fixes

2025-05-19 13:59:16 +02:00
parent 426f4d6963
commit c6defa2065
196 changed files with 18625 additions and 1 deletions
@@ -0,0 +1,132 @@
+from typing import Callable
+
+import configs
+from configs.feature_config import feature_config
+from configs.cnn_run_config import get_cnn_run_config
+from configs.transformer_run_config import get_transformer_run_config
+
+take_every_nth = int(288 / 12)
+shift_in_hours = 12
+input_window_length = (288 // take_every_nth) * 80
+# output_window_length = (288 // take_every_nth) * 1
+output_window_length = 1
+output_window_offset = input_window_length + (288 // take_every_nth) * 0
+window_shift = int((288 // take_every_nth) / 24 * shift_in_hours)
+min_input_length_fraction_for_padding = ((288 // take_every_nth) * 4) / input_window_length
+
+
+def config_generator(config_gen_fn: Callable,
+                     fixed_params: dict,
+                     variable_param_configs: list,
+                     ) -> list:
+    configs = list()
+    for variable_config in variable_param_configs:
+        config = fixed_params.copy()
+        for param_name, param_value in variable_config.items():
+            # update the config with the variable parameter, values can be None, if default should be used
+            if param_value is not None:
+                config[param_name] = param_value
+        configs.append(config_gen_fn(**config))
+
+    return configs
+
+
+run_configuration = {
+    "name": "ovulation_regression",
+    "runs": config_generator(
+        get_cnn_run_config,
+        fixed_params={
+            "run_name": "cnn_ovulation_regression",
+            "run_description": "CNN model for ovulation regression",
+            "input_window_length": input_window_length,
+            "output_window_length": output_window_length,
+            "take_every_nth": take_every_nth,
+            "shift_in_hours": shift_in_hours,
+            "output_window_offset": output_window_offset,
+            "batch_size": 256,
+            "max_lr": 1e-5,
+            "num_epochs": 10,
+            "patience": 3,
+            "feature_config": feature_config,
+        },
+        variable_param_configs=[
+            {
+                "model_parameters": {
+                    "cnn_channels": 32,
+                    "kernel_size": 3,
+                    "embed_dim": 32,
+                    "num_enc_layers": 2,
+                    "num_heads": 2,
+                },
+            },
+            {
+                "model_parameters": {
+                    "cnn_channels": 64,
+                    "kernel_size": 3,
+                    "embed_dim": 64,
+                    "num_enc_layers": 2,
+                    "num_heads": 2,
+                },
+            },
+            {
+                "batch_size": 128,
+                "model_parameters": {
+                    "cnn_channels": 128,
+                    "kernel_size": 5,
+                    "embed_dim": 128,
+                    "num_enc_layers": 4,
+                    "num_heads": 4,
+                },
+            },
+        ]
+    ) + config_generator(
+        get_transformer_run_config,
+        fixed_params={
+            "run_name": "transformer_ovulation_regression",
+            "run_description": "Transformer model for ovulation regression",
+            "input_window_length": input_window_length,
+            "output_window_length": output_window_length,
+            "take_every_nth": take_every_nth,
+            "shift_in_hours": shift_in_hours,
+            "output_window_offset": output_window_offset,
+            "batch_size": 128,
+            "max_lr": 1e-5,
+            "num_epochs": 10,
+            "patience": 3,
+            "feature_config": feature_config,
+        },
+        variable_param_configs=[
+            {
+                "model_parameters": {
+                    "embed_dim": 64,
+                    "num_enc_layers": 2,
+                    "num_heads": 2,
+                },
+            },
+            {
+                "batch_size": 64,
+                "model_parameters": {
+                    "embed_dim": 128,
+                    "num_enc_layers": 4,
+                    "num_heads": 4,
+                },
+            },
+            {
+                "batch_size": 64,
+                "model_parameters": {
+                    "embed_dim": 256,
+                    "num_enc_layers": 4,
+                    "num_heads": 4,
+                },
+            },
+            {
+                "batch_size": 32,
+                "model_parameters": {
+                    "embed_dim": 512,
+                    "num_enc_layers": 4,
+                    "num_heads": 4,
+                },
+            },
+        ]
+    )
+}