From 5a9ea9a73d51841790940ffb36790d8424adacba Mon Sep 17 00:00:00 2001
From: shippingwang <shipeng1108@163.com>
Date: Tue, 25 Dec 2018 02:25:45 +0000
Subject: [PATCH] Add ShuffleChannel Op

---
 paddle/fluid/operators/shuffle_channel_op.cc |  6 +++++-
 paddle/fluid/operators/shuffle_channel_op.cu |  2 ++
 python/paddle/fluid/layers/nn.py             | 10 +++++-----
 3 files changed, 12 insertions(+), 6 deletions(-)

diff --git a/paddle/fluid/operators/shuffle_channel_op.cc b/paddle/fluid/operators/shuffle_channel_op.cc
index 0ede3922ea..1ab8b42d8d 100644
--- a/paddle/fluid/operators/shuffle_channel_op.cc
+++ b/paddle/fluid/operators/shuffle_channel_op.cc
@@ -28,7 +28,7 @@ class ShuffleChannelOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE(input_dims.size() == 4, "The layout of input is NCHW.");
 
     // ENFORCE group
-    // auto group = ctx->Attrs().Get<int>("group");
+
     ctx->SetOutputDim("Out", input_dims);
   }
   /*
@@ -87,6 +87,10 @@ class ShuffleChannelGradOp : public framework::OperatorWithKernel {
                    "Output(X@Grad) should not be null");
 
     auto input_dims = ctx->GetInputDim("X");
+    PADDLE_ENFORCE(input_dims.size() == 4, "The layout of input is NCHW.");
+
+    // ENFORCE group
+
     ctx->SetOutputDim(framework::GradVarName("X"), input_dims);
   }
   /*
diff --git a/paddle/fluid/operators/shuffle_channel_op.cu b/paddle/fluid/operators/shuffle_channel_op.cu
index 77418ac7e3..e8badc40cd 100644
--- a/paddle/fluid/operators/shuffle_channel_op.cu
+++ b/paddle/fluid/operators/shuffle_channel_op.cu
@@ -81,6 +81,7 @@ class ShuffleChannelGradOpCUDAKernel : public framework::OpKernel<T> {
   void Compute(const framework::ExecutionContext& ctx) const override {
     auto* input = ctx.Input<framework::Tensor>("X");
     int group = ctx.Attr<int>("group");
+
     auto input_dims = input->dims();
     auto num = input_dims[0];
     auto channel = input_dims[1];
@@ -101,6 +102,7 @@ class ShuffleChannelGradOpCUDAKernel : public framework::OpKernel<T> {
     int blocks = NumBlocks(output_grad->numel());
     int threads = kNumCUDAThreads;
     int count = num * group_column * group_row * sp_sz;
+
     ShuffleChannel<
         T><<<blocks, threads, 0, ctx.cuda_device_context().stream()>>>(
         count, feature_map_size, input_grad_data, output_grad_data, group_row,
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 3e3eea084e..e654047df6 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -55,6 +55,8 @@ __all__ = [
     'softmax',
     'pool2d',
     'pool3d',
+    'adaptive_pool2d',
+    'adaptive_pool3d',
     'batch_norm',
     'beam_search_decode',
     'conv2d_transpose',
@@ -9342,24 +9344,22 @@ def shuffle_channel(x, group=1, name=None):
         x: The input tensor variable..
         group: The num of group
 
-
     Returns:
-        Variable: channel shuffled tensor variable.
+        Variable: channels shuffled tensor variable.
 
     Raises:
-        ValueError: If group in not an int type variable.
+        ValueError: If group is not an int type variable.
 
     Examples:
         .. code-block:: python
 
         out = fluid.layers.shuffle_channel(x=group_conv,group=4)
-    
 
     """
     helper = LayerHelper("shuffle_channel", **locals())
 
     out = helper.create_variable_for_type_inference(
-        dtype=helper.intput_dtype('x'))
+        dtype=helper.input_dtype('x'))
 
     if not isinstance(group, int):
         raise TypeError("group must be int type")
-- 
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