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WIP: Save and compare BB regressor and ResNet debug tensors, modularize comparison scripts, fix path issues, and improve reporting. [auto-commit]

resnet
mht 3 weeks ago
parent
0c40682ef6
commit
c646f63f00
47 changed files with 1898 additions and 148 deletions
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  1. 1
      CMakeLists.txt
  2. 4
      build/CMakeCache.txt
  3. BIN
      build/CMakeFiles/3.22.1/CMakeDetermineCompilerABI_CUDA.bin
  4. 176
      build/CMakeFiles/CMakeOutput.log
  5. 26
      build/CMakeFiles/Makefile2
  6. 1
      build/CMakeFiles/bb_regressor.dir/DependInfo.cmake
  7. 20
      build/CMakeFiles/bb_regressor.dir/build.make
  8. BIN
      build/CMakeFiles/bb_regressor.dir/cimp/bb_regressor/bb_regressor.cpp.o
  9. 18
      build/CMakeFiles/bb_regressor.dir/cimp/bb_regressor/bb_regressor.cpp.o.d
  10. 2
      build/CMakeFiles/bb_regressor.dir/cmake_clean.cmake
  11. 725
      build/CMakeFiles/bb_regressor.dir/compiler_depend.internal
  12. 768
      build/CMakeFiles/bb_regressor.dir/compiler_depend.make
  13. 2
      build/CMakeFiles/bb_regressor.dir/link.txt
  14. 1
      build/CMakeFiles/bb_regressor.dir/progress.make
  15. 4
      build/CMakeFiles/classifier.dir/progress.make
  16. 2
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  17. BIN
      build/CMakeFiles/tracking_demo.dir/cimp/demo.cpp.o
  18. 4
      build/CMakeFiles/tracking_demo.dir/progress.make
  19. 27
      build/Makefile
  20. BIN
      build/libbb_regressor.a
  21. BIN
      build/tracking_demo
  22. 20
      cimp/bb_regressor/bb_regressor.cpp
  23. 2
      cimp/bb_regressor/bb_regressor.h
  24. 14
      cimp/bb_regressor/utils.cpp
  25. 5
      cimp/bb_regressor/utils.h
  26. 51
      compare_bbreg_debug_tensors.py
  27. 45
      compare_bbreg_weights.py
  28. 45
      compare_resnet_features_debug.py
  29. BIN
      ltr/models/backbone/__pycache__/resnet.cpython-37.pyc
  30. BIN
      ltr/models/bbreg/__pycache__/atom_iou_net.cpython-311.pyc
  31. BIN
      ltr/models/bbreg/__pycache__/atom_iou_net.cpython-37.pyc
  32. BIN
      pytracking/features/__pycache__/net_wrappers.cpython-37.pyc
  33. BIN
      pytracking/utils/__pycache__/params.cpython-37.pyc
  34. 9
      test/compare_models.py
  35. 74
      test/model_comparison/bbreg_comparison.py
  36. BIN
      test/output_py/bb_regressor/sample_0_debug_conv3_1t_bn_py.pt
  37. BIN
      test/output_py/bb_regressor/sample_0_debug_conv3_1t_py.pt
  38. BIN
      test/output_py/bb_regressor/sample_0_debug_conv3_1t_relu_py.pt
  39. BIN
      test/output_py/bb_regressor/sample_0_debug_conv3_2t_bn_py.pt
  40. BIN
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  41. BIN
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  42. BIN
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  43. BIN
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  44. BIN
      test/output_py/bb_regressor/sample_0_debug_conv4_1t_relu_py.pt
  45. BIN
      test/output_py/bb_regressor/sample_0_debug_conv4_2t_bn_py.pt
  46. BIN
      test/output_py/bb_regressor/sample_0_debug_conv4_2t_py.pt
  47. BIN
      test/output_py/bb_regressor/sample_0_debug_conv4_2t_relu_py.pt

1
CMakeLists.txt
View File

@ -26,6 +26,7 @@ message(STATUS "Building with CUDA support")
set(BB_REGRESSOR_SOURCES
cimp/bb_regressor/bb_regressor.cpp
cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.cu
cimp/bb_regressor/utils.cpp
)
set(CLASSIFIER_SOURCES

