Fix guides (#29)

CAREamics · Feb 18, 2025 · 78dcdef · 78dcdef
1 parent b210f07
commit 78dcdef
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Showing 3 changed files with 39 additions and 45 deletions.
diff --git a/guides/careamist_api/configuration/build_configuration.py b/guides/careamist_api/configuration/build_configuration.py
@@ -3,19 +3,18 @@
 # %%
 # --8<-- [start:pydantic]
 from careamics.config import (  # (1)!
+    Configuration,
+    DataConfig,
     N2VAlgorithm,
-    N2VConfiguration,
-    N2VDataConfig,
     TrainingConfig,
-    configuration_factory,
 )
 from careamics.config.architectures import UNetModel
 from careamics.config.callback_model import CheckpointModel, EarlyStoppingModel
 from careamics.config.support import (
     SupportedData,
     SupportedLogger,
 )
-from careamics.config.transformations import N2VManipulateModel, XYFlipModel
+from careamics.config.transformations import XYFlipModel
 
 experiment_name = "N2V_example"
 
@@ -32,58 +31,46 @@
     # (6)!
 )
 
-# then the N2VDataConfig
-data_model = N2VDataConfig(  # (7)!
+# then the data configuration for N2V
+data_model = DataConfig(  # (7)!
     data_type=SupportedData.ARRAY.value,
     patch_size=(256, 256),
     batch_size=8,
     axes="YX",
-    transforms=[XYFlipModel(flip_y=False), N2VManipulateModel()],  # (8)!  # (9)!
-    dataloader_params={  # (10)!
+    transforms=[XYFlipModel(flip_y=False)],  # (8)!
+    dataloader_params={  # (9)!
         "num_workers": 4,
+        "shuffle": True,
     },
 )
 
 # then the TrainingConfig
 earlystopping = EarlyStoppingModel(
-    # (11)!
+    # (10)!
 )
 
-checkpoints = CheckpointModel(every_n_epochs=10)  # (12)!
+checkpoints = CheckpointModel(every_n_epochs=10)  # (11)!
 
 training_model = TrainingConfig(
     num_epochs=30,
     logger=SupportedLogger.WANDB.value,
     early_stopping_callback=earlystopping,
     checkpoint_callback=checkpoints,
-    # (13)!
+    # (12)!
 )
 
 # finally, build the Configuration
-config = N2VConfiguration(  # (14)!
+config = Configuration(  # (13)!
     experiment_name=experiment_name,
     algorithm_config=algorithm_model,
     data_config=data_model,
     training_config=training_model,
 )
-
-# alternatively, use the factory method
-config2 = configuration_factory(  # (15)!
-    {
-        "experiment_name": experiment_name,
-        "algorithm_config": algorithm_model,
-        "data_config": data_model,
-        "training_config": training_model,
-    }
-)
 # --8<-- [end:pydantic]
 
-if config != config2:
-    raise ValueError("Configurations are not equal (Pydantic).")
-
 # %%
 # --8<-- [start:as_dict]
-from careamics.config import N2VConfiguration, configuration_factory
+from careamics.config import Configuration
 
 config_dict = {
     "experiment_name": "N2V_example",
@@ -95,6 +82,7 @@
             "num_channels_init": 64,
             "depth": 3,
         },
+        # (3)!
     },
     "data_config": {
         "data_type": "array",
@@ -106,9 +94,6 @@
                 "name": "XYFlip",
                 "flip_y": False,
             },
-            {
-                "name": "N2VManipulate",
-            },
         ],
         "dataloader_params": {
             "num_workers": 4,
@@ -117,22 +102,17 @@
     "training_config": {
         "num_epochs": 30,
         "logger": "wandb",
-        "early_stopping_callback": {},  # (3)!
+        "early_stopping_callback": {},  # (4)!
         "checkpoint_callback": {
             "every_n_epochs": 10,
         },
     },
 }
 
 # instantiate specific configuration
-config_as_dict = N2VConfiguration(**config_dict)  # (4)!
+config_as_dict = Configuration(**config_dict)  # (5)!
 
-# alternatively, use the factory method
-config_as_dict2 = configuration_factory(config_dict)  # (5)!
 # --8<-- [end:as_dict]
 
-if config_as_dict != config_as_dict2:
-    raise ValueError("Configurations are not equal (Dict).")
-
 if config != config_as_dict:
     raise ValueError("Configurations are not equal (Pydantic vs Dict).")
diff --git a/guides/careamist_api/configuration/config.yml b/guides/careamist_api/configuration/config.yml
@@ -20,6 +20,14 @@ algorithm_config:
   lr_scheduler:
     name: ReduceLROnPlateau
     parameters: {}
+  n2v_config:
+    name: N2VManipulate
+    roi_size: 11
+    masked_pixel_percentage: 0.2
+    remove_center: true
+    strategy: uniform
+    struct_mask_axis: none
+    struct_mask_span: 5
 data_config:
   data_type: tiff
   axes: ZYX
@@ -35,12 +43,9 @@ data_config:
     p: 0.5
   - name: XYRandomRotate90
     p: 0.5
-  - name: N2VManipulate
-    roi_size: 11
-    masked_pixel_percentage: 0.2
-    strategy: uniform
-    struct_mask_axis: none
-    struct_mask_span: 5
+  train_dataloader_params:
+    shuffle: true
+  val_dataloader_params: {}
 training_config:
   num_epochs: 20
   precision: '32'

diff --git a/guides/careamist_api/configuration/convenience_functions.py b/guides/careamist_api/configuration/convenience_functions.py
@@ -359,9 +359,12 @@
     patch_size=[16, 64, 64],
     batch_size=8,
     num_epochs=20,
-    dataloader_params={
+    train_dataloader_params={
         "num_workers": 4,  # (1)!
     },
+    val_dataloader_params={
+        "num_workers": 2,  # (2)!
+    },
 )
 # --8<-- [end:n2v_dataloader_kwargs]
 # N2N with dataloader parameters
@@ -373,9 +376,12 @@
     patch_size=[16, 64, 64],
     batch_size=8,
     num_epochs=20,
-    dataloader_params={
+    train_dataloader_params={
         "num_workers": 4,  # (1)!
     },
+    val_dataloader_params={
+        "num_workers": 2,  # (2)!
+    },
 )
 # --8<-- [end:care_dataloader_kwargs]
 # N2N with dataloader parameters
@@ -387,8 +393,11 @@
     patch_size=[16, 64, 64],
     batch_size=8,
     num_epochs=20,
-    dataloader_params={
+    train_dataloader_params={
         "num_workers": 4,  # (1)!
     },
+    val_dataloader_params={
+        "num_workers": 2,  # (2)!
+    },
 )
 # --8<-- [end:n2n_dataloader_kwargs]