Added more detailed logging.

Author: adivekar-utexas

src/fmcore/framework/_algorithm.py

@@ -165,10 +165,10 @@ def _validate_outputs_type(cls, outputs: Type[Predictions]) -> Type[Predictions]
                 )
         return outputs
 
-    def __init__(self, *, stats: Optional[Metrics] = None, **kwargs):
-        ## Initialize the algorithm with optional statistics
-        super(Algorithm, self).__init__(stats=stats, **kwargs)
-        self.stats = stats
+    # def __init__(self, *, stats: Optional[Metrics] = None, **kwargs):
+    #     ## Initialize the algorithm with optional statistics
+    #     super(Algorithm, self).__init__(stats=stats, **kwargs)
+    #     self.stats = stats
 
     def __str__(self):
         ## String representation of the algorithm with its parameters

src/fmcore/framework/_chain/Chain.py

@@ -291,8 +291,8 @@ def run(
         background: bool = False,
         tracker: Optional[Union[Tracker, Dict, str]] = None,
         notifier: Optional[Union[Notifier, Dict, str]] = None,
-        store_step_inputs: bool = False,
-        store_step_outputs: bool = False,
+        store_step_inputs: bool = True,
+        store_step_outputs: bool = True,
         after: Optional[ChainExecution] = None,
         after_wait: conint(ge=0) = 15,
         step_wait: confloat(ge=0.0) = 0.0,

src/fmcore/framework/_dataset.py

@@ -85,6 +85,10 @@ def concat(
     @model_validator(mode="before")
     @classmethod
     def _set_dataset_params(cls, params: Dict) -> Dict:
+        if "data_schema" not in params:
+            raise ValueError(
+                f"Cannot create instance of class '{cls.class_name}' without passing `data_schema` parameter."
+            )
         data_schema: Union[Schema, MLTypeSchema] = params["data_schema"]
         if isinstance(data_schema, dict):
             ## We need to infer the schema:

src/fmcore/framework/_predictions.py

@@ -36,8 +36,8 @@
     MLTypeSchema,
     TaskOrStr,
 )
-from fmcore.framework._task_mixins import InputOutputDataMixin, SchemaValidationError
 from fmcore.framework._dataset import Dataset
+from fmcore.framework._task_mixins import InputOutputDataMixin, SchemaValidationError
 
 Predictions = "Predictions"
 Visualization = "Visualization"
@@ -69,6 +69,11 @@ def _pre_registration_hook(cls):
     @model_validator(mode="before")
     @classmethod
     def _set_predictions_params(cls, params: Dict) -> Dict:
+        if "data_schema" not in params:
+            raise ValueError(
+                f"Cannot create instance of class '{cls.class_name}' without passing `data_schema` parameter."
+            )
+
         params["data_schema"]: Schema = Schema.of(params["data_schema"], schema_template=cls.schema_template)
         # data_schema: Union[Schema, MLTypeSchema] = params['data_schema']
         # if isinstance(data_schema, dict):

src/fmcore/framework/_task/text_generation.py

@@ -757,7 +757,7 @@ class LanguageModelTaskMixin(Algorithm, ABC):
     icl_sampler: Optional[ICLSampler] = None  ## Will be not-None when icl_dataset is not-None.
 
     class Hyperparameters(Algorithm.Hyperparameters):
-        lm: Optional[Dict]  ## Params for llm
+        lm: Optional[Dict] = None  ## Params for llm
         batch_size: Optional[conint(ge=1)] = 1  ## By default, predict 1 row at a time.
         prompt_template: constr(min_length=1)
         icl_template: Optional[constr(min_length=1)] = None