fix by code review

paddle/phi/kernels/impl/einsum_impl.h

@@ -357,7 +357,7 @@ DenseTensor PerformReduction(const Context& dev_ctx,
 
 inline bool is_no_need_transpose(const std::vector<int>& axis) {
   for (size_t i = 0; i < axis.size(); ++i) {
-    if (i != size_t(axis[i])) return false;
+    if (i != static_cast<size_t>(axis[i])) return false;
   }
   return true;
 }

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

@@ -19,19 +19,6 @@
 from paddle.fluid import core
 
 
-def error_trans(func, *args, **kargs):
-    """ 
-    transport C++ exception into Python exception. 
-    because einsum_v2 raise different exception with einsum_v1.
-    """
-    try:
-        out = func(*args, **kargs)
-    except ValueError as e:
-        if "Same label have different shapes" in str(e):
-            raise AssertionError("Invalid operands: label i "
-                                 "corresponds to non-broadcastable dimensions.")
-
-
 class TestErrors(unittest.TestCase):
     def setUp(self):
         pass
@@ -95,7 +82,7 @@ def test_param_errors(self):
         with self.assertRaisesRegex(AssertionError, (
                 "Invalid operands: label i "
                 "corresponds to non-broadcastable dimensions.")):
-            error_trans(paddle.einsum, 'ij...,ji...', a, a)
+            paddle.einsum('ij...,ji...', a, a)
 
 
 class TestEinsum(unittest.TestCase):
@@ -383,21 +370,18 @@ def test_sums(self):
             self.check_output("...,...", a, a)
             self.check_output("i,i", a, a)
 
-        # TODO(@xiongkun): explict broadcast in EinsumOp is not supported, it's not recommend to use einsum like this.
-        #p = np.ones((10, 2)).astype('float')
-        #q = np.ones((1, 2)).astype('float')
-        #self.check_output('ij,ij->j', p, q)
+        p = np.ones((10, 2)).astype('float')
+        q = np.ones((1, 2)).astype('float')
+        self.check_output('ij,ij->j', p, q)
 
-        # TODO(@xiongkun): explict-label-broadcast in EinsumOp is not supported, it's not recommend to use einsum like this.
-        #x = np.array([2., 3.]).astype('float')
-        #y = np.array([4.]).astype('float')
-        #self.check_output("i, i", x, y)
+        x = np.array([2., 3.]).astype('float')
+        y = np.array([4.]).astype('float')
+        self.check_output("i, i", x, y)
 
-        # TODO(@xiongkun): explict-label-broadcast in EinsumOp is not supported, it's not recommend to use einsum like this.
-        #p = np.ones((1, 5)) / 2
-        #q = np.ones((5, 5)) / 2
-        #self.check_output("...ij,...jk->...ik", p, p)
-        #self.check_output("...ij,...jk->...ik", p, q)
+        p = np.ones((1, 5)) / 2
+        q = np.ones((5, 5)) / 2
+        self.check_output("...ij,...jk->...ik", p, p)
+        self.check_output("...ij,...jk->...ik", p, q)
 
         x = np.eye(2).astype('float')
         y = np.ones(2).astype('float')
@@ -406,13 +390,11 @@ def test_sums(self):
         self.check_output("ij,i->", x, y)
 
     def test_large_nops(self):
-        pass
-        # TODO(@xiongkun): explict broadcast in EinsumOp is not supported, it's not recommend to use einsum like this.
-        #a = np.arange(4 * 3 * 1 * 4).reshape(4, 3, 1, 4).astype('float')
-        #self.check_output('a...b,b...c,c...d', a, a, a)
-        #self.check_output('a...b,b...c,c...a', a, a, a)
-        #self.check_output('a...b,b...c,c...a', a, a, a)
-        #self.check_output('...ab,...ba,...ab,...ab', a, a, a, a)
+        a = np.arange(4 * 3 * 1 * 4).reshape(4, 3, 1, 4).astype('float')
+        self.check_output('a...b,b...c,c...d', a, a, a)
+        self.check_output('a...b,b...c,c...a', a, a, a)
+        self.check_output('a...b,b...c,c...a', a, a, a)
+        self.check_output('...ab,...ba,...ab,...ab', a, a, a, a)
 
     def test_static_graph(self):
         paddle.enable_static()