diff --git a/src/python/twitter/deepbird/projects/timelines/scripts/models/earlybird/example_weights.py b/src/python/twitter/deepbird/projects/timelines/scripts/models/earlybird/example_weights.py
index cf0c38ecc..934efa279 100644
--- a/src/python/twitter/deepbird/projects/timelines/scripts/models/earlybird/example_weights.py
+++ b/src/python/twitter/deepbird/projects/timelines/scripts/models/earlybird/example_weights.py
@@ -1,9 +1,12 @@
 # checkstyle: noqa
+from typing import Dict, Final
+from tensorflow import Tensor
+from twml import DefaultSubcommandArgParse
 import tensorflow.compat.v1 as tf
 from .constants import INDEX_BY_LABEL, LABEL_NAMES
 
 # TODO: Read these from command line arguments, since they specify the existing example weights in the input data.
-DEFAULT_WEIGHT_BY_LABEL = {
+DEFAULT_WEIGHT_BY_LABEL: Final[Dict[str, float]] = {
   "is_clicked": 0.3,
   "is_favorited": 1.0,
   "is_open_linked": 0.1,
@@ -11,19 +14,19 @@ DEFAULT_WEIGHT_BY_LABEL = {
   "is_profile_clicked": 1.0,
   "is_replied": 9.0,
   "is_retweeted": 1.0,
-  "is_video_playback_50": 0.01
+  "is_video_playback_50": 0.01,
 }
 
-def add_weight_arguments(parser):
+def add_weight_arguments(parser: DefaultSubcommandArgParse) -> DefaultSubcommandArgParse:
   for label_name in LABEL_NAMES:
     parser.add_argument(
       _make_weight_cli_argument_name(label_name),
       type=float,
       default=DEFAULT_WEIGHT_BY_LABEL[label_name],
-      dest=_make_weight_param_name(label_name)
+      dest=_make_weight_param_name(label_name),
     )
 
-def make_weights_tensor(input_weights, label, params):
+def make_weights_tensor(input_weights, label, params) -> Tensor:
   '''
   Replaces the weights for each positive engagement and keeps the input weights for negative examples.
   '''
@@ -32,12 +35,15 @@ def make_weights_tensor(input_weights, label, params):
     index, default_weight = INDEX_BY_LABEL[label_name], DEFAULT_WEIGHT_BY_LABEL[label_name]
     weight_param_name =_make_weight_param_name(label_name)
     weight_tensors.append(
-      tf.reshape(tf.math.scalar_mul(getattr(params, weight_param_name) - default_weight, label[:, index]), [-1, 1])
+      tf.reshape(
+        tf.math.scalar_mul(
+          getattr(params, weight_param_name) - default_weight, label[:, index]
+        ), [-1, 1])
     )
   return tf.math.accumulate_n(weight_tensors)
 
-def _make_weight_cli_argument_name(label_name):
+def _make_weight_cli_argument_name(label_name: str) -> str:
   return f"--weight.{label_name}"
 
-def _make_weight_param_name(label_name):
+def _make_weight_param_name(label_name: str) -> str:
   return f"weight_{label_name}"