forked from mindspore-Ecosystem/mindspore
add para glabal step to inceptionv3 lr generator
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2c91bace34
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@ -17,7 +17,7 @@ import math
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import numpy as np
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def _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps):
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def _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps, global_step=0):
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"""
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Applies three steps decay to generate learning rate array.
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@ -45,6 +45,7 @@ def _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps):
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else:
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lr = lr_max * 0.001
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lr_each_step.append(lr)
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lr_each_step = np.array(lr_each_step).astype(np.float32)[global_step:]
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return lr_each_step
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@ -131,7 +132,7 @@ def _generate_liner_lr(lr_init, lr_end, lr_max, total_steps, warmup_steps):
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return lr_each_step
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def get_lr(lr_init, lr_end, lr_max, warmup_epochs, total_epochs, steps_per_epoch, lr_decay_mode):
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def get_lr(lr_init, lr_end, lr_max, warmup_epochs, total_epochs, steps_per_epoch, lr_decay_mode, global_step=0):
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"""
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generate learning rate array
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@ -150,7 +151,7 @@ def get_lr(lr_init, lr_end, lr_max, warmup_epochs, total_epochs, steps_per_epoch
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total_steps = steps_per_epoch * total_epochs
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warmup_steps = steps_per_epoch * warmup_epochs
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if lr_decay_mode == 'steps':
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lr_each_step = _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps)
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lr_each_step = _generate_steps_lr(lr_init, lr_max, total_steps, warmup_steps, global_step)
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elif lr_decay_mode == 'steps_decay':
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lr_each_step = _generate_exponential_lr(lr_init, lr_max, total_steps, warmup_steps, steps_per_epoch)
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elif lr_decay_mode == 'cosine':
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