[NPU] add randperm_op_npu (#35763) (#36026)

* add randperm_op_npu

* fix test_set_value_op_npu

paddle/fluid/operators/randperm_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/randperm_op.h"
+#include "paddle/fluid/framework/op_registry.h"
+
+template <typename T>
+using kernel =
+    paddle::operators::RandpermKernel<paddle::platform::NPUDeviceContext, T>;
+
+REGISTER_OP_NPU_KERNEL(randperm, kernel<int64_t>, kernel<int>, kernel<float>,
+                       kernel<double>);

paddle/fluid/operators/utils.h

@@ -114,6 +114,11 @@ inline T GetValue(const framework::Tensor* x) {
   if (!platform::is_cpu_place(x->place())) {
     framework::Tensor cpu_x;
     framework::TensorCopy(*x, platform::CPUPlace(), &cpu_x);
+#ifdef PADDLE_WITH_ASCEND_CL
+    platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
+    const platform::DeviceContext* dev_ctx = pool.Get(x->place());
+    dev_ctx->Wait();
+#endif
     value = cpu_x.data<T>()[0];
   } else {
     value = x->data<T>()[0];

python/paddle/fluid/tests/unittests/npu/test_randperm_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 unittest
+import numpy as np
+import sys
+sys.path.append("..")
+from op_test import OpTest
+import paddle
+import paddle.fluid.core as core
+from paddle.static import program_guard, Program
+from test_randperm_op import check_randperm_out, error_msg, convert_dtype
+
+paddle.enable_static()
+
+
+class TestRandpermOp(OpTest):
+    """ Test randperm op."""
+
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "randperm"
+        self.n = 200
+        self.dtype = "int64"
+
+        self.inputs = {}
+        self.outputs = {"Out": np.zeros((self.n)).astype(self.dtype)}
+        self.init_attrs()
+        self.attrs = {
+            "n": self.n,
+            "dtype": convert_dtype(self.dtype),
+        }
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def _get_places(self):
+        return [paddle.NPUPlace(0)]
+
+    def init_attrs(self):
+        pass
+
+    def test_check_output(self):
+        self.check_output_customized(self.verify_output)
+
+    def verify_output(self, outs):
+        out_np = np.array(outs[0])
+        self.assertTrue(
+            check_randperm_out(self.n, out_np), msg=error_msg(out_np))
+
+
+class TestRandpermOpN(TestRandpermOp):
+    def init_attrs(self):
+        self.n = 10000
+
+
+class TestRandpermOpInt32(TestRandpermOp):
+    def init_attrs(self):
+        self.dtype = "int32"
+
+
+class TestRandpermOpFloat32(TestRandpermOp):
+    def init_attrs(self):
+        self.dtype = "float32"
+
+
+class TestRandpermOpFloat64(TestRandpermOp):
+    def init_attrs(self):
+        self.dtype = "float64"
+
+
+class TestRandpermOpError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            self.assertRaises(ValueError, paddle.randperm, -3)
+            self.assertRaises(TypeError, paddle.randperm, 10, 'int8')
+
+
+class TestRandpermAPI(unittest.TestCase):
+    def test_out(self):
+        n = 10
+        place = paddle.NPUPlace(0)
+        with program_guard(Program(), Program()):
+            x1 = paddle.randperm(n)
+            x2 = paddle.randperm(n, 'float32')
+
+            exe = paddle.static.Executor(place)
+            res = exe.run(fetch_list=[x1, x2])
+
+            self.assertEqual(res[0].dtype, np.int64)
+            self.assertEqual(res[1].dtype, np.float32)
+            self.assertTrue(check_randperm_out(n, res[0]))
+            self.assertTrue(check_randperm_out(n, res[1]))
+
+
+class TestRandpermImperative(unittest.TestCase):
+    def test_out(self):
+        paddle.disable_static(paddle.NPUPlace(0))
+        n = 10
+        for dtype in ['int32', np.int64, 'float32', 'float64']:
+            data_p = paddle.randperm(n, dtype)
+            data_np = data_p.numpy()
+            self.assertTrue(
+                check_randperm_out(n, data_np), msg=error_msg(data_np))
+        paddle.enable_static()
+
+
+if __name__ == "__main__":
+    unittest.main()

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

@@ -68,7 +68,7 @@ class TestSetValueApi(TestSetValueBase):
         return out
 
     def _run_dynamic(self):
-        paddle.disable_static()
+        paddle.disable_static(paddle.NPUPlace(0))
         x = paddle.ones(shape=self.shape, dtype=self.dtype)
         self._call_setitem(x)
         out = x.numpy()