【NPU】support npu kernel for fill_constant op (#31521)

* add fill_constant npu

* add fill_constant npu

* fix

paddle/fluid/operators/fill_constant_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 <memory>
+#include <string>
+
+#include "paddle/fluid/operators/fill_constant_op.h"
+#include "paddle/fluid/operators/npu_op_runner.h"
+#include "paddle/fluid/operators/utils.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename DeviceContext, typename T>
+class FillConstantNPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto data_type =
+        static_cast<framework::proto::VarType::Type>(ctx.Attr<int>("dtype"));
+    auto str_value = ctx.Attr<std::string>("str_value");
+    auto float_value = ctx.Attr<float>("value");
+
+    auto* out_var = ctx.Output<framework::Tensor>("Out");
+    auto place = ctx.GetPlace();
+    auto stream =
+        ctx.template device_context<paddle::platform::NPUDeviceContext>()
+            .stream();
+
+    T value;
+    if (str_value.empty()) {
+      value = static_cast<T>(float_value);
+    } else {
+      // handle NaN/Inf first, which cannot be read from stream.
+      if (str_value == "inf") {
+        value = static_cast<T>(std::numeric_limits<double>::infinity());
+      } else if (str_value == "-inf") {
+        value = static_cast<T>(-std::numeric_limits<double>::infinity());
+      } else if (str_value == "nan") {
+        value = static_cast<T>(std::numeric_limits<double>::quiet_NaN());
+      } else {
+        std::stringstream convert_stream(str_value);
+        if (std::is_same<int64_t, T>::value) {
+          int64_t tmp_value;
+          convert_stream >> tmp_value;
+          value = static_cast<T>(tmp_value);
+        } else {
+          double tmp_value;
+          convert_stream >> tmp_value;
+          value = static_cast<T>(tmp_value);
+        }
+      }
+    }
+    auto shape = GetShape(ctx);
+
+    Tensor tensor_tmp(data_type);
+    tensor_tmp.mutable_data<T>({1}, ctx.GetPlace());
+    TensorFromVector(std::vector<T>{value}, ctx.device_context(), &tensor_tmp);
+
+    out_var->mutable_data<T>(shape, place);
+    auto runner = NpuOpRunner("FillD", {tensor_tmp}, {*out_var},
+                              {{"dims", framework::vectorize(shape)}});
+    runner.Run(stream);
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_NPU_KERNEL(
+    fill_constant,
+    ops::FillConstantNPUKernel<paddle::platform::NPUDeviceContext, float>,
+    ops::FillConstantNPUKernel<paddle::platform::NPUDeviceContext, bool>,
+    ops::FillConstantNPUKernel<paddle::platform::NPUDeviceContext, int>,
+    ops::FillConstantNPUKernel<paddle::platform::NPUDeviceContext,
+                               paddle::platform::float16>);

python/paddle/fluid/tests/unittests/npu/test_fill_constant_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()
+SEED = 2021
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestFillConstant(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.place = paddle.NPUPlace(0)
+        self.op_type = "fill_constant"
+        self.init_dtype()
+
+        self.inputs = {}
+        self.attrs = {'shape': [123, 92], 'value': 3.8}
+        self.outputs = {'Out': np.full((123, 92), 3.8)}
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def init_dtype(self):
+        self.dtype = np.float32
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, check_dygraph=False)
+
+
+class TestFillConstantInt(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.place = paddle.NPUPlace(0)
+        self.op_type = "fill_constant"
+
+        self.inputs = {}
+        self.attrs = {
+            'shape': [123, 92],
+            'value': 1,
+            'dtype': core.VarDesc.VarType.INT32
+        }
+        self.outputs = {'Out': np.full((123, 92), 1).astype(self.dtype)}
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def init_dtype(self):
+        self.dtype = np.int32
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, check_dygraph=False)
+
+
+class TestFillConstantFP16(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.place = paddle.NPUPlace(0)
+        self.op_type = "fill_constant"
+
+        self.inputs = {}
+        self.attrs = {
+            'shape': [123, 92],
+            'value': 1.0,
+            'dtype': core.VarDesc.VarType.FP16
+        }
+        self.outputs = {'Out': np.full((123, 92), 1.0).astype(self.dtype)}
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def init_dtype(self):
+        self.dtype = np.float16
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, check_dygraph=False, atol=1e-3)
+
+
+if __name__ == '__main__':
+    unittest.main()