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| 1 | +# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. |
| 2 | +# |
| 3 | +# Licensed under the Apache License, Version 2.0 (the "License"); |
| 4 | +# you may not use this file except in compliance with the License. |
| 5 | +# You may obtain a copy of the License at |
| 6 | +# |
| 7 | +# http://www.apache.org/licenses/LICENSE-2.0 |
| 8 | +# |
| 9 | +# Unless required by applicable law or agreed to in writing, software |
| 10 | +# distributed under the License is distributed on an "AS IS" BASIS, |
| 11 | +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 12 | +# See the License for the specific language governing permissions and |
| 13 | +# limitations under the License. |
| 14 | + |
| 15 | +import copy |
| 16 | +import unittest |
| 17 | + |
| 18 | +import numpy as np |
| 19 | +from op_test import get_places |
| 20 | + |
| 21 | +import paddle |
| 22 | +from paddle.framework import core |
| 23 | + |
| 24 | + |
| 25 | +class TestScatterAddInplaceAPI(unittest.TestCase): |
| 26 | + def setUp(self): |
| 27 | + np.random.seed(0) |
| 28 | + self.shape = [10, 10] |
| 29 | + self.index_shape = [10, 10] |
| 30 | + self.index_np = np.random.randint(0, 10, (10, 10)).astype('int64') |
| 31 | + self.x_np = np.random.random(self.shape).astype(np.float32) |
| 32 | + self.place = get_places() |
| 33 | + self.axis = 0 |
| 34 | + self.value_np = np.random.randint(0, 10, (10, 10)).astype(np.float32) |
| 35 | + self.value_shape = [10, 10] |
| 36 | + |
| 37 | + def test_inplace_dygraph(self): |
| 38 | + def run(place): |
| 39 | + paddle.disable_static(place) |
| 40 | + x_tensor = paddle.to_tensor(self.x_np) |
| 41 | + index_tensor = paddle.to_tensor(self.index_np) |
| 42 | + value_tensor = paddle.to_tensor(self.value_np) |
| 43 | + |
| 44 | + x_tensor.scatter_add_(self.axis, index_tensor, value_tensor) |
| 45 | + |
| 46 | + out_ref = copy.deepcopy(self.x_np) |
| 47 | + for i in range(10): |
| 48 | + for j in range(10): |
| 49 | + out_ref[self.index_np[i, j], j] += self.value_np[i, j] |
| 50 | + |
| 51 | + np.testing.assert_allclose(x_tensor.numpy(), out_ref, rtol=0.001) |
| 52 | + |
| 53 | + paddle.enable_static() |
| 54 | + |
| 55 | + for place in self.place: |
| 56 | + run(place) |
| 57 | + |
| 58 | + |
| 59 | +@unittest.skipIf( |
| 60 | + not core.is_compiled_with_cuda(), |
| 61 | + "core is not compiled with CUDA", |
| 62 | +) |
| 63 | +class TestScatterAddInplaceAPILargeCase(unittest.TestCase): |
| 64 | + def setUp(self): |
| 65 | + np.random.seed(0) |
| 66 | + self.shape = [64, 102400] |
| 67 | + self.index_shape = [64, 102400] |
| 68 | + self.index_np = np.random.randint(0, 64, (64, 102400)).astype('int64') |
| 69 | + self.x_np = np.random.random(self.shape).astype(np.float32) |
| 70 | + self.axis = 1 |
| 71 | + self.value_np = np.random.randint(0, 50, (64, 102400)).astype( |
| 72 | + np.float32 |
| 73 | + ) |
| 74 | + self.place = [paddle.CUDAPlace(0)] |
| 75 | + |
| 76 | + def test_inplace_dygraph(self): |
| 77 | + def run(place): |
| 78 | + paddle.disable_static(place) |
| 79 | + x_tensor = paddle.to_tensor(self.x_np) |
| 80 | + index_tensor = paddle.to_tensor(self.index_np) |
| 81 | + value_tensor = paddle.to_tensor(self.value_np) |
| 82 | + |
| 83 | + x_tensor.scatter_add_(self.axis, index_tensor, value_tensor) |
| 84 | + |
| 85 | + out_ref = copy.deepcopy(self.x_np) |
| 86 | + for i in range(64): |
| 87 | + for j in range(102400): |
| 88 | + out_ref[i, self.index_np[i, j]] += self.value_np[i, j] |
| 89 | + |
| 90 | + np.testing.assert_allclose(x_tensor.numpy(), out_ref, rtol=0.001) |
| 91 | + |
| 92 | + paddle.enable_static() |
| 93 | + |
| 94 | + for place in self.place: |
| 95 | + run(place) |
| 96 | + |
| 97 | + |
| 98 | +class TestScatterAddInplaceAPIOtherCase(unittest.TestCase): |
