FullZing

https://github.com/Jittor/jittor/search?q=count_fuse

即时编译的收益是什么呢？

2

所有都是即时的 Jittor的所有代码都是即时编译并且运行的，包括Jittor本身。用户可以随时对Jittor的所有代码进行修改，并且动态运行。

why onnx-mlir defines return op rather than using standard return op?

can we support float16(half) datatype?

6

my model is float16 model which failed to transform in torch-mlir https://github.com/llvm/torch-mlir/blob/32159c4e545359d4ad9e3b492c07e07528f5b47e/python/torch_mlir/dialects/torch/importer/jit_ir/csrc/torch_to_mlir_utils.cpp#L327 case ScalarType::Int: case ScalarType::Long: case ScalarType::Float: case ScalarType::Double: case ScalarType::Bool: case ScalarType::QInt8: case ScalarType::BFloat16: default: throwUnsupportedTensorError(); } can...

is it possible to support dynamic shape from the design of TFRT? if so, could you please share the idea ? many thanks