!26841 [feat] [assistant] [I48O70] [I48O4W]Add Sinh and Cosh operators

Merge pull request !26841 from 桂宁馨/Sinh_Cosh

mindspore/ccsrc/plugin/device/cpu/kernel/arithmetic_self_cpu_kernel.cc

@@ -193,6 +193,16 @@ void ComplexSin(ArithmeticSelfCpuKernelMod *content, const T *in, T *out, size_t
   ParallelLaunchAutoSearch(task, size, content, &content->parallel_search_info_);
 }
 
+template <typename T>
+void ComplexSinh(ArithmeticSelfCpuKernelMod *content, const T *in, T *out, size_t size) {
+  auto task = [&in, &out](size_t start, size_t end) {
+    for (size_t i = start; i < end; i++) {
+      out[i] = static_cast<T>(sinh(in[i]));
+    }
+  };
+  ParallelLaunchAutoSearch(task, size, content, &content->parallel_search_info_);
+}
+
 template <typename T>
 void ComplexCos(ArithmeticSelfCpuKernelMod *content, const T *in, T *out, size_t size) {
   auto task = [&in, &out](size_t start, size_t end) {
@@ -203,6 +213,16 @@ void ComplexCos(ArithmeticSelfCpuKernelMod *content, const T *in, T *out, size_t
   ParallelLaunchAutoSearch(task, size, content, &content->parallel_search_info_);
 }
 
+template <typename T>
+void ComplexCosh(ArithmeticSelfCpuKernelMod *content, const T *in, T *out, size_t size) {
+  auto task = [&in, &out](size_t start, size_t end) {
+    for (size_t i = start; i < end; i++) {
+      out[i] = static_cast<T>(cosh(in[i]));
+    }
+  };
+  ParallelLaunchAutoSearch(task, size, content, &content->parallel_search_info_);
+}
+
 template <typename T>
 void Tan(ArithmeticSelfCpuKernelMod *content, const T *in, T *out, size_t size) {
   auto task = [&in, &out](size_t start, size_t end) {
@@ -399,6 +419,7 @@ void ArithmeticSelfCpuKernelMod::LaunchKernelComplex(const std::vector<AddressPt
                                   std::function<void(ArithmeticSelfCpuKernelMod *, const T *, T *, size_t)>>
     arithmeticSelfFuncMap{{prim::kPrimSquare->name(), Square<T>},      {prim::kPrimAcosh->name(), ComplexAcosh<T>},
                           {prim::kPrimAsinh->name(), ComplexAsinh<T>}, {prim::kPrimNeg->name(), Neg<T>},
+                          {prim::kPrimSinh->name(), ComplexSinh<T>},   {prim::kPrimCosh->name(), ComplexCosh<T>},
                           {prim::kPrimSin->name(), ComplexSin<T>},     {prim::kPrimCos->name(), ComplexCos<T>}};
   const auto func_pair = arithmeticSelfFuncMap.find(kernel_name_);
   if (arithmeticSelfFuncMap.find(kernel_name_) == arithmeticSelfFuncMap.end()) {

mindspore/ccsrc/plugin/device/cpu/kernel/arithmetic_self_cpu_kernel.h

@@ -151,6 +151,14 @@ MS_REG_CPU_KERNEL(Cosh, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputA
                   ArithmeticSelfCpuKernelMod);
 MS_REG_CPU_KERNEL(Cosh, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64),
                   ArithmeticSelfCpuKernelMod);
+MS_REG_CPU_KERNEL(Sinh, KernelAttr().AddInputAttr(kNumberTypeComplex64).AddOutputAttr(kNumberTypeComplex64),
+                  ArithmeticSelfCpuKernelMod);
+MS_REG_CPU_KERNEL(Cosh, KernelAttr().AddInputAttr(kNumberTypeComplex64).AddOutputAttr(kNumberTypeComplex64),
+                  ArithmeticSelfCpuKernelMod);
+MS_REG_CPU_KERNEL(Sinh, KernelAttr().AddInputAttr(kNumberTypeComplex128).AddOutputAttr(kNumberTypeComplex128),
+                  ArithmeticSelfCpuKernelMod);
+MS_REG_CPU_KERNEL(Cosh, KernelAttr().AddInputAttr(kNumberTypeComplex128).AddOutputAttr(kNumberTypeComplex128),
+                  ArithmeticSelfCpuKernelMod);
 MS_REG_CPU_KERNEL(Asinh, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
                   ArithmeticSelfCpuKernelMod);
 MS_REG_CPU_KERNEL(Asinh, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64),