4
build/CMakeCache.txt
View File

@ -201,8 +201,8 @@ CMAKE_STATIC_LINKER_FLAGS_RELWITHDEBINFO:STRING=
//Path to a program.
CMAKE_STRIP:FILEPATH=/usr/bin/strip
//No help, variable specified on the command line.
CMAKE_TOOLCHAIN_FILE:UNINITIALIZED=../vcpkg/scripts/buildsystems/vcpkg.cmake
//The CMake toolchain file
CMAKE_TOOLCHAIN_FILE:FILEPATH=/media/mht/ADATA/repos/cpp_tracker/vcpkg/scripts/buildsystems/vcpkg.cmake
//If this value is on, makefiles will be generated without the
// .SILENT directive, and all commands will be echoed to the console

BIN
build/CMakeFiles/3.22.1/CMakeDetermineCompilerABI_CUDA.bin
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176
build/CMakeFiles/CMakeOutput.log
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@ -35,8 +35,8 @@ The output was:
#$ _TARGET_DIR_=targets/x86_64-linux
#$ TOP=/usr/local/cuda-11.8/bin/..
#$ NVVMIR_LIBRARY_DIR=/usr/local/cuda-11.8/bin/../nvvm/libdevice
#$ LD_LIBRARY_PATH=/usr/local/cuda-11.8/bin/../lib:/usr/local/cuda-11.8/lib64:/tmp/.mount_CursorV5YAoS/usr/lib/:/tmp/.mount_CursorV5YAoS/usr/lib32/:/tmp/.mount_CursorV5YAoS/usr/lib64/:/tmp/.mount_CursorV5YAoS/lib/:/tmp/.mount_CursorV5YAoS/lib/i386-linux-gnu/:/tmp/.mount_CursorV5YAoS/lib/x86_64-linux-gnu/:/tmp/.mount_CursorV5YAoS/lib/aarch64-linux-gnu/:/tmp/.mount_CursorV5YAoS/lib32/:/tmp/.mount_CursorV5YAoS/lib64/:
#$ PATH=/usr/local/cuda-11.8/bin/../nvvm/bin:/usr/local/cuda-11.8/bin:/usr/local/cuda-11.8/bin:/home/mht/anaconda3/bin:/home/mht/anaconda3/condabin:/tmp/.mount_CursorV5YAoS/usr/bin:/tmp/.mount_CursorV5YAoS/usr/sbin:/tmp/.mount_CursorV5YAoS/usr/games:/tmp/.mount_CursorV5YAoS/bin:/tmp/.mount_CursorV5YAoS/sbin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/snap/bin:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts
#$ LD_LIBRARY_PATH=/usr/local/cuda-11.8/bin/../lib:/usr/local/cuda-11.8/lib64:/tmp/.mount_CursorSO8Tmf/usr/lib/:/tmp/.mount_CursorSO8Tmf/usr/lib32/:/tmp/.mount_CursorSO8Tmf/usr/lib64/:/tmp/.mount_CursorSO8Tmf/lib/:/tmp/.mount_CursorSO8Tmf/lib/i386-linux-gnu/:/tmp/.mount_CursorSO8Tmf/lib/x86_64-linux-gnu/:/tmp/.mount_CursorSO8Tmf/lib/aarch64-linux-gnu/:/tmp/.mount_CursorSO8Tmf/lib32/:/tmp/.mount_CursorSO8Tmf/lib64/:
#$ PATH=/usr/local/cuda-11.8/bin/../nvvm/bin:/usr/local/cuda-11.8/bin:/usr/local/cuda-11.8/bin:/home/mht/anaconda3/bin:/home/mht/anaconda3/condabin:/tmp/.mount_CursorSO8Tmf/usr/bin:/tmp/.mount_CursorSO8Tmf/usr/sbin:/tmp/.mount_CursorSO8Tmf/usr/games:/tmp/.mount_CursorSO8Tmf/bin:/tmp/.mount_CursorSO8Tmf/sbin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/snap/bin:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts
#$ INCLUDES="-I/usr/local/cuda-11.8/bin/../targets/x86_64-linux/include"
#$ LIBRARIES= "-L/usr/local/cuda-11.8/bin/../targets/x86_64-linux/lib/stubs" "-L/usr/local/cuda-11.8/bin/../targets/x86_64-linux/lib"
#$ CUDAFE_FLAGS=
@ -60,7 +60,7 @@ Compilation of the CUDA compiler identification source "CMakeCUDACompilerId.cu"
The CUDA compiler identification is NVIDIA, found in "/media/mht/ADATA/repos/cpp_tracker/build/CMakeFiles/3.22.1/CompilerIdCUDA/a.out"
Parsed CUDA nvcc implicit link information from above output:
found 'PATH=' string: [/usr/local/cuda-11.8/bin/../nvvm/bin:/usr/local/cuda-11.8/bin:/usr/local/cuda-11.8/bin:/home/mht/anaconda3/bin:/home/mht/anaconda3/condabin:/tmp/.mount_CursorV5YAoS/usr/bin:/tmp/.mount_CursorV5YAoS/usr/sbin:/tmp/.mount_CursorV5YAoS/usr/games:/tmp/.mount_CursorV5YAoS/bin:/tmp/.mount_CursorV5YAoS/sbin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/snap/bin:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts]
