wehub-resource-sync
115 lines
3.9 KiB
Python
115 lines
3.9 KiB
Python
# Copyright (c) 2023 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 paddle
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paddle.enable_static()
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class TestBuildModuleWithAssertOp(unittest.TestCase):
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def test_assert_construct(self):
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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x = paddle.static.data(name="x", shape=[2, 8], dtype="float32")
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condition = paddle.all(x > 0)
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paddle.static.nn.control_flow.Assert(condition, [x], 20)
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assert_op = main_program.global_block().ops[-1]
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self.assertEqual(assert_op.name(), "pd_op.assert")
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self.assertEqual(len(assert_op.results()), 0)
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def run_network(self, net_func):
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with paddle.pir_utils.IrGuard():
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.static.program_guard(main, startup):
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net_func()
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exe = paddle.static.Executor()
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exe.run(main)
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def test_assert_true(self):
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def net_func():
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condition = paddle.tensor.fill_constant(
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shape=[1], dtype='bool', value=True
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)
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paddle.static.nn.control_flow.Assert(condition, [])
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self.run_network(net_func)
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def test_assert_false(self):
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def net_func():
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condition = paddle.tensor.fill_constant(
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shape=[1], dtype='bool', value=False
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)
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paddle.static.nn.control_flow.Assert(condition)
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with self.assertRaises(ValueError):
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self.run_network(net_func)
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# TODO(MarioLulab): May lead `test_assert_construct` construct empty main_program. Fix it soon.
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# def test_assert_cond_numel_error(self):
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# def net_func():
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# condition = paddle.tensor.fill_constant(
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# shape=[1, 2], dtype='bool', value=True
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# )
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# paddle.static.nn.control_flow.Assert(condition, [])
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# with self.assertRaises(ValueError):
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# self.run_network(net_func)
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def test_assert_print_data(self):
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def net_func():
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zero = paddle.tensor.fill_constant(
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shape=[5], dtype='int64', value=0
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)
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one = paddle.tensor.fill_constant(shape=[5], dtype='int64', value=1)
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condition = paddle.less_than(one, zero).all() # False
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paddle.static.nn.control_flow.Assert(
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condition, [zero, one], summarize=8
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)
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with self.assertRaises(ValueError):
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self.run_network(net_func)
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def test_assert_summary(self):
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def net_func():
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x = paddle.tensor.fill_constant(
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shape=[10], dtype='float32', value=2.0
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)
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condition = paddle.max(x) < 1.0
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paddle.static.nn.control_flow.Assert(condition, (x,), 5)
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with self.assertRaises(ValueError):
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self.run_network(net_func)
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def test_assert_summary_greater_than_size(self):
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def net_func():
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x = paddle.tensor.fill_constant(
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shape=[2, 3], dtype='float32', value=2.0
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)
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condition = paddle.max(x) < 1.0
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paddle.static.nn.control_flow.Assert(
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condition, [x], 10, name="test"
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)
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with self.assertRaises(ValueError):
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self.run_network(net_func)
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if __name__ == "__main__":
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unittest.main()
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