forward pass compile time

paddle/operators/parallel_do_op.cc

@@ -23,9 +23,11 @@ namespace operators {
 constexpr char kInputs[] = "inputs";
 constexpr char kParameters[] = "parameters";
 constexpr char kPlaces[] = "places";
-constexpr char kParallelBlock[] = "sub_block";
+
 constexpr char kOutputs[] = "outputs";
-constexpr char kParallelScopes[] = "sub_scopes";
+constexpr char kParallelScopes[] = "parallel_scopes";
+
+constexpr char kParallelBlock[] = "sub_block";
 // #define GRAD_SUFFIX "@GRAD"
 // constexpr char kInputGrads[] = "inputs" GRAD_SUFFIX;
 // constexpr char kOutputGrads[] = "outputs" GRAD_SUFFIX;

python/paddle/v2/fluid/framework.py

@@ -424,7 +424,8 @@ class Operator(object):
         self.desc.check_attrs()
         no_kernel_op_set = {
             'feed', 'fetch', 'save', 'load', 'recurrent',
-            'rnn_memory_helper_grad', 'conditional_block', 'while'
+            'rnn_memory_helper_grad', 'conditional_block', 'while',
+            'parallel_do'
         }
         if type not in no_kernel_op_set:
             self.desc.infer_var_type(self.block.desc)

python/paddle/v2/fluid/layers/control_flow.py

@@ -103,6 +103,7 @@ class ParallelDo(object):
 
     def read_input(self, var):
         self.inputs.append(var)
+        return var
 
     def write_output(self, var):
         self.outputs.append(var)
@@ -149,7 +150,7 @@ class ParallelDo(object):
                 'places': self.places
             },
             outputs={'outputs': self.outputs,
-                     'step_scopes': [step_scope]},
+                     'parallel_scopes': [step_scope]},
             attrs={'sub_block': current_block})
 
 

python/paddle/v2/fluid/tests/test_parallel_op.py

+import unittest
+
+import paddle.v2.fluid.layers as layers
+import paddle.v2.fluid as fluid
+from paddle.v2.fluid.framework import Program
+from paddle.v2.fluid.executor import Executor
+from paddle.v2.fluid.backward import append_backward_ops
+import numpy as np
+import paddle.v2.fluid.core as core
+
+
+class ParallelOpTest(unittest.TestCase):
+    def setUp(self):
+        x = layers.data(
+            shape=[2, 3, 4], dtype='float32', name='x', append_batch_size=False)
+
+        places = fluid.default_main_program().global_block().create_var()
+        pd = layers.ParallelDo(places=places)
+
+        with pd.do():
+            data = pd.read_input(x)
+            hidden = layers.fc(input=data, size=7)
+            pd.write_output(hidden)
+        data = pd()
+        print data
+        print fluid.default_main_program()
+
+    def test_forward(self):
+        pass
+
+
+if __name__ == '__main__':
+    unittest.main()