[feat] [assistant] [I48O9Q] cosh with dynamic infer shape

mindspore/core/ops/cosh.cc

@@ -0,0 +1,59 @@
+/**
+ * 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/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"
+
+namespace mindspore {
+namespace ops {
+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();
+  MS_EXCEPTION_IF_NULL(x);
+  auto shape_element = x->cast<abstract::ShapePtr>();
+  MS_EXCEPTION_IF_NULL(shape_element);
+  return shape_element;
+}
+
+TypePtr CoshInferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
+  auto x_dtype = input_args[0]->BuildType();
+  (void)CheckAndConvertUtils::CheckTensorTypeValid("x", x_dtype, common_valid_types_with_complex, 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());
+  auto infer_type = CoshInferType(primitive, input_args);
+  auto infer_shape = CoshInferShape(primitive, input_args);
+  return abstract::MakeAbstract(infer_shape, infer_type);
+}
+REGISTER_PRIMITIVE_EVAL_IMPL(Cosh, prim::kPrimCosh, CoshInfer, nullptr, true);
+}  // namespace ops
+}  // namespace mindspore

mindspore/core/ops/cosh.h

@@ -0,0 +1,41 @@
+/**
+ * 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_COSH_H_
+#define MINDSPORE_CORE_OPS_COSH_H_
+#include <vector>
+#include <memory>
+#include "ops/primitive_c.h"
+#include "abstract/abstract_value.h"
+#include "utils/check_convert_utils.h"
+
+namespace mindspore {
+namespace ops {
+constexpr auto kNameCosh = "Cosh";
+class Cosh : public PrimitiveC {
+ public:
+  Cosh() : PrimitiveC(kNameCosh) { InitIOName({"x"}, {"output"}); }
+  ~Cosh() = default;
+  MS_DECLARE_PARENT(Cosh, PrimitiveC);
+  void Init() {}
+};
+AbstractBasePtr CoshInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
+                          const std::vector<AbstractBasePtr> &input_args);
+using kPrimCoshPtr = std::shared_ptr<Cosh>;
+}  // namespace ops
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CORE_OPS_COSH_H_

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

@@ -393,6 +393,7 @@ from .atan_grad_ds import _atan_grad_ds_tbe
 from .atanh import _atanh_tbe
 from .atanh_ds import _atanh_ds_tbe
 from .cosh import _cosh_tbe
+from .cosh_ds import _cosh_ds_tbe
 from .sinh import _sinh_tbe
 from .sinh_ds import _sinh_ds_tbe
 from .inv import _inv_tbe

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

@@ -0,0 +1,38 @@
+# 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, TBERegOp, DataType
+
+cosh_op_info = TBERegOp("Cosh") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("cosh.so") \
+    .compute_cost(10) \
+    .kernel_name("cosh") \
+    .partial_flag(True) \
+    .dynamic_shape(True) \
+    .op_pattern("formatAgnostic") \
+    .input(0, "x", False, "required", "all") \
+    .output(0, "y", True, "required", "all") \
+    .dtype_format(DataType.F16_None, DataType.F16_None) \
+    .dtype_format(DataType.F32_None, DataType.F32_None) \
+    .get_op_info()
+
+
+@op_info_register(cosh_op_info)
+def _cosh_ds_tbe():
+    """Cosh TBE register"""
+    return

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

@@ -3231,8 +3231,7 @@ class Acosh(Primitive):
         """Initialize Acosh"""
         self.init_prim_io_names(inputs=['x'], outputs='output')
 
-
-class Cosh(PrimitiveWithInfer):
+class Cosh(Primitive):
     r"""
     Computes hyperbolic cosine of input element-wise.
 
@@ -3265,13 +3264,6 @@ class Cosh(PrimitiveWithInfer):
     def __init__(self):
         """Initialize Cosh"""
 
-    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 Asinh(PrimitiveWithInfer):
     r"""