found 'PATH=' string: [/usr/local/cuda-11.8/bin/../nvvm/bin:/usr/local/cuda-11.8/bin:/usr/local/cuda-11.8/bin:/home/mht/anaconda3/bin:/home/mht/anaconda3/condabin:/tmp/.mount_CursorSO8Tmf/usr/bin:/tmp/.mount_CursorSO8Tmf/usr/sbin:/tmp/.mount_CursorSO8Tmf/usr/games:/tmp/.mount_CursorSO8Tmf/bin:/tmp/.mount_CursorSO8Tmf/sbin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/snap/bin:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts]
found 'LIBRARIES=' string: ["-L/usr/local/cuda-11.8/bin/../targets/x86_64-linux/lib/stubs" "-L/usr/local/cuda-11.8/bin/../targets/x86_64-linux/lib"]
considering line: [#$ rm tmp/a_dlink.reg.c]
considering line: [gcc -D__CUDA_ARCH__=520 -D__CUDA_ARCH_LIST__=520 -E -x c++ -DCUDA_DOUBLE_MATH_FUNCTIONS -D__CUDACC__ -D__NVCC__ "-I/usr/local/cuda-11.8/bin/../targets/x86_64-linux/include" -D__CUDACC_VER_MAJOR__=11 -D__CUDACC_VER_MINOR__=8 -D__CUDACC_VER_BUILD__=89 -D__CUDA_API_VER_MAJOR__=11 -D__CUDA_API_VER_MINOR__=8 -D__NVCC_DIAG_PRAGMA_SUPPORT__=1 -include "cuda_runtime.h" -m64 "CMakeCUDACompilerId.cu" -o "tmp/CMakeCUDACompilerId.cpp1.ii" ]
@ -108,7 +108,7 @@ Parsed CUDA nvcc implicit link information from above output:
Parsed CUDA nvcc include information from above output:
found 'PATH=' string: [/usr/local/cuda-11.8/bin/../nvvm/bin:/usr/local/cuda-11.8/bin:/usr/local/cuda-11.8/bin:/home/mht/anaconda3/bin:/home/mht/anaconda3/condabin:/tmp/.mount_CursorV5YAoS/usr/bin:/tmp/.mount_CursorV5YAoS/usr/sbin:/tmp/.mount_CursorV5YAoS/usr/games:/tmp/.mount_CursorV5YAoS/bin:/tmp/.mount_CursorV5YAoS/sbin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/snap/bin:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts]
found 'PATH=' string: [/usr/local/cuda-11.8/bin/../nvvm/bin:/usr/local/cuda-11.8/bin:/usr/local/cuda-11.8/bin:/home/mht/anaconda3/bin:/home/mht/anaconda3/condabin:/tmp/.mount_CursorSO8Tmf/usr/bin:/tmp/.mount_CursorSO8Tmf/usr/sbin:/tmp/.mount_CursorSO8Tmf/usr/games:/tmp/.mount_CursorSO8Tmf/bin:/tmp/.mount_CursorSO8Tmf/sbin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/snap/bin:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts:/home/mht/.local/share/JetBrains/Toolbox/scripts]
found 'LIBRARIES=' string: ["-L/usr/local/cuda-11.8/bin/../targets/x86_64-linux/lib/stubs" "-L/usr/local/cuda-11.8/bin/../targets/x86_64-linux/lib"]
considering line: [#$ rm tmp/a_dlink.reg.c]
considering line: [gcc -D__CUDA_ARCH__=520 -D__CUDA_ARCH_LIST__=520 -E -x c++ -DCUDA_DOUBLE_MATH_FUNCTIONS -D__CUDACC__ -D__NVCC__ "-I/usr/local/cuda-11.8/bin/../targets/x86_64-linux/include" -D__CUDACC_VER_MAJOR__=11 -D__CUDACC_VER_MINOR__=8 -D__CUDACC_VER_BUILD__=89 -D__CUDA_API_VER_MAJOR__=11 -D__CUDA_API_VER_MINOR__=8 -D__NVCC_DIAG_PRAGMA_SUPPORT__=1 -include "cuda_runtime.h" -m64 "CMakeCUDACompilerId.cu" -o "tmp/CMakeCUDACompilerId.cpp1.ii" ]
@ -159,10 +159,10 @@ Parsed CUDA nvcc include information from above output:
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@ -1092,6 +1834,8 @@ CMakeFiles/bb_regressor.dir/cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_im
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/usr/bin/ar qc libbb_regressor.a CMakeFiles/bb_regressor.dir/cimp/bb_regressor/bb_regressor.cpp.o CMakeFiles/bb_regressor.dir/cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.cu.o CMakeFiles/bb_regressor.dir/cimp/bb_regressor/utils.cpp.o
/usr/bin/ranlib libbb_regressor.a

