Support npu op fill_any_like (#34518)

* Support npu kernel for fill_any_like op

* modify the description of exception

* remove useless template element

* remove useless decorator

* fix the code format error

paddle/fluid/operators/fill_any_like_op.h

@@ -45,15 +45,18 @@ class FillAnyLikeKernel : public framework::OpKernel<T> {
          static_cast<CommonType>(std::numeric_limits<T>::lowest())) &&
             (common_type_value <=
              static_cast<CommonType>(std::numeric_limits<T>::max())),
-        true, platform::errors::InvalidArgument(
-                  "filled value is out of range for"
-                  " targeted type in fill_any_like, your kernel type is %s"
-                  ", please check value you set.",
-                  typeid(T).name()));
+        true,
+        platform::errors::InvalidArgument(
+            "The filled value is out of range for target type, "
+            "current kernel type is %s, the range should between %f "
+            "and %f, but now value is %f.",
+            typeid(T).name(),
+            static_cast<CommonType>(std::numeric_limits<T>::lowest()),
+            static_cast<CommonType>(std::numeric_limits<T>::max()), value));
+
     PADDLE_ENFORCE_EQ(
         std::isnan(value), false,
-        platform::errors::InvalidArgument("filled value should not be NaN,"
-                                          " but received NaN"));
+        platform::errors::InvalidArgument("The filled value is NaN."));
 
     math::SetConstant<DeviceContext, T> setter;
     setter(context.template device_context<DeviceContext>(), out,

paddle/fluid/operators/fill_any_like_op_npu.cc

+/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+
+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 "paddle/fluid/operators/fill_any_like_op.h"
+#include "paddle/fluid/operators/npu_op_runner.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class FillAnyLikeNPUKernel : public framework::OpKernel<T> {
+ public:
+  using CommonType = typename std::common_type<
+      float,
+      typename std::conditional<std::is_same<T, platform::float16>::value,
+                                float, T>::type>::type;
+
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto data_type = static_cast<framework::proto::VarType::Type>(
+        context.Attr<int>("dtype"));
+    auto* out = context.Output<framework::Tensor>("Out");
+    out->mutable_data<T>(context.GetPlace());
+
+    float value = context.Attr<float>("value");
+
+    auto common_type_value = static_cast<CommonType>(value);
+
+    PADDLE_ENFORCE_EQ(
+        (common_type_value >=
+         static_cast<CommonType>(std::numeric_limits<T>::lowest())) &&
+            (common_type_value <=
+             static_cast<CommonType>(std::numeric_limits<T>::max())),
+        true,
+        platform::errors::InvalidArgument(
+            "The filled value is out of range for target type, "
+            "current kernel type is %s, the range should between %f "
+            "and %f, but now value is %f.",
+            typeid(T).name(),
+            static_cast<CommonType>(std::numeric_limits<T>::lowest()),
+            static_cast<CommonType>(std::numeric_limits<T>::max()), value));
+
+    PADDLE_ENFORCE_EQ(
+        std::isnan(value), false,
+        platform::errors::InvalidArgument("The filled value is NaN."));
+
+    Tensor tensor_tmp(data_type);
+    tensor_tmp.mutable_data<T>({1}, context.GetPlace());
+    FillNpuTensorWithConstant<T>(&tensor_tmp, static_cast<T>(value));
+
+    auto stream =
+        context.template device_context<paddle::platform::NPUDeviceContext>()
+            .stream();
+
+    auto shape = out->dims();
+    const auto& runner = NpuOpRunner("FillD", {tensor_tmp}, {*out},
+                                     {{"dims", framework::vectorize(shape)}});
+    runner.Run(stream);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_NPU_KERNEL(fill_any_like, ops::FillAnyLikeNPUKernel<int>,
+                       ops::FillAnyLikeNPUKernel<float>,
+                       ops::FillAnyLikeNPUKernel<paddle::platform::float16>);

python/paddle/fluid/tests/unittests/npu/test_fill_any_like_op_npu.py

+#  Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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.
+
+from __future__ import print_function
+
+import numpy as np
+import unittest
+import sys
+sys.path.append("..")
+from op_test import OpTest
+import paddle
+import paddle.fluid as fluid
+from paddle.fluid import core
+
+paddle.enable_static()
+
+
+class TestFillAnyLikeNPUOp(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.place = paddle.NPUPlace(0)
+        self.op_type = "fill_any_like"
+        self.dtype = np.float32
+        self.shape = [2, 3, 4, 5]
+        self.value = 0.0
+
+        self.init()
+
+        self.inputs = {'X': np.random.random(self.shape).astype(self.dtype)}
+        self.attrs = {'value': self.value}
+        self.outputs = {'Out': np.full(self.shape, self.value, self.dtype)}
+
+    def init(self):
+        pass
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+
+class TestFillAnyLikeNPUOpInt32(TestFillAnyLikeNPUOp):
+    def init(self):
+        self.dtype = np.int32
+        self.value = -1
+
+
+class TestFillAnyLikeNPUOpFloat32(TestFillAnyLikeNPUOp):
+    def init(self):
+        self.dtype = np.float32
+        self.value = 0.09
+
+
+class TestFillAnyLikeNPUOpFloat16(TestFillAnyLikeNPUOp):
+    def init(self):
+        self.dtype = np.float16
+        self.value = 0.05
+
+
+class TestFillAnyLikeNPUOpValue1(TestFillAnyLikeNPUOp):
+    def init(self):
+        self.value = 1.0
+
+
+class TestFillAnyLikeNPUOpValue2(TestFillAnyLikeNPUOp):
+    def init(self):
+        self.value = 1e-9
+
+
+class TestFillAnyLikeNPUOpShape(TestFillAnyLikeNPUOp):
+    def init(self):
+        self.shape = [12, 10]
+
+
+if __name__ == "__main__":
+    unittest.main()