[Feature](mlu-ops): add dcn_forward and dcn_backward_weight op

docs/MLU-OPS-OpList.md

@@ -101,4 +101,6 @@ MLU Binary Op算子结构：　
 | voxel_pooling_forward                  | √             |               |
 | voxelization                           | √             |               |
 | yolo_box                               | √             |               |
-| dcn_backward_data                      |               | √             |
+| dcn_backward_data                      |               | √             |
+| dcn_forward                            |               | √             |
+| dcn_backward_weight                    |               | √             |

docs/user_guide/9_operators/index.rst

@@ -90,6 +90,24 @@ mluOpCopy
 -----------------------------
 该算子主要在语音网络中使用，对数据块进行 device 到 device 的拷贝。
 
+.. _dcn_backward_data:
+
+mluOpDCNBackwardData
+---------------------------------
+该算子用于求取可变形卷积算子关于input、offset、mask的反向梯度。
+
+.. _dcn_backward_weight:
+
+mluOpDCNBackwardWeight
+-----------------------------
+求取可变形卷积算子关于filter和bias的反向梯度。
+
+.. _dcn_forward:
+
+mluOpDCNForward
+-----------------------------
+可变形卷积。通过额外的offset和mask来增强滤波器对空间的几何表达能力，并且该卷积可以任意替代之前卷及网络里面的任意常规卷积层。
+
 .. _deform_roi_pool_backward:
 
 mluOpDeformRoiPoolBackward
@@ -1008,9 +1026,3 @@ mluOpConcat
  - ``N`` 为每个input和output的维度数。
  - ``sum(axis_1, ..., axis_m)`` 表示对待拼接维度求和，output的拼接维度大小为所有input拼接维度的总和。
  - 除拼接维度外，其余维度的大小需要相等。
-
-.. _dcn_backward_data:
-
-mluOpDCNBackwardData
----------------------------------
-该算子用于求取可变形卷积算子关于input、offset、mask的反向梯度。

kernel_depends.toml

@@ -41,3 +41,5 @@ deform_roi_pool_forward = ["deform_roi_pool"]
 deform_roi_pool_backward = ["deform_roi_pool"]
 carafe_forward = ["carafe"]
 carafe_backward = ["carafe"]
+dcn_backward_weight = ["dcn_forward"]
+dcn_backward_data = ["dcn_forward"]

kernels/dcn_backward_data/dcn_backward_data.cpp

@@ -1,5 +1,5 @@
 /*************************************************************************
- * Copyright (C) [2022] by Cambricon, Inc.
+ * Copyright (C) [2024] by Cambricon, Inc.
  *
  * Permission is hereby granted, free of charge, to any person obtaining a
  * copy of this software and associated documentation files (the
@@ -26,43 +26,7 @@
 
 #include "kernels/utils/cnnl_helper.h"
 
-#define DCNBPDATA_API "mluOpDcnBackwardData"
-
-mluOpStatus_t MLUOP_WIN_API
-mluOpCreateDCNDescriptor(mluOpDCNDescriptor_t *dcn_desc) {
-  PARAM_CHECK(DCNBPDATA_API, dcn_desc != NULL);
-  CHECK_FUNC_RETURN(cnnlCreateDCNDescriptor(dcn_desc), CNNL_STATUS_SUCCESS,
-                    "[mluOpCreateDCNDescriptor] Internal error accured in "
-                    "cnnlCreateDCNDescriptor.",
-                    MLUOP_STATUS_INTERNAL_ERROR);
-  return MLUOP_STATUS_SUCCESS;
-}
-
-mluOpStatus_t MLUOP_WIN_API
-mluOpDestroyDCNDescriptor(mluOpDCNDescriptor_t dcn_desc) {
-  PARAM_CHECK(DCNBPDATA_API, dcn_desc != NULL);
-  CHECK_FUNC_RETURN(cnnlDestroyDCNDescriptor(dcn_desc), CNNL_STATUS_SUCCESS,
-                    "[mluOpDestroyDCNDescriptor] Internal error accured in "
-                    "cnnlDestroyDCNDescriptor.",
-                    MLUOP_STATUS_INTERNAL_ERROR);
-  return MLUOP_STATUS_SUCCESS;
-}
-
-mluOpStatus_t MLUOP_WIN_API mluOpSetDCNDescriptor(
-    mluOpDCNDescriptor_t dcn_desc, int dimNb, const int pad[],
-    const int stride[], const int dilation[], int deformable_group,
-    int conv_group, int im2col_step, const mluOpDataType_t compute_type) {
-  PARAM_CHECK(DCNBPDATA_API, dcn_desc != NULL);
-  CHECK_FUNC_RETURN(
-      cnnlSetDCNDescriptor(dcn_desc, dimNb, pad, stride, dilation,
-                           deformable_group, conv_group, im2col_step,
-                           cnnlDataType_t(compute_type)),
-      CNNL_STATUS_SUCCESS,
-      "[mluOpSetDCNDescriptor] Internal error accured in "
-      "cnnlSetDCNDescriptor.",
-      MLUOP_STATUS_INTERNAL_ERROR);
-  return MLUOP_STATUS_SUCCESS;
-}
+#define DCNBPDATA_API "mluOpDCNBackwardData"
 
