Support NPU kernel stack op

paddle/fluid/operators/stack_op_npu.cc

@@ -0,0 +1,107 @@
+/* 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. */
+
+#ifdef PADDLE_WITH_ASCEND_CL
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "paddle/fluid/operators/activation_op.h"
+#include "paddle/fluid/operators/npu_op_runner.h"
+#include "paddle/fluid/operators/stack_op.h"
+#include "paddle/fluid/operators/unsqueeze_op.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+
+template <typename DeviceContext, typename T>
+class StackNPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto x = ctx.MultiInput<Tensor>("X");
+    int n = static_cast<int>(x.size());
+
+    PADDLE_ENFORCE_GT(
+        n, 0, platform::errors::InvalidArgument("number of input Tensor <= 0"));
+
+    std::vector<paddle::framework::Tensor> x_list;
+    for (int i = 0; i < n; i++) {
+      x_list.push_back(*x[i]);
+    }
+
+    int axis = ctx.Attr<int>("axis");
+
+    if (axis < 0) {
+      axis = axis + x_list[0].dims().size() + 1;
+    }
+    int32_t N = x.size();
+    auto* out = ctx.Output<Tensor>("Y");
+
+    auto place = ctx.GetPlace();
+
+    auto stream =
+        ctx.template device_context<paddle::platform::NPUDeviceContext>()
+            .stream();
+
+    out->mutable_data<T>(place);
+
+    if (axis != 0) {
+      auto x_dim = x_list[0].dims();
+      std::vector<int> vec_dim_tmp;
+      vec_dim_tmp.push_back(N);
+      for (auto i = 0; i < x_dim.size(); ++i) {
+        vec_dim_tmp.push_back(x_dim[i]);
+      }
+
+      Tensor tmp_stack(out->type());
+      tmp_stack.Resize(framework::make_ddim(vec_dim_tmp));
+      tmp_stack.mutable_data<T>(ctx.GetPlace());
+
+      auto runner =
+          NpuOpRunner("Pack", {x_list}, {tmp_stack}, {{"axis", 0}, {"N", N}});
+      runner.Run(stream);
+
+      std::vector<int64_t> vec_trans;
+      for (auto i = 1; i <= x_dim.size(); ++i) {
+        vec_trans.push_back(i);
+        if (i == axis) {
+          vec_trans.push_back(0);
+        }
+      }
+
+      auto runner_trans_final =
+          NpuOpRunner("TransposeD", {tmp_stack}, {*out}, {{"perm", vec_trans}});
+      runner_trans_final.Run(stream);
+
+    } else {
+      auto runner =
+          NpuOpRunner("Pack", {x_list}, {*out}, {{"axis", axis}, {"N", N}});
+      runner.Run(stream);
+    }
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_NPU_KERNEL(
+    stack, ops::StackNPUKernel<paddle::platform::NPUDeviceContext, float>,
+    ops::StackNPUKernel<paddle::platform::NPUDeviceContext,
+                        paddle::platform::float16>);
+
+#endif

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

@@ -0,0 +1,156 @@
+~
+#  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
+import paddle.fluid.core as core
+
+paddle.enable_static()
+SEED = 2021
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+
+class TestStack1(OpTest):
+
+    def initDefaultParameters(self):
+        self.num_inputs = 4
+        self.input_dim = (5, 6, 7)
+        self.axis = 0
+        self.dtype = 'float32'
+
+    def get_x_names(self):
+        x_names = []
+        for i in range(self.num_inputs):
+            x_names.append('x{}'.format(i))
+        return x_names
+
+    def setUp(self):
+        self.initDefaultParameters()
+        self.set_npu()
+        self.op_type = "stack"
+        self.place = paddle.NPUPlace(0)
+
+        self.x = []
+        for i in range(self.num_inputs):
+            self.x.append(
+                np.random.random(size=self.input_dim).astype(self.dtype))
+
+        tmp = []
+        x_names = self.get_x_names()
+        for i in range(self.num_inputs):
+            tmp.append((x_names[i], self.x[i]))
+
+        self.inputs = {'X': tmp}
+        self.outputs = {'Y': np.stack(self.x, axis=self.axis)}
+        self.attrs = {'axis': self.axis}
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, check_dygraph=False)
+
+
+class TestStack2(OpTest):
+
+    def initDefaultParameters(self):
+        self.num_inputs = 4
+        self.input_dim = (2, 3, 4)
+        self.axis = -1
+        self.dtype = 'float32'
+
+    def get_x_names(self):
+        x_names = []
+        for i in range(self.num_inputs):
+            x_names.append('x{}'.format(i))
+        return x_names
+
+    def setUp(self):
+        self.initDefaultParameters()
+        self.set_npu()
+        self.op_type = "stack"
+        self.place = paddle.NPUPlace(0)
+
+        self.x = []
+        for i in range(self.num_inputs):
+            self.x.append(
+                np.random.random(size=self.input_dim).astype(self.dtype))
+
+        tmp = []
+        x_names = self.get_x_names()
+        for i in range(self.num_inputs):
+            tmp.append((x_names[i], self.x[i]))
+
+        self.inputs = {'X': tmp}
+        self.outputs = {'Y': np.stack(self.x, axis=self.axis)}
+        self.attrs = {'axis': self.axis}
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, check_dygraph=False)
+
+class TestStack3(OpTest):
+
+    def initDefaultParameters(self):
+        self.num_inputs = 4
+        self.input_dim = (2, 3, 4)
+        self.axis = 1
+        self.dtype = 'float32'
+
+    def get_x_names(self):
+        x_names = []
+        for i in range(self.num_inputs):
+            x_names.append('x{}'.format(i))
+        return x_names
+
+    def setUp(self):
+        self.initDefaultParameters()
+        self.set_npu()
+        self.op_type = "stack"
+        self.place = paddle.NPUPlace(0)
+
+        self.x = []
+        for i in range(self.num_inputs):
+            self.x.append(
+                np.random.random(size=self.input_dim).astype(self.dtype))
+
+        tmp = []
+        x_names = self.get_x_names()
+        for i in range(self.num_inputs):
+            tmp.append((x_names[i], self.x[i]))
+
+        self.inputs = {'X': tmp}
+        self.outputs = {'Y': np.stack(self.x, axis=self.axis)}
+        self.attrs = {'axis': self.axis}
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, check_dygraph=False)
+
+if __name__ == '__main__':
+    unittest.main()