initial commit

README.md

-# SAMix
+# FC-NCCL
 
 Official code for:  
-**"SAMix: Calibrated and Accurate Continual Learning via Sphere-Adaptive Mixup and Neural Collapse"**
-
+**"Memory-efficient Continual Learning with Neural Collapse Contrastive"** (WACV2025)
+    
 ---
 
 ## 🛠️ Prerequisites
@@ -82,59 +82,27 @@ Official code for:
 
 ### 4.1. CIFAR-10
 
-- **FC-NCCL with SAMix**
-    ```bash
-    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/fc_nccl/fc_nccl_samix_cf10.sh
-    ```
-- **TA-NCCL with SAMix**
     ```bash
-    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/ta_nccl/ta_nccl_samix_cf10.sh
+    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/fc_nccl/fc_nccl_cf10.sh
     ```
 
+
 ### 4.2. CIFAR-100
 
-- **FC-NCCL with SAMix**
-    ```bash
-    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/fc_nccl/fc_nccl_samix_cf100.sh
-    ```
-- **TA-NCCL with SAMix**
     ```bash
-    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/ta_nccl/ta_nccl_samix_cf100.sh
+    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/fc_nccl/fc_nccl_cf100.sh
     ```
 
 ### 4.3. Tiny-ImageNet
 
-- **FC-NCCL with SAMix**
-    ```bash
-    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/fc_nccl/fc_nccl_samix_tiny_imagenet.sh
-    ```
-- **TA-NCCL with SAMix**
     ```bash
-    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/ta_nccl/ta_nccl_samix_tiny_imagenet.sh
+    MEM_SIZE=200 LOG_FOLDER_ZERO_MEM=not-use bash scripts/train/fc_nccl/fc_nccl_tiny_imagenet.sh
     ```
 
-> **Note 1:**  
-> Set `LOG_FOLDER_ZERO_MEM` to the log folder containing 200 auxiliary samples if `MEM_SIZE=0` (memory-free setting).
 
-> **Note 2:**  
-> **To run without SAMix:**
-> 1. Remove these arguments:
->     ```bash
->     --samix \
->     --loss_normal_samples fnc2 \
->     --weight_samix_loss 5.0 \
->     ```
-> 2. Change `--loss nc_samix` to:
->     ```bash
->     --loss fnc2
->     ```
->     or
->     ```bash
->     --loss dr
->     ```
-> 3. If using `--loss fnc2`, add `--focal_gamma` and `--main_mark`
+> **Note:**  
+> Set `LOG_FOLDER_ZERO_MEM` to the log folder containing 200 auxiliary samples if `MEM_SIZE=0` (memory-free setting).
 
----
 
 ## 🧪 Evaluation
 
@@ -157,22 +125,6 @@ CHECKPOINT_FOLDER=/path/check/point/folder LOG_FOLDER=/path/log/folder/ bash scr
 
