nihui
|
e71fdf8e51
|
pnnx write implicit int conversion in python script (#5767)
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1 year ago |
nihui
|
6077adc6bc
|
pnnx do not fold tensor with dynamic shape, use fp32 module by default (#5755)
|
1 year ago |
nihui
|
c1f9e959f5
|
pnnx torch 2.5 (#5748)
|
1 year ago |
nihui
|
f856011297
|
pnnx drop onnx weight-like graph input (#5736)
|
1 year ago |
nihui
|
66b54cbea2
|
multiheadattention int8 quantization (#5733)
* x86 vulkan fallback
* comment about bf16s
|
1 year ago |
nihui
|
1c7af00499
|
gemm int8 quantization (#5706)
* quantize gemm
* write gemm quantize scales
* update doc
* less openmp args
* x86 riscv fallback
* skip gemm vulkan int8
* fix noint8 test, fix arm bf16 test
* enable vfpv4 on neon build only
* fix gemm vulkan without C
* fp16 pack8 output
* enable elempack=8 only for asimdhp+
* tiled gemm int8 test
* opt arm64 tiles, fix asimdhp dispatch
|
1 year ago |
nihui
|
80c78a0e40
|
pnnx fuse t5-layernorm as rmsnorm (#5675)
|
1 year ago |
nihui
|
21e54d8c7a
|
update modelwriter for rmsnorm (#5676)
|
1 year ago |
nihui
|
5df5413c81
|
embed int8 quantization and add embed test (#5667)
|
1 year ago |
nihui
|
5e2d56d025
|
pnnx fuse mobilevit style selfattention, onnx2pnnx handle more general gemm (#5659)
|
1 year ago |
nihui
|
4de536951a
|
onnx2pnnx do not fold single constant for gemm weight (#5634)
|
1 year ago |
nihui
|
789d8686c7
|
pnnx functionize do not create shadow op for identity consumers (#5632)
|
1 year ago |
nihui
|
fdf0df3079
|
RMSNorm (#5630)
|
1 year ago |
nihui
|
abad90cb1c
|
pnnx drop torch.max torch.min indice node if not used (#5629)
|
1 year ago |
nihui
|
eb6e084c2d
|
pnnx convert nn.RMSNorm F.rms_norm (#5628)
|
1 year ago |
nihui
|
c46278d0bb
|
pnnx convert onnx resize with roi, torch.max torch.min with dim returns tuple (#5627)
* pnnx convert onnx resize with roi, torch.max torch.min with dim returns tuple
* torch max min only support single dim
|
1 year ago |
nihui
|
ecfd88a11b
|
pnnx2ncnn convert torch.roll with one or two shifts (#5623)
|
1 year ago |
nihui
|
f3cd4c2e91
|
pnnx2ncnn handle F.maxpool without dilation param (#5622)
|
1 year ago |
nihui
|
b9debee8fb
|
pnnx ci for torch 2.4 (#5618)
* update onnx proto
|
1 year ago |
nihui
|
60823a8de3
|
pnnx handles sdpa batch index (#5617)
|
2 years ago |
lll143653
|
d355b6dc5b
|
Add warning and recommend to use pnnx (#5588)
|
2 years ago |
nihui
|
3ee5c18f84
|
pnnx logaddexp (#5598)
|
2 years ago |
nihui
|
e82015878c
|
Update modelwriter.h for mha scale param
|
2 years ago |
nihui
|
f825d3a23c
|
pnnx fuse onnx sdpa pattern and ncnn qdim mha fusion (#5589)
|
2 years ago |
nihui
|
569617f212
|
pnnx convert onnx expand/permute/repeat/reshape/select/slice/cat/ceil/chunk/flatten/floor/maximum/minimum/split/squeeze/stack/transpose/unbind/unsqueeze (#5583)
|
2 years ago |
nihui
|
e7cae68a22
|
pnnx convert onnx logsoftmax/logsigmoid/mish/selu/sigmoid/silu/softmin/softplus/softshrink/softsign/tanh/tanhshrink (#5581)
