Read and write tensor protobufs from Javascript multidimensional arrays.
npm install tensorjsThis library allows you to read and write Tensor protobufs (specifically the
tensors that are used by the Google TensorFlow library). The tensors are encoded/decoded
from multidimensional JS arrays.
To install this:
``
$ npm install
If you want to rebuild the protobuf implementations, feel free to recompile them
by running (but there should be no reason to do this):
`
$ ./compile.sh
#### Function Signature
`
make_tensor(array, type)
- array: A multidimensional array representing the tensor you want to encodetype
- : One of lib.types.INT or lib.types.FLOAT representing which type of tensor it isRETURNS
- : A string encoding the binary value of the tensor protobuf (NOTE: There is some nonsense about encoding the strings as UINT8s but JS using utf-16. I think I've solved all the bugs, although it is possible there are still more.)
#### Example
`
const tensorjs = require('tensorjs');
tensorjs.make_tensor([[1, 2], [3, 4]], tensorjs.types.INT);
// returns '\b\u0003\u0012\b\u0012\u0002\b\u0002\u0012\u0002\b\u0002:\u0004\u0001\u0002\u0003\u0004'
`
#### Convenience Functions
We provide two convenience functions so that you don't have to pass in the type:
`
tensorjs.intTensor([[1, 2], [3, 4]]);
tensorjs.floatTensor([1.5, 2.5]);
#### Function Signature
`
make_array(tensor_pb)
- tensor_pb: A string encoding the tensor protobuf.RETURNS
- : A multidimensional array representing the tensor.
#### Example
`
const tensorjs = require('tensorjs');
tensorjs.make_array('\b\u0003\u0012\b\u0012\u0002\b\u0002\u0012\u0002\b\u0002:\u0004\u0001\u0002\u0003\u0004');
// returns [[1, 2], [3, 4]]
``
Copyright (c) 2017 Tomas Reimers
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