Fixrecordio (#16124)

* fix recordio on win
test=develop

* test=develop

* test=develop

* fix code style
test=develop

* test=develop

paddle/fluid/pybind/recordio.cc

@@ -31,7 +31,7 @@ class RecordIOWriter {
   RecordIOWriter(const std::string& filename, recordio::Compressor compressor,
                  size_t max_num_record)
       : closed_(false),
-        stream_(filename),
+        stream_(filename, std::ios::binary),
         writer_(&stream_, compressor, max_num_record) {}
 
   void AppendTensor(const framework::LoDTensor& tensor) {

paddle/fluid/recordio/scanner.cc

@@ -15,6 +15,7 @@
 #include "paddle/fluid/recordio/scanner.h"
 
 #include <string>
+#include <utility>
 
 #include "paddle/fluid/platform/enforce.h"
 
@@ -27,7 +28,8 @@ Scanner::Scanner(std::unique_ptr<std::istream> &&stream)
 }
 
 Scanner::Scanner(const std::string &filename)
-    : stream_(new std::ifstream(filename)), parser_(*stream_) {
+    : stream_(new std::ifstream(filename, std::ios::in | std::ios::binary)),
+      parser_(*stream_) {
   PADDLE_ENFORCE(static_cast<bool>(*stream_), "Cannot open file %s", filename);
   Reset();
 }

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

@@ -26,8 +26,8 @@ class TestAccuracyOp(OpTest):
         self.init_dtype()
         n = 8192
         infer = np.random.random((n, 1)).astype(self.dtype)
-        indices = np.random.randint(0, 2, (n, 1))
-        label = np.random.randint(0, 2, (n, 1))
+        indices = np.random.randint(0, 2, (n, 1)).astype('int64')
+        label = np.random.randint(0, 2, (n, 1)).astype('int64')
         self.inputs = {'Out': infer, 'Indices': indices, "Label": label}
         num_correct = 0
         for rowid in range(n):

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

@@ -31,7 +31,7 @@ class TestRandomCropOp(OpTest):
             np.array([[6, 7, 8], [10, 11, 12]]).astype(np.int32)
         ]
         self.op_type = "random_crop"
-        self.inputs = {'X': to_crop, 'Seed': np.array([10])}
+        self.inputs = {'X': to_crop, 'Seed': np.array([10]).astype('int64')}
         self.outputs = {'Out': np.array([]), 'SeedOut': np.array([])}
         self.attrs = {'shape': [2, 3]}