wehub-resource-sync
109 lines
3.2 KiB
Python
109 lines
3.2 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test_ipu import IPUOpTest, np_dtype_to_base_str
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import paddle
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import paddle.optimizer
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import paddle.static
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from paddle import base
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from paddle.base import compiler
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paddle.enable_static()
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class TestBase(IPUOpTest):
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def setUp(self):
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self.set_atol()
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self.set_training()
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self.set_feed()
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self.set_feed_attr()
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self.set_op()
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def set_op(self):
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# setup custom op
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self.op = paddle.incubate.identity_loss
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def set_feed(self):
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self.feed = {
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"x": np.random.uniform(low=-2, high=2, size=[3, 5]).astype(
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'float32'
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),
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}
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def set_feed_attr(self):
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self.feed_shape = [x.shape for x in self.feed.values()]
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self.feed_list = list(self.feed.keys())
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self.feed_dtype = [
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np_dtype_to_base_str(x.dtype) for x in self.feed.values()
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]
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def _test_base(self, reduction):
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scope = base.core.Scope()
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main_prog = paddle.static.Program()
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startup_prog = paddle.static.Program()
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SEED = 0
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paddle.seed(SEED)
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with base.scope_guard(scope):
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with paddle.static.program_guard(main_prog, startup_prog):
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x = paddle.static.data(
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name=self.feed_list[0],
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shape=self.feed_shape[0],
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dtype=self.feed_dtype[0],
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)
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out = self.op(x, reduction)
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fetch_list = [out.name]
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place = paddle.IPUPlace()
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exe = paddle.static.Executor(place)
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exe.run(startup_prog)
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feed_list = self.feed_list
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ipu_strategy = paddle.static.IpuStrategy()
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ipu_strategy.set_graph_config(num_ipus=1, is_training=False)
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ipu_compiler = compiler.IpuCompiledProgram(
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main_prog, ipu_strategy=ipu_strategy
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)
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program = ipu_compiler.compile(feed_list, fetch_list)
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ipu_res = exe.run(program, self.feed, fetch_list)
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if reduction == 0:
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# sum
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cpu_res = self.feed['x'].sum()
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elif reduction == 1:
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# mean
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cpu_res = self.feed['x'].mean()
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else:
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# none
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cpu_res = self.feed['x']
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np.testing.assert_allclose(
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ipu_res[0], cpu_res, rtol=1e-05, atol=self.atol
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)
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def test_base(self):
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# TODO: use string instead of int for reduction
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for reduction in [0, 1, 2]:
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self._test_base(reduction)
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if __name__ == "__main__":
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unittest.main()
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