Merge branch 'develop' into refine_relu_test

doc/fluid/build_and_install/paddleci.png

@@ -0,0 +1 @@
+../../v2/build_and_install/paddleci.png

doc/fluid/design/motivation/refactorization.md

@@ -125,12 +125,12 @@ Compile Time -> IR -> Runtime
 
 ## Operator/OpWithKernel/OpKernel
 
-![class_diagram](http://api.paddlepaddle.org/graphviz?dot=https://gist.githubusercontent.com/reyoung/53df507f6749762675dff3e7ce53372f/raw/49caf1fb70820fb4a6c217634317c9306f361f36/op_op_with_kern_class_diagram.dot)
+![class_diagram](https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/op_op_with_kern_class_diagram.dot)
 
 ---
 
 ## Operator
-![class_diagram](http://api.paddlepaddle.org/graphviz?dot=https://gist.githubusercontent.com/reyoung/53df507f6749762675dff3e7ce53372f/raw/dd598e8f1976f5759f58af5e5ef94738a6b2e661/op.dot)
+![class_diagram](https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/op.dot)
 
 * `Operator` is the fundamental building block of the user interface.
     * Operator stores input/output variable names and attributes.
@@ -141,7 +141,7 @@ Compile Time -> IR -> Runtime
 
 ## OpWithKernel/Kernel
 
-![class_diagram](http://api.paddlepaddle.org/graphviz?dot=https://gist.githubusercontent.com/reyoung/53df507f6749762675dff3e7ce53372f/raw/9d7f4eba185cf41c8e2fbfb40ae21890dbddcd39/op_with_kernel.dot)
+![class_diagram](https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/op_with_kernel.dot)
 
 * `OpWithKernel` inherits `Operator`.
 * `OpWithKernel` contains a Kernel map.

doc/fluid/images/op.dot

@@ -0,0 +1,4 @@
+digraph sample { 
+  graph [rankdir=TD]; node [shape=record];
+  op [label="{Operator| InferShape()=0\lRun()=0\l | map<string, string[]> inputs_\lmap<string, string[]> outputs_ \l AttributeMap attrs_\l}"]; 
+}

doc/fluid/images/op_op_with_kern_class_diagram.dot

@@ -0,0 +1,38 @@
+digraph sample { 
+  graph [rankdir=TD]; node [shape=record];
+  op [label="{Operator| InferShape()=0\lRun()=0\l | map<string, string[]> inputs_\lmap<string, string[]> outputs_ \l AttributeMap attrs_\l}"]; 
+  op_with_kern [label="{OpWithKernel | InferShape()=0\lRun()\l | map<OpKernelKey,OpKernel>kernels_ }"]
+  op_kernel [label="{OpKernel | Compute()=0}"]
+  op_kernel_key [label="{OpKernelKey| Place place\n...}"]
+
+  op -> op_with_kern [dir=back, arrowtail=onormal]
+  op_with_kern -> op_kernel [arrowhead=vee, label="contains many"]
+
+  {
+    rank=same;
+    op_with_kern
+    op_kernel
+  }
+
+  op_kernel -> op_kernel_key [style=invis]
+
+  {
+    rank=same;
+    op_kernel
+    op_kernel_key
+  }
+
+  op_with_kern -> op_kernel_key [arrowhead=vee, label ="\nas map key"]
+
+  mul_op [label="MulOp"]
+  op_with_kern -> mul_op [dir=back, arrowtail=onormal]
+  mul_kernel [label="template <typename Place>\lclass MulOpKernel\l"]
+  op_kernel -> mul_kernel [dir=back, arrowtail=onormal]
+  mul_op -> mul_kernel [arrowhead=vee, label="register many"]
+  
+  {
+    rank=same;
+    mul_op;
+    mul_kernel;
+  }
+}

doc/fluid/images/op_with_kernel.dot

@@ -0,0 +1,26 @@
+digraph sample { 
+  graph [rankdir=TD]; node [shape=record];
+  op [label="{Operator}"]; 
+  op_with_kern [label="{OpWithKernel | InferShape()=0\lRun()\l | map<OpKernelKey,OpKernel>kernels_ }"]
+  op_kernel [label="{OpKernel | Compute()=0}"]
+  op_kernel_key [label="{OpKernelKey| Place place\n...}"]
+
+  op -> op_with_kern [dir=back, arrowtail=onormal]
+  op_with_kern -> op_kernel [arrowhead=vee, label="contains many"]
+
+  {
+    rank=same;
+    op_with_kern
+    op_kernel
+  }
+
+  op_kernel -> op_kernel_key [style=invis]
+
+  {
+    rank=same;
+    op_kernel
+    op_kernel_key
+  }
+
+  op_with_kern -> op_kernel_key [arrowhead=vee, label ="\nas map key"]
+}

doc/v2/api/config/layer.rst

@@ -460,6 +460,11 @@ multi_binary_label_cross_entropy_cost
 ..  autoclass:: paddle.v2.layer.multi_binary_label_cross_entropy_cost
     :noindex:
 
