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tensorflowsessiongpugoogle-colaboratorytpu
Vineetha Vijayan
Vineetha Vijayan

Reputation: 308

Is there any limitations for google colab other than the session timeout after 12 hours?

one of the limitations is that we can get only 12 continuous hours per session. Is there any limitations for the usage for GPU and TPU?

Upvotes: 18

Views: 35751

Answers (2)

Anshuman Kumar
Anshuman Kumar

Reputation: 577

From Colab's documentation,

In order to be able to offer computational resources for free, Colab needs to maintain the flexibility to adjust usage limits and hardware availability on the fly. Resources available in Colab vary over time to accommodate fluctuations in demand, as well as to accommodate overall growth and other factors.

In a nutshell, Colab has dynamic resource provisioning. So they can change the hardware automatically if it is being taxed too much. Google giveth and Google taketh away.

Link

Upvotes: 8

Rishabh Sahrawat
Rishabh Sahrawat

Reputation: 2507

Yes, you can only use 1 GPU with a limited memory of 12GB and TPU has 64 GB High Bandwidth Mmeory.You can read here in this article. So, if you want to use large dataset then I would recommend you to use tf.data.Dataset for preparing it before training. If you want to use GPUs you can use any TF version. But for TPU I would recommend using TF1.14.

Upvotes: 14

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