From d4d19a75ba39aaf76fb7bc732a06244f87e7a01b Mon Sep 17 00:00:00 2001
From: Tracy Sharpe <42477615+tracysh@users.noreply.github.com>
Date: Sat, 4 Apr 2020 09:43:10 -0700
Subject: [PATCH] Use MlasConv for 1D convolutions (#3425)

Use the existing 2D convolution code in MlasConv to also handle 1D convolutions.
---
 onnxruntime/core/mlas/lib/convolve.cpp    | 29 +++++++++++++++++++++--
 onnxruntime/core/providers/cpu/nn/conv.cc |  2 +-
 2 files changed, 28 insertions(+), 3 deletions(-)

diff --git a/onnxruntime/core/mlas/lib/convolve.cpp b/onnxruntime/core/mlas/lib/convolve.cpp
index f744bc1159..72141607cf 100644
--- a/onnxruntime/core/mlas/lib/convolve.cpp
+++ b/onnxruntime/core/mlas/lib/convolve.cpp
@@ -1037,7 +1037,7 @@ Arguments:
     Parameters - Supplies the structure that stores the provided and computed
         parameters for the convolution operation.
 
-    Dimensions - Supplies the number of dimensions (must be 2 or 3).
+    Dimensions - Supplies the number of dimensions (must be between 1 and 3).
 
     BatchCount - Supplies the number of batches to the processed.
 
@@ -1080,7 +1080,6 @@ Return Value:
     //
 
     Parameters->Activation = Activation;
-    Parameters->Dimensions = Dimensions;
     Parameters->BatchCount = BatchCount;
     Parameters->GroupCount = GroupCount;
     Parameters->InputChannels = InputChannels;
@@ -1117,6 +1116,32 @@ Return Value:
     Parameters->OutputSize = OutputSize;
     Parameters->K = K;
 
+    //
+    // Promote 1D convolutions to 2D convolutions.
+    //
+
+    if (Dimensions == 1) {
+
+        Parameters->InputShape[1] = Parameters->InputShape[0];
+        Parameters->InputShape[0] = 1;
+        Parameters->OutputShape[1] = Parameters->OutputShape[0];
+        Parameters->OutputShape[0] = 1;
+        Parameters->KernelShape[1] = Parameters->KernelShape[0];
+        Parameters->KernelShape[0] = 1;
+        Parameters->DilationShape[1] = Parameters->DilationShape[0];
+        Parameters->DilationShape[0] = 1;
+        Parameters->Padding[3] = Parameters->Padding[1];
+        Parameters->Padding[2] = 0;
+        Parameters->Padding[1] = Parameters->Padding[0];
+        Parameters->Padding[0] = 0;
+        Parameters->StrideShape[1] = Parameters->StrideShape[0];
+        Parameters->StrideShape[0] = 1;
+
+        Dimensions = 2;
+    }
+
+    Parameters->Dimensions = Dimensions;
+
     //
     // Evaluate how the convolution will be performed.
     //
diff --git a/onnxruntime/core/providers/cpu/nn/conv.cc b/onnxruntime/core/providers/cpu/nn/conv.cc
index 771d0e9b7e..08645b55cb 100644
--- a/onnxruntime/core/providers/cpu/nn/conv.cc
+++ b/onnxruntime/core/providers/cpu/nn/conv.cc
@@ -207,7 +207,7 @@ Status Conv<float>::Compute(OpKernelContext* context) const {
   const size_t kernel_rank = kernel_shape.size();
   concurrency::ThreadPool* thread_pool = context->GetOperatorThreadPool();
 
-  if (kernel_rank == 2 || kernel_rank == 3) {
+  if (kernel_rank >= 1 && kernel_rank <= 3) {
     MLAS_CONV_PARAMETERS Parameters;
     size_t WorkingBufferSize;
     MlasConvPrepare(&Parameters,