google-colaboratory

问题 I want to run the code cells in Google Colab in sequence. For example: Cell[1] from catboost import CatBoostRegressor #do something here Cell[2] clf = CatBoostRegressor(task_type='GPU') #do some more things here But when I select "Run all" all cells seem to run in parallel, so my code does not work. When I do the same thing in a Kaggle Kernel it runs perfectly i.e, first cell[1] is executed, and then cell[2] and so on. I have tried searching for this in Google Colab but failed to come up with

问题 I am using Google Colaboratory, and mounting Google Drive. When I access a csv file, it gets me the following error: OSError: [Errno 5] Input/output error. This did not happen before. How can I access to the csv file as I used to? I have tried this, but did not work: Input/output error while using google colab with google drive This happened after conducting the following code. for segment_id in tqdm(range(segment_num)): with h5py.File(os.path.join(INPUT_PATH, "train.h5"), "r") as f: train

问题 I am using Google Colaboratory, and mounting Google Drive. When I access a csv file, it gets me the following error: OSError: [Errno 5] Input/output error. This did not happen before. How can I access to the csv file as I used to? I have tried this, but did not work: Input/output error while using google colab with google drive This happened after conducting the following code. for segment_id in tqdm(range(segment_num)): with h5py.File(os.path.join(INPUT_PATH, "train.h5"), "r") as f: train

问题 I have a simple jupyter notebook, say foo.ipynb . I wish simply to run nbconvert in the usual way: on my local machine I would execute !jupyter nbconvert foo.ipynb in the notebook itself, or jupyter notebook foo.ipynb in a shell. On Google Colaboratory, this does not work. Of course this is because foo.ipynb is not running locally on the drive, but the usual methods to connect Drive and Colab are not working in this case. Question: is running nbconvert on a Colab notebook possible from within

问题 Is there a Google Colab API? I'm looking to accomplish things like: Create users Create notebooks Share notebooks with users Retrieve the contents of a notebook 回答1: As pointed out in the other answer, Colab Notebooks are files on your Google Drive. Hence, sharing them or retrieving their contents can be done via the Google Drive API (from what I understand you can use the webContentLink to download it). However, your first question is: Where is the Google Colab API? For anyone coming here

问题 When I run this code in google colab n = 100000000 i = [] while True: i.append(n * 10**66) it happens to me all the time. My data is huge. After hitting 12.72 GB RAM, but I don't immediately get to the crash prompt and the option to increase my RAM. I have just this Your session crashed after using all available RAM. View runtime logs What is the solution ? Is there another way ? 回答1: You either need to upgrade to Colab Pro or if your computer itself has more RAM than the VM for Colab, you

问题 After training a model using Google Colab, I downloaded it using the following command (inside Google Colab): model.save('model.h5') from google.colab import files files.download('model.h5') My problem is that when I try to load the downloaded model.h5 using my local machine (outside Google Colab), I get the following error: [input] from keras.models import load_model model = load_model(model.h5) [output] Traceback (most recent call last): File "test.py", line 2, in <module> model = load

问题 After training a model using Google Colab, I downloaded it using the following command (inside Google Colab): model.save('model.h5') from google.colab import files files.download('model.h5') My problem is that when I try to load the downloaded model.h5 using my local machine (outside Google Colab), I get the following error: [input] from keras.models import load_model model = load_model(model.h5) [output] Traceback (most recent call last): File "test.py", line 2, in <module> model = load

问题 I am using TPU runtime in Google Colab, but having problems in reading files (not sure). I initialized TPU using: import tensorflow as tf import os import tensorflow_datasets as tfds resolver = tf.distribute.cluster_resolver.TPUClusterResolver(tpu='grpc://' + os.environ['COLAB_TPU_ADDR']) tf.config.experimental_connect_to_cluster(resolver) # This is the TPU initialization code that has to be at the beginning. tf.tpu.experimental.initialize_tpu_system(resolver) print("All devices: ", tf.config

问题 I'm trying to download the kaggle imagenet object localization challenge data into google colab so that I can use it to train my model. Kaggle uses an API for easy and fast access to their datasets. (https://github.com/Kaggle/kaggle-api) However, when calling the command "kaggle competitions download -c imagenet-object-localization-challenge" in google colab, it can't find the kaggle.json file which contains my username and api-key. I haven't had this problem on my mac when running a jupyter