1
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27
build/Makefile
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@ -297,6 +297,30 @@ cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.cu.s:
$(MAKE) $(MAKESILENT) -f CMakeFiles/bb_regressor.dir/build.make CMakeFiles/bb_regressor.dir/cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.cu.s
.PHONY : cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.cu.s
cimp/bb_regressor/utils.o: cimp/bb_regressor/utils.cpp.o
.PHONY : cimp/bb_regressor/utils.o
# target to build an object file
cimp/bb_regressor/utils.cpp.o:
$(MAKE) $(MAKESILENT) -f CMakeFiles/bb_regressor.dir/build.make CMakeFiles/bb_regressor.dir/cimp/bb_regressor/utils.cpp.o
.PHONY : cimp/bb_regressor/utils.cpp.o
cimp/bb_regressor/utils.i: cimp/bb_regressor/utils.cpp.i
.PHONY : cimp/bb_regressor/utils.i
# target to preprocess a source file
cimp/bb_regressor/utils.cpp.i:
$(MAKE) $(MAKESILENT) -f CMakeFiles/bb_regressor.dir/build.make CMakeFiles/bb_regressor.dir/cimp/bb_regressor/utils.cpp.i
.PHONY : cimp/bb_regressor/utils.cpp.i
cimp/bb_regressor/utils.s: cimp/bb_regressor/utils.cpp.s
.PHONY : cimp/bb_regressor/utils.s
# target to generate assembly for a file
cimp/bb_regressor/utils.cpp.s:
$(MAKE) $(MAKESILENT) -f CMakeFiles/bb_regressor.dir/build.make CMakeFiles/bb_regressor.dir/cimp/bb_regressor/utils.cpp.s
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cimp/classifier/classifier.o: cimp/classifier/classifier.cpp.o
.PHONY : cimp/classifier/classifier.o
@ -442,6 +466,9 @@ help:
@echo "... cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.o"
@echo "... cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.i"
@echo "... cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.s"
@echo "... cimp/bb_regressor/utils.o"
@echo "... cimp/bb_regressor/utils.i"
@echo "... cimp/bb_regressor/utils.s"
@echo "... cimp/classifier/classifier.o"
@echo "... cimp/classifier/classifier.i"
@echo "... cimp/classifier/classifier.s"

