diff --git a/metal/paddle-mobile-unit-test/paddle-mobile-unit-test/ViewController.swift b/metal/paddle-mobile-unit-test/paddle-mobile-unit-test/ViewController.swift
index 8d173d6bcc546916ceb1c011110340e6ebf2e95a..80d818a0b54f4159aa4b5c8b61a6c8781782ad96 100644
--- a/metal/paddle-mobile-unit-test/paddle-mobile-unit-test/ViewController.swift
+++ b/metal/paddle-mobile-unit-test/paddle-mobile-unit-test/ViewController.swift
@@ -20,7 +20,8 @@ class ViewController: UIViewController {
             inDevice: device,
             inQueue: queue
         )
-        test.testReshape()
+        test.testConcat()
+//        test.testReshape()
 //        test.testTranspose()
         print(" done ")
     }
diff --git a/metal/paddle-mobile/paddle-mobile/Common/PaddleMobileUnitTest.swift b/metal/paddle-mobile/paddle-mobile/Common/PaddleMobileUnitTest.swift
index f4bd21452e2a011c7dd0ab09479df94d4b1f17a6..0d1fd39a346f220e4afa5b2bc2e5a711e57e7c14 100644
--- a/metal/paddle-mobile/paddle-mobile/Common/PaddleMobileUnitTest.swift
+++ b/metal/paddle-mobile/paddle-mobile/Common/PaddleMobileUnitTest.swift
@@ -82,6 +82,37 @@ public class PaddleMobileUnitTest {
         indentPrintTensor(tensor: tensor, dim: ndim, ix: dim.map { $0 * 0 }, indentLevel: 0)
     }
     
+    public func testConcat() {
+        let buffer = queue.makeCommandBuffer() ?! "buffer is nil"
+        var it: [[Float32]] = []
+        for _ in 0..<7 {
+            it.append((0..<12).map { Float32($0) })
+        }
+        let input = it.map { device.tensor2texture(value: $0, dim: [3, 4]) }
+        let output = device.tensor2texture(value: [Float32](), dim: [3, 28])
+        
+        let param = ConcatTestParam.init(
+            input: input,
+            output: output,
+            dims: [[3, 4], [3, 4], [3, 4], [3, 4], [3, 4], [3, 4], [3, 4]],
+            axis: 1,
+            odim: [3, 28]
+        )
+        let concatKernel = ConcatKernel<Float32>.init(device: device, testParam: param)
+        concatKernel.test(cmdBuffer: buffer, param: param)
+        buffer.addCompletedHandler { (buffer) in
+            for i in 0..<it.count {
+                let _: Float32? = input[i].logDesc()
+                self.tensorPrint(tensor: it[i], dim: [3, 4])
+            }
+            let _: Float32? = output.logDesc()
+            let tx: [Float32] = self.device.texture2tensor(texture: output, dim: [3, 28])
+            self.tensorPrint(tensor: tx, dim: [3, 28])
+        }
+
+        buffer.commit()
+    }
+    
     public func testReshape() {
         let buffer = queue.makeCommandBuffer() ?! "buffer is nil"
 //        let input: [Float32] = (0..<24).map { Float32($0) }
diff --git a/metal/paddle-mobile/paddle-mobile/Operators/ConcatOp.swift b/metal/paddle-mobile/paddle-mobile/Operators/ConcatOp.swift
index bf2a60c613b00f09733dcff644d8417fb073b20b..1dd0a06ce7ee7bfee1bfcdefd74f772f3e5ce1cb 100644
--- a/metal/paddle-mobile/paddle-mobile/Operators/ConcatOp.swift
+++ b/metal/paddle-mobile/paddle-mobile/Operators/ConcatOp.swift
@@ -41,8 +41,8 @@ class ConcatParam<P: PrecisionType>: OpParam {
 class ConcatOp<P: PrecisionType>: Operator<ConcatKernel<P>, ConcatParam<P>>, Runable, Creator, InferShaperable{
     
     func inferShape() {
-        let dim = para.input.reduce([0, 0]) {[$0[0] + $1.dim[0], $1.dim[1]]}
-        para.output.dim = Dim.init(inDim: dim)
+//        let dim = para.input.reduce([0, 0]) {[$0[0] + $1.dim[0], $1.dim[1]]}
+//        para.output.dim = Dim.init(inDim: dim)
     }
     
     typealias OpType = ConcatOp<P>
diff --git a/metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConcatKernel.swift b/metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConcatKernel.swift
index f5a16141fa77a1a03eedbdb5748bd321f667d226..9e6e0c368f4f745fc6b2e7ef8d7bef802eb20b41 100644
--- a/metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConcatKernel.swift
+++ b/metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConcatKernel.swift
@@ -14,18 +14,114 @@
 
