add para glabal step to inceptionv3 lr generator

model_zoo/official/cv/inceptionv3/src/lr_generator.py

@@ -17,7 +17,7 @@ import math
 import numpy as np
 
 
-def _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps):
+def _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps, global_step=0):
     """
     Applies three steps decay to generate learning rate array.
 
@@ -45,6 +45,7 @@ def _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps):
             else:
                 lr = lr_max * 0.001
         lr_each_step.append(lr)
+        lr_each_step = np.array(lr_each_step).astype(np.float32)[global_step:]
     return lr_each_step
 
 
@@ -131,7 +132,7 @@ def _generate_liner_lr(lr_init, lr_end, lr_max, total_steps, warmup_steps):
     return lr_each_step
 
 
-def get_lr(lr_init, lr_end, lr_max, warmup_epochs, total_epochs, steps_per_epoch, lr_decay_mode):
+def get_lr(lr_init, lr_end, lr_max, warmup_epochs, total_epochs, steps_per_epoch, lr_decay_mode, global_step=0):
     """
     generate learning rate array
 
@@ -150,7 +151,7 @@ def get_lr(lr_init, lr_end, lr_max, warmup_epochs, total_epochs, steps_per_epoch
     total_steps = steps_per_epoch * total_epochs
     warmup_steps = steps_per_epoch * warmup_epochs
     if lr_decay_mode == 'steps':
-        lr_each_step = _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps)
+        lr_each_step = _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps, global_step)
     elif lr_decay_mode == 'steps_decay':
         lr_each_step = _generate_exponential_lr(lr_init, lr_max, total_steps, warmup_steps, steps_per_epoch)
     elif lr_decay_mode == 'cosine':