[NPU] add Increment op (#31563)

* add increment

* fix

* update test increment op inplace

* update increment op

* increment b = 2
Co-authored-by: Noyjxer <1728722986@qq.com>

paddle/fluid/operators/increment_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/increment_op.h"
+#include "paddle/fluid/platform/float16.h"
+#include "paddle/fluid/operators/npu_op_runner.h"
+
+namespace paddle {
+namespace framework {
+class OpDesc;
+class Variable;
+}  // namespace framework
+namespace imperative {
+class OpBase;
+}  // namespace imperative
+}  // namespace paddle
+
+namespace paddle {
+namespace operators {
+
+
+template <typename DeviceContext, typename T>
+class IncrementalNPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* x_tensor = context.Input<framework::Tensor>("X");
+    auto* out_tensor = context.Output<framework::Tensor>("Out");
+    float step = context.Attr<float>("step");
+    out_tensor->mutable_data<T>(context.GetPlace());
+
+    Tensor step_tensor(x_tensor->type());
+    std::vector<T> step_vec;
+    step_vec.push_back(static_cast<T>(step));
+    framework::TensorFromVector(
+                     step_vec,
+                     context.device_context(),
+                     &step_tensor);
+
+    auto runner = NpuOpRunner("Add",
+                              {*x_tensor, step_tensor},
+                              {*out_tensor},
+                              {});
+
+    auto stream =
+      context.template device_context<paddle::platform::NPUDeviceContext>()
+                .stream();
+    runner.Run(stream);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+
+namespace plat = paddle::platform;
+namespace ops = paddle::operators;
+
+REGISTER_OP_NPU_KERNEL(
+    increment,
+    ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, float>,
+    ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, double>,
+    ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, int>,
+    ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, int64_t>,
+    ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, plat::float16>)
+

paddle/fluid/operators/increment_op_npu_test.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. */
+
+#ifndef _WIN32
+#include <unistd.h>
+#endif
+
+#include <string>
+#include <thread>  // NOLINT
+#include <vector>
+
+#include "gtest/gtest.h"
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/operator.h"
+#include "paddle/fluid/framework/program_desc.h"
+#include "paddle/fluid/operators/dropout_op.h"
+#include "paddle/fluid/operators/math/math_function.h"
+#include "paddle/fluid/string/printf.h"
+
+namespace f = paddle::framework;
+namespace p = paddle::platform;
+namespace m = paddle::operators::math;
+
+USE_OP(increment);
+USE_OP_DEVICE_KERNEL(increment, NPU);
+
+template <typename T>
+void Compare(f::Scope* scope, const p::DeviceContext& ctx,
+             std::string op_type) {
+  // init
+  auto x = scope->Var("X");
+  auto tensor_x = x->GetMutable<f::LoDTensor>();
+
+  std::vector<T> init;
+  init.push_back(static_cast<T>(1.0));
+
+  TensorFromVector(init, ctx, tensor_x);
+  tensor_x->Resize({1});
+
+  ctx.Wait();
+
+  auto place = ctx.GetPlace();
+  auto out = scope->Var("Out");
+  auto tensor_out = out->GetMutable<f::LoDTensor>();
+
+  f::AttributeMap attr_input = { {"step", static_cast<float>(2.0)} };
+  auto op = f::OpRegistry::CreateOp("increment", {{"X", {"X"}}},
+                                                 {{"Out", {"Out"}}},
+                                                 attr_input);
+
+  op->Run(*scope, place);
+
+  std::vector<T> out_vec;
+  TensorToVector(*tensor_out, ctx, &out_vec);
+
+  ctx.Wait();
+
+  EXPECT_EQ((uint32_t)out_vec.size(), (uint32_t)1);
+  EXPECT_EQ(out_vec[0], static_cast<T>(3.0));
+}
+
+
+TEST(increment, NPU_fp32) {
+    f::Scope scope;
+    p::NPUDeviceContext ctx(p::NPUPlace(0));
+    Compare<float>(&scope, ctx, "increment");
+}
+
+TEST(increment, NPU_fp64) {
+    f::Scope scope;
+    p::NPUDeviceContext ctx(p::NPUPlace(0));
+    Compare<float>(&scope, ctx, "increment");
+}
+

python/paddle/fluid/tests/unittests/npu/test_increment_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
+
+NPUPlace = 5
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestIncrement(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.place = paddle.NPUPlace(NPUPlace)
+        self.op_type = "increment"
+        self.init_dtype()
+
+        self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(np.array([1]).astype(self.dtype)), }
+
+        self.attrs = {"Step": 1}
+        self.outputs = {'Out': np.array([2])}
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+        self.__class__.no_need_check_grad = True
+
+    def init_dtype(self):
+        self.dtype = np.int64
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, check_dygraph=False)
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestIncrementFP16(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.place = paddle.NPUPlace(NPUPlace)
+        self.op_type = "increment"
+        self.init_dtype()
+
+        self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(np.array([1]).astype(self.dtype)), }
+        self.pre_input_id = id(self.inputs['X'])
+
+        self.attrs = {"Step": 1}
+        self.outputs = {'Out': np.array([2])}
+
+    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)
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestIncrementInplace(unittest.TestCase):
+    def test_npu(self):
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+        np.random.seed(SEED)
+
+        a_np = np.array([1]).astype('float32')
+
+        with paddle.static.program_guard(main_prog, startup_prog):
+            a = paddle.static.data(name="a", shape=[1], dtype='float32')
+            b = fluid.layers.increment(a)
+
+        place = paddle.NPUPlace(NPUPlace)
+
+        exe = paddle.static.Executor(place)
+        exe.run(startup_prog)
+
+        b_value = exe.run(
+            main_prog,
+            feed={"a": a_np,},
+            fetch_list=[b])
+
+        print('input a id is : {}'.format(id(a)))
+        print('input b id is : {}'.format(id(b)))
+
+        self.assertEqual(id(a), id(b))
+        self.assertEqual(b_value[0], 2)
+
+
+if __name__ == '__main__':
+    unittest.main()