[Phi] support bincount yaml and _C_ops.bincount under eager (#46443)

paddle/phi/api/yaml/legacy_ops.yaml

@@ -3018,3 +3018,12 @@
     func: unpool3d
     data_type: x
   backward: unpool3d_grad
+
+- op: bincount
+  args: (Tensor x, Tensor weights, Scalar minlength)
+  output: Tensor(out)
+  infer_meta:
+    func: BincountInferMeta
+  kernel:
+    func: bincount
+  optional: weights

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

@@ -24,6 +24,7 @@ import paddle.fluid.core as core
 from paddle.fluid import Program, program_guard
 from op_test import OpTest
 import paddle.inference as paddle_infer
+from paddle.fluid.framework import in_dygraph_mode
 
 paddle.enable_static()
 
@@ -101,8 +102,15 @@ class TestBincountOpError(unittest.TestCase):
             input_value = paddle.to_tensor([1, 2, 3, 4, 5])
             paddle.bincount(input_value, minlength=-1)
 
-        with self.assertRaises(IndexError):
-            self.run_network(net_func)
+        with fluid.dygraph.guard():
+            if in_dygraph_mode():
+                # InvalidArgument for phi BincountKernel
+                with self.assertRaises(ValueError):
+                    self.run_network(net_func)
+            else:
+                # OutOfRange for EqualGreaterThanChecker
+                with self.assertRaises(IndexError):
+                    self.run_network(net_func)
 
     def test_input_type_errors(self):
         """Test input tensor should only contain non-negative ints."""

python/paddle/tensor/linalg.py

@@ -1651,7 +1651,9 @@ def bincount(x, weights=None, minlength=0, name=None):
     if x.dtype not in [paddle.int32, paddle.int64]:
         raise TypeError("Elements in Input(x) should all be integers")
 
-    if _non_static_mode():
+    if in_dygraph_mode():
+        return _C_ops.bincount(x, weights, minlength)
+    elif _in_legacy_dygraph():
         return _legacy_C_ops.bincount(x, weights, "minlength", minlength)
 
     helper = LayerHelper('bincount', **locals())