 mluOpStatus_t MLUOP_WIN_API mluOpGetDCNBakcwardDataWorkspaceSize(
     mluOpHandle_t handle, const mluOpDCNDescriptor_t dcn_desc,

kernels/dcn_backward_weight/dcn_backward_weight.cpp

@@ -0,0 +1,109 @@
+/*************************************************************************
+ * Copyright (C) [2024] by Cambricon, Inc.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a
+ * copy of this software and associated documentation files (the
+ * "Software"), to deal in the Software without restriction, including
+ * without limitation the rights to use, copy, modify, merge, publish,
+ * distribute, sublicense, and/or sell copies of the Software, and to
+ * permit persons to whom the Software is furnished to do so, subject to
+ * the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included
+ * in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
+ * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+ * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+ * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+ * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+ * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+ * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ *************************************************************************/
+#include <limits.h>
+#include <math.h>
+#include <vector>
+
+#include "kernels/utils/cnnl_helper.h"
+
+#define DCNBACKWARDWEIGHT_API "mluOpDCNBackwardWeight"
+
+mluOpStatus_t MLUOP_WIN_API mluOpGetDCNBackwardWeightWorkspaceSize(
+    mluOpHandle_t handle, const mluOpDCNDescriptor_t dcn_desc,
+    const mluOpTensorDescriptor_t input_desc,
+    const mluOpTensorDescriptor_t offset_desc,
+    const mluOpTensorDescriptor_t mask_desc,
+    const mluOpTensorDescriptor_t grad_output_desc,
+    const mluOpTensorDescriptor_t grad_filter_desc,
+    const mluOpTensorDescriptor_t grad_bias_desc, size_t *size) {
+  PARAM_CHECK("mluOpDCNBackwardWeight", handle != NULL);
+  PARAM_CHECK("mluOpDCNBackwardWeight", dcn_desc != NULL);
+  DEFINE_CREATE_AND_SET_CNNL_HANDLE(handle, _handle);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(input_desc, _input_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(offset_desc, _offset_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(mask_desc, _mask_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(grad_output_desc,
+                                               _grad_output_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(grad_filter_desc,
+                                               _grad_filter_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(grad_bias_desc, _grad_bias_desc);
+  CHECK_FUNC_RETURN(
+      cnnlGetDCNBackwardWeightWorkspaceSize(
+          _handle, dcn_desc, _input_desc, _offset_desc, _mask_desc,
+          _grad_output_desc, _grad_filter_desc, _grad_bias_desc, size),
+      CNNL_STATUS_SUCCESS,
+      "[mluOpDCNBackwardWeight] Internal error accured in "
+      "mluOpGetDCNBackwardWeightWorkspaceSize.",  // NOLINT
+      MLUOP_STATUS_INTERNAL_ERROR);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(_input_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(_offset_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(_mask_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(_grad_output_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(_grad_filter_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(_grad_bias_desc);
+  DESTROY_CNNL_HANDLE(_handle);
+  return MLUOP_STATUS_SUCCESS;
+}
+
+mluOpStatus_t MLUOP_WIN_API mluOpDCNBackwardWeight(
+    mluOpHandle_t handle, const mluOpDCNDescriptor_t dcn_desc,
+    const mluOpTensorDescriptor_t input_desc, const void *input,
+    const mluOpTensorDescriptor_t offset_desc, const void *offset,
+    const mluOpTensorDescriptor_t mask_desc, const void *mask,
+    const mluOpTensorDescriptor_t grad_output_desc, const void *grad_output,
+    void *workspace, const size_t workspace_size,
+    const mluOpTensorDescriptor_t grad_filter_desc, void *grad_filter,
+    const mluOpTensorDescriptor_t grad_bias_desc, void *grad_bias) {
+  PARAM_CHECK(DCNBACKWARDWEIGHT_API, handle != NULL);
+  if (workspace_size > 0) {
+    PARAM_CHECK(DCNBACKWARDWEIGHT_API, workspace != NULL);
+  }
+  DEFINE_CREATE_AND_SET_CNNL_HANDLE(handle, cnnl_handle);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(input_desc, cnnl_input_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(offset_desc, cnnl_offset_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(mask_desc, cnnl_mask_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(grad_output_desc,
+                                               cnnl_grad_output_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(grad_filter_desc,
+                                               cnnl_grad_filter_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(grad_bias_desc,
+                                               cnnl_grad_bias_desc);
+  CHECK_FUNC_RETURN(
+      cnnlDCNBackwardWeight(cnnl_handle, dcn_desc, cnnl_input_desc, input,
+                            cnnl_offset_desc, offset, cnnl_mask_desc, mask,
+                            cnnl_grad_output_desc, grad_output, workspace,
+                            workspace_size, cnnl_grad_filter_desc, grad_filter,
+                            cnnl_grad_bias_desc, grad_bias),
+      CNNL_STATUS_SUCCESS,
+      "[mluOpDcnBackwardWeight] Internal error accured in "
+      "mluOpDcnBackwardWeight.",
+      MLUOP_STATUS_INTERNAL_ERROR);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_input_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_offset_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_mask_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_grad_output_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_grad_filter_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_grad_bias_desc);
+  DESTROY_CNNL_HANDLE(cnnl_handle);
+  return MLUOP_STATUS_SUCCESS;
+}

kernels/dcn_forward/dcn_common.h

@@ -0,0 +1,69 @@
+/*************************************************************************
+ * Copyright (C) [2022] by Cambricon, Inc.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a
+ * copy of this software and associated documentation files (the
+ * "Software"), to deal in the Software without restriction, including
+ * without limitation the rights to use, copy, modify, merge, publish,
+ * distribute, sublicense, and/or sell copies of the Software, and to
+ * permit persons to whom the Software is furnished to do so, subject to
+ * the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included
+ * in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
+ * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+ * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+ * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+ * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+ * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+ * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ *************************************************************************/
+#ifndef KERNELS_DCN_COMMON_DCN_COMMON_H
+#define KERNELS_DCN_COMMON_DCN_COMMON_H
+#include <limits.h>
+#include <math.h>
+#include <vector>
+
+#include "kernels/utils/cnnl_helper.h"
+
+#define DCN_API "mluOpDCN"
+
+mluOpStatus_t MLUOP_WIN_API
+mluOpCreateDCNDescriptor(mluOpDCNDescriptor_t *dcn_desc) {
+  PARAM_CHECK(DCN_API, dcn_desc != NULL);
+  CHECK_FUNC_RETURN(cnnlCreateDCNDescriptor(dcn_desc), CNNL_STATUS_SUCCESS,
+                    "[mluOpDcn] Internal error accured in "
+                    "mluOpCreateDCNDescriptor.",
+                    MLUOP_STATUS_INTERNAL_ERROR);
+  return MLUOP_STATUS_SUCCESS;
+}
+
+mluOpStatus_t MLUOP_WIN_API
+mluOpDestroyDCNDescriptor(mluOpDCNDescriptor_t dcn_desc) {
+  PARAM_CHECK(DCN_API, dcn_desc != NULL);
+  CHECK_FUNC_RETURN(cnnlDestroyDCNDescriptor(dcn_desc), CNNL_STATUS_SUCCESS,
+                    "[mluOpDcn] Internal error accured in "
+                    "mluOpDestroyDCNDescriptor.",
+                    MLUOP_STATUS_INTERNAL_ERROR);
+  return MLUOP_STATUS_SUCCESS;
+}
+
+mluOpStatus_t MLUOP_WIN_API mluOpSetDCNDescriptor(
+    mluOpDCNDescriptor_t dcn_desc, int dimNb, const int pad[],
+    const int stride[], const int dilation[], int deformable_group,
+    int conv_group, int im2col_step, const mluOpDataType_t compute_type) {
+  PARAM_CHECK(DCN_API, dcn_desc != NULL);
+  CHECK_FUNC_RETURN(
+      cnnlSetDCNDescriptor(dcn_desc, dimNb, pad, stride, dilation,
+                           deformable_group, conv_group, im2col_step,
+                           cnnlDataType_t(compute_type)),
+      CNNL_STATUS_SUCCESS,
+      "[mluOpDcn] Internal error accured in "
+      "mluOpSetDCNDescriptor.",
+      MLUOP_STATUS_INTERNAL_ERROR);
+  return MLUOP_STATUS_SUCCESS;
+}
+
+#endif  // KERNELS_DCN_COMMON_DCN_COMMON_H

