update cosine decay doc

doc/doc_ch/config.md

@@ -58,6 +58,6 @@
 |         beta1           |    设置一阶矩估计的指数衰减率  |       0.9         |               \             |
 |         beta2           |    设置二阶矩估计的指数衰减率  |     0.999         |               \             |
 |         decay           |         是否使用decay       |    \              |               \             |
-|      function(decay)    |         设置decay方式       |   cosine_decay    |               \             |
+|      function(decay)    |         设置decay方式       |   cosine_decay    |       目前只支持cosin_decay  |
 |      step_each_epoch    |      每个epoch包含多少次迭代  |         20       | 计算方式：total_image_num / (batch_size_per_card * card_size) |
 |        total_epoch      |    总共迭代多少个epoch        |       1000      | 与Global.epoch_num 一致        |

doc/doc_en/config_en.md

@@ -58,6 +58,6 @@ Take `rec_icdar15_train.yml` as an example:
 |         beta1           |    Set the exponential decay rate for the 1st moment estimates  |       0.9         |               \             |
 |         beta2           |    Set the exponential decay rate for the 2nd moment estimates  |     0.999         |               \             |
 |         decay           |         Whether to use decay       |    \              |               \             |
-|      function(decay)    |         Set the decay function       |   cosine_decay    |               \             |
+|      function(decay)    |         Set the decay function       |   cosine_decay    |           Only support cosine_decay            |
 |      step_each_epoch    |      The number of steps in an epoch.  |         20       | Calculation ：total_image_num / (batch_size_per_card * card_size) |
 |        total_epoch      |    The number of epochs      |       1000      | Consistent with Global.epoch_num      |

ppocr/optimizer.py

@@ -15,6 +15,9 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 import paddle.fluid as fluid
+from ppocr.utils.utility import initial_logger
+
+logger = initial_logger()
 
 
 def AdamDecay(params, parameter_list=None):
@@ -38,6 +41,8 @@ def AdamDecay(params, parameter_list=None):
                 learning_rate=base_lr,
                 step_each_epoch=step_each_epoch,
                 epochs=total_epoch)
+        else:
+            logger.info("Only support Cosine decay currently")
     optimizer = fluid.optimizer.Adam(
         learning_rate=base_lr,
         beta1=beta1,