Hello everyone I have a question about compiling Pytorch 1.9
retinanet_resnet50_fpn model, more specific while compiling this line
(github.com/pytorch/vision/blob/v0.10.0/torchvision/models/detection/_utils.py#L205)
**Traced jit graph:**
**aten::slice: Tensor slice(const Tensor& self, int64_t dim, int64_t start,
int64_t end, int64_t step)**
%6064 : int = prim::Constant(value=0](), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6065 : int = prim::Constant(value=0](), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6066 : int = prim::Constant(value=9223372036854775807](), scope:
__module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6067 : int = prim::Constant(value=1](), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6068 : Float(0, 4, strides=(4, 1], requires_grad=0, device=cpu) =
aten::slice(%rel_codes.1, %6064, %6065, %6066, %6067), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6069 : int = prim::Constant[value=1](), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6070 : int = prim::Constant[value=0](), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6071 : int = prim::Constant[value=9223372036854775807](), scope:
__module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6072 : int = prim::Constant[value=4](), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
%6073 : Float(0, 1, strides=[4, 4], requires_grad=0, device=cpu) =
aten::slice(%6068, %6069, %6070, %6071, %6072), scope: __module.model #
/home/ubuntu/.local/lib/python3.6/site-packages/torchvision/models/detection/_utils.py:205:0
My understanding here we get a N by 1 dx vector and later stacked together in
_utils.py#L223
**while the relay graph generates this**
%1804 = adv_index(%1802) /* ty=Tensor[(?, 4), float32] */;
%1844 = where(%1839, %1835, %1838) /* ty=Tensor[(2), int32] */;
%1845 = cast(%1843, dtype="int64") /* ty=Tensor[(2), int64] */;
%1846 = dyn.strided_slice(%1804, %1844, %1845, meta[relay.Constant][88] /*
ty=Tensor[(2), int32] */, begin=None, end=None, strides=None, axes=None) /*
ty=Tensor[(?, ?), float32] */;
**Later the missing dimension causes an error while unbinding along static
dimension using this**
https://github.com/pytorch/vision/blob/v0.10.0/torchvision/models/detection/transform.py#L287
The error is this:
>> in unbind, ishapes: (?, ?)
Traceback (most recent call last):
File "retinanet_test.py", line 110, in <module>
retina_net_lab()
File "retinanet_test.py", line 74, in retina_net_lab
mod, params = relay.frontend.from_pytorch(script_module, shape_list)
File "/home/ubuntu/neo-ai/tvm/python/tvm/relay/frontend/pytorch.py", line
3363, in from_pytorch
ret = converter.convert_operators(_get_operator_nodes(graph.nodes()),
outputs, ret_name)[0]
File "/home/ubuntu/neo-ai/tvm/python/tvm/relay/frontend/pytorch.py", line
2785, in convert_operators
inputs, _get_input_types(op_node, outputs,
default_dtype=self.default_dtype)
File "/home/ubuntu/neo-ai/tvm/python/tvm/relay/frontend/pytorch.py", line
2142, in unbind
res_split = _op.split(data, selections, dim)
File "/home/ubuntu/neo-ai/tvm/python/tvm/relay/op/transform.py", line
908, in split
ret_size = len(indices_or_sections) + 1
TypeError: object of type 'Any' has no len()
I wonder whether this behavior is expected and if there is any workaround to
enable this model?
Thanks! :slightly_smiling_face:
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