 import Foundation
 
+struct ConcatTestParam: TestParam {
+    var input: [MTLTexture]
+    var output: MTLTexture
+    var dims: [[Int]]
+    var axis: Int
+    var odim: [Int]
+}
+
+struct ConcatMetalParam {
+    var odim: (Int32, Int32, Int32, Int32) = (1, 1, 1, 1)
+    var axis: Int32 = 0
+    var offset: Int32 = 0
+    var vdim: (Int32, Int32, Int32, Int32, Int32, Int32) = (0, 0, 0, 0, 0, 0)
+}
+
 class ConcatKernel<P: PrecisionType>: Kernel, Computable{
-    func compute(commandBuffer: MTLCommandBuffer, param: ConcatParam<P>) throws {
-        guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
+    
+    func encodeTest(_ cmdBuffer: MTLCommandBuffer, _ param: ConcatTestParam, _ istart: Int, _ iend: Int) {
+        let encoder = cmdBuffer.makeComputeCommandEncoder()!
+        var p = ConcatMetalParam.init()
+        var odim: [Int32] = [1, 1, 1, 1]
+        for i in 0..<param.odim.count {
+            odim[4-param.odim.count+i] = Int32(param.odim[i])
+        }
+        p.odim = (odim[0], odim[1], odim[2], odim[3])
+        p.axis = Int32(4 - param.odim.count + param.axis)
+        for i in 0..<istart {
+            p.offset += Int32(param.dims[i][param.axis])
+        }
+        var vdim: [Int32] = []
+        for i in 0..<(iend - istart) {
+            encoder.setTexture(param.input[i+istart], index: i)
+            vdim.append(Int32(param.dims[i+istart][Int(param.axis)]))
+        }
+        for i in (iend-istart)..<6 {
+            encoder.setTexture(param.input[0], index: i)
+            vdim.append(0)
+        }
+        p.vdim = (vdim[0], vdim[1], vdim[2], vdim[3], vdim[4], vdim[5])
+        encoder.setTexture(param.output, index: 6)
+        encoder.setTexture(param.output, index: 7)
+        encoder.setBytes(&p, length: MemoryLayout<ConcatMetalParam>.size, index: 0)
+        encoder.dispatch(computePipline: pipline, outTexture: param.output)
+        encoder.endEncoding()
+    }
+    
+    func encode(_ cmdBuffer: MTLCommandBuffer, _ param: ConcatParam<P>, _ istart: Int, _ iend: Int) throws {
+        guard let encoder = cmdBuffer.makeComputeCommandEncoder() else {
             throw PaddleMobileError.predictError(message: " encode is nil")
         }
-//        encoder.setTexture(param.input.metalTexture, index: 0)
-//        encoder.setTexture(param.output.metalTexture, index: 1)
+        var p = ConcatMetalParam.init()
+        let odim = (0..<4).map { Int32(param.output.dim[$0]) }
+        p.odim = (odim[0], odim[1], odim[2], odim[3])
+        p.axis = Int32(4 - param.output.tensorDim.cout() + param.axis)
+        for i in 0..<istart {
+            p.offset += Int32(param.input[i+istart].dim[Int(p.axis)])
+        }
+        var vdim: [Int32] = []
+        for i in 0..<(iend - istart) {
+            encoder.setTexture(param.input[i+istart].metalTexture, index: i)
+            vdim.append(Int32(param.input[i+istart].dim[Int(p.axis)]))
+        }
+        for i in (iend-istart)..<6 {
+            encoder.setTexture(param.input[0].metalTexture, index: i)
+            vdim.append(0)
+        }
+        p.vdim = (vdim[0], vdim[1], vdim[2], vdim[3], vdim[4], vdim[5])
+        encoder.setTexture(param.output.metalTexture, index: 6)
+        encoder.setTexture(param.output.metalTexture, index: 7)
+        encoder.setBytes(&p, length: MemoryLayout<ConcatMetalParam>.size, index: 0)
         encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
         encoder.endEncoding()
     }
     
