Adapt GUI to v3.3.10 of BiaPy

Author: danifranco

biapy_check_configuration.py

@@ -1,4 +1,4 @@
-## Copied from BiaPy commit: 5505d3e3c0499fbed2e4f162e665a529931ca110
+## Copied from BiaPy commit: a0f3ee1e03b9e5a7d749ca029d4e8dcecc02adc1 (3.3.10)
 import os
 import numpy as np
 import collections
@@ -10,6 +10,9 @@ def check_configuration(cfg, jobname, check_data_paths=True):
     Check if the configuration is good. 
     """
 
+    if cfg.SYSTEM.NUM_WORKERS < 0:
+        raise ValueError("'SYSTEM.NUM_WORKERS' can not be less than 0")
+
     dim_count = 2 if cfg.PROBLEM.NDIM == '2D' else 3
 
     # Adjust overlap and padding in the default setting if it was not set
@@ -148,8 +151,8 @@ def check_configuration(cfg, jobname, check_data_paths=True):
 
     #### General checks ####
     assert cfg.PROBLEM.NDIM in ['2D', '3D'], "Problem needs to be '2D' or '3D'"
-    assert cfg.PROBLEM.TYPE in ['SEMANTIC_SEG', 'INSTANCE_SEG', 'CLASSIFICATION', 'DETECTION', 'DENOISING', 'SUPER_RESOLUTION', 'SELF_SUPERVISED'],\
-        "PROBLEM.TYPE not in ['SEMANTIC_SEG', 'INSTANCE_SEG', 'CLASSIFICATION', 'DETECTION', 'DENOISING', 'SUPER_RESOLUTION', 'SELF_SUPERVISED']"
+    assert cfg.PROBLEM.TYPE in ['SEMANTIC_SEG', 'INSTANCE_SEG', 'CLASSIFICATION', 'DETECTION', 'DENOISING', 'SUPER_RESOLUTION', 'SELF_SUPERVISED', 'IMAGE_TO_IMAGE'],\
+        "PROBLEM.TYPE not in ['SEMANTIC_SEG', 'INSTANCE_SEG', 'CLASSIFICATION', 'DETECTION', 'DENOISING', 'SUPER_RESOLUTION', 'SELF_SUPERVISED', 'IMAGE_TO_IMAGE']"
 
     if cfg.PROBLEM.NDIM == '3D' and cfg.TEST.FULL_IMG:
         print("WARNING: TEST.FULL_IMG == True while using PROBLEM.NDIM == '3D'. As 3D images are usually 'huge'"
@@ -300,9 +303,11 @@ def check_configuration(cfg, jobname, check_data_paths=True):
 
     #### Super-resolution ####
     elif cfg.PROBLEM.TYPE == 'SUPER_RESOLUTION':
-        if cfg.PROBLEM.SUPER_RESOLUTION.UPSCALING == 1:
+        if not( cfg.PROBLEM.SUPER_RESOLUTION.UPSCALING ):
             raise ValueError("Resolution scale must be provided with 'PROBLEM.SUPER_RESOLUTION.UPSCALING' variable")
-        assert cfg.PROBLEM.SUPER_RESOLUTION.UPSCALING in [2, 4], "PROBLEM.SUPER_RESOLUTION.UPSCALING not in [2, 4]"
+        assert all( i > 0 for i in cfg.PROBLEM.SUPER_RESOLUTION.UPSCALING), "'PROBLEM.SUPER_RESOLUTION.UPSCALING' are not positive integers"
+        if len(cfg.PROBLEM.SUPER_RESOLUTION.UPSCALING) != dim_count:
+            raise ValueError(f"'PROBLEM.SUPER_RESOLUTION.UPSCALING' needs to be a tuple of {dim_count} integers")
         if cfg.MODEL.SOURCE == "torchvision":
             raise ValueError("'MODEL.SOURCE' as 'torchvision' is not available in super-resolution workflow")
         if cfg.DATA.NORMALIZATION.TYPE != "div":
@@ -539,15 +544,7 @@ def check_configuration(cfg, jobname, check_data_paths=True):
 
         # Adjust Z_DOWN values to feature maps
         if all(x == 0 for x in cfg.MODEL.Z_DOWN):
-                opts.extend(['MODEL.Z_DOWN', (2,)*(len(cfg.MODEL.FEATURE_MAPS)-1)])
-                opts.extend(['MODEL.Z_DOWN', (2,)*(len(cfg.MODEL.FEATURE_MAPS)-1)])
-        elif (cfg.PROBLEM.TYPE == 'SUPER_RESOLUTION' and cfg.PROBLEM.NDIM == '3D') and \
-            any(x != 1 for x in cfg.MODEL.Z_DOWN):
-            raise ValueError("'MODEL.Z_DOWN' != 1 not allowed in super-resolution workflow")
             opts.extend(['MODEL.Z_DOWN', (2,)*(len(cfg.MODEL.FEATURE_MAPS)-1)])
-        elif (cfg.PROBLEM.TYPE == 'SUPER_RESOLUTION' and cfg.PROBLEM.NDIM == '3D') and \
-            any(x != 1 for x in cfg.MODEL.Z_DOWN):
-            raise ValueError("'MODEL.Z_DOWN' != 1 not allowed in super-resolution workflow")
         elif any([False for x in cfg.MODEL.Z_DOWN if x != 1 and x != 2]):
             raise ValueError("'MODEL.Z_DOWN' needs to be 1 or 2")
         else:
@@ -556,6 +553,10 @@ def check_configuration(cfg, jobname, check_data_paths=True):
             elif len(cfg.MODEL.FEATURE_MAPS)-1 != len(cfg.MODEL.Z_DOWN):
                 raise ValueError("'MODEL.FEATURE_MAPS' length minus one and 'MODEL.Z_DOWN' length must be equal")
 
