!25302 [feat] [assistant] [I48OD7] [I48O9K] add dynamic shape for Asinh and AsinhGrad operator

Merge pull request !25302 from 路雄博/asinh

mindspore/core/ops/asinh.cc

@@ -0,0 +1,62 @@
+/**
+ * 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 <algorithm>
+#include <map>
+#include <memory>
+#include <set>
+#include <string>
+#include <vector>
+
+#include "ops/asinh.h"
+#include "ops/op_utils.h"
+#include "utils/check_convert_utils.h"
+#include "abstract/primitive_infer_map.h"
+#include "abstract/param_validator.h"
+
+namespace mindspore {
+namespace ops {
+namespace {
+abstract::ShapePtr AsinhInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
+  auto prim_name = primitive->name();
+  (void)CheckAndConvertUtils::CheckArgs<abstract::AbstractTensor>(prim_name, input_args, 0);
+  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 AsinhInferType(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
+  auto prim_name = primitive->name();
+  MS_EXCEPTION_IF_NULL(input_args[0]);
+  auto x_type = input_args[0]->BuildType();
+  (void)CheckAndConvertUtils::CheckTensorTypeValid("input_x", x_type, common_valid_types, prim_name);
+  return x_type;
+}
+}  // namespace
+
+AbstractBasePtr AsinhInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
+                           const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
+  const int64_t input_num = 1;
+  CheckAndConvertUtils::CheckInputArgs(input_args, kEqual, input_num, primitive->name());
+  auto infer_type = AsinhInferType(primitive, input_args);
+  auto infer_shape = AsinhInferShape(primitive, input_args);
+  return abstract::MakeAbstract(infer_shape, infer_type);
+}
+REGISTER_PRIMITIVE_EVAL_IMPL(Asinh, prim::kPrimAsinh, AsinhInfer, nullptr, true);
+}  // namespace ops
+}  // namespace mindspore

mindspore/core/ops/asinh.h

@@ -0,0 +1,42 @@
+/**
+ * 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_ASINH_H_
+#define MINDSPORE_CORE_OPS_ASINH_H_
+
+#include <map>
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "ops/primitive_c.h"
+#include "abstract/abstract_value.h"
+#include "utils/check_convert_utils.h"
+
+namespace mindspore {
+namespace ops {
+constexpr auto kNameAsinh = "Asinh";
+class Asinh : public PrimitiveC {
+ public:
+  Asinh() : PrimitiveC(kNameAsinh) { InitIOName({"x"}, {"output"}); }
+  ~Asinh() = default;
+  MS_DECLARE_PARENT(Asinh, PrimitiveC);
+  void Init() {}
+};
+}  // namespace ops
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CORE_OPS_ASINH_H_

mindspore/core/ops/grad/asinh_grad.cc

@@ -0,0 +1,65 @@
+/**
+ * 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/asinh_grad.h"
+#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 {
+namespace {
+abstract::ShapePtr AsinhGradInferShape(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 AsinhGradInferType(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
+  const std::set<TypePtr> valid_types = {kFloat16, kFloat32};
+  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);
+  MS_EXCEPTION_IF_NULL(input_args[0]);
+  auto x_type = input_args[0]->BuildType();
+  MS_EXCEPTION_IF_NULL(x_type);
+  (void)CheckAndConvertUtils::CheckTensorTypeValid("input_x", x_type, valid_types, prim_name);
+  return x_type;
+}
+}  // namespace
+
+AbstractBasePtr AsinhGradInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
+                               const std::vector<AbstractBasePtr> &input_args) {
+  auto type = AsinhGradInferType(primitive, input_args);
+  auto shape = AsinhGradInferShape(primitive, input_args);
+  return abstract::MakeAbstract(shape, type);
+}
+
+REGISTER_PRIMITIVE_EVAL_IMPL(AsinhGrad, prim::kPrimAsinhGrad, AsinhGradInfer, nullptr, true);
+}  // namespace ops
+}  // namespace mindspore

