diff --git a/deepmd/common.py b/deepmd/common.py
index 449729c556..0f22318ae8 100644
--- a/deepmd/common.py
+++ b/deepmd/common.py
@@ -26,6 +26,7 @@
 from deepmd.env import (
     GLOBAL_NP_FLOAT_PRECISION,
     GLOBAL_PD_FLOAT_PRECISION,
+    GLOBAL_TF_FLOAT_PRECISION,
     op_module,
     paddle,
     tf,
diff --git a/deepmd/descriptor/se_a.py b/deepmd/descriptor/se_a.py
index c55890e038..b2d9d93202 100644
--- a/deepmd/descriptor/se_a.py
+++ b/deepmd/descriptor/se_a.py
@@ -557,6 +557,7 @@ def forward(
         coord = paddle.reshape(coord_, [-1, natoms[1] * 3])
         box = paddle.reshape(box_, [-1, 9])
         atype = paddle.reshape(atype_, [-1, natoms[1]])
+
         (
             self.descrpt,
             self.descrpt_deriv,
@@ -705,6 +706,7 @@ def _pass_filter(
                 layer = paddle.reshape(
                     layer, [inputs.shape[0], natoms[2 + type_i], self.get_dim_out()]
                 )
+
                 qmat = paddle.reshape(
                     qmat,
                     [
diff --git a/deepmd/infer/deep_eval.py b/deepmd/infer/deep_eval.py
index e983bb4ec7..3f77789c4e 100644
--- a/deepmd/infer/deep_eval.py
+++ b/deepmd/infer/deep_eval.py
@@ -430,7 +430,7 @@ def _get_value(
             name of tensor to get
         attr_name : Optional[str], optional
             if specified, class attribute with this name will be created and tensor will
-            be assigned to it, by default None.
+            be assigned to it, by default None
         """
         # do not use os.path.join as it doesn't work on Windows
         value = None
diff --git a/deepmd/utils/network.py b/deepmd/utils/network.py
index 4a031aaa14..e3c2420c35 100644
--- a/deepmd/utils/network.py
+++ b/deepmd/utils/network.py
@@ -305,13 +305,13 @@ def variable_summaries(var: tf.Variable, name: str):
         tf.summary.scalar("min", tf.reduce_min(var))
         tf.summary.histogram("histogram", var)
 
-
+        
 def cast_to_dtype(x, dtype: paddle.dtype) -> paddle.Tensor:
     if x.dtype != dtype:
         return paddle.cast(x, dtype)
     return x
 
-
+  
 class OneLayer(nn.Layer):
     def __init__(
         self,
@@ -546,4 +546,5 @@ def forward(self, xx):
                 xx = hidden
         if self.mixed_prec is not None:
             xx = cast_to_dtype(xx, get_precision(self.mixed_prec["output_prec"]))
+
         return xx
diff --git a/source/lib/paddle_src/paddle_prod_env_mat.cu b/source/lib/paddle_src/paddle_prod_env_mat.cu
index 1324289a4b..d0f58ff896 100644
--- a/source/lib/paddle_src/paddle_prod_env_mat.cu
+++ b/source/lib/paddle_src/paddle_prod_env_mat.cu
@@ -2,10 +2,7 @@
 #include <cub/block/block_radix_sort.cuh>
 #include <cub/block/block_store.cuh>
 #include <type_traits>
-<<<<<<< HEAD
-=======
 
->>>>>>> paddle2
 #include "paddle/extension.h"
 
 #define GOOGLE_CUDA 1
@@ -21,7 +18,9 @@
 #include "region.h"
 #include "utilities.h"
 
-    typedef long long int_64;
+
+typedef long long int_64;
+
 
 #define CHECK_INPUT(x) PD_CHECK(x.is_gpu(), #x " must be a GPU Tensor.")
 #define CHECK_INPUT_ON_CPU(x) PD_CHECK(x.is_cpu(), #x " must be a CPU Tensor.")