Fix typo from StepConsineDecayWithOffset -> StepCosineDecayWithOffset

PiperOrigin-RevId: 428599243

official/legacy/detection/modeling/learning_rates.py

@@ -61,7 +61,7 @@ class CosineLearningRateWithLinearWarmup(
   """Class to generate learning rate tensor."""
 
   def __init__(self, total_steps, params):
-    """Creates the consine learning rate tensor with linear warmup."""
+    """Creates the cosine learning rate tensor with linear warmup."""
     super(CosineLearningRateWithLinearWarmup, self).__init__()
     self._total_steps = total_steps
     assert isinstance(params, (dict, params_dict.ParamsDict))

official/legacy/image_classification/learning_rate.py

@@ -78,7 +78,7 @@ class CosineDecayWithWarmup(tf.keras.optimizers.schedules.LearningRateSchedule):
   """Class to generate learning rate tensor."""
 
   def __init__(self, batch_size: int, total_steps: int, warmup_steps: int):
-    """Creates the consine learning rate tensor with linear warmup.
+    """Creates the cosine learning rate tensor with linear warmup.
 
     Args:
       batch_size: The training batch size used in the experiment.

official/modeling/optimization/configs/learning_rate_config.py

@@ -216,14 +216,14 @@ class StepCosineLrConfig(base_config.Config):
   """Configuration for stepwise learning rate decay.
 
   This class is a container for the piecewise cosine learning rate scheduling
-  configs. It will configure an instance of StepConsineDecayWithOffset keras
+  configs. It will configure an instance of StepCosineDecayWithOffset keras
   learning rate schedule.
 
     ```python
     boundaries: [100000, 110000]
     values: [1.0, 0.5]
     lr_decayed_fn = (
-    lr_schedule.StepConsineDecayWithOffset(
+    lr_schedule.StepCosineDecayWithOffset(
         boundaries,
         values))
     ```
@@ -243,7 +243,7 @@ class StepCosineLrConfig(base_config.Config):
               [boundaries[n], end]               -> values[n+1] to 0.
     offset: An int. The offset applied to steps. Defaults to 0.
   """
-  name: str = 'StepConsineDecayWithOffset'
+  name: str = 'StepCosineDecayWithOffset'
   boundaries: Optional[List[int]] = None
   values: Optional[List[float]] = None
   offset: int = 0

official/modeling/optimization/lr_schedule.py

@@ -386,11 +386,11 @@ class PowerDecayWithOffset(tf.keras.optimizers.schedules.LearningRateSchedule):
     }
 
 
-class StepConsineDecayWithOffset(
+class StepCosineDecayWithOffset(
     tf.keras.optimizers.schedules.LearningRateSchedule):
   """Stepwise cosine learning rate decay with offset.
 
-  Learning rate is equivalent to one or more consine decay(s) starting and
+  Learning rate is equivalent to one or more cosine decay(s) starting and
   ending at each interval.
 
   ExampleL
@@ -399,7 +399,7 @@ class StepConsineDecayWithOffset(
     boundaries: [100000, 110000]
     values: [1.0, 0.5]
     lr_decayed_fn = (
-    lr_schedule.StepConsineDecayWithOffset(
+    lr_schedule.StepCosineDecayWithOffset(
         boundaries,
         values))
     ```
@@ -412,7 +412,7 @@ class StepConsineDecayWithOffset(
                boundaries,
                values,
                offset: int = 0,
-               name: str = "StepConsineDecayWithOffset"):
+               name: str = "StepCosineDecayWithOffset"):
     """Initialize configuration of the learning rate schedule.
 
     Args:
@@ -444,7 +444,7 @@ class StepConsineDecayWithOffset(
         ] + [0])
 
   def __call__(self, global_step):
-    with tf.name_scope(self.name or "StepConsineDecayWithOffset"):
+    with tf.name_scope(self.name or "StepCosineDecayWithOffset"):
       global_step = tf.cast(global_step - self.offset, tf.float32)
       lr_levels = self.values
       lr_steps = self.boundaries

official/modeling/optimization/optimizer_factory.py

@@ -47,7 +47,7 @@ LR_CLS = {
     'power': lr_schedule.DirectPowerDecay,
     'power_linear': lr_schedule.PowerAndLinearDecay,
     'power_with_offset': lr_schedule.PowerDecayWithOffset,
-    'step_cosine_with_offset': lr_schedule.StepConsineDecayWithOffset,
+    'step_cosine_with_offset': lr_schedule.StepCosineDecayWithOffset,
 }
 
 WARMUP_CLS = {