【NPU】add scale op for npu (#31499)

* add scale npu

* fix

* fix

paddle/fluid/operators/scale_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/npu_op_runner.h"
+#include "paddle/fluid/operators/scale_op.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename DeviceContext, typename T>
+class ScaleNPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<framework::Tensor>("X");
+    auto* out = ctx.Output<framework::Tensor>("Out");
+    auto scale = static_cast<float>(ctx.Attr<float>("scale"));
+    auto bias = static_cast<float>(ctx.Attr<float>("bias"));
+    auto bias_after_scale = ctx.Attr<bool>("bias_after_scale");
+    auto stream =
+        ctx.template device_context<paddle::platform::NPUDeviceContext>()
+            .stream();
+    float _power = 1.0;
+    if (bias_after_scale) {
+      out->mutable_data<T>(ctx.GetPlace());
+      auto runner =
+          NpuOpRunner("Power", {*x}, {*out},
+                      {{"power", _power}, {"scale", scale}, {"shift", bias}});
+
+      runner.Run(stream);
+    } else {
+      Tensor tmp_x(x->type());
+      tmp_x.Resize(x->dims());
+      tmp_x.mutable_data<T>(ctx.GetPlace());
+      auto runner_tmp = NpuOpRunner("Adds", {*x}, {tmp_x}, {{"value", bias}});
+      runner_tmp.Run(stream);
+
+      out->mutable_data<T>(ctx.GetPlace());
+      float _bias = 0.0;
+      auto runner =
+          NpuOpRunner("Power", {tmp_x}, {*out},
+                      {{"power", _power}, {"scale", scale}, {"shift", _bias}});
+      runner.Run(stream);
+    }
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_NPU_KERNEL(
+    scale, ops::ScaleNPUKernel<paddle::platform::NPUDeviceContext, float>,
+    ops::ScaleNPUKernel<paddle::platform::NPUDeviceContext,
+                        paddle::platform::float16>);

python/paddle/fluid/tests/unittests/npu/test_scale_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
+
+paddle.enable_static()
+SEED = 2021
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestScale(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "scale"
+        self.place = paddle.NPUPlace(0)
+        self.init_dtype()
+
+        self.inputs = {
+            'X': OpTest.np_dtype_to_fluid_dtype(
+                np.random.random((10, 10)).astype(self.dtype))
+        }
+        self.attrs = {'scale': -2.3, 'bias': 0, 'bias_after_scale': True}
+        self.outputs = {
+            'Out': self.inputs['X'] * self.dtype(self.attrs['scale'])
+        }
+
+    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 TestFP16Scale(TestScale):
+    def init_dtype(self):
+        self.dtype = np.float16
+
+
+class TestBiasAfterScale(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "scale"
+        self.place = paddle.NPUPlace(0)
+        self.init_dtype()
+
+        self.inputs = {
+            'X': OpTest.np_dtype_to_fluid_dtype(
+                np.random.random((10, 10)).astype(self.dtype))
+        }
+        self.attrs = {'scale': -2.3, 'bias': 0, 'bias_after_scale': False}
+        self.outputs = {
+            'Out': self.inputs['X'] * self.dtype(self.attrs['scale'])
+        }
+
+    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)
+
+
+if __name__ == '__main__':
+    unittest.main()