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- # 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.
-
- 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):
- x = np.random.uniform(size=[1, 3, 2, 2])
- y = np.random.uniform(size=[1, 3, 2, 2])
- self.feed_fp32 = {"x": x.astype(np.float32), "y": y.astype(np.float32)}
- self.feed_fp16 = {"x": x.astype(np.float16), "y": y.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())
- self.feed_dtype = [x.dtype for x in self.feed_fp32.values()]
-
- def set_op_attrs(self):
- self.attrs = {}
-
- @IPUOpTest.static_graph
- def build_model(self):
- x = paddle.static.data(
- name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
- )
- y = paddle.static.data(
- name=self.feed_list[1], shape=self.feed_shape[1], dtype='float32'
- )
- out = paddle.add_n([x, y], **self.attrs)
- self.fetch_list = [out.name]
-
- 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)
- self.check()
-
-
- class TestCase1(TestBase):
- def set_data_feed(self):
- x = np.random.uniform(size=[1, 3, 2, 2])
- y = np.random.uniform(size=[1, 3, 2, 2])
- z = np.random.uniform(size=[1, 3, 2, 2])
- self.feed_fp32 = {
- "x": x.astype(np.float32),
- "y": y.astype(np.float32),
- "z": z.astype(np.float32),
- }
- self.feed_fp16 = {
- "x": x.astype(np.float16),
- "y": y.astype(np.float16),
- "z": z.astype(np.float16),
- }
-
- @IPUOpTest.static_graph
- def build_model(self):
- x = paddle.static.data(
- name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
- )
- y = paddle.static.data(
- name=self.feed_list[1], shape=self.feed_shape[1], dtype='float32'
- )
- z = paddle.static.data(
- name=self.feed_list[2], shape=self.feed_shape[2], dtype='float32'
- )
- out = paddle.add_n([x, y, z], **self.attrs)
- self.fetch_list = [out.name]
-
-
- if __name__ == "__main__":
- unittest.main()
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