refactor: minor changes

GANDLF/configuration/user_defined_config.py → GANDLF/Configuration/user_defined_config.py

@@ -1,16 +1,16 @@
 from typing import Union
 from pydantic import BaseModel, model_validator, Field, AfterValidator
-from GANDLF.configuration.default_config import DefaultParameters
-from GANDLF.configuration.differential_privacy_config import DifferentialPrivacyConfig
-from GANDLF.configuration.nested_training_config import NestedTraining
-from GANDLF.configuration.optimizer_config import OptimizerConfig
-from GANDLF.configuration.patch_sampler_config import PatchSamplerConfig
-from GANDLF.configuration.scheduler_config import SchedulerConfig
+from GANDLF.Configuration.default_config import DefaultParameters
+from GANDLF.Configuration.differential_privacy_config import DifferentialPrivacyConfig
+from GANDLF.Configuration.nested_training_config import NestedTraining
+from GANDLF.Configuration.optimizer_config import OptimizerConfig
+from GANDLF.Configuration.patch_sampler_config import PatchSamplerConfig
+from GANDLF.Configuration.scheduler_config import SchedulerConfig
 from GANDLF.utils import version_check
 from importlib.metadata import version
 from typing_extensions import Self, Literal, Annotated
-from GANDLF.configuration.validators import (
-    validate_schedular,
+from GANDLF.Configuration.validators import (
+    validate_scheduler,
     validate_optimizer,
     validate_loss_function,
     validate_metrics,
@@ -22,7 +22,8 @@
     validate_data_postprocessing_after_reverse_one_hot_encoding,
     validate_differential_privacy,
 )
-from GANDLF.configuration.model_config import ModelConfig
+from GANDLF.Configuration.model_config import ModelConfig
+from GANDLF.Configuration.scheduler_config import base_triangle_config
 
 
 class Version(BaseModel):  # TODO: Maybe should be to another folder
@@ -65,8 +66,7 @@ class UserDefinedParameters(DefaultParameters):
         default="", description="Parallel compute command."
     )
     scheduler: Union[str, SchedulerConfig] = Field(
-        description="Scheduler.", default=SchedulerConfig(type="triangle_modified")
-    )
+        description="Scheduler.")
     optimizer: Union[str, OptimizerConfig] = Field(
         description="Optimizer.", default=OptimizerConfig(type="adam")
     )  # TODO: Check it again for (opt)
@@ -103,7 +103,7 @@ def validate(self) -> Self:
             self.parallel_compute_command
         )
         # validate scheduler
-        self.scheduler = validate_schedular(self.scheduler, self.learning_rate)
+        self.scheduler = validate_scheduler(self.scheduler, self.learning_rate)
         # validate optimizer
         self.optimizer = validate_optimizer(self.optimizer)
         # validate patch_sampler

GANDLF/configuration/utils.py → GANDLF/Configuration/utils.py

@@ -1,9 +1,8 @@
 import logging
 from typing import Optional, Union
 
-
 from typing import Type
-from pydantic import BaseModel, ValidationError
+from pydantic import BaseModel, ValidationError, create_model
 from pydantic_core import ErrorDetails
 
 
@@ -107,3 +106,25 @@ def handle_configuration_errors(e: ValidationError):
     messages = extract_messages(convert_errors(e))
     for message in messages:
         logging.error(message)
+
+def combine_models(base_model: Type[BaseModel], extra_model: Type[BaseModel]):
+    """Combine base model with an extra model dynamically."""
+    fields = {}
+    # Collect base model fields
+    for field_name, field_info in base_model.model_fields.items():
+        fields[field_name] = (field_info.annotation, field_info.default if field_info.default is not Ellipsis else ...)
+
+    # Add fields from the extra model
+    for field_name, field_info in extra_model.model_fields.items():
+        fields[field_name] = (field_info.annotation, field_info.default if field_info.default is not Ellipsis else ...)
+
+    # Return the new dynamically combined model
+    return create_model(base_model.__name__, **fields)
+
+
+def add_config_at_the_end_of_values(schedulers_dict):
+    # Create a new dictionary with '_config' appended to each value
+    updated_dict = {key: value.__name__ + "_config" if callable(value) else str(value).replace('"', '').replace("'", '')
+                    for key, value in schedulers_dict.items()}
+
+    return updated_dict

GANDLF/configuration/validators.py → GANDLF/Configuration/validators.py

@@ -1,15 +1,16 @@
 import ast
 import traceback
 from copy import deepcopy
+from sched import scheduler
 
