!24792 [feat] [assistant] [I48OFK] add the dynamic shape for AbsGrad

Merge pull request !24792 from 彭涛/op_abs_grad

mindspore/core/ops/grad/abs_grad.cc

@@ -15,10 +15,53 @@
  */
 
 #include "ops/grad/abs_grad.h"
-#include <memory>
+#include <algorithm>
+#include <set>
+#include "abstract/param_validator.h"
+#include "utils/check_convert_utils.h"
+#include "abstract/primitive_infer_map.h"
 
 namespace mindspore {
 namespace ops {
-REGISTER_PRIMITIVE_C(kNameAbsGrad, AbsGrad);
+namespace {
+abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
+  auto prim_name = primitive->name();
+  const int64_t input_num = 2;
+  (void)CheckAndConvertUtils::CheckInteger("input number", SizeToLong(input_args.size()), kEqual, input_num, prim_name);
+  for (const auto &item : input_args) {
+    MS_EXCEPTION_IF_NULL(item);
+  }
+  auto x = input_args[0]->BuildShape();
+  MS_EXCEPTION_IF_NULL(x);
+  auto shape_element = x->cast<abstract::ShapePtr>();
+  MS_EXCEPTION_IF_NULL(shape_element);
+  return shape_element;
+}
+
+TypePtr InferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(prim);
+  auto prim_name = prim->name();
+  const int64_t input_num = 2;
+  (void)CheckAndConvertUtils::CheckInteger("input number", SizeToLong(input_args.size()), kEqual, input_num, prim_name);
+  MS_EXCEPTION_IF_NULL(input_args[0]);
+  auto x_type = input_args[0]->BuildType();
+  MS_EXCEPTION_IF_NULL(x_type);
+  if (!x_type->isa<TensorType>()) {
+    MS_EXCEPTION(TypeError) << "The " << prim_name << "'s "
+                            << " input must be tensor type but got " << x_type->ToString();
+  }
+  return x_type;
+}
+}  // namespace
+
+AbstractBasePtr AbsGradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
+                             const std::vector<AbstractBasePtr> &input_args) {
+  auto type = InferType(primitive, input_args);
+  auto shape = InferShape(primitive, input_args);
+  return abstract::MakeAbstract(shape, type);
+}
+
+REGISTER_PRIMITIVE_EVAL_IMPL(AbsGrad, prim::kPrimAbsGrad, AbsGradInfer, nullptr, true);
 }  // namespace ops
 }  // namespace mindspore

mindspore/core/ops/grad/abs_grad.h

@@ -21,6 +21,7 @@
 #include <string>
 #include <memory>
 #include "ops/primitive_c.h"
+#include "ops/op_utils.h"
 #include "abstract/abstract_value.h"
 #include "utils/check_convert_utils.h"
 

mindspore/ops/_op_impl/tbe/__init__.py

@@ -20,6 +20,7 @@ from .abs_ds import _abs_ds_tbe
 from .inplace_add import _inplace_add_tbe
 from .inplace_sub import _inplace_sub_tbe
 from .abs_grad import _abs_grad_tbe
+from .abs_grad_ds import _abs_grad_ds_tbe
 from .acos import _acos_tbe
 from .acos_grad import _acos_grad_tbe
 from .acosh import _acosh_tbe

mindspore/ops/_op_impl/tbe/abs_grad_ds.py

@@ -0,0 +1,44 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+"""AbsGrad op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+abs_grad_op_info = TBERegOp("AbsGrad") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("abs_grad.so") \
+    .compute_cost(10) \
+    .kernel_name("abs_grad") \
+    .dynamic_shape(True)\
+    .partial_flag(True) \
+    .input(0, "y", None, "required", None) \
+    .input(1, "dy", None, "required", None) \
+    .output(0, "z", False, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD) \
+    .dtype_format(DataType.F16_FracZ, DataType.F16_FracZ, DataType.F16_FracZ) \
+    .dtype_format(DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0) \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
+    .dtype_format(DataType.F32_FracZ, DataType.F32_FracZ, DataType.F32_FracZ) \
+    .dtype_format(DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
+    .get_op_info()
+
+
+@op_info_register(abs_grad_op_info)
+def _abs_grad_ds_tbe():
+    """AbsGrad TBE register"""
+    return

mindspore/ops/operations/_grad_ops.py

@@ -32,12 +32,6 @@ class AbsGrad(PrimitiveWithInfer):
     def __init__(self):
         """Initialize AbsGrad"""
 
-    def infer_shape(self, y, dy):
-        return y
-
-    def infer_dtype(self, y, dy):
-        return y
-
 
 class ACosGrad(PrimitiveWithInfer):
     """