+    func compute(commandBuffer: MTLCommandBuffer, param: ConcatParam<P>) throws {
+        for i in 0..<param.input.count {
+            for j in 0..<4 {
+                assert(param.input[i].transpose[j] == j)
+            }
+        }
+        
+        let group = param.input.count / 6
+        let remain = param.input.count % 6
+        for i in 0..<group {
+            try self.encode(commandBuffer, param, 6 * i, 6 * (i + 1))
+        }
+        if remain > 0 {
+            try self.encode(commandBuffer, param, 6 * group, param.input.count)
+        }
+    }
+    
+    func test(cmdBuffer: MTLCommandBuffer, param: ConcatTestParam) {
+        let group = param.input.count / 6
+        let remain = param.input.count % 6
+        for i in 0..<group {
+            try self.encodeTest(cmdBuffer, param, 6 * i, 6 * (i + 1))
+        }
+        if remain > 0 {
+            try self.encodeTest(cmdBuffer, param, 6 * group, param.input.count)
+        }
+    }
+    
     required init(device: MTLDevice, param: ConcatParam<P>) {
+        param.output.initTexture(device: device)
+        super.init(device: device, inFunctionName: "concat")
+    }
+    
+    required init(device: MTLDevice, testParam: ConcatTestParam) {
         super.init(device: device, inFunctionName: "concat")
     }
 }
diff --git a/metal/paddle-mobile/paddle-mobile/Operators/Kernels/Kernels.metal b/metal/paddle-mobile/paddle-mobile/Operators/Kernels/Kernels.metal
index f8c9099415b3675c5f583d2905a1fa52e46b05a3..234fbd0fd61fed4def08a3526a4b5fe17aae80fc 100644
--- a/metal/paddle-mobile/paddle-mobile/Operators/Kernels/Kernels.metal
+++ b/metal/paddle-mobile/paddle-mobile/Operators/Kernels/Kernels.metal
@@ -425,3 +425,55 @@ kernel void reshape(texture2d_array<float, access::read> inTexture [[texture(0)]
 //    half4 r = inTexture.read(uint2(0, 0), gid.x);
 //    outTexture.write(r, gid.xy, gid.z);
 //}
+
+struct ConcatParam {
+    int32_t odim[4];
+    int32_t axis;
+    int32_t offset;
+    int32_t vdim[6];
+};
+
+kernel void concat(texture2d_array<float, access::read> in0 [[texture(0)]],
+                   texture2d_array<float, access::read> in1 [[texture(1)]],
+                   texture2d_array<float, access::read> in2 [[texture(2)]],
+                   texture2d_array<float, access::read> in3 [[texture(3)]],
+                   texture2d_array<float, access::read> in4 [[texture(4)]],
+                   texture2d_array<float, access::read> in5 [[texture(5)]],
+                   texture2d_array<float, access::read> inx [[texture(6)]],
+                   texture2d_array<float, access::write> out [[texture(7)]],
+                   constant ConcatParam & pm [[buffer(0)]],
+                   uint3 gid [[thread_position_in_grid]]) {
+    ConcatParam cp = pm;
+    int xyzn[4] = {int(gid.x), int(gid.y), int(gid.z), 0}, abcd[4], oxyzn[4];
+    float4 r;
+    for (int i = 0; i < 4; i++) {
+        xyzn[3] = i;
+        xyzn2abcd(cp.odim[3], xyzn, abcd);
+        int k = abcd[cp.axis] - cp.offset;
+        int j = 0;
+        if (k < 0) {
+            r[i] = inx.read(gid.xy, gid.z)[i];
+        } else {
+            for (; j < 6; j++) {
+                if (k < cp.vdim[j]) {
+                    break;
+                }
+                k -= cp.vdim[j];
+            }
+            int ta = cp.odim[cp.axis];
+            abcd[cp.axis] = k;
+            cp.odim[cp.axis] = cp.vdim[j];
+            abcd2xyzn(cp.odim[3], abcd, oxyzn);
+            cp.odim[cp.axis] = ta;
+            switch (j) {
+            case 0: r[i] = in0.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+            case 1: r[i] = in1.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+            case 2: r[i] = in2.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+            case 3: r[i] = in3.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+            case 4: r[i] = in4.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+            case 5: r[i] = in5.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+            }
+        }
+    }
+    out.write(r, gid.xy, gid.z);
+}
diff --git a/metal/paddle-mobile/paddle-mobile/framework/Texture.swift b/metal/paddle-mobile/paddle-mobile/framework/Texture.swift
index f34cebbfc9bf344fe52b3a5c77a9ab20288516c8..04e48c7b08ab3165175bb37aeb6e9a2568794a47 100644
--- a/metal/paddle-mobile/paddle-mobile/framework/Texture.swift
+++ b/metal/paddle-mobile/paddle-mobile/framework/Texture.swift
@@ -40,6 +40,7 @@ extension InputTexture {
 
 public class Texture<P: PrecisionType>: Tensorial {
     var dim: Dim
+    var tensorDim: Dim
     private(set) var originDim: Dim
     private var textureDesc: MTLTextureDescriptor!
     var metalTexture: MTLTexture!
@@ -89,7 +90,7 @@ public class Texture<P: PrecisionType>: Tensorial {
         } else {
             fatalError(" not support ")
         }
-        
+        tensorDim = inDim
         dim = fourDim
         originDim = fourDim
         layout = DataLayout.init([(.N, fourDim[0]), (.C, fourDim[1]), (.H, fourDim[2]), (.W, fourDim[3])])