# Copyright (c) 2022 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. import unittest import numpy as np from op_test_ipu import IPUOpTest import paddle import paddle.static class TestBase(IPUOpTest): def setUp(self): self.set_atol() self.set_training() self.set_data_feed() self.set_feed_attr() self.set_op_attrs() def set_data_feed(self): data1 = np.random.uniform(size=[1, 3, 10, 10]) self.feed_fp32 = {'x': data1.astype(np.float32)} self.feed_fp16 = {'x': data1.astype(np.float16)} def set_feed_attr(self): self.feed_shape = [x.shape for x in self.feed_fp32.values()] self.feed_list = list(self.feed_fp32.keys()) def set_op_attrs(self): self.attrs = {"num_or_sections": [1, 1, 1], "axis": 1} @IPUOpTest.static_graph def build_model(self): x = paddle.static.data( name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32' ) out = paddle.split(x, **self.attrs) self.fetch_list = [fetch.name for fetch in out] def run_model(self, exec_mode): self.run_op_test(exec_mode) def test(self): for m in IPUOpTest.ExecutionMode: if not self.skip_mode(m): self.build_model() self.run_model(m) for k, v in self.output_dict.items(): self.output_dict[k] = np.concatenate([vv.flatten() for vv in v]) self.check() class TestCase1(TestBase): def set_op_attrs(self): self.attrs = {"num_or_sections": [2, 8], "axis": 2} if __name__ == "__main__": unittest.main()