From ce1d98e083017afadac9fcd9f94f5c59aceaf6c0 Mon Sep 17 00:00:00 2001
From: hedaoyuan <hedaoyuan@github.com>
Date: Thu, 15 Dec 2016 10:31:45 +0800
Subject: [PATCH] Add a Tensor to use as a Function argument

---
 paddle/math/Function.h                   | 12 +++++++-
 paddle/math/cross_map_normal_op.cpp      | 37 +++++++++++-------------
 paddle/math/tests/test_matrixCompare.cpp |  9 ++++--
 3 files changed, 35 insertions(+), 23 deletions(-)

diff --git a/paddle/math/Function.h b/paddle/math/Function.h
index b41ba2a13d..539759782b 100644
--- a/paddle/math/Function.h
+++ b/paddle/math/Function.h
@@ -40,7 +40,17 @@ struct MatrixT<DEVICE_TYPE_GPU> {
   using type = GpuMatrix;
 };
 
-typedef std::vector<Matrix> Arguments;
+typedef std::vector<size_t> Dims;
+
+class Tensor {
+public:
+  Tensor(real* data, const Dims& dim) : buf_(data), dims_(dim) {}
+
+  real* buf_;
+  Dims dims_;
+};
+
+typedef std::vector<Tensor> Arguments;
 
 class FuncConfig {
 public:
diff --git a/paddle/math/cross_map_normal_op.cpp b/paddle/math/cross_map_normal_op.cpp
index 0b72732063..d55bd78c62 100644
--- a/paddle/math/cross_map_normal_op.cpp
+++ b/paddle/math/cross_map_normal_op.cpp
@@ -144,26 +144,23 @@ public:
     CHECK_EQ(2, outputs.size());
     CHECK_EQ(0, inouts.size());
 
-    auto input = dynamic_cast<const typename MatrixT<Device>::type&>(inputs[0]);
-    auto output =
-        dynamic_cast<const typename MatrixT<Device>::type&>(outputs[0]);
-    auto denom =
-        dynamic_cast<const typename MatrixT<Device>::type&>(outputs[1]);
-
-    CHECK(input.isContiguous());
-    CHECK(output.isContiguous());
-    CHECK(denom.isContiguous());
-    CHECK_EQ(output.getHeight(), input.getHeight());
-    CHECK_EQ(output.getWidth(), input.getWidth());
-    CHECK_EQ(output.getHeight(), denom.getHeight());
-    CHECK_EQ(output.getWidth(), denom.getWidth());
-
-    // CrossMapNormal<Device> cross;
-    // need:
-    // size_t channels,
-    // size_t imgSizeH,
-    // size_t imgSizeW,
-    // cross(output, denom, input, );
+    CHECK_EQ(inputs[0].dims_.size(), 4);
+    for (size_t i = 0; i < inputs[0].dims_.size(); i++) {
+      CHECK_EQ(inputs[0].dims_[i], outputs[0].dims_[i]);
+      CHECK_EQ(inputs[0].dims_[i], outputs[1].dims_[i]);
+    }
+
+    size_t samples = inputs[0].dims_[0];
+    size_t channels = inputs[0].dims_[1];
+    size_t height = inputs[0].dims_[2];
+    size_t width = inputs[0].dims_[3];
+    size_t imageSize = channels * height * width;
+    CpuMatrix input(inputs[0].buf_, samples, imageSize);
+    CpuMatrix output(outputs[0].buf_, samples, imageSize);
+    CpuMatrix denom(outputs[1].buf_, samples, imageSize);
+
+    CrossMapNormal<Device> cross;
+    cross(output, denom, input, channels, height, width, size_, scale_, pow_);
   }
 
 private:
diff --git a/paddle/math/tests/test_matrixCompare.cpp b/paddle/math/tests/test_matrixCompare.cpp
index 0b75785528..cd34ea18a7 100644
--- a/paddle/math/tests/test_matrixCompare.cpp
+++ b/paddle/math/tests/test_matrixCompare.cpp
@@ -1288,12 +1288,17 @@ void testCrossMapNormalFwd(
   FunctionBase* cpu =
       FunctionBase::funcRegistrar_.createByType(FUNC_NAME(CrossMapNormal, CPU));
   cpu->init(config);
-  // cpu->calc();
 
+  Dims dims{
+      (size_t)numSamples, (size_t)channels, (size_t)imgSizeH, (size_t)imgSizeW};
+  cpu->calc({Tensor(inputs.getData(), dims)},
+            {Tensor(outputs.getData(), dims), Tensor(denoms.getData(), dims)},
+            {});
+#if 0
   CrossMapNormal<DEVICE_TYPE_CPU> cpuCross;
   cpuCross(
       outputs, denoms, inputs, channels, imgSizeH, imgSizeW, sizeX, scale, pow);
-
+#endif
   CrossMapNormal<DEVICE_TYPE_GPU> gpuCross;
   gpuCross(outputsGpu,
            denomsGpu,
-- 
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