Support npu kernel for eye op (#34543)

* add eye npu op

* remove useless headers

* code style

* Update eye_op_npu.cc

* Update eye_op_npu.cc

* remove useless code in test file

* code style check

* change Copyright to 2021

* add test case and do some fix

* fix

* update code

* fix for CI

* return

* fix

paddle/fluid/operators/eye_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/eye_op.h"
+#include "paddle/fluid/operators/npu_op_runner.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+
+template <typename DeviceContext, typename T>
+class EyeNPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto num_rows = ctx.Attr<int64_t>("num_rows");
+
+    auto d_nums = ctx.Attr<int>("dtype");
+    auto dtype =
+        ConvertToNpuDtype(static_cast<framework::proto::VarType::Type>(d_nums));
+
+    auto num_columns = ctx.Attr<int64_t>("num_columns");
+    if (num_columns == -1) num_columns = num_rows;
+
+    framework::NPUAttributeMap attr_input = {
+        {"num_rows", num_rows}, {"num_columns", num_columns}, {"dtype", dtype}};
+
+    auto* out = ctx.Output<framework::Tensor>("Out");
+    out->mutable_data<T>(ctx.GetPlace());
+
+    const auto& runner = NpuOpRunner("Eye", {}, {*out}, attr_input);
+    auto stream =
+        ctx.template device_context<paddle::platform::NPUDeviceContext>()
+            .stream();
+    runner.Run(stream);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_NPU_KERNEL(
+    eye, ops::EyeNPUKernel<paddle::platform::NPUDeviceContext, float>,
+    ops::EyeNPUKernel<paddle::platform::NPUDeviceContext, int>,
+    ops::EyeNPUKernel<paddle::platform::NPUDeviceContext,
+                      paddle::platform::float16>);

python/paddle/fluid/tests/unittests/npu/test_eye_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
+import paddle.fluid.framework as framework
+
+paddle.enable_static()
+np.random.seed(10)
+
+
+class TestEyeOp(OpTest):
+    def setUp(self):
+        '''
+	    Test eye op with specified shape
+        '''
+        self.set_npu()
+        self.place = paddle.NPUPlace(0)
+        self.op_type = "eye"
+        self.inputs = {}
+
+        self.num_rows = 0
+        self.num_columns = 0
+        self.dtype = np.float32
+
+        self.initTestCase()
+
+        if self.num_columns == 0:
+            self.attrs = {
+                'num_rows': self.num_rows,
+                'dtype': framework.convert_np_dtype_to_dtype_(self.dtype)
+            }
+            self.outputs = {'Out': np.eye(self.num_rows, dtype=self.dtype)}
+        else:
+            self.attrs = {
+                'num_rows': self.num_rows,
+                'num_columns': self.num_columns,
+                'dtype': framework.convert_np_dtype_to_dtype_(self.dtype)
+            }
+            self.outputs = {
+                'Out': np.eye(self.num_rows, self.num_columns, dtype=self.dtype)
+            }
+
+    def initTestCase(self):
+        self.num_rows = 219
+        self.num_columns = 319
+        self.dtype = np.int32
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+
+class TestEyeOp1(TestEyeOp):
+    def initTestCase(self):
+        self.num_rows = 50
+
+
+class TestEyeOp2(TestEyeOp):
+    def initTestCase(self):
+        self.num_rows = 50
+        self.dtype = np.int32
+
+
+class TestEyeOp3(TestEyeOp):
+    def initTestCase(self):
+        self.num_rows = 50
+        self.dtype = np.float16
+
+
+class TestEyeOp4(TestEyeOp):
+    def initTestCase(self):
+        self.num_rows = 1
+        self.num_columns = 99
+
+
+class TestEyeOp5(TestEyeOp):
+    def initTestCase(self):
+        self.num_rows = 100
+        self.num_columns = 100
+
+
+class TestEyeOp6(TestEyeOp):
+    def initTestCase(self):
+        self.num_rows = 100
+        self.num_columns = 100
+        self.dtype = np.float32
+
+
+class API_TestTensorEye(unittest.TestCase):
+    def test_out(self):
+        with paddle.static.program_guard(paddle.static.Program()):
+            data = paddle.eye(10)
+            place = paddle.NPUPlace(0)
+            exe = paddle.static.Executor(place)
+            result, = exe.run(fetch_list=[data])
+            expected_result = np.eye(10, dtype="float32")
+        self.assertEqual((result == expected_result).all(), True)
+
+        with paddle.static.program_guard(paddle.static.Program()):
+            data = paddle.eye(10, num_columns=7, dtype="float16")
+            place = paddle.NPUPlace(0)
+            exe = paddle.static.Executor(place)
+            result, = exe.run(fetch_list=[data])
+            expected_result = np.eye(10, 7, dtype="float16")
+        self.assertEqual((result == expected_result).all(), True)
+
+        with paddle.static.program_guard(paddle.static.Program()):
+            data = paddle.eye(10, dtype="int32")
+            place = paddle.NPUPlace(0)
+            exe = paddle.static.Executor(place)
+            result, = exe.run(fetch_list=[data])
+            expected_result = np.eye(10, dtype="int32")
+        self.assertEqual((result == expected_result).all(), True)
+
+        paddle.disable_static(paddle.NPUPlace(0))
+        out = paddle.eye(10, dtype="int32")
+        expected_result = np.eye(10, dtype="int32")
+        paddle.enable_static()
+        self.assertEqual((out.numpy() == expected_result).all(), True)
+
+        paddle.disable_static(paddle.NPUPlace(0))
+        batch_shape = [2]
+        out = fluid.layers.eye(10, 10, dtype="int32", batch_shape=batch_shape)
+        result = np.eye(10, dtype="int32")
+        expected_result = []
+        for index in reversed(batch_shape):
+            tmp_result = []
+            for i in range(index):
+                tmp_result.append(result)
+            result = tmp_result
+            expected_result = np.stack(result, axis=0)
+        paddle.enable_static()
+        self.assertEqual(out.numpy().shape == np.array(expected_result).shape,
+                         True)
+        self.assertEqual((out.numpy() == expected_result).all(), True)
+
+        paddle.disable_static(paddle.NPUPlace(0))
+        batch_shape = [3, 2]
+        out = fluid.layers.eye(10, 10, dtype="int32", batch_shape=batch_shape)
+        result = np.eye(10, dtype="int32")
+        expected_result = []
+        for index in reversed(batch_shape):
+            tmp_result = []
+            for i in range(index):
+                tmp_result.append(result)
+            result = tmp_result
+            expected_result = np.stack(result, axis=0)
+        paddle.enable_static()
+        self.assertEqual(out.numpy().shape == np.array(expected_result).shape,
+                         True)
+        self.assertEqual((out.numpy() == expected_result).all(), True)
+
+    def test_errors(self):
+        with paddle.static.program_guard(paddle.static.Program()):
+
+            def test_num_rows_type_check():
+                paddle.eye(-1, dtype="int64")
+
+            self.assertRaises(TypeError, test_num_rows_type_check)
+
+            def test_num_columns_type_check():
+                paddle.eye(10, num_columns=5.2, dtype="int64")
+
+            self.assertRaises(TypeError, test_num_columns_type_check)
+
+            def test_num_columns_type_check1():
+                paddle.eye(10, num_columns=10, dtype="int8")
+
+            self.assertRaises(TypeError, test_num_columns_type_check1)
+
+
+if __name__ == "__main__":
+    unittest.main()