masahi edited a comment on issue #5243: [Frontend][TensorFlow]Improve TensorFlow Static Shape Tensor Array URL: https://github.com/apache/incubator-tvm/pull/5243#issuecomment-609552445 Hi @kevinthesun, I started experimenting with how to integrate static tensor array in Torch frontend. My use case is to support Python tensor list append and stack. I got two problems below: 1. When I append the tensor to tensor array (by concat), I can do infer shape on the input tensor to get the fixed shape static tensor array expects. But after I've done some appends and try to stack the static tensor array, I don't have a way to tell what fixed shape the input tensor array to stack expects. See https://github.com/masahi/tvm/blob/support-more-rnn/python/tvm/relay/frontend/pytorch.py#L989-L990 Since the shape is fixed, I think there should be an easy way to query the shape associated with a static array. I see you have such function `check_tensor_array_shape` in this PR (by parsing op name). Is this the recommended way? 2. The output type of stack is currently `static_tensor_float32_?_2_4_t[]` in my test. Is there a way to easily unwrap static tensor type wrapper and get relay `Tensor`? @wweic had such unwrapper in https://github.com/apache/incubator-tvm/pull/4325 for generic arrays. We should have something equivalent for static arrays.
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