From 20f30dd604df409e13f8aa78e9e30f4cda93d61f Mon Sep 17 00:00:00 2001
From: ceci3 <ceci3@users.noreply.github.com>
Date: Wed, 22 Jan 2020 12:37:07 +0800
Subject: [PATCH] add benchmark flag for conv_transpose (#22389)

---
 paddle/fluid/operators/conv_cudnn_op.cu           | 11 +++++++++++
 paddle/fluid/operators/conv_transpose_cudnn_op.cu |  9 ++++++++-
 2 files changed, 19 insertions(+), 1 deletion(-)

diff --git a/paddle/fluid/operators/conv_cudnn_op.cu b/paddle/fluid/operators/conv_cudnn_op.cu
index ad11906f3f1..cc5ae4c8375 100644
--- a/paddle/fluid/operators/conv_cudnn_op.cu
+++ b/paddle/fluid/operators/conv_cudnn_op.cu
@@ -272,6 +272,16 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
     algo = search::Find<T>(args, exhaustive_search, false, 0, ctx);
     workspace_size = search::GetWorkspaceSize(args, algo);
 
+#if CUDNN_VERSION_MIN(7, 0, 1)
+    // when groups > 1, SearchAlgorithm find algo is CUDNN_CONVOLUTION_\
+    // FWD_ALGO_WINOGRAD_NONFUSED, but this kind of algorithm is unstable
+    // in forward computation, so change the algorithm to CUDNN_CONVOLUTION_\
+    // FWD_ALGO_IMPLICIT_GEMM manually.
+    if (ctx.Attr<int>("groups") > 1) {
+      algo = static_cast<cudnnConvolutionFwdAlgo_t>(0);
+    }
+#endif
+
     // ------------------- cudnn conv forward ---------------------
     ScalingParamType<T> alpha = 1.0f, beta = 0.0f;
     for (int i = 0; i < groups; i++) {
@@ -881,6 +891,7 @@ class CUDNNConvDoubleGradOpKernel : public framework::OpKernel<T> {
 #if CUDNN_VERSION_MIN(7, 0, 1)
     iwo_group = 1;
     c_group = groups;
+    groups = 1;
 #endif
     auto dtype = platform::CudnnDataType<T>::type;
 
diff --git a/paddle/fluid/operators/conv_transpose_cudnn_op.cu b/paddle/fluid/operators/conv_transpose_cudnn_op.cu
index b827f200c0e..b39aaa29cf3 100644
--- a/paddle/fluid/operators/conv_transpose_cudnn_op.cu
+++ b/paddle/fluid/operators/conv_transpose_cudnn_op.cu
@@ -245,7 +245,7 @@ class CUDNNConvTransposeOpKernel : public framework::OpKernel<T> {
             CUDNN_CONVOLUTION_BWD_DATA_SPECIFY_WORKSPACE_LIMIT,
             workspace_size_limit, &algo));
 
-    if (algo == 0 && FLAGS_cudnn_deterministic) {
+    if (FLAGS_cudnn_deterministic) {
       algo = static_cast<cudnnConvolutionBwdDataAlgo_t>(1);
     }
 
@@ -476,6 +476,10 @@ class CUDNNConvTransposeGradOpKernel : public framework::OpKernel<T> {
               handle, cudnn_output_desc, cudnn_filter_desc, cudnn_conv_desc,
               cudnn_input_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT,
               workspace_size_limit, &data_algo));
+
+      if (FLAGS_cudnn_deterministic) {
+        data_algo = static_cast<cudnnConvolutionFwdAlgo_t>(1);
+      }
       PADDLE_ENFORCE_CUDA_SUCCESS(
           platform::dynload::cudnnGetConvolutionForwardWorkspaceSize(
               handle, cudnn_output_desc, cudnn_filter_desc, cudnn_conv_desc,
@@ -492,6 +496,9 @@ class CUDNNConvTransposeGradOpKernel : public framework::OpKernel<T> {
               CUDNN_CONVOLUTION_BWD_FILTER_SPECIFY_WORKSPACE_LIMIT,
               workspace_size_limit, &filter_algo));
 
+      if (FLAGS_cudnn_deterministic) {
+        filter_algo = static_cast<cudnnConvolutionBwdFilterAlgo_t>(1);
+      }
       // get workspace for backwards filter algorithm
       PADDLE_ENFORCE_CUDA_SUCCESS(
           platform::dynload::cudnnGetConvolutionBackwardFilterWorkspaceSize(
-- 
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