avoid loop import

mindspore/ops/operations/thor_ops.py

@@ -13,10 +13,9 @@
 # limitations under the License.
 # ============================================================================
 """thor_ops"""
-from mindspore.ops import prim_attr_register, PrimitiveWithInfer
-from mindspore.ops.composite import multitype_ops as C
+from ..primitive import prim_attr_register, PrimitiveWithInfer
+from ...common import dtype as mstype
 
-import mindspore as ms
 
 __all__ = ["CusBatchMatMul",
            "CusCholeskyTrsm",
@@ -58,11 +57,6 @@ class CusBatchMatMul(PrimitiveWithInfer):
         """init CusBatchMatMul"""
         self.init_prim_io_names(inputs=['x1', 'x2'], outputs=['y'])
         from mindspore.ops._op_impl._custom_op.batch_matmul_impl import CusBatchMatMul
-    def get_bprop(self):
-        def bprop(x1, x2, out, dout):
-            return (C.zeros_like(x1), C.zeros_like(x2))
-
-        return bprop
 
     def infer_shape(self, data1_shape, data2_shape):
         return data1_shape
@@ -97,11 +91,6 @@ class CusCholeskyTrsm(PrimitiveWithInfer):
         self.init_prim_io_names(inputs=['x1'], outputs=['y'])
         from mindspore.ops._op_impl._custom_op.cholesky_trsm_impl import CusCholeskyTrsm
 
-    def get_bprop(self):
-        def bprop(x, out, dout):
-            return (C.zeros_like(x),)
-        return bprop
-
     def infer_shape(self, data1_shape):
         ll = []
         m, _ = data1_shape
@@ -138,11 +127,6 @@ class CusFusedAbsMax1(PrimitiveWithInfer):
         self.init_prim_io_names(inputs=['x1'], outputs=['y'])
         self.origin_shape = origin_shape
         from mindspore.ops._op_impl._custom_op.fused_abs_max1_impl import CusFusedAbsMax1
-    def get_bprop(self):
-        def bprop(x, out, dout):
-            return (C.zeros_like(x),)
-
-        return bprop
 
     def infer_shape(self, data1_shape):
         ll = []
@@ -182,11 +166,6 @@ class CusImg2Col(PrimitiveWithInfer):
         self.dilates = dilates
         self.mode = mode
         from mindspore.ops._op_impl._custom_op.img2col_impl import CusImg2Col
-    def get_bprop(self):
-        def bprop(x, out, dout):
-            return (C.zeros_like(x),)
-
-        return bprop
 
     def infer_shape(self, data1_shape):
         bs, c, h, w = data1_shape
@@ -229,17 +208,12 @@ class CusMatMulCubeDenseLeft(PrimitiveWithInfer):
         """init CusMatMulCubeDenseLeft"""
         self.init_prim_io_names(inputs=['x1', 'x2'], outputs=['y'])
         from mindspore.ops._op_impl._custom_op.matmul_cube_dense_left_impl import CusMatMulCubeDenseLeft
-    def get_bprop(self):
-        def bprop(x1, x2, out, dout):
-            return (C.zeros_like(x1), C.zeros_like(x2))
-
-        return bprop
 
     def infer_shape(self, data1_shape, data2_shape):
         return data2_shape
 
     def infer_dtype(self, data1_dtype, data2_dtype):
-        return ms.common.dtype.tensor_type(getattr(ms, "float16"))
+        return mstype.float16
 
 
 class CusMatMulCubeFraczRightMul(PrimitiveWithInfer):
@@ -269,17 +243,12 @@ class CusMatMulCubeFraczRightMul(PrimitiveWithInfer):
         """init CusMatMulCubeFraczRightMul"""
         self.init_prim_io_names(inputs=['x1', 'x2', 'x3'], outputs=['y'])
         from mindspore.ops._op_impl._custom_op.matmul_cube_fracz_right_mul_impl import CusMatMulCubeFraczRightMul
-    def get_bprop(self):
-        def bprop(x1, x2, x3, out, dout):
-            return (C.zeros_like(x1), C.zeros_like(x2), C.zeros_like(x3))
-
-        return bprop
 
