Add shape and type check at read_op (#20754)

paddle/fluid/framework/reader.h

@@ -20,6 +20,7 @@
 #include <vector>
 
 #include "paddle/fluid/framework/ddim.h"
+#include "paddle/fluid/framework/framework.pb.h"
 #include "paddle/fluid/framework/lod_tensor_array.h"
 #include "paddle/fluid/platform/place.h"
 
@@ -28,6 +29,20 @@ namespace framework {
 
 class ReaderBase {
  public:
+  explicit ReaderBase(const std::vector<DDim>& shapes,
+                      const std::vector<proto::VarType::Type>& var_types,
+                      const std::vector<bool>& need_check_feed)
+      : shapes_(shapes),
+        var_types_(var_types),
+        need_check_feed_(need_check_feed) {
+    PADDLE_ENFORCE_EQ(shapes_.size(), need_check_feed_.size(),
+                      "Construct ReaderBase with mismatched sizes of shapes "
+                      "and need_check_feed");
+    PADDLE_ENFORCE_EQ(var_types_.size(), need_check_feed_.size(),
+                      "Construct ReaderBase with mismatched sizes of var_types "
+                      "and need_check_feed");
+  }
+
   virtual void ReadNext(std::vector<LoDTensor>* out);
 
   virtual void Shutdown();
@@ -38,6 +53,18 @@ class ReaderBase {
   // they are readers just before read op.
   std::unordered_set<ReaderBase*> GetEndPoints();
 
+  // Returns the shapes of the feeded variables
+  const std::vector<DDim>& Shapes() const { return shapes_; }
+
+  // Returns the dtypes of the feeded variables
+  const std::vector<proto::VarType::Type>& VarTypes() const {
+    return var_types_;
+  }
+
+  // For Backward compatibility, old fluid.layers.data doesn't check shape.
+  // This function returns whether you have the check shape for this Reader.
+  const std::vector<bool>& NeedCheckFeed() const { return need_check_feed_; }
+
   virtual ~ReaderBase();
 
  protected:
@@ -53,6 +80,17 @@ class ReaderBase {
 
   mutable std::mutex mu_;
 
+  // The shapes of the feeded variables.
+  std::vector<DDim> shapes_;
+
+  // The dtypes of the feeded variables.
+  std::vector<proto::VarType::Type> var_types_;
+
+  // Whether to check the shape and dtype of feeded variables.
+  // For Backward compatibility, variables created by old API fluid.layers.data
+  // doesn't check shape but fluid.data checks.
+  std::vector<bool> need_check_feed_;
+
  private:
   friend class DecoratedReader;
   // These methods can be only invoked inside DecoratedReader to record the
@@ -67,7 +105,9 @@ class DecoratedReader : public ReaderBase,
                         public std::enable_shared_from_this<DecoratedReader> {
  public:
   explicit DecoratedReader(const std::shared_ptr<ReaderBase>& reader)
-      : ReaderBase(), reader_(reader) {
+      : ReaderBase(reader->Shapes(), reader->VarTypes(),
+                   reader->NeedCheckFeed()),
+        reader_(reader) {
     PADDLE_ENFORCE_NOT_NULL(reader_);
   }
 
@@ -89,7 +129,13 @@ class DecoratedReader : public ReaderBase,
 };
 
 // FileReader is just a conceptual class.
-class FileReader : public ReaderBase {};
+class FileReader : public ReaderBase {
+ public:
+  explicit FileReader(const std::vector<DDim>& shapes,
+                      const std::vector<proto::VarType::Type>& var_types,
+                      const std::vector<bool>& need_check_feed)
+      : ReaderBase(shapes, var_types, need_check_feed) {}
+};
 
 // The ReaderHolder is used as reader' unified wrapper,
 // making it easier to access different type reader in Variables.
@@ -134,6 +180,16 @@ class ReaderHolder {
     reader_->Start();
   }
 
