pnnx转换模型遇到标量输入怎么办

[sen-O]

error log | 日志或报错信息 | ログ

model | 模型 | モデル

1. original model

how to reproduce | 复现步骤 | 再現方法

1.模型输入为两个张量+一个标量[640,640,3],[640,640,3],2048
2.运行命令./pnnx model.pt inputshape=[640,640,3],[640,640,3],2048后报错
3.ori@WP:~/download/pnnx-20250725-linux$ ./pnnx model.pt inputshape=[640,640,3],[640,640,3],2048
pnnxparam = model.pnnx.param
pnnxbin = model.pnnx.bin
pnnxpy = model_pnnx.py
pnnxonnx = model.pnnx.onnx
ncnnparam = model.ncnn.param
ncnnbin = model.ncnn.bin
ncnnpy = model_ncnn.py
fp16 = 1
optlevel = 2
device = cpu
inputshape = [640,640,3]f32,[640,640,3]f32
inputshape2 =
customop =
moduleop =
############# pass_level0
inline function adaptive_avg_pool2d
inline function adaptive_avg_pool3d
inline function interpolate
inline function rgb_to_grayscale
inline function _get_softmax_dim
inline function softmax
inline function calculate_gradient_radius_map
inline function _max_pool2d
inline function _max_pool2d
inline function _max_pool2d
inline function simple_nms
inline function _max_pool2d
inline function adaptive_nms
inline function iterative_adaptive_nms
inline function pad_to_length
inline function pad_and_stack_dynamic
inline function normalize
inline function grid_sample
inline function normalize
inline function sample_descriptors
inline function cdist
inline function cdist
inline function normalize_keypoints
inline function normalize_keypoints
inline function normalize
inline function normalize
inline function compute_similarity
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function rotate_half
inline function apply_cached_rotary_emb
inline function apply_cached_rotary_emb
inline function softmax
inline function softmax
inline function softmax
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function _get_softmax_dim
inline function log_softmax
inline function log_softmax
inline function sigmoid_log_double_softmax
inline function filter_matches
inline function softmax
inline function softmax
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.Attention
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.CrossBlock
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.LearnableFourierPositionalEncoding
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.MatchAssignment
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.Matcher
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.SelfBlock
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.TransformerLayer
inline module = LightGlue.superpoint_new_pt.SES
inline module = torch.autograd.grad_mode.no_grad
inline module = torch.nn.modules.linear.Identity
inline function adaptive_avg_pool2d
inline function adaptive_avg_pool3d
inline function interpolate
inline function rgb_to_grayscale
inline function _get_softmax_dim
inline function softmax
inline function calculate_gradient_radius_map
inline function _max_pool2d
inline function _max_pool2d
inline function _max_pool2d
inline function simple_nms
inline function _max_pool2d
inline function adaptive_nms
inline function iterative_adaptive_nms
inline function pad_to_length
inline function pad_and_stack_dynamic
inline function normalize
inline function grid_sample
inline function normalize
inline function sample_descriptors
inline function cdist
inline function cdist
inline function normalize_keypoints
inline function normalize_keypoints
inline function normalize
inline function normalize
inline function compute_similarity
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function rotate_half
inline function apply_cached_rotary_emb
inline function apply_cached_rotary_emb
inline function softmax
inline function softmax
inline function softmax
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function select_top_k_indices
inline function compute_similarity
inline function select_top_k_indices
inline function _get_softmax_dim
inline function log_softmax
inline function log_softmax
inline function sigmoid_log_double_softmax
inline function filter_matches
inline function softmax
inline function softmax
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.Attention
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.CrossBlock
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.LearnableFourierPositionalEncoding
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.MatchAssignment
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.Matcher
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.SelfBlock
inline module = LightGlue.lightglue_lightgluemask_pt_multigpu_name.TransformerLayer
inline module = LightGlue.superpoint_new_pt.SES
inline module = torch.autograd.grad_mode.no_grad
inline module = torch.nn.modules.linear.Identity

---

terminate called after throwing an instance of 'c10::Error'
what(): forward() is missing value for argument 'max_num_keypoints.1'. Declaration: forward(torch.___torch_mangle_15.MapGlue self.1, Tensor image0.3, Tensor image1.3, int max_num_keypoints.1) -> ((Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) 17347)
Exception raised from checkAndNormalizeInputs at /project/pytorch-v2.7.1/aten/src/ATen/core/function_schema_inl.h:61 (most recent call first):
frame #0: ./pnnx() [0x3042850]
frame #1: ./pnnx() [0x3041d95]
frame #2: ./pnnx() [0x47ce23]
frame #3: ./pnnx() [0x85103e]
frame #4: ./pnnx() [0x8511f8]
frame #5: ./pnnx() [0x2b9be1d]
frame #6: ./pnnx() [0x615f7e]
frame #7: ./pnnx() [0x63bdde]
frame #8: ./pnnx() [0x48417d]
frame #9: __libc_start_main + 0xe7 (0x7ff47482cc87 in /lib/x86_64-linux-gnu/libc.so.6)
frame #10: ./pnnx() [0x4f2d6e]

已放弃 (核心已转储)

[nihui]

pnnx 转换 trace 出来的 torchscript，不支持scripting，输出信息中大量 inline function 是有问题的
标量输入需要修改模型 forward 接口，改为传入 tensor，如果标量是固定的，那么写死参数，模型不输入这个标量