BIN
build/libbb_regressor.a
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BIN
build/tracking_demo
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20
cimp/bb_regressor/bb_regressor.cpp
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@ -512,6 +512,7 @@ void BBRegressor::to(torch::Device device) {
// Get IoU features from backbone features
std::vector<torch::Tensor> BBRegressor::get_iou_feat(std::vector<torch::Tensor> feat2_input, int sample_idx) {
std::cout << "[DEBUG] Entered get_iou_feat with sample_idx=" << sample_idx << std::endl;
std::cout << "[DEBUG] sample_idx value before if: " << sample_idx << std::endl;
torch::Tensor feat3_t_original = feat2_input[0];
torch::Tensor feat4_t_original = feat2_input[1];
@ -544,11 +545,20 @@ std::vector<torch::Tensor> BBRegressor::get_iou_feat(std::vector<torch::Tensor>
auto c3_1t_bn = conv3_1t[1]->as<torch::nn::BatchNorm2d>()->forward(c3_1t_conv);
auto c3_1t_relu = conv3_1t[2]->as<torch::nn::ReLU>()->forward(c3_1t_bn);
if (sample_idx == 0) {
std::cout << "[DEBUG] About to save debug tensors for sample_idx == 0" << std::endl;
save_tensor_to_file(c3_1t_bn.cpu(), "test/output/bb_regressor/sample_0_debug_conv3_1t_bn.pt");
save_tensor_to_file(c3_1t_relu.cpu(), "test/output/bb_regressor/sample_0_debug_conv3_1t_relu.pt");
std::cout << "conv3_1t_bn: dtype=" << c3_1t_bn.dtype() << ", device=" << c3_1t_bn.device() << ", shape=" << c3_1t_bn.sizes() << std::endl;
std::cout << "conv3_1t_relu: dtype=" << c3_1t_relu.dtype() << ", device=" << c3_1t_relu.device() << ", shape=" << c3_1t_relu.sizes() << std::endl;
std::cout << "[DEBUG] sample_idx=" << sample_idx << " about to save conv3_1t_bn. Defined: " << c3_1t_bn.defined() << ", device: " << c3_1t_bn.device() << ", dtype: " << c3_1t_bn.dtype() << ", shape: " << c3_1t_bn.sizes() << std::endl;
try {
save_tensor_to_file(c3_1t_bn.cpu(), "test/output/bb_regressor/sample_0_debug_conv3_1t_bn.pt");
std::cout << "[DEBUG] Finished saving conv3_1t_bn." << std::endl;
} catch (const std::exception& e) {
std::cerr << "[ERROR] Exception saving conv3_1t_bn: " << e.what() << std::endl;
}
std::cout << "[DEBUG] sample_idx=" << sample_idx << " about to save conv3_1t_relu. Defined: " << c3_1t_relu.defined() << ", device: " << c3_1t_relu.device() << ", dtype: " << c3_1t_relu.dtype() << ", shape: " << c3_1t_relu.sizes() << std::endl;
try {
save_tensor_to_file(c3_1t_relu.cpu(), "test/output/bb_regressor/sample_0_debug_conv3_1t_relu.pt");
std::cout << "[DEBUG] Finished saving conv3_1t_relu." << std::endl;
} catch (const std::exception& e) {
std::cerr << "[ERROR] Exception saving conv3_1t_relu: " << e.what() << std::endl;
}
}
auto c3_t_1 = c3_1t_relu;
// conv3_2t

2
cimp/bb_regressor/bb_regressor.h
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@ -77,7 +77,7 @@ public:
void eval();
// Get IoU features from backbone features
std::vector<torch::Tensor> get_iou_feat(std::vector<torch::Tensor> feat);
std::vector<torch::Tensor> get_iou_feat(std::vector<torch::Tensor> feat, int sample_idx = -1);
// Get modulation vectors for target
std::vector<torch::Tensor> get_modulation(std::vector<torch::Tensor> feat, torch::Tensor bb);

14
cimp/bb_regressor/utils.cpp
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@ -0,0 +1,14 @@
#include "utils.h"
#include <torch/torch.h>
#include <string>
#include <iostream>
void save_tensor_to_file(const torch::Tensor& tensor, const std::string& file_path) {
try {
std::cout << "[DEBUG] Entering save_tensor_to_file for: " << file_path << ", tensor shape: " << tensor.sizes() << std::endl;
torch::save(tensor, file_path);
std::cout << "Saved tensor to: " << file_path << std::endl;
} catch (const c10::Error& e) {
std::cerr << "Error saving tensor to " << file_path << ": " << e.what() << std::endl;
}
}

5
cimp/bb_regressor/utils.h
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@ -0,0 +1,5 @@
#pragma once
#include <torch/torch.h>
#include <string>
void save_tensor_to_file(const torch::Tensor& tensor, const std::string& file_path);

