diff --git a/x2paddle/op_mapper/tf_op_mapper_nhwc.py b/x2paddle/op_mapper/tf_op_mapper_nhwc.py
index 53e52a4b177665e0b376f93b3da21423ed9ecc48..65b9c55e9f17d4f0447109384c03b21b82388850 100644
--- a/x2paddle/op_mapper/tf_op_mapper_nhwc.py
+++ b/x2paddle/op_mapper/tf_op_mapper_nhwc.py
@@ -308,6 +308,10 @@ class TFOpMapperNHWC(OpMapper):
         dilations = node.get_attr("dilations")
         data_format = node.get_attr("data_format").decode()
         pad_mode = node.get_attr("padding").decode()
+        if data_format == "NHWC":
+            n, c, h, w = input.out_shapes[0]
+        else:
+            n, h, w, c = input.out_shapes[0]
 
         if kernel.layer_type == 'Const':
             kernel_value = kernel.value
@@ -334,6 +338,16 @@ class TFOpMapperNHWC(OpMapper):
                 perm=[0, 3, 1, 2])
             input_name = transpose_name
 
+        if c == -1:
+            attr = {"shape": [0, k_size[2], 0, 0]}
+            node.fluid_code.add_layer(
+                "reshape", inputs=input, output=input, param_attr=attr)
+            program.add_layer(
+                kernel="fluid.layers.reshape",
+                inputs={"x": input_name},
+                outputs=[input_name],
+                shape=[0, k_size[2], 0, 0])
+
         program.add_layer(
             kernel="fluid.layers.conv2d",
             inputs={"input": input_name},
@@ -701,7 +715,7 @@ class TFOpMapperNHWC(OpMapper):
         if len(new_axes) > 0:
             program.add_layer(
                 kernel="fluid.layers.unsqueeze",
-                inputs={"x": node.name},
+                inputs={"input": node.name},
                 outputs=[node.name],
                 axes=new_axes)
         if len(shrink_axes) > 0:
@@ -710,7 +724,7 @@ class TFOpMapperNHWC(OpMapper):
             else:
                 program.add_layer(
                     kernel="fluid.layers.unsqueeze",
-                    inputs={"x": node.name},
+                    inputs={"input": node.name},
                     outputs=[node.name],
                     axes=new_axes)
 
@@ -741,14 +755,16 @@ class TFOpMapperNHWC(OpMapper):
             begin = begin.value.tolist()
             attrs['offsets'] = begin
         else:
-            shape = begin.out_shapes[0]
-            reshape_name = gen_name("slice", "reshape")
-            program.add_layer(
-                kernel="fluid.layers.reshape",
-                inputs={"x": begin.name},
-                outputs=[reshape_name],
-                shape=shape)
-            inputs['offsets'] = reshape_name
+            #             shape = begin.out_shapes[0]
+            #             reshape_name = gen_name("slice", "reshape")
+            #             program.add_layer(
+            #                 kernel="fluid.layers.reshape",
+            #                 inputs={"x": begin.name},
+            #                 outputs=[reshape_name],
+            #                 shape=shape)
+            #             inputs['offsets'] = reshape_name
+            begin = self.decoder.infer_tensor(begin).tolist()
+            attrs['offsets'] = begin
         if size.layer_type == "Const":
             size = size.value.tolist()
             attrs['shape'] = size
@@ -966,3 +982,47 @@ class TFOpMapperNHWC(OpMapper):
                 inputs={"x": node.name},
                 outputs=[node.name],
                 perm=[0, 2, 3, 1])
+
+    def Tile(self, node):
+        input = self.graph.get_node(node.layer.input[0], copy=True)
+        expand_times = self.graph.get_node(node.layer.input[1], copy=True)
+        inputs = {"x": input.name}
+        attr = dict()
+        if expand_times.layer_type == "Const":
+            expand_times = expand_times.value.tolist()
+            attr["expand_times"] = expand_times
+        else:
+            inputs["expand_times"] = expand_times.name
+
+        program.add_layer(
+            kernel="fluid.layers.expand",
+            inputs=inputs,
+            outputs=[node.name],
+            **attr)
+
+    def Range(self, node):
+        start = self.graph.get_node(node.layer.input[0], copy=True)
+        limit = self.graph.get_node(node.layer.input[1], copy=True)
+        delta = self.graph.get_node(node.layer.input[2], copy=True)
+        inputs = dict()
+        attr = dict()
+
+        if start.layer_type == "Const":
+            attr["start"] = start.value
+        else:
+            inputs["start"] = start.name
+        if limit.layer_type == "Const":
+            attr["end"] = limit.value
+        else:
+            inputs["end"] = limit.name
+        if delta.layer_type == "Const":
+            attr["step"] = delta.value
+        else:
+            inputs["step"] = delta.name
+        attr["dtype"] = string(node.dtype)
+
+        program.add_layer(
+            kernel="fluid.layers.range",
+            inputs=inputs,
+            outputs=[node.name],
+            **attr)