expose random_data_generator

paddle/fluid/operators/reader/create_random_data_generator_op.cc

@@ -21,14 +21,15 @@ namespace reader {
 template <typename T>
 class RandomDataGenerator : public framework::ReaderBase {
  public:
-  RandomDataGenerator(const std::vector<framework::DDim>& shapes, float min,
-                      float max)
-      : framework::ReaderBase(), min_(min), max_(max), shapes_(shapes) {
-    PADDLE_ENFORCE_LE(
-        min, max, "'min' shouldn't be greater than 'max'.(%f vs %f)", min, max);
+  RandomDataGenerator(const std::vector<framework::DDim>& shapes, float low,
+                      float high)
+      : framework::ReaderBase(), low_(low), high_(high), shapes_(shapes) {
+    PADDLE_ENFORCE_LE(low, high,
+                      "'low' shouldn't be greater than 'high'.(%f vs %f)", low,
+                      high);
     unsigned int seed = std::random_device()();
     engine_.seed(seed);
-    dist_ = std::uniform_real_distribution<float>(min_, max_);
+    dist_ = std::uniform_real_distribution<float>(low_, high_);
   }
 
   void ReadNext(std::vector<framework::LoDTensor>* out) override {
@@ -53,8 +54,8 @@ class RandomDataGenerator : public framework::ReaderBase {
   void ReInit() override { return; }
 
  private:
-  float min_;
-  float max_;
+  float low_;
+  float high_;
   std::minstd_rand engine_;
   std::uniform_real_distribution<float> dist_;
   std::vector<framework::DDim> shapes_;
@@ -78,22 +79,22 @@ class CreateRandomDataGeneratorOp : public framework::OperatorBase {
     std::vector<framework::DDim> shapes = RestoreShapes(shape_concat, ranks);
     auto* out = scope.FindVar(Output("Out"))
                     ->template GetMutable<framework::ReaderHolder>();
-    out->Reset(new RandomDataGenerator<T>(shapes, Attr<float>("min"),
-                                          Attr<float>("max")));
+    out->Reset(new RandomDataGenerator<T>(shapes, Attr<float>("low"),
+                                          Attr<float>("high")));
   }
 };
 
 class CreateRandomDataGeneratorOpMaker : public FileReaderMakerBase {
  protected:
   void Apply() override {
-    AddAttr<float>("min", "The lower bound of reader's uniform distribution.");
-    AddAttr<float>("max", "The upper bound of reader's uniform distribution.");
+    AddAttr<float>("low", "The lower bound of reader's uniform distribution.");
+    AddAttr<float>("high", "The upper bound of reader's uniform distribution.");
     AddComment(R"DOC(
       CreateRandomDataGenerator Operator
 
       This Op creates a random reader.
       The reader generates random data instead of really reading from files.
-      Generated data follow an uniform distribution between 'min' and 'max'.
+      Generated data follow an uniform distribution between 'low' and 'high'.
     )DOC");
   }
 };

python/paddle/fluid/layers/io.py

@@ -321,7 +321,7 @@ def open_recordio_file(filename,
                                           dtypes=['float32', 'int64'])
 
          # Via the reader, we can use 'read_file' layer to get data:
-         image, label = fluid.layers.read_file(reader)
+         image, label = fluid.layers.io.read_file(reader)
     """
     dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
     shape_concat = []
@@ -359,6 +359,73 @@ def open_recordio_file(filename,
     return monkey_patch_reader_methods(main_prog_var)
 
 
+def random_data_generator(low, high, shapes, lod_levels, for_parallel=True):
+    """
+    Create a uniform random data generator
+
+    This layer returns a Reader Variable.
+    Instead of opening a file and reading data from it, this 
+    Reader Variable generates float uniform random data by itself. 
+    It can be used as a dummy reader to test a network without 
+    opening a real file.
+
+    Args:
+       low(float): The lower bound of data's uniform distribution.
+       high(float): The upper bound of data's uniform distribution.
+       shapes(list): List of tuples which declaring data shapes.
+       lod_levels(list): List of ints which declaring data lod_level.
+       for_parallel(Bool): Set it as True if you are going to run
+            subsequent operators in parallel.
+
+    Returns:
+       Variable: A Reader Variable from which we can get random data.
+
+    Examples:
+       .. code-block:: python
+
+         reader = fluid.layers.io.random_data_generator(
+                                          low=0.0,
+                                          high=1.0,
+                                          shapes=[(3,224,224), (1)],
+                                          lod_levels=[0, 0])
+
+         # Via the reader, we can use 'read_file' layer to get data:
+         image, label = fluid.layers.io.read_file(reader)
+    """
+    dtypes = [core.VarDesc.VarType.FP32] * len(shapes)
+    shape_concat = []
+    ranks = []
+
+    for shape in shapes:
+        shape_concat.extend(shape)
+        ranks.append(len(shape))
+
+    var_name = unique_name('random_data_generator')
+
+    startup_blk = default_startup_program().current_block()
+    startup_var = startup_blk.create_var(name=var_name)
+    startup_blk.append_op(
+        type='create_random_data_generator',
+        outputs={'Out': [startup_var]},
+        attrs={
+            'low': low,
+            'high': high,
+            'shape_concat': shape_concat,
+            'lod_levels': lod_levels,
+            'ranks': ranks
+        })
+
+    startup_var.desc.set_dtypes(dtypes)
+    startup_var.persistable = True
+    main_prog_var = _copy_reader_var_(default_main_program().current_block(),
+                                      startup_var)
+
+    if for_parallel:
+        main_prog_var = parallel(reader=main_prog_var)
+
+    return monkey_patch_reader_methods(main_prog_var)
+
+
 def open_files(filenames,
                shapes,
                lod_levels,

python/paddle/fluid/tests/test_cpp_reader.py

@@ -44,8 +44,8 @@ create_random_data_generator_op = startup_block.append_op(
     attrs={
         "shape_concat": [1, 2, 1, 1],
         "ranks": [2, 2],
-        "min": 0.0,
-        "max": 1.0,
+        "low": 0.0,
+        "high": 1.0,
         'lod_levels': [0, 0]
     })