+  const std::vector<DDim>& Shapes() const { return reader_->Shapes(); }
+
+  const std::vector<proto::VarType::Type>& VarTypes() const {
+    return reader_->VarTypes();
+  }
+
+  const std::vector<bool>& NeedCheckFeed() const {
+    return reader_->NeedCheckFeed();
+  }
+
   operator const std::shared_ptr<ReaderBase>&() const { return this->reader_; }
 
  private:

paddle/fluid/framework/reader_test.cc

@@ -15,6 +15,7 @@
 #include "paddle/fluid/framework/reader.h"
 #include <memory>
 #include "gtest/gtest.h"
+#include "paddle/fluid/framework/ddim.h"
 
 class StubDecoratedReader : public paddle::framework::DecoratedReader {
  public:
@@ -26,11 +27,23 @@ class StubDecoratedReader : public paddle::framework::DecoratedReader {
 
 class StubRootReader : public paddle::framework::ReaderBase {
  public:
+  explicit StubRootReader(
+      const std::vector<paddle::framework::DDim> &dims,
+      const std::vector<paddle::framework::proto::VarType::Type> &var_types,
+      const std::vector<bool> &need_check_feed)
+      : paddle::framework::ReaderBase(dims, var_types, need_check_feed) {}
   void ReadNextImpl(std::vector<paddle::framework::LoDTensor> *out) override {}
 };
 
 TEST(READER, decorate_chain) {
-  auto root = std::make_shared<StubRootReader>();
+  paddle::framework::proto::VarType::Type dtype =
+      paddle::framework::proto::VarType::FP32;
+  paddle::framework::DDim dim = paddle::framework::make_ddim({5, 7});
+  std::vector<paddle::framework::DDim> init_dims(4, dim);
+  std::vector<paddle::framework::proto::VarType::Type> init_types(4, dtype);
+  std::vector<bool> init_need_check(4, true);
+  auto root =
+      std::make_shared<StubRootReader>(init_dims, init_types, init_need_check);
   auto end_point1 =
       paddle::framework::MakeDecoratedReader<StubDecoratedReader>(root);
   auto end_point2 =
@@ -49,4 +62,10 @@ TEST(READER, decorate_chain) {
     ASSERT_EQ(root->GetEndPoints().size(), 3U);
   }
   { ASSERT_EQ(root->GetEndPoints().size(), 2U); }
+
+  {
+    ASSERT_EQ(end_point1->Shapes(), init_dims);
+    ASSERT_EQ(end_point1->VarTypes(), init_types);
+    ASSERT_EQ(end_point1->NeedCheckFeed(), init_need_check);
+  }
 }

paddle/fluid/operators/reader/create_py_reader_op.cc

@@ -12,6 +12,8 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include "paddle/fluid/framework/ddim.h"
+#include "paddle/fluid/framework/framework.pb.h"
 #include "paddle/fluid/operators/reader/py_reader.h"
 #include "paddle/fluid/operators/reader/reader_op_registry.h"
 
@@ -39,7 +41,38 @@ class CreatePyReaderOp : public framework::OperatorBase {
     auto* queue_holder =
         queue_holder_var->template GetMutable<LoDTensorBlockingQueueHolder>();
 
-    out->Reset(std::make_shared<PyReader>(queue_holder->GetQueue()));
+    /* Coverting shape_concat and ranks into DDim of each data.
+     shape_concat and ranks are shapes and shape ranks of each data.E.g.
+     shape_concat = [2,3,4,5,6], ranks = [3,2] means two data whose shapes are
+     [2,3,4] and [5,6] respectively. */
+    auto& shape_concat = Attr<std::vector<int>>("shape_concat");
+    auto& ranks = Attr<std::vector<int>>("ranks");
+    int shape_start_index = 0;
+    std::vector<framework::DDim> dims;
+    for (size_t i = 0; i < ranks.size(); ++i) {
+      int shape_end_index = shape_start_index + ranks[i];
+      auto shape = std::vector<int>(shape_concat.begin() + shape_start_index,
+                                    shape_concat.begin() + shape_end_index);
+      dims.push_back(framework::make_ddim(shape));
+      shape_start_index = shape_end_index;
+    }
+
+    // Converts VarType from int to enum
+    auto& dtype_int = Attr<std::vector<int>>("dtypes");
+    std::vector<framework::proto::VarType::Type> var_types;
+    for (size_t i = 0; i < dtype_int.size(); ++i) {
+      var_types.push_back(
+          static_cast<framework::proto::VarType::Type>(dtype_int[i]));
+    }
+
+    // Converts need_check_feed from int to bool
+    auto& need_check_feed_int = Attr<std::vector<int>>("need_check_feed");
+    std::vector<bool> need_check_feed;
+    for (size_t i = 0; i < need_check_feed_int.size(); ++i) {
+      need_check_feed.push_back(static_cast<bool>(need_check_feed_int[i]));
+    }
+    out->Reset(std::make_shared<PyReader>(queue_holder->GetQueue(), dims,
+                                          var_types, need_check_feed));
   }
 };
 

