fill_constant op supports NaN and Inf (#28109)

* fill_constant supports nan and inf

* add ut

paddle/fluid/operators/fill_constant_op.h

@@ -14,9 +14,11 @@ limitations under the License. */
 
 #pragma once
 
+#include <limits>
 #include <sstream>
 #include <string>
 #include <vector>
+
 #include "paddle/fluid/framework/data_type.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/math/math_function.h"
@@ -44,6 +46,12 @@ class FillConstantKernel : public framework::OpKernel<T> {
     T value;
     if (str_value.empty()) {
       value = static_cast<T>(float_value);
+    } else {
+      // handle NaN/Inf first, which cannot be read from stream.
+      if (str_value == "inf") {
+        value = static_cast<T>(std::numeric_limits<double>::infinity());
+      } else if (str_value == "nan") {
+        value = static_cast<T>(std::numeric_limits<double>::quiet_NaN());
       } else {
         std::stringstream convert_stream(str_value);
         if (std::is_same<int64_t, T>::value) {
@@ -56,6 +64,7 @@ class FillConstantKernel : public framework::OpKernel<T> {
           value = static_cast<T>(tmp_value);
         }
       }
+    }
     if (ctx.HasInput("ValueTensor")) {
       auto *value_tensor = ctx.Input<framework::Tensor>("ValueTensor");
       PADDLE_ENFORCE_EQ(

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

@@ -330,6 +330,16 @@ class TestFillConstantImperative(unittest.TestCase):
                 res4.numpy(), np.full(
                     [1, 2], 88, dtype="int32"))
 
+    def test_nan(self):
+        with fluid.dygraph.guard():
+            res = fluid.layers.fill_constant([1], 'float32', np.nan)
+            self.assertTrue(np.isnan(res.numpy().item(0)))
+
+    def test_inf(self):
+        with fluid.dygraph.guard():
+            res = fluid.layers.fill_constant([1], 'float32', np.inf)
+            self.assertTrue(np.isinf(res.numpy().item(0)))
+
 
 class TestFillConstantOpError(unittest.TestCase):
     def test_errors(self):