't keep the same numbers. import random a=range(0,100) random.seed(1) a = random.sample(a,10) print a then change the sample much higher and the sequence will change(at least for me they always do): a = random.sample(a,40)

问题 I'm trying to get reproducible results with Keras, however every time I run the program I get different results. I've set the python hash seed, the Numpy random seed, the random seed, the TensorFlow seed, and the kernel_initializer glorot_uniform seed, but I still don't get reproducible results. Are there any other things I can do to get reproducible results? I expect the predictions to be the same, however they are not. I get different results every single time. 回答1: Because you're using

问题 Is this the only way to 'unseed' the random number generator: np.random.seed(int(time.time())) If you have some code that you want to be repeatable (e.g. a test) in a loop with other code that you want to be random each loop, how do you 'reset' the seed to random number generator after setting it? The following code illustrates the issue: import numpy as np def test(): np.random.seed(2) print("Repeatable test:", [np.random.randint(10) for i in range(3)]) for i in range(4): print("Random

问题 Currently, in my ModelFactory.php, I have: $factory->define(App\Reply::class, function (Faker\Generator $faker) { return [ 'thread_id' => 1, 'user_id' => 1, 'body' => $faker->paragraph ]; }); I would like to generate a random user_id from one of the user ID's already stored in the user table. I'm stumped because I don't know the way to display data output to code properly, and I was wondering how I would be able to allow Laravel to choose a random user ID and insert into the database. Thank