mindspore/core/ops/cosh.cc

@@ -13,16 +13,11 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-
 #include "ops/cosh.h"
-#include <string>
-#include <algorithm>
-#include <memory>
+
 #include <set>
-#include <vector>
-#include "ops/op_utils.h"
-#include "utils/check_convert_utils.h"
-#include "abstract/primitive_infer_map.h"
+#include <map>
+#include <string>
 
 namespace mindspore {
 namespace ops {
@@ -30,9 +25,12 @@ namespace {
 abstract::ShapePtr CoshInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
   auto prim_name = primitive->name();
-  (void)CheckAndConvertUtils::CheckInteger("input numbers", SizeToLong(input_args.size()), kGreaterEqual, 1, prim_name);
-  (void)CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 0);
   auto x = input_args[0]->BuildShape();
+  const int64_t max_dim = 8;
+  auto in_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape())[kShape];
+  (void)CheckAndConvertUtils::CheckInteger("The dimension of Cosh input", SizeToLong(in_shape.size()), kLessThan,
+                                           max_dim, prim_name);
+  (void)CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 0);
   MS_EXCEPTION_IF_NULL(x);
   auto shape_element = x->cast<abstract::ShapePtr>();
   MS_EXCEPTION_IF_NULL(shape_element);
@@ -40,16 +38,18 @@ abstract::ShapePtr CoshInferShape(const PrimitivePtr &primitive, const std::vect
 }
 
 TypePtr CoshInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
+  const std::set<TypePtr> valid_types = {kFloat16, kFloat32, kFloat64, kComplex64, kComplex128};
   auto x_dtype = input_args[0]->BuildType();
-  (void)CheckAndConvertUtils::CheckTensorTypeValid("x", x_dtype, common_valid_types_with_complex, prim->name());
+  (void)CheckAndConvertUtils::CheckTensorTypeValid("x", x_dtype, valid_types, prim->name());
   return x_dtype;
 }
 }  // namespace
+
 AbstractBasePtr CoshInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                           const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
-  const int64_t kInputNum = 1;
-  CheckAndConvertUtils::CheckInputArgs(input_args, kGreaterEqual, kInputNum, primitive->name());
+  const int64_t input_num = 1;
+  CheckAndConvertUtils::CheckInputArgs(input_args, kEqual, input_num, primitive->name());
   auto infer_type = CoshInferType(primitive, input_args);
   auto infer_shape = CoshInferShape(primitive, input_args);
   return abstract::MakeAbstract(infer_shape, infer_type);

mindspore/core/ops/sinh.cc

@@ -13,16 +13,11 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+#include "ops/sinh.h"
 
-#include <string>
-#include <algorithm>
-#include <memory>
 #include <set>
-#include <vector>
-#include "ops/sinh.h"
-#include "ops/op_utils.h"
-#include "utils/check_convert_utils.h"
-#include "abstract/primitive_infer_map.h"
+#include <map>
+#include <string>
 