+classification_cost
+-------------------
+.. autoclass:: paddle.v2.layer.classification_cost
+   :noindex:
+
 huber_regression_cost
 -------------------------
 ..  autoclass:: paddle.v2.layer.huber_regression_cost

paddle/fluid/inference/tests/book/CMakeLists.txt

@@ -36,5 +36,5 @@ inference_test(label_semantic_roles)
 inference_test(recognize_digits ARGS mlp conv)
 inference_test(recommender_system)
 #inference_test(rnn_encoder_decoder)
-inference_test(understand_sentiment ARGS conv)
+#inference_test(understand_sentiment ARGS conv)
 inference_test(word2vec)

paddle/fluid/operators/conv_op.h

@@ -187,7 +187,8 @@ class GemmConvKernel : public framework::OpKernel<T> {
         // gemm
         Tensor out_slice = out_batch.Slice(g * out_step, (g + 1) * out_step);
         Tensor filter_slice = filter.Slice(g * out_step, (g + 1) * out_step);
-        blas.MatMul(filter_slice, col_matrix, &out_slice);
+        blas.MatMul(filter_slice, false, col_matrix, false, T(1.0), &out_slice,
+                    T(0.0));
       }
     }
   }
@@ -304,7 +305,8 @@ class GemmConvGradKernel : public framework::OpKernel<T> {
             col_matrix.ShareDataWith(in_grad_slice);
             col_matrix.Resize(col_matrix_shape);
           }
-          blas.MatMul(filter_slice, true, out_grad_slice, false, &col_matrix);
+          blas.MatMul(filter_slice, true, out_grad_slice, false, T(1.0),
+                      &col_matrix, T(0.0));
 
           if (is_expand && data_dim == 2U) {
             col2im(dev_ctx, col, dilations, strides,
@@ -351,8 +353,8 @@ class GemmConvGradKernel : public framework::OpKernel<T> {
           // gemm
           Tensor filter_grad_slice =
               filter_grad_.Slice(g * out_step, (g + 1) * out_step);
-          blas.MatMul(out_grad_slice, false, col_matrix, true,
+          blas.MatMul(out_grad_slice, false, col_matrix, true, T(1.0),
-                      &filter_grad_slice);
+                      &filter_grad_slice, T(1.0));
         }
       }
     }

paddle/fluid/operators/conv_transpose_op.h

@@ -135,7 +135,8 @@ class GemmConvTransposeKernel : public framework::OpKernel<T> {
 
       // col_matrix = filter * input_batch
       // of shape (c * k_h * k_w, h * w) or (c * k_d * k_h * k_w, d * h * w)
-      blas.MatMul(filter, true, input_batch, false, &col_matrix);
+      blas.MatMul(filter, true, input_batch, false, static_cast<T>(1.0),
+                  &col_matrix, static_cast<T>(0.0));
 
       if (data_dim == 2U) {
         // col2im: col_matrix -> dy
@@ -267,7 +268,8 @@ class GemmConvTransposeGradKernel : public framework::OpKernel<T> {
           // or
           // (m, c * k_d * k_h * k_w) * (c * k_d * k_h * k_w, d * h * w) -> (m,
           // d, h, w)
-          blas.MatMul(filter, false, col_matrix, false, &input_grad_batch);
+          blas.MatMul(filter, false, col_matrix, false, static_cast<T>(1.0),
+                      &input_grad_batch, static_cast<T>(0.0));
         }
         if (filter_grad) {
           // input batch
@@ -277,7 +279,8 @@ class GemmConvTransposeGradKernel : public framework::OpKernel<T> {
           // or
           // (m, d * h * w) * (d * h * w, c * k_d * k_h * k_w) -> (m, c * k_d *
           // k_h * k_w)
-          blas.MatMul(in_batch, false, col_matrix, true, &filter_grad_);
+          blas.MatMul(in_batch, false, col_matrix, true, static_cast<T>(1.0),
+                      &filter_grad_, static_cast<T>(1.0));
         }
       }
     }

paddle/fluid/platform/cuda_device_function.h

@@ -63,6 +63,7 @@ __device__ T reduceSum(T val, int tid, int len) {
     val += platform::CudaShuffleDownSync(mask, val, offset);
 
   if (tid < warpSize) shm[tid] = 0;
+  __syncthreads();
 
   if (tid % warpSize == 0) {
     shm[tid / warpSize] = val;

python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py

@@ -18,7 +18,7 @@ import unittest
 import paddle.fluid.layers as layers
 import paddle.fluid.optimizer as optimizer
 from paddle.fluid.framework import Program, program_guard
-from paddle.fluid.memory_optimization_transpiler import memory_optimize
+from paddle.fluid.transpiler import memory_optimize
 
 
 class TestControlFlowGraph(unittest.TestCase):

python/paddle/fluid/tests/unittests/test_split_var.py

@@ -14,7 +14,7 @@
 
 import math
 import unittest
-from paddle.fluid.distribute_transpiler import split_dense_variable
+from paddle.fluid.transpiler.distribute_transpiler import split_dense_variable
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 import random