diff --git a/utensor_cgen/backend/utensor/code_generator/rearch/_operators/_impls.py b/utensor_cgen/backend/utensor/code_generator/rearch/_operators/_impls.py
index c6dbed26..d0488a5a 100644
--- a/utensor_cgen/backend/utensor/code_generator/rearch/_operators/_impls.py
+++ b/utensor_cgen/backend/utensor/code_generator/rearch/_operators/_impls.py
@@ -544,6 +544,39 @@ def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
       tensor_var_map=tensor_var_map,
     )
 
+@OperatorFactory.register
+class _ConvOperator(_CommonParams):
+  op_type = "ConvOperator"
+
+  @classmethod
+  @must_return_type(Hashable)
+  def get_constructor_parameters(cls, op_info):
+
+    strides = [
+        1,
+        op_info.op_attr['StrideW'],
+        op_info.op_attr['StrideH'],
+        1,
+      ]
+    padding = cls._PADDING_MAP[op_info.op_attr['Padding']]
+    strides_str = ','.join(map(str, strides))
+    return ("{{ {} }}".format(strides_str), padding)
+
+  def get_declare_snippet(self, op_var_name, tensor_var_map):
+    return DeclareOpSnippet(
+      op=self,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_var_name=op_var_name,
+    )
+
+  def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
+    return ConvOpEvalSnippet(
+      op_info=op_info,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_name=op_var_name,
+      tensor_var_map=tensor_var_map,
+    )
+
 