     def infer_shape(self, data1_shape, data2_shape, data3_shape):
         return data1_shape
 
     def infer_dtype(self, data1_dtype, data2_dtype, data3_dtype):
-        return ms.common.dtype.tensor_type(getattr(ms, "float32"))
+        return mstype.float32
 
 
 class CusMatMulCube(PrimitiveWithInfer):
@@ -315,11 +284,6 @@ class CusMatMulCube(PrimitiveWithInfer):
         self.transpose_a = transpose_a
         self.transpose_b = transpose_b
         from mindspore.ops._op_impl._custom_op.matmul_cube_impl import CusMatMulCube
-    def get_bprop(self):
-        def bprop(x1, x2, out, dout):
-            return (C.zeros_like(x1), C.zeros_like(x2))
-
-        return bprop
 
     def infer_shape(self, data1_shape, data2_shape):
         # shape = [1, data1_shape[1], data2_shape[2], 16, 16]
@@ -337,7 +301,7 @@ class CusMatMulCube(PrimitiveWithInfer):
         return shape
 
     def infer_dtype(self, data1_dtype, data2_dtype):
-        return ms.common.dtype.tensor_type(getattr(ms, "float32"))
+        return mstype.float32
 
 
 class CusMatrixCombine(PrimitiveWithInfer):
@@ -362,11 +326,6 @@ class CusMatrixCombine(PrimitiveWithInfer):
         """init CusMatrixCombine"""
         self.init_prim_io_names(inputs=['x'], outputs=['y'])
         from mindspore.ops._op_impl._custom_op.matrix_combine_impl import CusMatrixCombine
-    def get_bprop(self):
-        def bprop(x, out, dout):
-            return (C.zeros_like(x),)
-
-        return bprop
 
     def infer_shape(self, data_shape):
         a, b, c = data_shape
@@ -446,17 +405,12 @@ class CusMatMulCubeDenseRight(PrimitiveWithInfer):
         """init CusMatMulCubeDenseRight"""
         self.init_prim_io_names(inputs=['x1', 'x2', 'x3'], outputs=['y'])
         from mindspore.ops._op_impl._custom_op.matmul_cube_dense_right_impl import CusMatMulCubeDenseRight
-    def get_bprop(self):
-        def bprop(x1, x2, x3, out, dout):
-            return (C.zeros_like(x1), C.zeros_like(x2), C.zeros_like(x3))
-
-        return bprop
 
     def infer_shape(self, data1_shape, data2_shape, data3_shape):
         return data1_shape
 
     def infer_dtype(self, data1_dtype, data2_dtype, data3_dtype):
-        return ms.common.dtype.tensor_type(getattr(ms, "float32"))
+        return mstype.float32
 
 
 class CusMatMulCubeFraczLeftCast(PrimitiveWithInfer):
@@ -486,14 +440,9 @@ class CusMatMulCubeFraczLeftCast(PrimitiveWithInfer):
         """init CusMatMulCubeFraczLeftCast"""
         self.init_prim_io_names(inputs=['x1', 'x2'], outputs=['y'])
         from mindspore.ops._op_impl._custom_op.matmul_cube_fracz_left_cast_impl import CusMatMulCubeFraczLeftCast
-    def get_bprop(self):
-        def bprop(x1, x2, out, dout):
-            return (C.zeros_like(x1), C.zeros_like(x2))
-
-        return bprop
 
     def infer_shape(self, data1_shape, data2_shape):
         return data2_shape
 
     def infer_dtype(self, data1_dtype, data2_dtype):
-        return ms.common.dtype.tensor_type(getattr(ms, "float16"))
+        return mstype.float16