51
compare_bbreg_debug_tensors.py
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@ -0,0 +1,51 @@
import torch
import os
import numpy as np
from torch.nn.functional import cosine_similarity
def load_tensor(path):
obj = torch.load(path, map_location='cpu', weights_only=False)
if isinstance(obj, torch.Tensor):
return obj
# Try to extract tensor from JIT module
if hasattr(obj, 'tensor') and isinstance(obj.tensor, torch.Tensor):
return obj.tensor
if hasattr(obj, 'data') and isinstance(obj.data, torch.Tensor):
return obj.data
# Try named_parameters or named_buffers
for name, p in getattr(obj, 'named_parameters', lambda: [])():
if isinstance(p, torch.Tensor):
return p
for name, b in getattr(obj, 'named_buffers', lambda: [])():
if isinstance(b, torch.Tensor):
return b
raise RuntimeError(f"Could not extract tensor from {path}")
def compare_tensors(tensor_py, tensor_cpp, label):
a = tensor_py.float().cpu().contiguous().view(-1)
b = tensor_cpp.float().cpu().contiguous().view(-1)
if a.shape != b.shape:
print(f"{label}: Shape mismatch: {a.shape} vs {b.shape}")
return
cos_sim = torch.nn.functional.cosine_similarity(a, b, dim=0).item()
mae = torch.mean(torch.abs(a - b)).item()
max_abs = torch.max(torch.abs(a - b)).item()
print(f"{label}: cos_sim={cos_sim:.8f}, MAE={mae:.8e}, max_abs={max_abs:.8e}")
def main():
pairs = [
("test/output_py/bb_regressor/sample_0_debug_conv3_1t_py.pt", "test/output/bb_regressor/sample_0_debug_conv3_1t.pt", "conv3_1t"),
("test/output_py/bb_regressor/sample_0_debug_conv3_2t_py.pt", "test/output/bb_regressor/sample_0_debug_conv3_2t.pt", "conv3_2t"),
("test/output_py/bb_regressor/sample_0_debug_conv4_1t_py.pt", "test/output/bb_regressor/sample_0_debug_conv4_1t.pt", "conv4_1t"),
("test/output_py/bb_regressor/sample_0_debug_conv4_2t_py.pt", "test/output/bb_regressor/sample_0_debug_conv4_2t.pt", "conv4_2t"),
]
for py_path, cpp_path, label in pairs:
if not (os.path.exists(py_path) and os.path.exists(cpp_path)):
print(f"{label}: Missing file(s): {py_path if not os.path.exists(py_path) else ''} {cpp_path if not os.path.exists(cpp_path) else ''}")
continue
tensor_py = load_tensor(py_path)
tensor_cpp = load_tensor(cpp_path)
compare_tensors(tensor_py, tensor_cpp, label)
if __name__ == "__main__":
main()

45
compare_bbreg_weights.py
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@ -0,0 +1,45 @@
import torch
import os
from ltr.models.bbreg.atom_iou_net import AtomIoUNet
def compare_tensors(a, b, label):
a = a.float().cpu().contiguous().view(-1)
b = b.float().cpu().contiguous().view(-1)
if a.shape != b.shape:
print(f"{label}: Shape mismatch: {a.shape} vs {b.shape}")
return
cos_sim = torch.nn.functional.cosine_similarity(a, b, dim=0).item()
mae = torch.mean(torch.abs(a - b)).item()
max_abs = torch.max(torch.abs(a - b)).item()
print(f"{label}: cos_sim={cos_sim:.8f}, MAE={mae:.8e}, max_abs={max_abs:.8e}")
def main():
# Layer names and file patterns
layers = [
("conv3_1t", 0),
("conv3_2t", 0),
("conv4_1t", 0),
("conv4_2t", 0),
]
model_dir = "exported_weights/bb_regressor"
# Load Python model
model = AtomIoUNet(input_dim=(512, 1024), pred_input_dim=(256, 256), pred_inter_dim=(256, 256))
# Load weights from exported files
state_dict = {}
for lname, idx in layers:
wfile = os.path.join(model_dir, f"{lname}_{idx}_weight.pt")
bfile = os.path.join(model_dir, f"{lname}_{idx}_bias.pt")
state_dict[f"{lname}.{idx}.weight"] = torch.load(wfile, map_location='cpu', weights_only=False)
state_dict[f"{lname}.{idx}.bias"] = torch.load(bfile, map_location='cpu', weights_only=False)
model.load_state_dict(state_dict, strict=False)
# Compare each weight and bias
for lname, idx in layers:
py_w = getattr(getattr(model, lname)[idx], 'weight').data
py_b = getattr(getattr(model, lname)[idx], 'bias').data
cpp_w = state_dict[f"{lname}.{idx}.weight"]
cpp_b = state_dict[f"{lname}.{idx}.bias"]
compare_tensors(py_w, cpp_w, f"{lname}_weight")
compare_tensors(py_b, cpp_b, f"{lname}_bias")
if __name__ == "__main__":
main()