paddle/fluid/operators/reader/py_reader.cc

@@ -19,8 +19,12 @@ namespace paddle {
 namespace operators {
 namespace reader {
 
-PyReader::PyReader(const std::shared_ptr<LoDTensorBlockingQueue>& queue)
-    : framework::FileReader() {
+PyReader::PyReader(
+    const std::shared_ptr<LoDTensorBlockingQueue>& queue,
+    const std::vector<framework::DDim>& dims,
+    const std::vector<framework::proto::VarType::Type>& var_types,
+    const std::vector<bool>& need_check_feed)
+    : framework::FileReader(dims, var_types, need_check_feed) {
   PADDLE_ENFORCE(queue != nullptr, "LoDTensorBlockingQueue must not be null");
   queue_ = queue;
 }

paddle/fluid/operators/reader/py_reader.h

@@ -26,7 +26,11 @@ namespace reader {
 
 class PyReader : public framework::FileReader {
  public:
-  explicit PyReader(const std::shared_ptr<LoDTensorBlockingQueue>& queue);
+  explicit PyReader(
+      const std::shared_ptr<LoDTensorBlockingQueue>& queue,
+      const std::vector<framework::DDim>& dims,
+      const std::vector<framework::proto::VarType::Type>& var_types,
+      const std::vector<bool>& need_check_feed);
 
   void ReadNext(std::vector<framework::LoDTensor>* out) override;
 

paddle/fluid/operators/reader/read_op.cc

@@ -1,4 +1,4 @@
-//   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -12,6 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include "paddle/fluid/framework/framework.pb.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/reader.h"
 #include "paddle/fluid/operators/detail/safe_ref.h"
@@ -20,6 +21,26 @@
 namespace paddle {
 namespace operators {
 
+// Returns true if the two dimensions are compatible.
+// A dimension is compatible with the other if:
+// 1. The length of the dimensions are same.
+// 2. Each non-negative number of the two dimentions are same.
+// 3. For negative number in a dimention, it means unknown so it is compatible
+//    with any number.
+bool DimensionIsCompatibleWith(const framework::DDim& first,
+                               const framework::DDim& second) {
+  int dim_size = first.size();
+  if (dim_size != second.size()) {
+    return false;
+  }
+  for (int i = 0; i < dim_size; ++i) {
+    if (first[i] >= 0 && second[i] >= 0 && first[i] != second[i]) {
+      return false;
+    }
+  }
+  return true;
+}
+
 class ReadInferShape : public framework::InferShapeBase {
  public:
   void operator()(framework::InferShapeContext* ctx) const override {
@@ -89,10 +110,32 @@ class ReadOp : public framework::OperatorBase {
       VLOG(3) << "throw_eof_exp";
       PADDLE_THROW_EOF();
     }
-    PADDLE_ENFORCE_EQ(ins.size(), out_arg_names.size());
+    PADDLE_ENFORCE_EQ(ins.size(), out_arg_names.size(),
+                      "input size and output size of read_op do not match");
+
+    const std::vector<framework::DDim>& shapes = reader->Shapes();
+    const std::vector<framework::proto::VarType::Type>& var_types =
+        reader->VarTypes();
+    const std::vector<bool>& need_check_feed = reader->NeedCheckFeed();
+    PADDLE_ENFORCE_EQ(out_arg_names.size(), need_check_feed.size(),
+                      "output size of read_op and the number of feeded "
+                      "variables of reader do not match");
+
     for (size_t i = 0; i < out_arg_names.size(); ++i) {
       auto* out =
           scope.FindVar(out_arg_names[i])->GetMutable<framework::LoDTensor>();
+      if (need_check_feed[i]) {
+        auto in_dims = ins[i].dims();
+        PADDLE_ENFORCE_EQ(DimensionIsCompatibleWith(shapes[i], in_dims), true,
+                          "The feeded Variable %s should have dimensions = %d, "
+                          "shape = [%s], but received feeded shape [%s]",
+                          out_arg_names[i], shapes[i].size(), shapes[i],
+                          in_dims);
+        PADDLE_ENFORCE_EQ(
+            ins[i].type(), var_types[i],
+            "The data type of feeded Variable %s must be %s, but received %s",
+            out_arg_names[i], var_types[i], ins[i].type());
+      }
       out->ShareDataWith(ins[i]);
       out->set_lod(ins[i].lod());
     }

