fix some quant op bug

mindspore/ops/_grad/grad_quant_ops.py

@@ -85,7 +85,7 @@ def get_bprop_batchnorm_fold2(self):
 @bprop_getters.register(P.BatchNormFoldD)
 def get_bprop_BatchNormFold(self):
     """Generate bprop for BatchNormFold for Ascend"""
-    op = P.BatchNormFoldGrad_(self.epsilon, self.is_training, self.freeze_bn)
+    op = P.BatchNormFoldGradD(self.epsilon, self.is_training, self.freeze_bn)
 
     def bprop(x, x_sum, x_square_sum, mean, variance, out, dout):
         dx = op(dout[1], dout[2], x, out[1], out[2])

mindspore/ops/_op_impl/_custom_op/batchnorm_fold.py

@@ -16,6 +16,7 @@
 """_BatchNormFold op"""
 
 from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+import te
 from te import tvm
 from topi import generic
 from topi.cce import util

mindspore/ops/operations/_quant_ops.py

@@ -31,8 +31,11 @@ __all__ = ["FakeQuantWithMinMax",
            "BatchNormFold2",
            "BatchNormFold2Grad",
            "BatchNormFoldD",
+           "BatchNormFoldGradD",
            "BNTrainingReduce",
            "BatchNormFold2_D",
+           "BatchNormFold2GradD",
+           "BatchNormFold2GradReduce",
            "FakeQuantWithMinMaxUpdate",
            ]