45
compare_resnet_features_debug.py
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@ -0,0 +1,45 @@
import torch
import os
def load_tensor(path):
obj = torch.load(path, map_location='cpu', weights_only=False)
if isinstance(obj, torch.Tensor):
return obj
if hasattr(obj, 'tensor') and isinstance(obj.tensor, torch.Tensor):
return obj.tensor
if hasattr(obj, 'data') and isinstance(obj.data, torch.Tensor):
return obj.data
for name, p in getattr(obj, 'named_parameters', lambda: [])():
if isinstance(p, torch.Tensor):
return p
for name, b in getattr(obj, 'named_buffers', lambda: [])():
if isinstance(b, torch.Tensor):
return b
raise RuntimeError(f"Could not extract tensor from {path}")
def compare_tensors(tensor_py, tensor_cpp, label):
a = tensor_py.float().cpu().contiguous().view(-1)
b = tensor_cpp.float().cpu().contiguous().view(-1)
if a.shape != b.shape:
print(f"{label}: Shape mismatch: {a.shape} vs {b.shape}")
return
cos_sim = torch.nn.functional.cosine_similarity(a, b, dim=0).item()
mae = torch.mean(torch.abs(a - b)).item()
max_abs = torch.max(torch.abs(a - b)).item()
print(f"{label}: cos_sim={cos_sim:.8f}, MAE={mae:.8e}, max_abs={max_abs:.8e}")
def main():
pairs = [
("test/output_py/resnet_py/sample_0/layer2.pt", "test/output/resnet/sample_0_layer2.pt", "layer2"),
("test/output_py/resnet_py/sample_0/layer3.pt", "test/output/resnet/sample_0_layer3.pt", "layer3"),
]
for py_path, cpp_path, label in pairs:
if not (os.path.exists(py_path) and os.path.exists(cpp_path)):
print(f"{label}: Missing file(s): {py_path if not os.path.exists(py_path) else ''} {cpp_path if not os.path.exists(cpp_path) else ''}")
continue
tensor_py = load_tensor(py_path)
tensor_cpp = load_tensor(cpp_path)
compare_tensors(tensor_py, tensor_cpp, label)
if __name__ == "__main__":
main()

BIN
ltr/models/backbone/__pycache__/resnet.cpython-37.pyc
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BIN
ltr/models/bbreg/__pycache__/atom_iou_net.cpython-311.pyc
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ltr/models/bbreg/__pycache__/atom_iou_net.cpython-37.pyc
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pytracking/features/__pycache__/net_wrappers.cpython-37.pyc
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pytracking/utils/__pycache__/params.cpython-37.pyc
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9
test/compare_models.py
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@ -764,6 +764,15 @@ class ComparisonRunner:
processed_input_tensor = input_tensor.to(self.device) # Ensure device
# --- END REINSTATED INPUT LOADING AND PREPROCESSING ---
# --- Save preprocessed input for sample 0 ---
if sample_idx == 0:
preprocessed_dir = Path(self.cpp_output_dir) / 'resnet'
preprocessed_dir.mkdir(parents=True, exist_ok=True)
py_preprocessed_path = preprocessed_dir / f'sample_{sample_idx}_image_preprocessed_python.pt'
torch.save(processed_input_tensor.cpu(), py_preprocessed_path)
print(f"Saved Python preprocessed image for sample {sample_idx} to {py_preprocessed_path}")
# --- END save preprocessed input ---
# Initialize dictionaries to store Python-side outputs for the current sample
python_outputs = {} # To store outputs from the Python model for this sample