paddle/fluid/operators/reader/reader_op_registry.cc

@@ -50,6 +50,10 @@ void FileReaderMakerBase::Make() {
       "It means the reader will generate two data each time,"
       "whose shapes are [2,3,4] and [5,6] respectively.");
   AddAttr<std::vector<int>>("lod_levels", "The LoD levels of each data.");
+  AddAttr<std::vector<int>>("dtypes",
+                            "The int value of enum dtypes of each data.");
+  AddAttr<std::vector<int>>("need_check_feed",
+                            "Whether to check shape and dtypes of input");
   AddAttr<bool>(
       "use_data_config",
       "Use the config of all datas like shape_concat/ranks/lod_levels")
@@ -77,6 +81,17 @@ void FileReaderInferShape::operator()(framework::InferShapeContext* ctx) const {
                       "The number of 'lod_levels'(%d) doesn't match the number "
                       "of 'shapes'(%d).",
                       lod_levels.size(), shapes.size());
+    const auto dtypes = ctx->Attrs().Get<std::vector<int>>("dtypes");
+    PADDLE_ENFORCE_EQ(
+        dtypes.size(), shapes.size(),
+        "The number of 'dtypes'(%d) doesn't match the number of 'shapes'(%d).",
+        dtypes.size(), shapes.size());
+    const auto need_check_feed =
+        ctx->Attrs().Get<std::vector<int>>("need_check_feed");
+    PADDLE_ENFORCE_EQ(need_check_feed.size(), shapes.size(),
+                      "The number of 'need_check_feed'(%d) doesn't match the "
+                      "number of 'shapes'(%d).",
+                      need_check_feed.size(), shapes.size());
     framework::VarDesc* reader =
         boost::get<framework::VarDesc*>(ctx->GetOutputVarPtrs("Out")[0]);
     reader->SetLoDLevels(lod_levels);

paddle/fluid/pybind/reader_py.cc

@@ -20,6 +20,7 @@
 #include <utility>
 #include <vector>
 #include "Python.h"
+#include "paddle/fluid/framework/ddim.h"
 #include "paddle/fluid/framework/reader.h"
 #include "paddle/fluid/operators/reader/buffered_reader.h"
 #include "paddle/fluid/operators/reader/py_reader.h"
@@ -40,12 +41,19 @@ class MultiDeviceFeedReader {
   MultiDeviceFeedReader(
       const std::shared_ptr<operators::reader::LoDTensorBlockingQueue> &queue,
       const std::vector<std::string> &names,
+      const std::vector<std::vector<int>> &shapes,
+      const std::vector<framework::proto::VarType::Type> &dtypes,
+      const std::vector<bool> &need_check_feed,
       const std::vector<platform::Place> &dst_places, bool use_double_buffer)
       : queue_(queue),
         names_(names),
         pool_(new ::ThreadPool(dst_places.size())) {
+    std::vector<framework::DDim> dims;
+    for (auto &shape : shapes) {
+      dims.push_back(framework::make_ddim(shape));
+    }
     std::shared_ptr<framework::ReaderBase> reader(
-        new operators::reader::PyReader(queue));
+        new operators::reader::PyReader(queue, dims, dtypes, need_check_feed));
 
     readers_.reserve(dst_places.size());
     for (auto &p : dst_places) {
@@ -206,9 +214,13 @@ void BindReader(py::module *module) {
         [](const std::shared_ptr<operators::reader::LoDTensorBlockingQueue>
                &queue,
            const std::vector<std::string> &names,
+           const std::vector<std::vector<int>> &shapes,
+           const std::vector<framework::proto::VarType::Type> &dtypes,
+           const std::vector<bool> &need_check_feed,
            const std::vector<platform::Place> &dst_places,
            bool use_double_buffer) {
-          return new MultiDeviceFeedReader(queue, names, dst_places,
+          return new MultiDeviceFeedReader(queue, names, shapes, dtypes,
+                                           need_check_feed, dst_places,
                                            use_double_buffer);
         },
         py::return_value_policy::take_ownership);

python/paddle/fluid/layers/io.py

@@ -385,6 +385,7 @@ def _py_reader(capacity,
         shape_concat = []
         ranks = []
         shapes = []
+        need_check_feed = []
 
         for feed_data in feed_list:
             dtypes.append(feed_data.dtype)
@@ -392,8 +393,10 @@ def _py_reader(capacity,
             ranks.append(len(feed_data.shape))
             shapes.append(feed_data.shape)
             lod_levels.append(feed_data.lod_level)
+            need_check_feed.append(int(feed_data.desc.need_check_feed()))
     else:
         dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
+        need_check_feed = [0 for dt in dtypes]
         shape_concat = []
         ranks = []
 
