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Now that we have a Dockerfile.cpu, we need a Dockerfile.gpu. This should be tested in a machine with a GPU.
Also, as we will have two Dockerfiles and two requirements files, we should check what the best practices are for managing this duplicity.
Requirements
Things you need in order to complete the issue.
Machine with a GPU
Knowledge about best practices for managing two Dockerfiles.
Acceptance Criteria
Criteria that must be met in order to close the issue successfully.
A Dockerfile for gpu is created.
This new Dockerfile can be built successfully. Check command: python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
The two Dockerfiles are managed in the best way.
The text was updated successfully, but these errors were encountered:
Description
Now that we have a Dockerfile.cpu, we need a Dockerfile.gpu. This should be tested in a machine with a GPU.
Also, as we will have two Dockerfiles and two requirements files, we should check what the best practices are for managing this duplicity.
Requirements
Things you need in order to complete the issue.
Acceptance Criteria
Criteria that must be met in order to close the issue successfully.
python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
The text was updated successfully, but these errors were encountered: