From 8573ca5406132b472e3df071da7e10564199fc29 Mon Sep 17 00:00:00 2001
From: fwenguang <95677191+fwenguang@users.noreply.github.com>
Date: Mon, 8 Aug 2022 11:37:27 +0800
Subject: [PATCH] [MLU] fix bn_grad and hard_sigmoid_grad error (#44919)

---
 paddle/fluid/operators/activation_op_mlu.cc   |  8 ++---
 paddle/fluid/operators/batch_norm_op_mlu.cc   |  2 +-
 .../fluid/operators/conv_transpose_op_mlu.cc  | 32 +++++++------------
 paddle/phi/kernels/funcs/activation_functor.h |  4 +++
 4 files changed, 21 insertions(+), 25 deletions(-)

diff --git a/paddle/fluid/operators/activation_op_mlu.cc b/paddle/fluid/operators/activation_op_mlu.cc
index 72e0e9ceac..6cfe4738d7 100644
--- a/paddle/fluid/operators/activation_op_mlu.cc
+++ b/paddle/fluid/operators/activation_op_mlu.cc
@@ -370,7 +370,7 @@ class HardSigmoidGradMLUKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const override {
     auto* dout = ctx.Input<Tensor>(framework::GradVarName("Out"));
-    auto* out = ctx.Input<Tensor>("Out");
+    auto* x = ctx.Input<Tensor>("X");
     auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
     float slope = ctx.Attr<float>("slope");
     float offset = ctx.Attr<float>("offset");
@@ -381,7 +381,7 @@ class HardSigmoidGradMLUKernel : public framework::OpKernel<T> {
                                    1.0f /*sliced_dim useless*/,
                                    slope,
                                    offset);
-    MLUCnnlTensorDesc out_desc(*out);
+    MLUCnnlTensorDesc x_desc(*x);
     MLUCnnlTensorDesc dout_desc(*dout);
     MLUCnnlTensorDesc dx_desc(*dx);
     MLUCnnl::ActiveGrad(ctx,
@@ -392,8 +392,8 @@ class HardSigmoidGradMLUKernel : public framework::OpKernel<T> {
                         nullptr,
                         dout_desc.get(),
                         GetBasePtr(dout),
-                        out_desc.get(),
-                        GetBasePtr(out),
+                        x_desc.get(),
+                        GetBasePtr(x),
                         dx_desc.get(),
                         GetBasePtr(dx));
   }
diff --git a/paddle/fluid/operators/batch_norm_op_mlu.cc b/paddle/fluid/operators/batch_norm_op_mlu.cc
index 199a9b95ec..1aa445bda3 100644
--- a/paddle/fluid/operators/batch_norm_op_mlu.cc
+++ b/paddle/fluid/operators/batch_norm_op_mlu.cc
@@ -273,7 +273,7 @@ class MLUBatchNormGradOpKernel : public framework::OpKernel<T> {
       const auto *running_mean = ctx.Input<Tensor>("Mean");
       const auto *running_variance = ctx.Input<Tensor>("Variance");
       MLUCnnl::FusedBatchNormGrad(ctx,
-                                  true /*is_training*/,
+                                  false /*is_training*/,
                                   transformed_desc.get(),
                                   GetBasePtr(&transformed_d_y),
                                   transformed_desc.get(),
diff --git a/paddle/fluid/operators/conv_transpose_op_mlu.cc b/paddle/fluid/operators/conv_transpose_op_mlu.cc
index 322328b1c2..f757898886 100644
--- a/paddle/fluid/operators/conv_transpose_op_mlu.cc
+++ b/paddle/fluid/operators/conv_transpose_op_mlu.cc
@@ -271,26 +271,18 @@ class Conv2DTransposeGradMLUKernel : public framework::OpKernel<T> {
           data_layout_mlu,
           ToCnnlDataType(input_grad_tensor.dtype()));
 
-      cnnlDataType_t tensor_dtype = ToCnnlDataType<T>();
-      cnnlDataType_t dt_onchip = ToCnnlDataType<T>();
-      MLUCnnl::Conv2D(ctx,
-                      conv_desc.get(),
-                      tensor_dtype,
-                      dt_onchip,
-                      nullptr /* input_position */,
-                      nullptr /* input_scale */,
-                      nullptr /* input_offset */,
-                      nullptr /* filter_position */,
-                      nullptr /* filter_scale */,
-                      nullptr /* filter_offset */,
-                      output_grad_desc.get(),
-                      GetBasePtr(&output_grad_tensor),
-                      trans_filter_desc.get(),
-                      GetBasePtr(&trans_filter),
-                      nullptr /* bias_desc*/,
-                      nullptr /* bias */,
-                      input_grad_desc.get(),
-                      GetBasePtr(&input_grad_tensor));
+      MLUCnnl::ConvolutionForward(ctx,
+                                  conv_desc.get(),
+                                  nullptr /*alpha*/,
+                                  nullptr /*beta*/,
+                                  nullptr /*bias_desc*/,
+                                  nullptr /*bias_ptr*/,
+                                  output_grad_desc.get(),
+                                  GetBasePtr(&output_grad_tensor),
+                                  trans_filter_desc.get(),
+                                  GetBasePtr(&trans_filter),
+                                  input_grad_desc.get(),
+                                  GetBasePtr(&input_grad_tensor));
       if (!channel_last) {
         // transpose output from NHWC to NCHW
         const std::vector<int> perm_to_nchw = {0, 3, 1, 2};
diff --git a/paddle/phi/kernels/funcs/activation_functor.h b/paddle/phi/kernels/funcs/activation_functor.h
index 542c59bec1..318f2e8b6b 100644
--- a/paddle/phi/kernels/funcs/activation_functor.h
+++ b/paddle/phi/kernels/funcs/activation_functor.h
@@ -1604,7 +1604,11 @@ struct HardSigmoidGradFunctor : public BaseActivationFunctor<T> {
   }
 
   static constexpr ActBwdOpFwdDeps FwdDeps() {
+#ifdef PADDLE_WITH_MLU
+    return ActBwdOpFwdDeps::kDepX;
+#else
     return ActBwdOpFwdDeps::kDepOut;
+#endif
   }
 };
 
-- 
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