tensorfx
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tensorlab
TensorFlow framework for training and serving machine learning models
I'd like to start using tensorfx but I'd like to train tensorfx models on SageMaker. Additionally, I'd like to deploy trained tensorfx models on SageMaker as REST Endpoints. I have...
I'd like to contribute to tensorfx but I get the following error when I'm running `./build.sh test`: ``` File "main.py", line 24, in import data.dataset_tests File "/Users/pntompos/Documents/repos/tensorfx/build/tests/data/dataset_tests.py", line 17, in...
Hi, I noticed that the files https://github.com/TensorLab/tensorfx/blob/master/src/data/__init__.py and https://github.com/TensorLab/tensorfx/blob/master/src/training/_trainer.py are missing the dot before after the "from " import statements. So tensorfx does not run on my machine. Is this...
Input would be a discrete field, with arguments on number of hash buckets, and output is the result of `tf.string_to_hash_bucket_fast()`.
in /src/prediction/_model.py s/'SERVING'/tag_constants.SERVING/g that will help in making the output model work with gcloud local predict
The current training job checkpoints every N sec, and only produces a saved model at the very end. The idea is any checkpoint can be converted to a saved model...
Support for a cluster setup where master does training + checkpointing, and a separate eval node does continuous evaluation over the last checkpoint. Likely a few details to figure out......
Having one file with all the vocabs can be a problem for large examples. I think this was a performance problem with a criteo sample. It would be nice to...
In tf.Example, this is intrinsically supported by a feature with N entries in a list field. Think about what is the best way to support this in csv. Couple of...
The input is one or more feature columns, and args are embedding output size, to produce the results of `tf.nn.embedding_lookup()`.