change misleading description of m_mul
@@ -662,7 +662,7 @@ class CosineDecayRestarts(LearningRateSchedule):
The learning rate multiplier first decays
from 1 to `alpha` for `first_decay_steps` steps. Then, a warm
restart is performed. Each new warm restart runs for `t_mul` times more
- steps and with `m_mul` times smaller initial learning rate.
+ steps and with `m_mul` times larger initial learning rate.
Example usage:
```python
@@ -700,9 +700,9 @@ class CosineDecayRestarts(LearningRateSchedule):
first_decay_steps: A scalar `int32` or `int64` `Tensor` or a Python
number. Number of steps to decay over.
t_mul: A scalar `float32` or `float64` `Tensor` or a Python number.
- Used to derive the number of iterations in the i-th period
+ Used to derive the number of iterations in the i-th period.
m_mul: A scalar `float32` or `float64` `Tensor` or a Python number.
- Used to derive the initial learning rate of the i-th period:
+ Used to derive the initial learning rate of the i-th period.
alpha: A scalar `float32` or `float64` Tensor or a Python number.
Minimum learning rate value as a fraction of the initial_learning_rate.
name: String. Optional name of the operation. Defaults to 'SGDRDecay'.
