axes_change

torch_to_nnef.op.aten.axes_change

flatten

flatten(g, node, name_to_tensor, inference_target, **kwargs)

Translate operator: aten::flatten to NNEF.

Using NNEF:. fragment reshape<?>( input: tensor<?>, shape: integer[], axis_start: integer = 0, axis_count: integer = -1 ) -> ( output: tensor<?> );

permute

permute(g, node, name_to_tensor, **kwargs)

Map PyTorch: 'aten:permute' to NNEF.

reshape

reshape(g, node, name_to_tensor, torch_graph, inference_target, **kwargs)

Map PyTorch: 'aten:reshape' to NNEF.

squeeze

squeeze(g, node, name_to_tensor, **kwargs)

Map PyTorch: 'aten:squeeze' to NNEF.

transpose

transpose(g, node, name_to_tensor, inference_target, **kwargs)

Map PyTorch: 'aten:transpose' to NNEF.

unflatten

unflatten(g, node, name_to_tensor, torch_graph, op_helper, inference_target, **kwargs)

Map PyTorch: 'aten:unflatten' to NNEF.

unsqueeze

unsqueeze(g, node, name_to_tensor, **kwargs)

Map PyTorch: 'aten:unsqueeze' to NNEF.

view

view(g, node, name_to_tensor, torch_graph, inference_target, **kwargs)

Map PyTorch: 'aten:view' to NNEF.