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paddle/fluid/operators/reader/create_custom_reader_op.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/executor.h"
+#include "paddle/fluid/operators/detail/safe_ref.h"
 #include "paddle/fluid/operators/reader/reader_op_registry.h"
 
 namespace paddle {
@@ -148,35 +149,31 @@ void CustomReader::ReadNext(std::vector<framework::LoDTensor>* out) {
     // There is not next data.
     return;
   }
-  PADDLE_ENFORCE(
-      source_var_names_.size() == underlying_outs.size() &&
-          sink_var_names_.size() == underlying_outs.size(),
-      "The size of source_var_names(%d), the size of sink_var_names(%d) and "
-      "the size of underlying_outs(%d) are not consistent. Each feeding "
-      "element must have its own source and sink variable.",
-      source_var_names_.size(), sink_var_names_.size(), underlying_outs.size());
+  PADDLE_ENFORCE(source_var_names_.size() == underlying_outs.size(),
+                 "The size of source_var_names(%d) and the size of "
+                 "underlying_outs(%d) are not consistent. Each feeding element "
+                 "must have its own source variable.",
+                 source_var_names_.size(), underlying_outs.size());
   // The scope for CustomReader's sub-block should be independent and shouldn't
   // be any other computation scope's child. Otherwise, data preprocessing and
   // compution cannot be concurrent.
-  auto* scope = new framework::Scope();
+  framework::Scope scope;
   // 1. Copy LoDTensors from underlying reader's output to source variables.
   for (size_t i = 0; i < source_var_names_.size(); ++i) {
-    framework::Variable* var = scope->Var(source_var_names_[i]);
+    framework::Variable* var = scope.Var(source_var_names_[i]);
     framework::LoDTensor* tensor = var->GetMutable<framework::LoDTensor>();
     tensor->ShareDataWith(underlying_outs[i]);
     tensor->set_lod(underlying_outs[i].lod());
   }
   // 2. Run the sub-block.
-  exe_.Run(program_, scope, sub_block_id_, false, true);
+  exe_.Run(program_, &scope, sub_block_id_, false, true);
   // 3. Copy LoDTensors from sink variables to out.
   out->resize(sink_var_names_.size());
   for (size_t i = 0; i < sink_var_names_.size(); ++i) {
-    framework::Variable* var = scope->FindVar(sink_var_names_[i]);
-    PADDLE_ENFORCE_NOT_NULL(var);
-    const framework::LoDTensor& tensor = var->Get<framework::LoDTensor>();
+    const auto& tensor = detail::Ref(scope.FindVar(sink_var_names_[i]))
+                             .Get<framework::LoDTensor>();
     framework::TensorCopySync(tensor, platform::CPUPlace(), &(*out)[i]);
   }
-  delete scope;
 }
 
 }  // namespace reader

python/paddle/fluid/layers/io.py

@@ -559,15 +559,16 @@ class Preprocessor(object):
         source_shapes = self.underlying_reader.desc.shapes()
         source_dtypes = self.underlying_reader.desc.dtypes()
         source_lod_levels = self.underlying_reader.desc.lod_levels()
-        self.source_var_names = []
+        self.source_var_names = [
+            unique_name("preprocessor_source")
+            for _ in xrange(len(source_shapes))
+        ]
         source_vars = []
-        for idx in xrange(len(source_shapes)):
-            self.source_var_names.append(unique_name("preprocessor_source"))
+        for var_name, shape, dtype, lod_level in zip(
+                self.source_var_names, source_shapes, source_dtypes,
+                source_lod_levels):
             source_vars.append(self.main_prog.current_block().create_var(
-                name=self.source_var_names[-1],
-                shape=source_shapes[idx],
-                dtype=source_dtypes[idx],
-                lod_level=source_lod_levels[idx]))
+                name=var_name, shape=shape, dtype=dtype, lod_level=lod_level))
         return source_vars
 
     def outputs(self, *outs):