|
2 years ago |
nihui
|
1c40615b2d
|
pnnx convert onnx sdap reduce min/max/mean/sum/prod (#5579)
* pnnx convert onnx sdap
* test reduce
|
2 years ago |
nihui
|
c59885aeac
|
pnnx convert onnx multiheadattention (#5575)
* pnnx convert onnx multiheadattention
* onnx reducemean reducesum
* reducemax reducemin reduceprod
* mask buggy torch
* avoid shadow output
|
2 years ago |
nihui
|
854678b5f3
|
pnnx convert onnx prelu gelu elu leakyrelu relu6 celu hardshrink hardsigmoid hardswish clip (#5572)
|
2 years ago |
nihui
|
d264b6353a
|
pnnx convert onnx rnn lstm gru (#5553)
|
2 years ago |
nihui
|
74d3eb2345
|
pnnx convert onnx layernorm instancenorm groupnorm (#5533)
* pnnx convert onnx layernorm
* fuse early
* skip layernorm affine false test for torch 2.1
* pnnx convert onnx layernorm instancenorm groupnorm
* take num_features from input shape for instancenorm module
* torch < 1.10 can not handle track_running_stats=True
|
2 years ago |
nihui
|
98de53920e
|
pnnx convert onnx lrn, fuse if with constant condition, canonicalize and check foldable inside subgraph (#5532)
|
2 years ago |
nihui
|
755f8e1a6b
|
pnnx convert onnx batchnorm (#5529)
|
2 years ago |
nihui
|
109ed2665c
|
pnnx convert onnx avgpool maxpool (#5527)
* pnnx convert onnx avgpool
* fuse gather indices
* generalized conv convtranspose
* skip maxpool dilation test for torch < 1.12
* ceil mode for opset 9
|
2 years ago |
nihui
|
f56b18aaf0
|
pnnx convert onnx resize upsample (#5522)
|
2 years ago |
nihui
|
2828e7ae96
|
pnnx reset onnx input shape, convert torch.tile torch.where (#5517)
* pnnx reset onnx input shape
* eliminate noop cast
|
2 years ago |
nihui
|
ffb2fe60ee
|
pnnx convert onnx pad linear sigmoid softmax relu (#5516)
* pnnx convert onnx pad
* pnnx convert onnx linear sigmoid softmax relu
* old onnx softmax
|
2 years ago |
nihui
|
21babb7eed
|
pnnx convert onnx conv convtranspose (#5515)
|
2 years ago |
nihui
|
75ba2a01c9
|
pnnx fill tensor data for ort inference, fix output shape2 mismatch (#5488)
|
2 years ago |
nihui
|
5b49d0aa0a
|
pnnx onnx fold partial shape constant, fix dce node lost bug (#5486)
|
2 years ago |
nihui
|
740f437462
|
pnnx fuse simple onnx shape slice chain, fix squeeze dim list (#5485)
|
2 years ago |
nihui
|
e009c36155
|
fix onnx bn silu (#5483)
|
2 years ago |
nihui
|
5e9bf90455
|
pnnx onnx with inputshape (#5480)
|
2 years ago |
nihui
|
f40d5414d5
|
pnnx build onnx2pnnx (#5461)
|
2 years ago |
nihui
|
1b7e6358c9
|
pnnx load dynamo onnx of segmentation models (#5458)
|
2 years ago |
nihui
|
432a8d9aa1
|
pnnx replace ncnn input long type with int (#5457)
|
2 years ago |
nihui
|
ab088e05b8
|
pnnx do not fold aliased tensors with inplace op (#5455)
|
2 years ago |
nihui
|
6110d41b19
|
pnnx bf16 data type (#5456)
|
2 years ago |
nihui
|
08b7d99a75
|
rnn/lstm/gru dynamic quantization (#5435)
|
2 years ago |
nihuini
|
802a625ae2
|
fix pnnx windows build
|
2 years ago |