Technical Preview

Features:
BM1686: support post handle op, provided parallelOp codegen, add DivOp for f16/bf16.
BM1684: Support dynamic compilation load tensor from L2mem, implement GROUP_3D local layer function, support more dynamic ops, like MinConst, MaxConst, Lut; and some static ops, like deform_conv2d.
CV18XX: Support more ops like equalOp.
Support IfOp for f16/bf16/int8 mode.
Implement post process function of sensitive layer, unranked tensor and dynamic tensor at frontend, add empty and baddbmm torch converter/interpreter.
Support weight split when layer group if op is broadcastbinary, suppoprt parse ops of each layer in top.mlir, support int32 to i/u8 inference for modeol_runner.py.
Remove onnx-sim and use unranked_type for all ops.
Implement more graph opimize: merge matmul + add to matmul if float type, fuse same operation pass, weight trans when permute+add.
Support more torch ops, like rmsnorm, ceil, remainder.
Other new operations: lowering of GatherElements, multi-input Add.

Bug Fixes:
Fix chatglm2 rmsnorm untransformed prob, ScaleOp inference error, bmodel_dis format bin, shape inference of matmul, subnet output order mismatch cause error in dynamic runtime.
Avoid duplicate name of inserted CastOp, distinguish caffe matmul shape.

Code Refactoring:
Use llvm::md5, llvm::sha256.
Use Clang to speed up code compilation.
Remove some unused header files.
Use rewriter.eraseOp instead of op->earse, use string to define padding mode.
Refine disassembler, refactor mix_precision.

Documentation Updates:
Update document version and change some model-zoo requirements.
Modified English part and modified developer_manual doc for visual.py part.

Testing and Verification:
Updated list of test models supported by BM1684X.