diff --git a/.gitignore b/.gitignore
index 6d40de30..bb03a7b6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -15,3 +15,7 @@ tests/*/cpp
 */*/models
 tests/deep_mlp/data 
 .vscode
+*.pyc
+.*.pyc
+*.swp
+.*.swp
diff --git a/utensor_cgen/backend/operators.py b/utensor_cgen/backend/operators.py
index a5d0209d..83062db9 100644
--- a/utensor_cgen/backend/operators.py
+++ b/utensor_cgen/backend/operators.py
@@ -477,10 +477,10 @@ class _QuantizedFusedConv2DMaxpoolOperator(_Operator):
   def __init__(self, op_info, **kwargs):
     _Operator.__init__(self)
     inputs = [tensor_info.name for tensor_info in op_info.input_tensors]
-    output = op_info.output_tensors[0].name
+    outputs = [tensor_info.name for tensor_info in op_info.output_tensors]
     in_dtype, filter_dtype = (op_info.input_tensors[0].dtype,
                               op_info.input_tensors[1].dtype)
-    out_dtype = op_info.output_tensors[0].dtype
+    out_dtypes = [tensor_info.dtype for tensor_info in op_info.output_tensors]
     strides = op_info.op_attr['_utensor_conv']["strides"].value.ints_value
     ksize = op_info.op_attr['_utensor_pool']["ksize"].value.ints_value
     padding = op_info.op_attr['_utensor_conv']["padding"].value.decode('utf8')
@@ -488,8 +488,8 @@ def __init__(self, op_info, **kwargs):
                                     op_info.op_attr)
     ref_count = parser.get('ref_counts', [0])[0]
     to_eval = parser.get('to_eval', False)
-    self._snippet = QuantizedFusedConv2DMaxpoolOpSnippet(inputs, output, strides, ksize, padding,
-                                     in_dtype=in_dtype, filter_dtype=filter_dtype, out_dtype=out_dtype,
+    self._snippet = QuantizedFusedConv2DMaxpoolOpSnippet(inputs, outputs, strides, ksize, padding,
+                                     in_dtype=in_dtype, filter_dtype=filter_dtype, out_dtypes=out_dtypes,
                                      ref_count=ref_count, to_eval=to_eval)
 
 @OperatorFactory.register
@@ -726,7 +726,7 @@ def __init__(self, op_info, **kwargs):
 @OperatorFactory.register
 class _GatherOperator(_Operator):
 
-  op_type = "Gather" # tf op type
+  op_type = "GatherV2" # tf op type
 
   def __init__(self, op_info, **kwargs):
     _Operator.__init__(self)
diff --git a/utensor_cgen/backend/snippets/_snippets.py b/utensor_cgen/backend/snippets/_snippets.py
index 2314a7a6..f4e65169 100644
--- a/utensor_cgen/backend/snippets/_snippets.py
+++ b/utensor_cgen/backend/snippets/_snippets.py
@@ -666,21 +666,23 @@ def __init__(self, inputs, output, strides, ksize, padding,
     self.template_vars["to_eval"] = to_eval
 
 class QuantizedFusedConv2DMaxpoolOpSnippet(Snippet):
-  __template_name__ = "snippets/fused_conv2d_maxpool_op.cpp"
+  __template_name__ = "snippets/quantized_fused_conv2d_maxpool_op.cpp"
   __headers__ = set(['"uTensor/ops/MatrixOps.hpp"'])
 
-  def __init__(self, inputs, output, strides, ksize, padding,
-               in_dtype, filter_dtype, out_dtype,
+  def __init__(self, inputs, outputs, strides, ksize, padding,
+               in_dtype, filter_dtype, out_dtypes,
                ref_count=0,
                to_eval=False):
     Snippet.__init__(self)
     if ref_count:
       self.template_vars["ref_count"] = ref_count
+    print(outputs)
+    print(out_dtypes)
     self.template_vars["inputs"] = inputs
-    self.template_vars["output"] = output
+    self.template_vars["outputs"] = outputs
     self.template_vars["in_dtype"] = NP_TYPES_MAP[in_dtype].tensor_type_str
     self.template_vars["filter_dtype"] = NP_TYPES_MAP[filter_dtype].tensor_type_str
-    self.template_vars["out_dtype"] = NP_TYPES_MAP[out_dtype].tensor_type_str
+    self.template_vars["out_dtypes"] = [NP_TYPES_MAP[out_dtype].tensor_type_str for out_dtype in out_dtypes]
     self.template_vars["strides"] = strides
     self.template_vars["ksize"] = ksize
     self.template_vars["padding"] = padding
diff --git a/utensor_cgen/backend/snippets/templates/snippets/quantized_fused_conv2d_maxpool_op.cpp b/utensor_cgen/backend/snippets/templates/snippets/quantized_fused_conv2d_maxpool_op.cpp
index 7aa4f07a..1161e3df 100644
--- a/utensor_cgen/backend/snippets/templates/snippets/quantized_fused_conv2d_maxpool_op.cpp
+++ b/utensor_cgen/backend/snippets/templates/snippets/quantized_fused_conv2d_maxpool_op.cpp
@@ -8,7 +8,7 @@
     ctx.add(new RamTensor<{{out_dtypes[1]}}>({1}), "{{outputs[1]}}");
     ctx.add(new RamTensor<{{out_dtypes[2]}}>({1}), "{{outputs[2]}}");
     {% endif %}
-    ctx.push(new QuantizedFusedConvMaxpoolOp<{{in_dtype}}, {{filter_dtype}}, {{out_dtype}}>({ {% for s in strides[:-1]%}{{s}}, {%endfor%}{{strides[-1]}} }, { {% for s in ksize[:-1]%}{{s}}, {%endfor%}{{ksize[-1]}} },{{padding}}),
+    ctx.push(new QuantizedFusedConvMaxpoolOp<{{in_dtype}}, {{filter_dtype}}, {{out_dtypes[0]}}>({ {% for s in strides[:-1]%}{{s}}, {%endfor%}{{strides[-1]}} }, { {% for s in ksize[:-1]%}{{s}}, {%endfor%}{{ksize[-1]}} },{{padding}}),
              { {% for tname in inputs[:-1]%}"{{tname}}", {%endfor%}"{{inputs[-1]}}" },
              { {% for tname in outputs[:-1]%}"{{tname}}", {%endfor%}"{{outputs[-1]}}" });
     {% if to_eval %}