fix codex

mindspore/ccsrc/backend/kernel_compiler/gpu/rl/buffer_append_gpu_kernel.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace kernel {
-
 BufferAppendKernel::BufferAppendKernel() : element_nums_(0), exp_batch_(0), capacity_(0) {}
 
 BufferAppendKernel::~BufferAppendKernel() {}

mindspore/ccsrc/backend/kernel_compiler/gpu/rl/buffer_get_gpu_kernel.cc

@@ -26,7 +26,6 @@
 
 namespace mindspore {
 namespace kernel {
-
 BufferGetKernel::BufferGetKernel() : element_nums_(0), capacity_(0) {}
 
 BufferGetKernel::~BufferGetKernel() {}

mindspore/ccsrc/backend/kernel_compiler/gpu/rl/buffer_sample_gpu_kernel.cc

@@ -29,7 +29,6 @@
 
 namespace mindspore {
 namespace kernel {
-
 BufferSampleKernel::BufferSampleKernel()
     : element_nums_(0), capacity_(0), batch_size_(0), seed_(0), states_init_(false), unique_(false) {}
 

mindspore/ops/operations/rl_ops.py

@@ -22,6 +22,7 @@ from ..._checkparam import Rel
 from ...common import dtype as mstype
 from ..primitive import prim_attr_register, PrimitiveWithInfer
 
+
 class BufferSample(PrimitiveWithInfer):
     r"""
     In reinforcement learning, the data is sampled from the replaybuffer randomly.
@@ -134,6 +135,7 @@ class BufferSample(PrimitiveWithInfer):
         validator.check_type_name("head type", head_type, (mstype.int32), self.name)
         return tuple(self._buffer_dtype)
 
+
 class BufferAppend(PrimitiveWithInfer):
     r"""
     In reinforcement learning, the experience data is collected in each step. We use `BufferAppend` to
@@ -227,6 +229,7 @@ class BufferAppend(PrimitiveWithInfer):
         validator.check_type_name("head type", head_type, (mstype.int32), self.name)
         return count_type
 
+
 class BufferGetItem(PrimitiveWithInfer):
     r"""
     Get the data from buffer in the position of input inedx.