 ---
 
-## 📊 Network Calibration
-
-**Modify bash file:** "scripts/calibration/run_calibration.sh", and then run:
-
-```bash
-    bash scripts/calibration/run_calibration.sh
-```
-
-This will compute and display:
-- Expected Calibration Error (ECE) each task
-- Overconfidence Error (OE) each task
-- Average Expected Calibration Error (AECE) 
-- Average Overconfidence Error (AOE)
-
----
-
 ## 📂 Project Structure
 
 ```
@@ -216,4 +168,3 @@ root_path: in 'root_save_folder' in config/base.yaml
 │       │   │   │── prototypes_dim={d}_k={n_cls}_seed={seed}.npy
 │       │   │   │── subset_indices_random_{i}.npy
 │       │   │   │── replay_indices_random_{i}.npy
-

scripts/calibration/run_calibration.sh

-#!/bin/bash
-# Run calibration computation
-python main_compute_calibration.py \
-    --dataset cifar10 \
-    --target_task 4 \
-    --n_bins 10 \
-    --checkpoint_path \path\checkpoint_name.pth \
-    --classifier_path \path\classifier.pth
\ No newline at end of file

scripts/train/fc_nccl/fc_nccl_samix_cf10.sh → scripts/train/fc_nccl/fc_nccl_cf10.sh

@@ -17,14 +17,11 @@ python3 -W ignore main_train.py \
   --wandb \
   --wandb_project_name your_project_name \
   --wandb_entity your_entity \
-  --job_run_name fcnccl-samix-cf10-m-${MEM_SIZE} \
+  --job_run_name fcnccl-cf10-m-${MEM_SIZE} \
   --distillation hsd \
   --log_folder_zero_mem ${LOG_FOLDER_ZERO_MEM} \
-  --loss nc_samix \
-  --loss_normal_samples fnc2 \
-  --weight_samix_loss 5.0 \
+  --loss fnc2 \
   --filter_distillation_point \
-  --samix \
   --predictor_hidden_dim 128 \
   --main_mark 30 \
   --focal_gamma 1
\ No newline at end of file

scripts/train/fc_nccl/fc_nccl_samix_cf100.sh → scripts/train/fc_nccl/fc_nccl_cf100.sh

@@ -17,14 +17,11 @@ python3 -W ignore main_train.py \
   --wandb \
   --wandb_project_name your_project_name \
   --wandb_entity your_entity \
-  --job_run_name fcnccl-samix-cf100-m-${MEM_SIZE} \
+  --job_run_name fcnccl-cf100-m-${MEM_SIZE} \
   --distillation hsd \
   --log_folder_zero_mem ${LOG_FOLDER_ZERO_MEM} \
-  --loss nc_samix \
-  --loss_normal_samples fnc2 \
-  --weight_samix_loss 5.0 \
+  --loss fnc2 \
   --filter_distillation_point \
-  --samix \
   --predictor_hidden_dim 128 \
   --main_mark 30 \
   --focal_gamma 4
\ No newline at end of file

scripts/train/fc_nccl/fc_nccl_samix_tiny_imagenet.sh → scripts/train/fc_nccl/fc_nccl_tiny_imagenet.sh

@@ -17,14 +17,11 @@ python3 -W ignore main_train.py \
   --wandb \
   --wandb_project_name your_project_name \
   --wandb_entity your_entity \
-  --job_run_name fcnccl-samix-tiny-imagenet-m-${MEM_SIZE} \
+  --job_run_name fcnccl-tiny-imagenet-m-${MEM_SIZE} \
   --distillation hsd \
   --log_folder_zero_mem ${LOG_FOLDER_ZERO_MEM} \
-  --loss nc_samix \
-  --loss_normal_samples fnc2 \
-  --weight_samix_loss 5.0 \
+  --loss fnc2 \
   --filter_distillation_point \
-  --samix \
   --predictor_hidden_dim 256 \
   --main_mark 20 \
   --focal_gamma 4
\ No newline at end of file

scripts/train/ta_nccl/ta_nccl_samix_cf10.sh

-python3 -W ignore main_train.py \
-  --seed 1234 \
-  --batch_size 512 \
-  --model resnet18 \
-  --dataset cifar10 \
-  --mem_size $MEM_SIZE \
-  --epochs 100 \
-  --start_epoch 500 \
-  --learning_rate 0.5 \
-  --temperature 0.5 \
-  --current_temp 0.2 \
-  --past_temp 0.01  \
-  --current_temp_sprd 0.2  \
-  --past_temp_sprd 0.1  \
-  --cosine \
-  --num_workers 16 \
-  --wandb \
-  --wandb_project_name your_project_name \
-  --wandb_entity your_entity \
-  --job_run_name tanccl-samix-cf00-m-${MEM_SIZE} \
-  --distillation hsd \
-  --log_folder_zero_mem ${LOG_FOLDER_ZERO_MEM} \
-  --loss nc_samix \
-  --loss_normal_samples dr \
-  --weight_samix_loss 5.0 \
-  --filter_distillation_point \
-  --samix \
-  --predictor_hidden_dim 128

scripts/train/ta_nccl/ta_nccl_samix_cf100.sh

-python3 -W ignore main_train.py \
-  --seed 1234 \
-  --batch_size 512 \
-  --model resnet18 \
-  --dataset cifar100 \
-  --mem_size $MEM_SIZE \
-  --epochs 100 \
-  --start_epoch 500 \
-  --learning_rate 0.5 \
-  --temperature 0.5 \
-  --current_temp 0.2 \
-  --past_temp 0.01  \
-  --current_temp_sprd 0.2  \
-  --past_temp_sprd 0.1  \
-  --cosine \
-  --num_workers 16 \
-  --wandb \
-  --wandb_project_name your_project_name \
-  --wandb_entity your_entity \
-  --job_run_name tanccl-samix-cf100-m-${MEM_SIZE} \
-  --distillation hsd \
-  --log_folder_zero_mem ${LOG_FOLDER_ZERO_MEM} \
-  --loss nc_samix \
-  --loss_normal_samples dr \
-  --weight_samix_loss 5.0 \
-  --filter_distillation_point \
-  --samix \
-  --predictor_hidden_dim 128

scripts/train/ta_nccl/ta_nccl_samix_tiny_imagenet.sh

-python3 -W ignore main_train.py \
-  --seed 1234 \
-  --batch_size 512 \
-  --model resnet18 \
-  --dataset tiny-imagenet \
-  --mem_size $MEM_SIZE \
-  --epochs 50 \
-  --start_epoch 500 \
-  --learning_rate 0.1 \
-  --temperature 0.5 \
-  --current_temp 0.1 \
-  --past_temp 0.1  \
-  --current_temp_sprd 0.2  \
-  --past_temp_sprd 0.1  \
-  --cosine \
-  --num_workers 16 \
-  --wandb \
-  --wandb_project_name your_project_name \
-  --wandb_entity your_entity \
-  --job_run_name tanccl-samix-tiny-imagenet-m-${MEM_SIZE} \
-  --distillation hsd \
-  --log_folder_zero_mem ${LOG_FOLDER_ZERO_MEM} \
-  --loss nc_samix \
-  --loss_normal_samples dr \
-  --weight_samix_loss 5.0 \
-  --filter_distillation_point \
-  --samix \
-  --predictor_hidden_dim 256