| 99 | + def setUp(self): |
| 100 | + np.random.seed(0) |
| 101 | + self.shape = [3, 5] |
| 102 | + self.index1_shape = [1, 4] |
| 103 | + self.index_np1 = np.array([[0, 1, 2, 0]]).astype('int64') |
| 104 | + self.index2_shape = [2, 3] |
| 105 | + self.index_np2 = np.array([[0, 1, 2], [0, 1, 4]]).astype('int64') |
| 106 | + self.x_np = np.zeros((3, 5)).astype(np.float32) |
| 107 | + self.value_shape = [2, 5] |
| 108 | + self.value = ( |
| 109 | + np.arange(1, 11).reshape(self.value_shape).astype(np.float32) |
| 110 | + ) |
| 111 | + self.place = get_places() |
| 112 | + |
| 113 | + def test_api_dygraph(self): |
| 114 | + def run_inplace(place): |
| 115 | + paddle.disable_static(place) |
| 116 | + out1 = paddle.to_tensor(self.x_np) |
| 117 | + index_tensor1 = paddle.to_tensor(self.index_np1) |
| 118 | + value_tensor = paddle.to_tensor(self.value) |
| 119 | + out1.scatter_add_(0, index_tensor1, value_tensor) |
| 120 | + out_ref = copy.deepcopy(self.x_np) |
| 121 | + for i in range(self.index1_shape[0]): |
| 122 | + for j in range(self.index1_shape[1]): |
| 123 | + out_ref[self.index_np1[i, j], j] += self.value[i, j] |
| 124 | + np.testing.assert_allclose(out1.numpy(), out_ref, rtol=0.001) |
| 125 | + |
| 126 | + index_tensor2 = paddle.to_tensor(self.index_np2) |
| 127 | + out2 = paddle.to_tensor(self.x_np) |
| 128 | + out2.scatter_add_(1, index_tensor2, value_tensor) |
| 129 | + out_ref = copy.deepcopy(self.x_np) |
| 130 | + for i in range(self.index2_shape[0]): |
| 131 | + for j in range(self.index2_shape[1]): |
| 132 | + out_ref[i, self.index_np2[i, j]] += self.value[i, j] |
| 133 | + np.testing.assert_allclose(out2.numpy(), out_ref, rtol=0.001) |
| 134 | + |
| 135 | + paddle.enable_static() |
| 136 | + |
| 137 | + for place in self.place: |
| 138 | + run_inplace(place) |
| 139 | + |
| 140 | + def test_error(self): |
| 141 | + tensorx = paddle.to_tensor([[1, 2, 3], [4, 5, 6]]).astype("float32") |
| 142 | + indices = paddle.to_tensor([[1, 0, 1], [0, 1, 1]]).astype("int32") |
| 143 | + values = paddle.to_tensor([1]) |
| 144 | + |
| 145 | + try: |
| 146 | + tensorx.scatter_add_(0, indices, values) |
| 147 | + except Exception as error: |
| 148 | + self.assertIsInstance(error, ValueError) |
| 149 | + |
| 150 | + indices = paddle.to_tensor([1]).astype("int32") |
| 151 | + values = paddle.to_tensor([[1, 2, 3], [4, 5, 6]]) |
| 152 | + |
| 153 | + try: |
| 154 | + tensorx.scatter_add_(0, indices, values) |
| 155 | + except Exception as error: |
| 156 | + self.assertIsInstance(error, ValueError) |
| 157 | + |
| 158 | + indices = paddle.to_tensor( |
| 159 | + [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] |
| 160 | + ).astype("int32") |
| 161 | + # indices too large |
| 162 | + try: |
| 163 | + tensorx.scatter_add_(0, indices, values) |
| 164 | + except Exception as error: |
| 165 | + self.assertIsInstance(error, RuntimeError) |
| 166 | + |
| 167 | + indices = paddle.to_tensor([[3, 0, 4], [0, 5, 10]]).astype("int32") |
| 168 | + # the element of indices out of range |
| 169 | + try: |
| 170 | + tensorx.scatter_add_(0, indices, values) |
| 171 | + except Exception as error: |
| 172 | + self.assertIsInstance(error, RuntimeError) |
| 173 | + |
| 174 | + def test_index_type_error(self): |
| 175 | + tensorx = paddle.to_tensor([[1, 2, 3], [4, 5, 6]]).astype("float32") |
| 176 | + indices = paddle.to_tensor([[1, 0, 1], [0, 1, 1]]).astype("float32") |
| 177 | + values = paddle.to_tensor([[1, 2, 3], [4, 5, 6]]) |
| 178 | + with self.assertRaises(TypeError): |
| 179 | + tensorx.scatter_add_(0, indices, values) |
| 180 | + |
| 181 | + |
| 182 | +if __name__ == "__main__": |
| 183 | + paddle.enable_static() |
| 184 | + unittest.main() |
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