(indices, updates, shape)
return ret
pytorch edition of tensorflow scatter_nd.
    this function don't contain except handle code. so use this carefully
    when indice repeats, don't support repeat add which is supported
    in tensorflow.
pytorch edition of tensorflow scatter_nd.
    this function don't contain except handle code. so use this carefully
    when indice repeats, don't support repeat add which is supported
    in tensorflow.
pytorch edition of tensorflow scatter_nd . this function don t contain except handle code . so use this carefully when indice repeats don t support repeat add which is supported in tensorflow .
def scatter_nd(indices, updates, shape):
    """pytorch edition of tensorflow scatter_nd.
    this function don't contain except handle code. so use this carefully
    when indice repeats, don't support repeat add which is supported
    in tensorflow.
    """
    ret = torch.zeros(*shape, dtype=updates.dtype, device=updates.device)
    ndim = indices.shape[-1]
    output_shape = list(indices.shape[:-1]) + shape[indices.shape[-1]:]
    flatted_indices = indices.view(-1, ndim)
    slices = [flatted_indices[:, i] for i in range(ndim)]
    slices += [Ellipsis]
    ret[slices] = updates.view(*output_shape)
    return ret
def scatter_nd ( indices , updates , shape ) : ret = torch . zeros ( * shape , dtype = updates . dtype , device = updates . device ) ndim = indices . shape [ - 1 ] output_shape = list ( indices . shape [ : - 1 ] ) + shape [ indices . shape [ - 1 ] : ] flatted_indices = indices . view ( - 1 , ndim ) slices = [ flatted_indices [ : , i ] for i in range ( ndim ) ] slices += [ Ellipsis ] ret [ slices ] = updates . view ( * output_shape ) return ret