honghuichao commented on issue #13759:
URL: https://github.com/apache/tvm/issues/13759#issuecomment-1443725461
@liaojianjin
@classmethod
def _index_put(cls, inputs, attr, params):
in_tensor = inputs[0]
indices, values = cls._check_index(inputs[1 : len(inputs) - 2],
inputs[len(inputs) - 2])
accumulate = inputs[len(inputs) - 1].data.asnumpy() != 0
if not accumulate:
mode = "update"
else:
mode = "add"
index_tensor = _op.stack(indices, axis=0)
return _op.transform.scatter_nd(in_tensor, index_tensor, values,
mode)
def _check_index(cls, indices, values):
def unfolding_indices(indices, values):
n = len(indices)
flatten_indices = []
slices_size = []
for index in indices:
flatten_indices.append(_op.reshape(index, _op.const([-1])))
slices_size.append(infer_shape(flatten_indices[-1])[0])
repeat_size = [1]
tile_size = [1]
for i in range(1, n):
repeat_size.append(slices_size[-i] * repeat_size[-1])
tile_size.append(slices_size[i - 1] * tile_size[-1])
repeat_size.reverse()
unflod_slices = []
for i in range(n):
unflod_slices.append(
fold_constant(
_op.repeat(_op.tile(flatten_indices[i],
(tile_size[i],)), repeat_size[i], 0)
)
)
return unflod_slices, _op.reshape(values, _op.const([-1]))
in the function _check_index(cls, indices, values) ,it will call
infer_shape to get the indices size,but the indice size cannot inference when
shape is dynamatic. my environment base pytorch == 1.8.0. and I think if
torch.onnx.export base pytorch1.13.1, the aten::indexput cannot show in onnx
graph,but maybe scatter_nd show in onnx graph.
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