enabling gradient information to be saved out correctly

pythia_training_metrics.py → pythia-training-metrics.py

@@ -120,19 +120,21 @@ class PythiaTrainingMetrics(datasets.GeneratorBasedBuilder):
                 elif self.config_name == "gradients_mini":
                     for gradient_step in get_gradient_step(checkpoint_step)[:2]:
                         model_size_to_fp[model_size].append(f"{directory_path}/checkpoint_gradients_mini_{gradient_step}.pickle")
+                else: 
+                    raise Exception("Invalid config name")
 
         downloaded_files = dl_manager.download_and_extract(model_size_to_fp)
 
         return [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
+                name=model_size_name,
                 gen_kwargs={
                     "filepaths": downloaded_fps
                 }
-            )  for downloaded_fps in downloaded_files.values()
+            )  for model_size_name, downloaded_fps in downloaded_files.items()
         ]
 
-    def _generate_examples(self, filepaths):
+    def _generate_examples(self, filepaths, **kwargs):
 
         # the filepaths should be a list of filepaths 
         if isinstance(filepaths, str):
@@ -149,11 +151,12 @@ class PythiaTrainingMetrics(datasets.GeneratorBasedBuilder):
                 
                 if self.config.name in ["activations", "weights"]:
                     for layer_name, layer_data in data.items():
-                        for data in layer_data: 
-                            yield global_idx, {"checkpoint_step": checkpoint_step, "layer_name": layer_name, "data": data}
-                            global_idx += 1
+                        yield global_idx, {"checkpoint_step": checkpoint_step, "layer_name": layer_name, "data": data}
+                        global_idx += 1
                 elif self.config.name in ["gradients", "gradients_mini"]:
+
+                    gradient_step = int(filepath.split('/')[-1].split("_")[-1].split(".")[0])
+
                     for layer_name, layer_data in data.items():
-                        for gradient_step, gradient in layer_data.items():
-                            yield global_idx, {"checkpoint_step": checkpoint_step, "layer_name": layer_name, "gradient_step": gradient_step, "gradient": gradient}
-                            global_idx += 1
+                        yield global_idx, {"checkpoint_step": checkpoint_step, "layer_name": layer_name, "gradient_step": gradient_step, "gradient": layer_data}
+                        global_idx += 1