mindspore/core/ops/grad/asinh_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_ASINH_GRAD_H_
+#define MINDSPORE_CORE_OPS_ASINH_GRAD_H_
+#include <map>
+#include <vector>
+#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"
+
+namespace mindspore {
+namespace ops {
+constexpr auto kNameAsinhGrad = "AsinhGrad";
+class AsinhGrad : public PrimitiveC {
+ public:
+  AsinhGrad() : PrimitiveC(kNameAsinhGrad) { InitIOName({"x"}, {"output"}); }
+  ~AsinhGrad() = default;
+  MS_DECLARE_PARENT(AsinhGrad, PrimitiveC);
+};
+}  // namespace ops
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CORE_OPS_ASINH_GRAD_H_

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

@@ -410,7 +410,9 @@ from .asin_ds import _asin_ds_tbe
 from .asin_grad import _asin_grad_tbe
 from .asin_grad_ds import _asin_grad_ds_tbe
 from .asinh import _asinh_tbe
+from .asinh_ds import _asinh_ds_tbe
 from .asinh_grad import _asinh_grad_tbe
+from .asinh_grad_ds import _asinh_grad_ds_tbe
 from .div_no_nan import _div_no_nan_tbe
 from .div_no_nan_ds import _div_no_nan_ds_tbe
 from .atan import _atan_tbe

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

@@ -0,0 +1,38 @@
+# 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.
+# ============================================================================
+
+"""Asinh op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+asinh_ds_op_info = TBERegOp("Asinh") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("asinh.so") \
+    .compute_cost(10) \
+    .kernel_name("asinh") \
+    .partial_flag(True) \
+    .dynamic_shape(True) \
+    .op_pattern("formatAgnostic") \
+    .input(0, "x", False, "required", "all") \
+    .output(0, "y", False, "required", "all") \
+    .dtype_format(DataType.F16_None, DataType.F16_None) \
+    .dtype_format(DataType.F32_None, DataType.F32_None) \
+    .get_op_info()
+
+
+@op_info_register(asinh_ds_op_info)
+def _asinh_ds_tbe():
+    """Asinh TBE register"""
+    return

mindspore/python/mindspore/ops/_op_impl/tbe/asinh_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.
+# ============================================================================
+
+"""AsinhGrad op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+asinh_grad_op_info = TBERegOp("AsinhGrad") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("asinh_grad.so") \
+    .compute_cost(10) \
+    .kernel_name("asinh_grad") \
+    .partial_flag(True) \
+    .dynamic_shape(True) \
+    .input(0, "y", False, "required", "all") \
+    .input(1, "dy", False, "required", "all") \
+    .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(asinh_grad_op_info)
+def _asinh_grad_ds_tbe():
+    """AsinhGrad TBE register"""
+    return

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

@@ -70,15 +70,6 @@ class AsinhGrad(PrimitiveWithInfer):
     def __init__(self):
         """Initialize AsinhGrad"""
 
-    def infer_shape(self, x, dout):
-        validator.check("x shape", x, "dout shape", dout, Rel.EQ, self.name)
-        return x
-
-    def infer_dtype(self, x, dout):
-        args = {"x": x, "dout": dout}
-        validator.check_tensors_dtypes_same_and_valid(args, mstype.number_type, self.name)
-        return x
-
 
 class ReciprocalGrad(Primitive):
     """Performs grad of Reciprocal operation."""

mindspore/python/mindspore/ops/operations/math_ops.py

@@ -3321,7 +3321,7 @@ class Cosh(Primitive):
         """Initialize Cosh"""
 
 
-class Asinh(PrimitiveWithInfer):
+class Asinh(Primitive):
     r"""
     Computes inverse hyperbolic sine of the input element-wise.
 
@@ -3355,13 +3355,6 @@ class Asinh(PrimitiveWithInfer):
     def __init__(self):
         """Initialize Asinh"""
 
-    def infer_shape(self, x_shape):
-        return x_shape
-
-    def infer_dtype(self, x_dtype):
-        validator.check_tensor_dtype_valid('x', x_dtype, mstype.number_type, self.name)
-        return x_dtype
-
 
 class Sinh(Primitive):
     r"""