diff --git a/examples/inception_v3/inception_v3.cpp b/examples/inception_v3/inception_v3.cpp
index 9127027..ba945b6 100644
--- a/examples/inception_v3/inception_v3.cpp
+++ b/examples/inception_v3/inception_v3.cpp
@@ -101,7 +101,7 @@ class InceptionA : public CUDANet::Module {
 
         // Branch Pool
         branchPool_1 = new CUDANet::Layers::AvgPooling2d(
-            inputSize, inputChannels, {3, 3}, {1, 1},
+            inputSize, inputChannels, {3, 3}, {1, 1}, {1, 1},
             CUDANet::Layers::ActivationType::NONE
         );
         addLayer("", branchPool_1);
@@ -197,7 +197,7 @@ class InceptionB : public CUDANet::Module {
         addLayer("", branch3x3dbl_3);
 
         branchPool = new CUDANet::Layers::MaxPooling2d(
-            inputSize, inputChannels, {3, 3}, {2, 2},
+            inputSize, inputChannels, {3, 3}, {2, 2}, {0, 0},
             CUDANet::Layers::ActivationType::NONE
         );
         addLayer(prefix + ".branchPool", branchPool);
@@ -240,4 +240,126 @@ class InceptionB : public CUDANet::Module {
 
     CUDANet::Layers::Concat *concat_1;
     CUDANet::Layers::Concat *concat_2;
+};
+
+class InceptionC : public CUDANet::Module {
+  public:
+    InceptionC(
+        const dim2d        inputSize,
+        const int          inputChannels,
+        const int          nChannels_7x7,
+        const std::string &prefix
+    )
+        : inputSize(inputSize), inputChannels(inputChannels) {
+        // Branch 1x1
+        branch1x1 = new BasicConv2d(
+            inputSize, inputChannels, 192, {1, 1}, {1, 1}, {0, 0}, "branch1x1"
+        );
+
+        // Branch 7x7
+        branch7x7_1 = new BasicConv2d(
+            inputSize, inputChannels, nChannels_7x7, {1, 1}, {1, 1}, {0, 0},
+            "branch7x7_1"
+        );
+        branch7x7_2 = new BasicConv2d(
+            branch7x7_1->getOutputDims(), nChannels_7x7, nChannels_7x7, {1, 7},
+            {1, 1}, {0, 3}, "branch7x7_2"
+        );
+        branch7x7_3 = new BasicConv2d(
+            branch7x7_2->getOutputDims(), nChannels_7x7, 192, {7, 1}, {1, 1},
+            {3, 0}, "branch7x7_3"
+        );
+
+        // Branch 7x7dbl
+        branch7x7dbl_1 = new BasicConv2d(
+            inputSize, inputChannels, nChannels_7x7, {1, 1}, {1, 1}, {0, 0},
+            "branch7x7dbl_1"
+        );
+        branch7x7dbl_2 = new BasicConv2d(
+            branch7x7dbl_1->getOutputDims(), nChannels_7x7, nChannels_7x7, {7, 1},
+            {1, 1}, {3, 0}, "branch7x7dbl_2"
+        );
+        branch7x7dbl_3 = new BasicConv2d(
+            branch7x7dbl_2->getOutputDims(), nChannels_7x7, nChannels_7x7, {1, 7},
+            {1, 1}, {0, 3}, "branch7x7dbl_3"
+        );
+        branch7x7dbl_4 = new BasicConv2d(
+            branch7x7dbl_3->getOutputDims(), nChannels_7x7, nChannels_7x7, {7, 1},
+            {1, 1}, {3, 0}, "branch7x7dbl_4"
+        );
+        branch7x7dbl_5 = new BasicConv2d(
+            branch7x7dbl_4->getOutputDims(), nChannels_7x7, 192, {1, 7}, {1, 1},
+            {0, 3}, "branch7x7dbl_5"
+        );
+
+        // Branch Pool
+        branchPool_1 = new CUDANet::Layers::AvgPooling2d(
+            inputSize, inputChannels, {3, 3}, {1, 1}, {1, 1}, CUDANet::Layers::ActivationType::NONE
+        );
+        branchPool_2 = new BasicConv2d(
+            branchPool_1->getOutputDims(), inputChannels, 192, {1, 1}, {1, 1},
+            {0, 0}, "branchPool_2"
+        );
+
+        // Concat
+        concat_1 = new CUDANet::Layers::Concat(
+            branch1x1->getOutputSize(),
+            branch7x7_3->getOutputSize()
+        );
+        concat_2 = new CUDANet::Layers::Concat(
+            concat_1->getOutputSize(),
+            branch7x7dbl_5->getOutputSize()
+        );
+        concat_3 = new CUDANet::Layers::Concat(
+            concat_2->getOutputSize(),
+            branchPool_2->getOutputSize()
+        );
+    }
+
+    float *forward(const float *d_input) {
+
+        float *branch1x1_output = branch1x1->forward(d_input);
+
+        float *branch7x7_output = branch7x7_1->forward(d_input);
+        branch7x7_output = branch7x7_2->forward(branch7x7_output);
+        branch7x7_output = branch7x7_3->forward(branch7x7_output);
+
+        float *branch7x7dbl_output = branch7x7dbl_1->forward(d_input);
+        branch7x7dbl_output = branch7x7dbl_2->forward(branch7x7dbl_output);
+        branch7x7dbl_output = branch7x7dbl_3->forward(branch7x7dbl_output);
+        branch7x7dbl_output = branch7x7dbl_4->forward(branch7x7dbl_output);
+        branch7x7dbl_output = branch7x7dbl_5->forward(branch7x7dbl_output);
+
+        float *branchPool_output = branchPool_1->forward(d_input);
+        branchPool_output = branchPool_2->forward(branchPool_output);
+
+        float *d_output = concat_1->forward(branch1x1_output, branch7x7_output);
+        d_output = concat_2->forward(d_output, branch7x7dbl_output);
+        d_output = concat_3->forward(d_output, branchPool_output);
+
+        return d_output;
+    }
+
+  private:
+    dim2d inputSize;
+    int   inputChannels;
+
+    BasicConv2d *branch1x1;
+
+    BasicConv2d *branch7x7_1;
+    BasicConv2d *branch7x7_2;
+    BasicConv2d *branch7x7_3;
+
+    BasicConv2d *branch7x7dbl_1;
+    BasicConv2d *branch7x7dbl_2;
+    BasicConv2d *branch7x7dbl_3;
+    BasicConv2d *branch7x7dbl_4;
+    BasicConv2d *branch7x7dbl_5;
+
+    CUDANet::Layers::AvgPooling2d *branchPool_1;
+    BasicConv2d *branchPool_2;
+
+    CUDANet::Layers::Concat *concat_1;
+    CUDANet::Layers::Concat *concat_2;
+    CUDANet::Layers::Concat *concat_3;
 };
\ No newline at end of file