@@ -403,7 +406,7 @@ def _py_reader(capacity,
 
         if lod_levels is None:
             lod_levels = [0] * len(shapes)
-
+    dtype_int = [int(t) for t in dtypes]
     if name is None:
         queue_name = unique_name('lod_tensor_blocking_queue')
         reader_name = unique_name('create_py_reader')
@@ -425,6 +428,8 @@ def _py_reader(capacity,
         attrs={
             'shape_concat': shape_concat,
             'lod_levels': lod_levels,
+            'dtypes': dtype_int,
+            'need_check_feed': need_check_feed,
             'ranks': ranks
         })
 

python/paddle/fluid/reader.py

@@ -331,7 +331,7 @@ class GeneratorLoader(DataLoaderBase):
             self._init_non_iterable()
 
     def _wait_thread_ends(self):
-        # Get self._thread first to prevent data race, because __thread_main__ 
+        # Get self._thread first to prevent data race, because __thread_main__
         # would set self._thread be None at the end
         thread = self._thread
         if thread is not None and self._iterable:
@@ -342,12 +342,21 @@ class GeneratorLoader(DataLoaderBase):
         self._wait_thread_ends()
         if in_dygraph_mode():
             self._var_names = []
+            self._shapes = []
+            self._dtypes = []
+            self._need_check_feed = []
         else:
             self._var_names = [v.name for v in self._feed_list]
+            self._shapes = [v.shape for v in self._feed_list]
+            self._dtypes = [v.dtype for v in self._feed_list]
+            self._need_check_feed = [
+                v.desc.need_check_feed() for v in self._feed_list
+            ]
         self._queue = core.init_lod_tensor_blocking_queue(core.Variable(),
                                                           self._capacity)
         self._reader = core.create_py_reader(
-            self.queue, self._var_names, self._places, self._use_double_buffer)
+            self.queue, self._var_names, self._shapes, self._dtypes,
+            self._need_check_feed, self._places, self._use_double_buffer)
 
     def _init_non_iterable(self):
         lod_levels = []
@@ -355,6 +364,7 @@ class GeneratorLoader(DataLoaderBase):
         shape_concat = []
         ranks = []
         shapes = []
+        need_check_feed = []
 
         for feed_data in self._feed_list:
             dtypes.append(feed_data.dtype)
@@ -362,6 +372,7 @@ class GeneratorLoader(DataLoaderBase):
             ranks.append(len(feed_data.shape))
             shapes.append(feed_data.shape)
             lod_levels.append(feed_data.lod_level)
+            need_check_feed.append(int(feed_data.desc.need_check_feed()))
 
         queue_name = data_loader_unique_name_generator(
             'lod_tensor_blocking_queue')
@@ -374,6 +385,7 @@ class GeneratorLoader(DataLoaderBase):
         startup_blk = default_startup_program().current_block()
         startup_var = startup_blk.create_var(name=reader_name)
 
+        dtype_int = [int(t) for t in dtypes]
         startup_blk.append_op(
             type='create_py_reader',
             inputs={'blocking_queue': [queue_name]},
@@ -381,6 +393,8 @@ class GeneratorLoader(DataLoaderBase):
             attrs={
                 'shape_concat': shape_concat,
                 'lod_levels': lod_levels,
+                'dtypes': dtype_int,
+                'need_check_feed': need_check_feed,
                 'ranks': ranks
             })
 

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

@@ -73,8 +73,7 @@ class TestPyReader(unittest.TestCase):
             for _ in range(10):
                 sample = np.random.uniform(
                     low=0, high=1, size=[3, 2, 1]).astype("float32")
-                label = np.random.uniform(
-                    low=0, high=10, size=[1]).astype("int64")
+                label = np.random.randint(low=0, high=10, dtype="int64")
                 self.inputs.append((sample, label))
 
             self.input_tensors = []