You Have Been Asked to Develop an Input Pipeline for an ML

question 25

Multiple Choice

You have been asked to develop an input pipeline for an ML training model that processes images from disparate sources at a low latency. You discover that your input data does not fit in memory. How should you create a dataset following Google-recommended best practices?

• A) Create a tf.data.Dataset.prefetch transformation. Create a tf.data.Dataset.prefetch transformation.
• B) Convert the images to tf.Tensor objects, and then run Dataset.from_tensor_slices() . Convert the images to tf.Tensor objects, and then run Dataset.from_tensor_slices() .
• C) Convert the images to tf.Tensor objects, and then run tf.data.Dataset.from_tensors() . tf.data.Dataset.from_tensors()
• D) Convert the images into TFRecords, store the images in Cloud Storage, and then use the tf.data API to read the images for training. Convert the images into TFRecords, store the images in Cloud Storage, and then use the tf.data API to read the images for training.

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