-from GANDLF.configuration.differential_privacy_config import DifferentialPrivacyConfig
+from GANDLF.Configuration.differential_privacy_config import DifferentialPrivacyConfig
 from GANDLF.data.post_process import postprocessing_after_reverse_one_hot_encoding
 import numpy as np
 import sys
-from GANDLF.configuration.optimizer_config import OptimizerConfig
-from GANDLF.configuration.patch_sampler_config import PatchSamplerConfig
-from GANDLF.configuration.scheduler_config import SchedulerConfig
-from GANDLF.configuration.utils import initialize_key
+from GANDLF.Configuration.optimizer_config import OptimizerConfig
+from GANDLF.Configuration.patch_sampler_config import PatchSamplerConfig
+from GANDLF.Configuration.scheduler_config import SchedulerConfig, base_triangle_config
+from GANDLF.Configuration.utils import initialize_key, combine_models
 from GANDLF.metrics import surface_distance_ids
 
 
@@ -169,11 +170,14 @@ def validate_parallel_compute_command(value):
     return value
 
 
-def validate_schedular(value, learning_rate):
+def validate_scheduler(value, learning_rate):
     if isinstance(value, str):
         value = SchedulerConfig(type=value)
     if value.step_size is None:
         value.step_size = learning_rate / 5.0
+    schedulerConfigCombine = combine_models(SchedulerConfig,base_triangle_config)
+    combineScheduler = schedulerConfigCombine(**value.model_dump())
+    value = SchedulerConfig(**combineScheduler.model_dump())
     return value
 
 

GANDLF/config_manager.py

@@ -3,9 +3,9 @@
 import yaml
 from pydantic import ValidationError
 
-from GANDLF.configuration.parameters_config import Parameters
-from GANDLF.configuration.exclude_parameters import exclude_parameters
-from GANDLF.configuration.utils import handle_configuration_errors
+from GANDLF.Configuration.parameters_config import Parameters
+from GANDLF.Configuration.exclude_parameters import exclude_parameters
+from GANDLF.Configuration.utils import handle_configuration_errors
 
 
 def _parseConfig(

GANDLF/configuration/model_config.py

@@ -1,7 +1,7 @@
 from pydantic import BaseModel, model_validator, Field, AliasChoices, ConfigDict
 from typing_extensions import Self, Literal, Optional
 from typing import Union
-from GANDLF.configuration.validators import validate_class_list, validate_norm_type
+from GANDLF.Configuration.validators import validate_class_list, validate_norm_type
 from GANDLF.models import global_models_dict
 
 # Define model architecture options

GANDLF/configuration/parameters_config.py

@@ -1,5 +1,5 @@
 from pydantic import BaseModel, ConfigDict
-from GANDLF.configuration.user_defined_config import UserDefinedParameters
+from GANDLF.Configuration.user_defined_config import UserDefinedParameters
 
 
 class ParametersConfiguration(BaseModel):

GANDLF/configuration/scheduler_config.py

@@ -5,13 +5,17 @@
 
 TYPE_OPTIONS = Literal[tuple(global_schedulers_dict.keys())]
 
+class base_triangle_config(BaseModel):
+    min_lr: float = Field(default= (10 ** -3))
+    max_lr: float = Field(default=1)
+
+
 
 # It allows extra parameters
 class SchedulerConfig(BaseModel):
     model_config = ConfigDict(extra="allow")
     type: TYPE_OPTIONS = Field(
-        description="triangle/triangle_modified use LambdaLR but triangular/triangular2/exp_range uses CyclicLR"
+        description="triangle/triangle_modified use LambdaLR but triangular/triangular2/exp_range uses CyclicLR",
+        default = "triangle"
     )
-    # min_lr: 0.00001, #TODO: this should be defined ??
-    # max_lr: 1, #TODO: this should be defined ??
-    step_size: float = Field(description="step_size", default=None)
+    step_size: float = Field(description="step_size", default=None)

GANDLF/schedulers/wrap_torch.py

@@ -49,9 +49,9 @@ def base_triangle(parameters):
     This function parses the parameters from the config file and returns the appropriate object
     """
 
-    # pick defaults
-    parameters["scheduler"]["min_lr"] = parameters["scheduler"].get("min_lr", 10**-3)
-    parameters["scheduler"]["max_lr"] = parameters["scheduler"].get("max_lr", 1)
+    # # pick defaults
+    # parameters["scheduler"]["min_lr"] = parameters["scheduler"].get("min_lr", 10**-3)
+    # parameters["scheduler"]["max_lr"] = parameters["scheduler"].get("max_lr", 1)
 
     clr = cyclical_lr(
         parameters["scheduler"]["step_size"],