diff --git a/x2paddle/op_mapper/tf_op_mapper_nhwc.py b/x2paddle/op_mapper/tf_op_mapper_nhwc.py
index c747611f7f005a98b607870c8d2dec8ebca3ca6c..6b00c5c212d4d0cd92067dc4ec83d8f543f244c9 100644
--- a/x2paddle/op_mapper/tf_op_mapper_nhwc.py
+++ b/x2paddle/op_mapper/tf_op_mapper_nhwc.py
@@ -550,6 +550,12 @@ class TFOpMapperNHWC(OpMapper):
             transpose_x=transpose_a,
             transpose_y=transpose_b)
 
+    def BatchMatMul(self, node):
+        return self.MatMul(node)
+
+    def BatchMatMulV2(self, node):
+        return self.MatMul(node)
+
     def DepthwiseConv2dNative(self, node):
         input = self.graph.get_node(node.layer.input[0])
         kernel = self.graph.get_node(node.layer.input[1])
@@ -1043,3 +1049,93 @@ class TFOpMapperNHWC(OpMapper):
         inputs = {"x": node.name, "y": node.name}
         program.add_layer(
             "fluid.layers.elementwise_mul", inputs=inputs, outputs=[node.name])
+
+    def OneHot(self, node):
+        input = self.graph.get_node(node.layer.input[0])
+        depth = self.graph.get_node(node.layer.input[1])
+        on_value = self.graph.get_node(node.layer.input[2])
+        off_value = self.graph.get_node(node.layer.input[3])
+        assert depth.layer_type == 'Const', 'Parameter depth should be Const in OneHot'
+        assert on_value.layer_type == 'Const', 'Parameter on_value should be Const in OneHot'
+        assert off_value.layer_type == 'Const', 'Parameter off_value should be Const in OneHot'
+
+        attr = {'depth': depth.value}
+        on_value = on_value.value
+        off_value = off_value.value
+        assert math.fabs(on_value -
+                         1.0) < 1e-06, "on_value should be 1 in OneHot"
+        assert math.fabs(off_value -
+                         0.0) < 1e-06, "off_value should be 0 in OneHot"
+
+        program.add_layer(
+            "fluid.one_hot",
+            inputs={"input": input.name},
+            outputs=[node.name],
+            depth=depth.value)
+
+    def Pow(self, node):
+        x = self.graph.get_node(node.layer.input[0])
+        factor = self.graph.get_node(node.layer.input[1])
+        inputs = {"x": x.name}
+        attr = dict()
+        if factor.layer_type == 'Const':
+            attr["factor"] = factor.value.tolist()
+        else:
+            inputs["factor"] = factor.name
+        program.add_layer(
+            "fluid.layers.pow", inputs=inputs, outputs=[node.name], **attr)
+
+    def All(self, node):
+        input = self.graph.get_node(node.layer.input[0])
+        reduce_idx = self.graph.get_node(node.layer.input[1])
+        assert reduce_idx.layer_type == "Const", "Only support Const parameter[reduce_idx]"
+        attr = dict()
+        attr["dim"] = reduce_idx.value.tolist()
+        attr["keep_dim"] = node.get_attr("keep_dims")
+
+        program.add_layer(
+            "fluid.layers.reduce_all",
+            inputs={"input": input.name},
+            outputs=[node.name],
+            **attr)
+
+    def GatherV2(self, node):
+        embeddings = self.graph.get_node(node.layer.input[0])
+        index = self.graph.get_node(node.layer.input[1])
+        axis = self.graph.get_node(node.layer.input[2])
+        assert axis.layer_type == 'Const', "Only support Const parameter[axis]"
+        axis = axis.value.tolist()
+        assert axis == 0, "Only support axis=0 in GatherV2 OP"
+        index_name = index.name
+        if len(index.out_shapes[0]) != 1:
+            reshape_name = gen_name("gather", "reshape")
+            index_name = reshape_name
+            program.add_layer(
+                "fluid.layers.reshape",
+                inputs={"x": index.name},
+                outputs=[reshape_name],
+                shape=[-1])
+        inputs = {'input': embeddings.name, 'index': index_name}
+        program.add_layer(
+            "fluid.layers.gather",
+            inputs=inputs,
+            outputs=[node.name],
+            overwrite=False)
+
+    def ExpandDims(self, node):
+        x = self.graph.get_node(node.layer.input[0], copy=True)
+        y = self.graph.get_node(node.layer.input[1], copy=True)
+        inputs = {"input": x.name}
+        attr = dict()
+        if y.layer_type == 'Const':
+            dim = y.value.tolist()
+            if not isinstance(dim, list):
+                dim = [dim]
+            attr['axes'] = dim
+        else:
+            inputs['axes'] = y.name
+        program.add_layer(
+            "fluid.layers.unsqueeze",
+            inputs=inputs,
+            outputs=[node.name],
+            **attr)