Comments (11)
If you want to continue in Eager mode check also https://www.tensorflow.org/tutorials/eager/eager_basics#datasets
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Generally the dataset API is already highly optimized.
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Yeah, you're right
I am currently using my custom Loader for loading and performing data augmentation but... I think it's about time to move into the data.Dataset API haha
I am gonna open another issue for that
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https://www.tensorflow.org/performance/datasets_performance
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Nevertheless... I just saw it andd... Do you know if you can use it when the data does not fit into RAM? I mean, if you cannot load the entire dataset at once... You can still use the Dataset API?
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Yes of course
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You know how? I mean, can you provide me a link or a function name or something? I'll try to search on internet and on the guide you linked in previous messages too
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Almost all the real datasets don't fit in memory so you will find many many dataset API examples. Just to mention one https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/contrib/eager/python/examples/generative_examples/image_captioning_with_attention.ipynb
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I mean, referring to the size of the dataset
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That dataset doesn't fit in memory
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Thanks a lot!
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Related Issues (12)
- Deconvolution HOT 6
- Why are all data sets labeled black and black?
- Why are all the predicted data sets black? HOT 4
- about saving model
- Results are strange HOT 3
- Error with different dataset HOT 8
- Bilinear Upsample HOT 3
- Move to Dataset API HOT 2
- where is imgaug HOT 2
- is there a plan to add detection function? HOT 1
- Can you tell me the corresponding network structure. HOT 1
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