Tensor.fill
Tensor.index_put
Tensor.to
Tensor.type_as
torch.topk
fmod
call Tensor member functions with inputnames
static shape_as_tensor
nn.Linear dynamic bias
eliminate noop type_as
convert two-dim nn.Linear to ncnn gemm
convert torch.stack to ncnn concat+reshape
ignore torch einsum path input

* fix build, prepend batch for broadcast reshape

* sanitize filename

* do not fuse to eltwise if broadcast

* update riscv qemu

* c906 test on qemu

* fix qemu aarch64

* write shape, fuse sam image encoder attention

* set more dynamic shape as static

* less warning for constant tensor node

fuse F.scaled_dot_product_attention

* pnnx fuse transformer clip attention

* skip fuse mha for 1.8

* select one method other than forward

* pnnx fuse diffusers attentionblock

* pnnx convert sdpa

* pnnx fuse diffuser attention2

* pnnx convert torch std

* fix multiple fuse pass on torch 2.0

* fuse vit pytorch mha pattern

pnnx reset maxpool return_indices if only output found, drop convtransposed output_size arg for static output padding (#4654)

* fix build with torch-2.0

* torch 2.0 new patterns

* add torch 2.0 ci

* torch baddbmm

* always convert to fp32 for shape inference

* silence info on nonetype and devicetype