5b648ef909fbf89c53f28ebc1b3bd2f4fde168c5,torch/onnx/symbolic_opset9.py,,embedding,#Any#Any#Any#Any#Any#Any#,475

Before Change

    // return out.view(size);
    weight = g.op("Gather", weight, indices)
    if (padding_idx >= 0):
        mask = eq(g, indices, g.op("Constant", value_t=torch.tensor(padding_idx)))
        if sym_help._export_onnx_opset_version < 11:
            mask = unsqueeze(g, mask, -1)
        else:
            mask = sym_help._unsqueeze_helper(g, mask, [-1])
        weight = masked_fill(g, weight, mask, torch.tensor(0.))
    return weight


@parse_args("v", "v", "v", "i", "i", "i", "v", "i")
def embedding_bag(g,

After Change

def embedding(g, weight, indices, padding_idx, scale_grad_by_freq, sparse):
    return g.op("Gather", weight, indices)


@parse_args("v", "v", "v", "i", "i", "i", "v", "i")
def embedding_bag(g,

Instances