[NPU] add is_empty_op_npu, test=develop (#34234)

paddle/fluid/memory/allocation/allocator_facade.cc

@@ -240,6 +240,12 @@ class AllocatorFacadePrivate {
       places.emplace_back(platform::XPUPlace(dev_id));
     }
 #endif
+#ifdef PADDLE_WITH_ASCEND_CL
+    int device_count = platform::GetNPUDeviceCount();
+    for (int dev_id = 0; dev_id < device_count; ++dev_id) {
+      places.emplace_back(platform::NPUPlace(dev_id));
+    }
+#endif
 
     for (auto& p : places) {
       zero_size_allocators_[p] = std::make_shared<ZeroSizeAllocator>(p);

paddle/fluid/operators/is_empty_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 Licnse. */
+
+#include "paddle/fluid/operators/is_empty_op.h"
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_NPU_KERNEL(
+    is_empty, ops::IsEmptyOpKernel<plat::NPUDeviceContext, float>,
+    ops::IsEmptyOpKernel<plat::NPUDeviceContext, plat::float16>);

paddle/fluid/platform/npu_info.cc

@@ -192,6 +192,10 @@ void NPUMemcpySync(void *dst, const void *src, size_t count,
   dst_max_count = dst_max_count ? dst_max_count : count;
   VLOG(4) << dst << " " << dst_max_count << " " << src << " " << count << " "
           << kind;
+  if (dst == nullptr && dst_max_count == 0) {
+    VLOG(4) << "Dot not call aclrtMemcpy for zero_size_allocation on NPU";
+    return;
+  }
   PADDLE_ENFORCE_NPU_SUCCESS(aclrtMemcpy(dst, dst_max_count, src, count, kind));
 }
 

python/paddle/fluid/tests/unittests/npu/test_is_empty_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
+
+paddle.enable_static()
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestEmpty(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.init_dtype()
+        self.op_type = "is_empty"
+        self.set_data()
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+        self.place = paddle.NPUPlace(0)
+
+    def init_dtype(self):
+        self.dtype = np.float32
+
+    def set_data(self):
+        self.inputs = {'X': np.array([1, 2, 3]).astype(self.dtype)}
+        self.outputs = {'Out': np.array([False])}
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestNotEmpty(TestEmpty):
+    def set_data(self):
+        self.inputs = {'X': np.array([])}
+        self.outputs = {'Out': np.array([True])}
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestIsEmptyOpError(unittest.TestCase):
+    def test_errors(self):
+        paddle.enable_static()
+        with paddle.static.program_guard(paddle.static.Program(),
+                                         paddle.static.Program()):
+            input_data = np.random.random((3, 2)).astype("float32")
+
+            def test_Variable():
+                # the input type must be Variable
+                paddle.is_empty(x=input_data)
+
+            self.assertRaises(TypeError, test_Variable)
+
+            def test_type():
+                # dtype must be float32, float16 in NPU
+                x3 = paddle.static.data(
+                    name="x3", shape=[4, 32, 32], dtype="bool")
+                res = paddle.is_empty(x=x3)
+
+            self.assertRaises(TypeError, test_type)
+
+            def test_name_type():
+                # name type must be string.
+                x4 = paddle.static.data(
+                    name="x4", shape=[3, 2], dtype="float32")
+                res = paddle.is_empty(x=x4, name=1)
+
+            self.assertRaises(TypeError, test_name_type)
+
+
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestIsEmptyOpDygraph(unittest.TestCase):
+    def test_dygraph(self):
+        paddle.disable_static(paddle.NPUPlace(0))
+        input = paddle.rand(shape=[4, 32, 32], dtype='float32')
+        res = paddle.is_empty(x=input)
+
+
+if __name__ == "__main__":
+    unittest.main()