kernels/dcn_forward/dcn_forward.cpp

@@ -0,0 +1,103 @@
+/*************************************************************************
+ * Copyright (C) [2024] by Cambricon, Inc.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a
+ * copy of this software and associated documentation files (the
+ * "Software"), to deal in the Software without restriction, including
+ * without limitation the rights to use, copy, modify, merge, publish,
+ * distribute, sublicense, and/or sell copies of the Software, and to
+ * permit persons to whom the Software is furnished to do so, subject to
+ * the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included
+ * in all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
+ * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+ * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+ * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+ * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+ * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+ * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ *************************************************************************/
+#include "kernels/dcn_forward/dcn_common.h"
+
+#define DCNFORWARD_API "mluOpDCNForward"
+
+mluOpStatus_t MLUOP_WIN_API mluOpGetDCNForwardWorkspaceSize(
+    mluOpHandle_t handle, const mluOpDCNDescriptor_t dcn_desc,
+    const mluOpTensorDescriptor_t input_desc,
+    const mluOpTensorDescriptor_t offset_desc,
+    const mluOpTensorDescriptor_t mask_desc,
+    const mluOpTensorDescriptor_t filter_desc,
+    const mluOpTensorDescriptor_t bias_desc,
+    const mluOpTensorDescriptor_t output_desc, size_t *size) {
+  PARAM_CHECK("mluOpDCNForward", handle != NULL);
+  PARAM_CHECK("mluOpDCNForward", dcn_desc != NULL);
+  PARAM_CHECK("mluOpDCNForward", input_desc != NULL);
+  PARAM_CHECK("mluOpDCNForward", offset_desc != NULL);
+  PARAM_CHECK("mluOpDCNForward", filter_desc != NULL);
+  PARAM_CHECK("mluOpDCNForward", output_desc != NULL);
+  PARAM_CHECK("mluOpDCNForward", size != NULL);
+  DEFINE_CREATE_AND_SET_CNNL_HANDLE(handle, cnnl_handle);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(input_desc, cnnl_input_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(offset_desc, cnnl_offset_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(mask_desc, cnnl_mask_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(filter_desc, cnnl_filter_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(bias_desc, cnnl_bias_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(output_desc, cnnl_output_desc);
+  CHECK_FUNC_RETURN(cnnlGetDCNForwardWorkspaceSize(
+                        cnnl_handle, dcn_desc, cnnl_input_desc,
+                        cnnl_offset_desc, cnnl_mask_desc, cnnl_filter_desc,
+                        cnnl_bias_desc, cnnl_output_desc, size),
+                    CNNL_STATUS_SUCCESS,
+                    "[mluOpDCNForward] Internal error accured in "
+                    "mluOpGetDCNForwardWorkspaceSize.",  // NOLINT
+                    MLUOP_STATUS_INTERNAL_ERROR);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_input_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_offset_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_mask_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_filter_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_bias_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_output_desc);
+  DESTROY_CNNL_HANDLE(cnnl_handle);
+  return MLUOP_STATUS_SUCCESS;
+}
+
+mluOpStatus_t MLUOP_WIN_API
+mluOpDCNForward(mluOpHandle_t handle, const mluOpDCNDescriptor_t dcn_desc,
+                const mluOpTensorDescriptor_t input_desc, const void *input,
+                const mluOpTensorDescriptor_t offset_desc, const void *offset,
+                const mluOpTensorDescriptor_t mask_desc, const void *mask,
+                const mluOpTensorDescriptor_t filter_desc, const void *filter,
+                const mluOpTensorDescriptor_t bias_desc, const void *bias,
+                void *workspace, size_t workspace_size,
+                const mluOpTensorDescriptor_t output_desc, void *output) {
+  PARAM_CHECK(DCNFORWARD_API, handle != NULL);
+  if (workspace_size > 0) {
+    PARAM_CHECK(DCNFORWARD_API, workspace != NULL);
+  }
+  DEFINE_CREATE_AND_SET_CNNL_HANDLE(handle, cnnl_handle);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(input_desc, cnnl_input_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(offset_desc, cnnl_offset_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(mask_desc, cnnl_mask_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(filter_desc, cnnl_filter_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(bias_desc, cnnl_bias_desc);
+  DEFINE_CREATE_AND_SET_CNNL_TENSOR_DESCRIPTOR(output_desc, cnnl_output_desc);
+  CHECK_FUNC_RETURN(
+      cnnlDCNForward(cnnl_handle, dcn_desc, cnnl_input_desc, input,
+                     cnnl_offset_desc, offset, cnnl_mask_desc, mask,
+                     cnnl_filter_desc, filter, cnnl_bias_desc, bias, workspace,
+                     workspace_size, cnnl_output_desc, output),
+      CNNL_STATUS_SUCCESS,
+      "[mluOpDcnForward] Internal error accured in mluOpDcnForward.",
+      MLUOP_STATUS_INTERNAL_ERROR);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_input_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_offset_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_mask_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_filter_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_bias_desc);
+  DESTROY_CNNL_TENSOR_DESCRIPTOR(cnnl_output_desc);
+  DESTROY_CNNL_HANDLE(cnnl_handle);
+  return MLUOP_STATUS_SUCCESS;
+}