Comments (14)
@lee-man Thanks for taking it a shot. We've pushed fixes for argmax
and expand
. gather
is taking us a bit longer, but we will make it available soon.
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@peterjc123 Got it. Thanks a lot!
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@lee-man gather
is supported now. You may have a try.
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Got an Error (tinynn/converter/operators/torch/aten.py, line 1568):
TypeError: create_attr_tensor() got an unexpected keyword argument 'dtype'.
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@lee-man Should be fixed by 10da5c6. Please try again.
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Some problems with the data type for index:
File "/Users/mli/prj/pose/movenet-pytorch/TinyNeuralNetwork/tinynn/converter/base.py", line 256, in convert
self.init_operations()
File "/Users/mli/prj/pose/movenet-pytorch/TinyNeuralNetwork/tinynn/converter/base.py", line 226, in init_operations
converter.parse(node, attrs, args, self.common_graph)
File "/Users/mli/prj/pose/movenet-pytorch/TinyNeuralNetwork/tinynn/converter/operators/torch/aten.py", line 1661, in parse
self.run(node)
File "/Users/mli/prj/pose/movenet-pytorch/TinyNeuralNetwork/tinynn/converter/operators/torch/base.py", line 135, in run
raise e
File "/Users/mli/prj/pose/movenet-pytorch/TinyNeuralNetwork/tinynn/converter/operators/torch/base.py", line 129, in run
o = func(**kwargs)
RuntimeError: gather_out_cpu(): Expected dtype int64 for index
I check the current type of index, and it's int32.
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I tried to convert the type manually, and other errors were raised. I think it's due to the complex decoding part of the model I use. I will join the DingTalk group and discuss it with you guys directly. Thanks! @peterjc123
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@lee-man Okay. I managed to fixed the type-related issues.
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@lee-man I've looked into your model. It seems that you tries to call gather
with the index tensor as a variable, which is unsupported at this time.
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@peterjc123 Got it. Really appreciate your help.
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@lee-man I mean this can be fixed. We will do that later.
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@peterjc123 Great! Looking forward to your update!
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@lee-man BTW, could you please share the TorchScript model and the shapes of the inputs so that we can look into it easier? Or, maybe we should communicate with each other via DingTalk?
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Now that gather
should be fully supported. Let's close this issue.
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Related Issues (20)
- tinynn.converter module not found! HOT 2
- [CI] several tests for modifier failed
- Whether to support pytorch to keras HOT 1
- TransposeConv wrong shape? HOT 15
- change input to INT8 after converting to tflite HOT 2
- [converter] implement torch's `aten::scaled_dot_product_attention` operator HOT 2
- Request: clamp would be more efficient to go to Bounded Relu than Maximum + Minimum HOT 3
- Do not support PReLU module? HOT 5
- torch.max not working HOT 2
- OneShotChannelPruner results in the miss of some operators HOT 4
- KeyError when executing quantization HOT 5
- PyTorch 转 TFLite 使用 int8 量化 HOT 4
- Does tinynn support following int16 quantization? HOT 1
- jit.trace succeed but tinynn tracer failed HOT 1
- It became larger after converting to tflite model HOT 4
- how to do Post-training integer quantization with int16 activation HOT 4
- unnecessary float() variables cause quantization to fail. HOT 7
- aten::index nodes take multiple indices in PyTorch model but cause an error when trying to convert to TFLite HOT 1
- aten::repeat_interleave is considered an unsupported Tensor and causing an error when trying to convert to TFLite HOT 2
- convert model error HOT 5
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