 @OperatorFactory.register
 class _QuantizedFullyConnectedOperator(_CommonParams):
@@ -842,3 +875,142 @@ def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
       op_name=op_var_name,
       tensor_var_map=tensor_var_map,
     )
+
+@OperatorFactory.register
+class _BatchNormOperator(_CommonParams):
+  op_type = "BatchNormOperator"
+
+  @classmethod
+  @must_return_type(Hashable)
+  def get_constructor_parameters(cls, op_info):
+    strides = [
+        1,
+        op_info.op_attr['StrideW'],
+        op_info.op_attr['StrideH'],
+        1,
+      ]
+    padding = cls._PADDING_MAP[op_info.op_attr['Padding']]
+    strides_str = ','.join(map(str, strides))
+    return ("{{ {} }}".format(strides_str), padding)
+
+  def get_declare_snippet(self, op_var_name, tensor_var_map):
+    return DeclareOpSnippet(
+      op=self,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_var_name=op_var_name,
+    )
+
+  def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
+    return BatchNormSnippet(
+      op_info=op_info,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_name=op_var_name,
+      tensor_var_map=tensor_var_map,
+    )
+
+@OperatorFactory.register
+class _MeanOperator(_CommonParams):
+  op_type = "MeanOperator"
+
+  @classmethod
+  @must_return_type(Hashable)
+  def get_constructor_parameters(cls, op_info):
+    keep_dims = str(op_info.op_attr["keep_dims"])
+    return (" {} ".format(keep_dims), )
+
+  def get_declare_snippet(self, op_var_name, tensor_var_map):
+    return DeclareOpSnippet(
+      op=self,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_var_name=op_var_name,
+    )
+
+  def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
+    return BatchNormSnippet(
+      op_info=op_info,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_name=op_var_name,
+      tensor_var_map=tensor_var_map,
+    )
+
+@OperatorFactory.register
+class _SoftmaxOperator(_CommonParams):
+  op_type = "SoftmaxOperator"
+
+  @classmethod
+  @must_return_type(Hashable)
+  def get_constructor_parameters(cls, op_info):
+    Beta = op_info.op_attr["Beta"]
+    return (" %f " % Beta,)
+
+  def get_declare_snippet(self, op_var_name, tensor_var_map):
+    return DeclareOpSnippet(
+      op=self,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_var_name=op_var_name,
+    )
+
+  def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
+    return BatchNormSnippet(
+      op_info=op_info,
+      templ_dtypes=[self.out_dtypes[0]],
+      op_name=op_var_name,
+      tensor_var_map=tensor_var_map,
+    )
+
+@OperatorFactory.register
+class _MulOperator(_Operator):
+  op_type = 'MulOperator'
+
+  def get_declare_snippet(self, op_var_name, tensor_var_map):
+    return DeclareOpSnippet(
+      op=self,
+      templ_dtypes=[self.in_dtypes[0]],
+      op_var_name=op_var_name,
+    )
+
+  def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
+    return MulOpEvalSnippet(
+      op_info=op_info,
+      templ_dtypes=[self.in_dtypes[0]],
+      op_name=op_var_name,
+      tensor_var_map=tensor_var_map,
+    )
+
+@OperatorFactory.register
+class _SubOperator(_Operator):
+  op_type = 'SubOperator'
+
+  def get_declare_snippet(self, op_var_name, tensor_var_map):
+    return DeclareOpSnippet(
+      op=self,
+      templ_dtypes=[self.in_dtypes[0]],
+      op_var_name=op_var_name,
+    )
+
+  def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
+    return SubOpEvalSnippet(
+      op_info=op_info,
+      templ_dtypes=[self.in_dtypes[0]],
+      op_name=op_var_name,
+      tensor_var_map=tensor_var_map,
+    )
+
+@OperatorFactory.register
+class _SigmoidOperator(_Operator):
+  op_type = 'SigmoidOperator'
+
+  def get_declare_snippet(self, op_var_name, tensor_var_map):
+    return DeclareOpSnippet(
+      op=self,
+      templ_dtypes=[self.in_dtypes[0]],
+      op_var_name=op_var_name,
+    )
+
+  def get_eval_snippet(self, op_var_name, op_info, tensor_var_map):
+    return SigmoidOpEvalSnippet(
+      op_info=op_info,
+      templ_dtypes=[self.in_dtypes[0]],
+      op_name=op_var_name,
+      tensor_var_map=tensor_var_map,
+    )
diff --git a/utensor_cgen/backend/utensor/snippets/rearch/_snippets.py b/utensor_cgen/backend/utensor/snippets/rearch/_snippets.py
index c40b4613..0010416b 100644
--- a/utensor_cgen/backend/utensor/snippets/rearch/_snippets.py
+++ b/utensor_cgen/backend/utensor/snippets/rearch/_snippets.py
@@ -29,12 +29,14 @@
   "MaxPoolEvalSnippet",
   "QuantizedFullyConnectedSnippet",
   "MissingOpEvalSnippet",
+  "BatchNormSnippet",
   "TimeSlotContainer",
   "MulOpEvalSnippet",
   "SubOpEvalSnippet",
   "ConvOpEvalSnippet",
   "MeanOpEvalSnippet",
   "SoftmaxOpEvalSnippet",
+  "SigmoidOpEvalSnippet",
   "SimpleContainer",
 ]
 
@@ -256,6 +258,7 @@ class SoftmaxOpEvalSnippet(OpEvalSnippet):
   __inputs__ = ['input']
   __outputs__ = ['output']
 
+<<<<<<< HEAD
 
 class MissingOpEvalSnippet(OpEvalSnippet):
   __template_name__ = "snippets/rearch/op_missing.cpp"
@@ -277,6 +280,11 @@ def __init__(self, op_info, tensor_var_map):
     ]
     self.template_vars['output_tensors'] = op_info.output_tensors[:]
     self.template_vars['quant_params_map'] = quant_params_map
+=======
+class SigmoidOpEvalSnippet(OpEvalSnippet):
+  __inputs__ = ['in']
+  __outputs__ = ['out']
+>>>>>>> 05e8882f5f9fd828586bbb708782c9e173677041
 
 
 class TimeSlotContainer(SnippetBase):
diff --git a/utensor_cgen/legalizer/tflite.py b/utensor_cgen/legalizer/tflite.py
index 5e0ec445..8eec014a 100644
--- a/utensor_cgen/legalizer/tflite.py
+++ b/utensor_cgen/legalizer/tflite.py
@@ -38,6 +38,7 @@ class _OpTypeRename(object):
     "Mean": "MeanOperator",
     "Softmax": "SoftmaxOperator",
     "Sigmoid": "SigmoidOperator",
+    "Logistic": "SigmoidOperator",
   }
   
   @classmethod