 namespace mindspore {
 namespace ops {
@@ -30,9 +25,12 @@ namespace {
 abstract::ShapePtr SinhInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
   auto prim_name = primitive->name();
-  (void)CheckAndConvertUtils::CheckInteger("input numbers", SizeToLong(input_args.size()), kGreaterEqual, 1, prim_name);
-  (void)CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 0);
   auto x = input_args[0]->BuildShape();
+  const int64_t max_dim = 8;
+  auto in_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape())[kShape];
+  (void)CheckAndConvertUtils::CheckInteger("The dimension of Sinh input", SizeToLong(in_shape.size()), kLessThan,
+                                           max_dim, prim_name);
+  (void)CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 0);
   MS_EXCEPTION_IF_NULL(x);
   auto shape_element = x->cast<abstract::ShapePtr>();
   MS_EXCEPTION_IF_NULL(shape_element);
@@ -40,8 +38,9 @@ abstract::ShapePtr SinhInferShape(const PrimitivePtr &primitive, const std::vect
 }
 
 TypePtr SinhInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
+  const std::set<TypePtr> valid_types = {kFloat16, kFloat32, kFloat64, kComplex64, kComplex128};
   auto x_dtype = input_args[0]->BuildType();
-  (void)CheckAndConvertUtils::CheckTensorTypeValid("x", x_dtype, common_valid_types_with_complex, prim->name());
+  (void)CheckAndConvertUtils::CheckTensorTypeValid("x", x_dtype, valid_types, prim->name());
   return x_dtype;
 }
 }  // namespace
@@ -49,8 +48,8 @@ TypePtr SinhInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePt
 AbstractBasePtr SinhInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                           const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
-  const int64_t kInputNum = 1;
-  CheckAndConvertUtils::CheckInputArgs(input_args, kGreaterEqual, kInputNum, primitive->name());
+  const int64_t input_num = 1;
+  CheckAndConvertUtils::CheckInputArgs(input_args, kEqual, input_num, primitive->name());
   auto infer_type = SinhInferType(primitive, input_args);
   auto infer_shape = SinhInferShape(primitive, input_args);
   return abstract::MakeAbstract(infer_shape, infer_type);

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

@@ -48,6 +48,8 @@ from .reshape import _reshape_aicpu
 from .flatten import _flatten_aicpu
 from .sin import _sin_aicpu
 from .cos import _cos_aicpu
+from .sinh import _sinh_aicpu
+from .cosh import _cosh_aicpu
 from .squeeze import _squeeze_aicpu
 from .acos import _acos_aicpu
 from .acos_grad import _acos_grad_aicpu

mindspore/python/mindspore/ops/_op_impl/aicpu/cosh.py

@@ -0,0 +1,34 @@
+# 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.
+# ============================================================================
+
+"""Cosh op"""
+from mindspore.ops.op_info_register import op_info_register, AiCPURegOp, DataType
+
+cosh_op_info = AiCPURegOp("Cosh") \
+    .fusion_type("ELEMWISE") \
+    .input(0, "x", "required") \
+    .output(0, "y", "required") \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default) \
+    .dtype_format(DataType.F64_Default, DataType.F64_Default) \
+    .dtype_format(DataType.C64_Default, DataType.C64_Default) \
+    .dtype_format(DataType.C128_Default, DataType.C128_Default) \
+    .get_op_info()
+
+
+@op_info_register(cosh_op_info)
+def _cosh_aicpu():
+    """Cosh AiCPU register"""
+    return

mindspore/python/mindspore/ops/_op_impl/aicpu/sinh.py

@@ -0,0 +1,34 @@
+# 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.
+# ============================================================================
+
+"""Sinh op"""
+from mindspore.ops.op_info_register import op_info_register, AiCPURegOp, DataType
+
+sinh_op_info = AiCPURegOp("Sinh") \
+    .fusion_type("ELEMWISE") \
+    .input(0, "x", "required") \
+    .output(0, "y", "required") \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default) \
+    .dtype_format(DataType.F64_Default, DataType.F64_Default) \
+    .dtype_format(DataType.C64_Default, DataType.C64_Default) \
+    .dtype_format(DataType.C128_Default, DataType.C128_Default) \
+    .get_op_info()
+
+
+@op_info_register(sinh_op_info)
+def _sinh_aicpu():
+    """Sinh AiCPU register"""
+    return