74
test/model_comparison/bbreg_comparison.py
View File

@ -2,6 +2,25 @@ import os
import torch
import numpy as np
def extract_tensor_from_jit(obj):
# Try to extract a tensor from a TorchScript module
if isinstance(obj, torch.Tensor):
return obj
# Try .tensor attribute (used in some containers)
if hasattr(obj, 'tensor') and isinstance(obj.tensor, torch.Tensor):
return obj.tensor
# Try named_parameters
if hasattr(obj, 'named_parameters'):
params = list(obj.named_parameters())
if params:
return params[0][1]
# Try named_buffers
if hasattr(obj, 'named_buffers'):
bufs = list(obj.named_buffers())
if bufs:
return bufs[0][1]
return None
def compare_debug_tensors(cpp_dir, py_dir, sample_idx=0, verbose=True):
"""
Compare C++ and Python debug tensors for BB regressor (BatchNorm and ReLU outputs).
@ -20,35 +39,32 @@ def compare_debug_tensors(cpp_dir, py_dir, sample_idx=0, verbose=True):
for stage in stages:
cpp_file = os.path.join(cpp_dir, f"sample_{sample_idx}_debug_{layer}_{stage}.pt")
py_file = os.path.join(py_dir, f"sample_{sample_idx}_debug_{layer}_{stage}_py.pt")
if not os.path.exists(cpp_file) or not os.path.exists(py_file):
results[f"{layer}_{stage}"] = None
if verbose:
print(f"[WARN] Missing file: {cpp_file if not os.path.exists(cpp_file) else py_file}")
continue
cpp_tensor = torch.load(cpp_file, map_location="cpu")
py_tensor = torch.load(py_file, map_location="cpu")
cpp_np = cpp_tensor.cpu().detach().numpy().astype(np.float32)
py_np = py_tensor.cpu().detach().numpy().astype(np.float32)
if cpp_np.shape != py_np.shape:
results[f"{layer}_{stage}"] = None
if verbose:
print(f"[WARN] Shape mismatch for {layer}_{stage}: C++ {cpp_np.shape}, Py {py_np.shape}")
cpp_tensor = None
py_tensor = None
if os.path.exists(cpp_file):
try:
obj = torch.load(cpp_file, map_location="cpu", weights_only=False)
cpp_tensor = extract_tensor_from_jit(obj)
except Exception as e:
print(f"[WARN] Could not load {cpp_file}: {e}")
else:
print(f"[WARN] Missing file: {cpp_file}")
if os.path.exists(py_file):
try:
obj = torch.load(py_file, map_location="cpu", weights_only=False)
py_tensor = extract_tensor_from_jit(obj)
except Exception as e:
print(f"[WARN] Could not load {py_file}: {e}")
else:
print(f"[WARN] Missing file: {py_file}")
if cpp_tensor is None or py_tensor is None:
print(f"Warning: Cannot compare 'BBReg Debug_{layer.capitalize()}' for sample {sample_idx}, one or both tensors are None.")
continue
flat_cpp = cpp_np.flatten()
flat_py = py_np.flatten()
mae = np.mean(np.abs(flat_cpp - flat_py))
max_err = np.max(np.abs(flat_cpp - flat_py))
l2_cpp = np.linalg.norm(flat_cpp)
l2_py = np.linalg.norm(flat_py)
cos_sim = np.dot(flat_cpp, flat_py) / (l2_cpp * l2_py) if l2_cpp > 0 and l2_py > 0 else float('nan')
results[f"{layer}_{stage}"] = {
"mae": mae,
"max_err": max_err,
"cos_sim": cos_sim,
"l2_cpp": l2_cpp,
"l2_py": l2_py,
"shape": cpp_np.shape
}
# Flatten and compare
cpp_flat = cpp_tensor.detach().cpu().numpy().flatten()
py_flat = py_tensor.detach().cpu().numpy().flatten()
cos_sim = np.dot(cpp_flat, py_flat) / (np.linalg.norm(cpp_flat) * np.linalg.norm(py_flat) + 1e-12)
results[(layer, stage)] = cos_sim
if verbose:
print(f"{layer}_{stage}: cos_sim={cos_sim:.6f}, mae={mae:.4e}, max_err={max_err:.4e}, shape={cpp_np.shape}")
print(f"Cosine similarity for {layer} {stage}: {cos_sim:.6f}")
return results

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test/output_py/bb_regressor/sample_0_debug_conv3_1t_bn_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv3_1t_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv3_1t_relu_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv3_2t_bn_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv3_2t_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv3_2t_relu_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv4_1t_bn_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv4_1t_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv4_1t_relu_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv4_2t_bn_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv4_2t_py.pt
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test/output_py/bb_regressor/sample_0_debug_conv4_2t_relu_py.pt
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