!25271 [feat] [assistant] [I48OC4] add dynamic shape for ReLU6Grad operator

Merge pull request !25271 from 路雄博/Relu6Grad

mindspore/core/ops/grad/relu6_grad.cc

@@ -0,0 +1,72 @@
+/**
+ * Copyright 2021 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.
+ */
+#include "ops/grad/relu6_grad.h"
+#include <string>
+#include <algorithm>
+#include <map>
+#include <set>
+#include <vector>
+#include "abstract/param_validator.h"
+#include "ops/op_utils.h"
+#include "utils/check_convert_utils.h"
+#include "abstract/primitive_infer_map.h"
+
+namespace mindspore {
+namespace ops {
+namespace {
+abstract::ShapePtr ReLU6GradInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
+  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 ReLU6GradInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
+  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 dout = CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 0);
+  auto out = CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 1);
+  (void)abstract::CheckDtypeSame(prim_name, out, dout);
+  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();
+  }
+  const std::set<TypePtr> valid_types = {kFloat16, kFloat32};
+  (void)CheckAndConvertUtils::CheckTensorTypeValid("input_x", x_type, valid_types, prim_name);
+  return x_type;
+}
+}  // namespace
+AbstractBasePtr ReLU6GradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
+                               const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
+  auto type = ReLU6GradInferType(primitive, input_args);
+  auto shape = ReLU6GradInferShape(primitive, input_args);
+  return abstract::MakeAbstract(shape, type);
+}
+REGISTER_PRIMITIVE_EVAL_IMPL(ReLU6Grad, prim::kPrimRelu6Grad, ReLU6GradInfer, nullptr, true);
+}  // namespace ops
+}  // namespace mindspore

mindspore/core/ops/grad/relu6_grad.h

@@ -0,0 +1,40 @@
+/**
+ * Copyright 2021 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.
+ */
+
+#ifndef MINDSPORE_CORE_OPS_RELU6_GRAD_H_
+#define MINDSPORE_CORE_OPS_RELU6_GRAD_H_
+#include <map>
+#include <vector>
+#include <string>
+#include <memory>
+#include "ops/primitive_c.h"
+#include "abstract/abstract_value.h"
+#include "utils/check_convert_utils.h"
+
+namespace mindspore {
+namespace ops {
+constexpr auto kNameReLU6Grad = "ReLU6Grad";
+class ReLU6Grad : public PrimitiveC {
+ public:
+  ReLU6Grad() : PrimitiveC(kNameReLU6Grad) {}
+  ~ReLU6Grad() = default;
+  MS_DECLARE_PARENT(ReLU6Grad, PrimitiveC);
+  void Init() {}
+};
+}  // namespace ops
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CORE_OPS_ABS_GRAD_H_

mindspore/python/mindspore/ops/_op_impl/tbe/__init__.py

@@ -122,7 +122,9 @@ from .relu_ds import _relu_ds_tbe
 from .relu_grad import _relu_grad_tbe
 from .relu_grad_ds import _relu_grad_ds_tbe
 from .relu6 import _relu6_tbe
+from .relu6_ds import _relu6_ds_tbe
 from .relu6_grad import _relu6_grad_tbe
+from .relu6_grad_ds import _relu6_grad_ds_tbe
 from .relu_v2 import _relu_v2_tbe
 from .relu_grad_v2 import _relu_grad_v2_tbe
 from .relu_v2_ds import _relu_v2_ds_tbe

mindspore/python/mindspore/ops/_op_impl/tbe/relu6_ds.py

@@ -0,0 +1,39 @@
+# Copyright 2021 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.
+# ============================================================================
+
+"""ReLU6 op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+relu6_ds_op_info = TBERegOp("ReLU6") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("relu6.so") \
+    .compute_cost(10) \
+    .kernel_name("relu6") \
+    .partial_flag(True) \
+    .dynamic_shape(True) \
+    .input(0, "x", False, "required", "all") \
+    .output(0, "y", False, "required", "all") \
+    .op_pattern("formatAgnostic") \
+    .dtype_format(DataType.F16_None, DataType.F16_None) \
+    .dtype_format(DataType.F32_None, DataType.F32_None) \
+    .dtype_format(DataType.I32_None, DataType.I32_None) \
+    .get_op_info()
+
+
+@op_info_register(relu6_ds_op_info)
+def _relu6_ds_tbe():
+    """Relu6 TBE register"""
+    return

mindspore/python/mindspore/ops/_op_impl/tbe/relu6_grad_ds.py

@@ -0,0 +1,44 @@
+# Copyright 2021 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.
+# ============================================================================
+
+"""ReLU6Grad op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+relu6_grad_ds_op_info = TBERegOp("ReLU6Grad") \
+    .fusion_type("OPAQUE") \
+    .async_flag(False) \
+    .binfile_name("relu6_grad.so") \
+    .compute_cost(10) \
+    .kernel_name("relu6_grad") \
+    .partial_flag(True) \
+    .dynamic_shape(True) \
+    .input(0, "gradients", False, "required", "all") \
+    .input(1, "features", False, "required", "all") \
+    .output(0, "backprops", False, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD) \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F16_FracNZ, DataType.F16_FracNZ, DataType.F16_FracNZ) \
+    .dtype_format(DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
+    .dtype_format(DataType.F32_FracNZ, DataType.F32_FracNZ, DataType.F32_FracNZ) \
+    .dtype_format(DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0) \
+    .get_op_info()
+
+
+@op_info_register(relu6_grad_ds_op_info)
+def _relu6_grad_ds_tbe():
+    """Relu6Grad TBE register"""
+    return

mindspore/python/mindspore/ops/operations/_grad_ops.py

@@ -1629,7 +1629,7 @@ class ReluGrad(Primitive):
         raise NotImplementedError
 
 
-class ReLU6Grad(PrimitiveWithInfer):
+class ReLU6Grad(Primitive):
     """Performs grad of ReLU6 operation."""
 
     @prim_attr_register
@@ -1639,15 +1639,6 @@ class ReLU6Grad(PrimitiveWithInfer):
     def __call__(self, y_grad, x):
         raise NotImplementedError
 
-    def infer_shape(self, y_grad_shape, x_shape):
-        return x_shape
-
-    def infer_dtype(self, y_grad_dtype, x_dtype):
-        valid_dtypes = (mstype.float16, mstype.float32)
-        validator.check_tensor_dtype_valid("y_grad", y_grad_dtype, valid_dtypes, self.name)
-        validator.check_tensor_dtype_valid("x", x_dtype, valid_dtypes, self.name)
-        return x_dtype
-
 
 class ReluGradV2(Primitive):
     """Performs grad of ReLUV2 operation."""