+    # Correct UPSCALING for other workflows than SR
+    if len(cfg.PROBLEM.SUPER_RESOLUTION.UPSCALING) == 0:
+        opts.extend(['PROBLEM.SUPER_RESOLUTION.UPSCALING', (1,)*dim_count])
+
     if len(opts) > 0:
         cfg.merge_from_list(opts)
 

biapy_config.py

@@ -1,6 +1,5 @@
-## Copied from BiaPy commit: 5505d3e3c0499fbed2e4f162e665a529931ca110
+## Copied from BiaPy commit: a0f3ee1e03b9e5a7d749ca029d4e8dcecc02adc1 (3.3.10)
 # Model definition variables (source BMZ/BiaPy/Torchvision) not updated yet
-
 import os
 from yacs.config import CfgNode as CN
 
@@ -138,8 +137,8 @@ def __init__(self, job_dir, job_identifier):
 
         ### SUPER_RESOLUTION
         _C.PROBLEM.SUPER_RESOLUTION = CN()
-        # Upscaling to be done to the input images. Options: [2, 4]
-        _C.PROBLEM.SUPER_RESOLUTION.UPSCALING = 1
+        # Upscaling to be done to the input images on every dimension. Examples: (2,2) in 2D or (2,2,2) in 3D.
+        _C.PROBLEM.SUPER_RESOLUTION.UPSCALING = ()
 
         ### SELF_SUPERVISED
         _C.PROBLEM.SELF_SUPERVISED = CN()
@@ -410,7 +409,7 @@ def __init__(self, job_dir, job_identifier):
         # “no change” and 0.5 denotes “half of the axis size”.
         _C.AUGMENTOR.SHIFT_RANGE = (0.1, 0.2)
         # How to fill up the new values created with affine transformations (rotations, shear, shift and zoom).
-        # Same meaning as in scipy: 'reflect', 'grid-mirror', 'constant', 'grid-constant', 'nearest', 'mirror', 
+        # Same meaning as in scipy: 'reflect', grid-'mirror', 'constant', 'grid-constant', 'nearest', 'mirror', 
         # 'grid-wrap' and 'wrap'. 
         _C.AUGMENTOR.AFFINE_MODE = 'constant'
         # Make vertical flips
@@ -721,7 +720,9 @@ def __init__(self, job_dir, job_identifier):
         # Learning rate 
         _C.TRAIN.LR = 1.E-4
         # Weight decay
-        _C.TRAIN.W_DECAY = 0.05
+        _C.TRAIN.W_DECAY = 0.02
+        # Coefficients used for computing running averages of gradient and its square. Used in ADAM and ADAMW optimizers
+        _C.TRAIN.OPT_BETAS = (0.9, 0.999)
         # Batch size
         _C.TRAIN.BATCH_SIZE = 2
         # If memory or # gpus is limited, use this variable to maintain the effective batch size, which is 

main.py

@@ -317,7 +317,8 @@ def __init__(self, log_file, log_dir):
             "MODEL__MAE_DEC_MLP_DIMS__INPUT", "MODEL__MAE_DEC_MLP_DIMS__INFO", "MODEL__MAE_DEC_MLP_DIMS__LABEL"], 
             widgets_to_set=["transformers_label"]))
         self.ui.TRAIN__OPTIMIZER__INPUT.currentIndexChanged.connect(lambda: self.condition_db.combobox_hide_visible_action(self, 
-            ["TRAIN__W_DECAY__INPUT", "adamw_weight_decay_label", "TRAIN__W_DECAY__INFO"]))
+            ["TRAIN__W_DECAY__INPUT", "adamw_weight_decay_label", "TRAIN__W_DECAY__INFO",
+            "TRAIN__OPT_BETAS__INPUT", "TRAIN__OPT_BETAS__LABEL", "TRAIN__OPT_BETAS__INFO"]))
         self.ui.TRAIN__PROFILER__INPUT.currentIndexChanged.connect(lambda: self.condition_db.combobox_hide_visible_action(self,
             ["profiler_batch_range_label", "TRAIN__PROFILER_BATCH_RANGE__INPUT", "TRAIN__PROFILER_BATCH_RANGE__INFO"]))
         self.ui.DATA__NORMALIZATION__TYPE__INPUT.currentIndexChanged.connect(lambda: self.condition_db.combobox_hide_visible_action(self, 

settings.py

@@ -30,11 +30,11 @@ def init_default_settings(self):
         self.settings['CUDA_version'] = [10.2, 11.8]
 
         # BiaPy 
-        self.settings['biapy_code_version'] = "v3.3.9"
+        self.settings['biapy_code_version'] = "v3.3.10"
         self.settings['biapy_code_github'] = "https://github.com/BiaPyX/BiaPy"
-        self.settings['biapy_gui_version'] = "v1.0.3"
+        self.settings['biapy_gui_version'] = "v1.0.4"
         self.settings['biapy_gui_github'] = "https://github.com/BiaPyX/BiaPy-GUI"
-        self.settings['biapy_gui_last_version_hash'] = "6aadbc94b47cdc9ad4c321b841dc97ddc7fc16bc"
+        self.settings['biapy_gui_last_version_hash'] = "69a6e455261ebb15f87035984470265c1c301ab7"
         self.settings['biapy_container_basename'] = "biapyx/biapy"
         self.settings['biapy_container_name'] = self.settings['biapy_container_basename']+":latest-"+str(self.settings['CUDA_version'][-1])
         self.settings['biapy_container_sizes'] = ["7.68GB", "11.6GB"]