Current implementation of Go binding can not specify options.

GPUOptions struct is in internal package. And go generate doesn't work for protobuf directory. So we can't specify GPUOptions for NewSession.

🚀 The feature, motivation and pitch

JIT serialization & freezing uses equality checks for things like common subexpression elimination (CSE).

Since aten::equal isn't implemented for sparse tensors, sparseTensorA.equals(sparseTensorB) fails, preventing CSE during freezing.

repro:

import torch

x = torch.rand((3, 4)).to_sparse()
y = torch.rand((3, 4))
print(torch.equal(x, 

fitDataset() expects a Dataset that produces elements of a certain shape, with matching batch sizes etc., and throws errors (from standardizeDataIteratorOutput()) when the conditions are not met. These errors should be tested.

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?