Get rid of numpy dtypes in scheduler, prevent numpy dtypes ending up in train checkpoints

Author: rwightman

src/open_clip_train/scheduler.py

@@ -1,4 +1,4 @@
-import numpy as np
+import math
 
 
 def assign_learning_rate(optimizer, new_lr):
@@ -18,6 +18,7 @@ def _lr_adjuster(step):
             lr = base_lr
         assign_learning_rate(optimizer, lr)
         return lr
+
     return _lr_adjuster
 
 
@@ -33,10 +34,11 @@ def _lr_adjuster(step):
                 e = step - start_cooldown_step
                 es = steps - start_cooldown_step
                 # linear decay if power == 1; polynomial decay otherwise;
-                decay = (1 - (e/es)) ** cooldown_power
+                decay = (1 - (e / es)) ** cooldown_power
                 lr = decay * (base_lr - cooldown_end_lr) + cooldown_end_lr
         assign_learning_rate(optimizer, lr)
         return lr
+
     return _lr_adjuster
 
 
@@ -47,7 +49,9 @@ def _lr_adjuster(step):
         else:
             e = step - warmup_length
             es = steps - warmup_length
-            lr = 0.5 * (1 + np.cos(np.pi * e / es)) * base_lr
+            lr = 0.5 * (1 + math.cos(math.pi * e / es)) * base_lr
         assign_learning_rate(optimizer, lr)
         return lr
+
     return _lr_adjuster
+