wehub-resource-sync
135 lines
4.2 KiB
Python
135 lines
4.2 KiB
Python
# Copyright (c) 2020 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 os
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import tempfile
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import unittest
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import paddle
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from paddle import base, static
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from paddle.base import core
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class TestSaveLoadAPIError(unittest.TestCase):
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def setUp(self):
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self.temp_dir = tempfile.TemporaryDirectory()
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self.save_dir = os.path.join(self.temp_dir.name, "fake_dir")
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def tearDown(self):
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self.temp_dir.cleanup()
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def test_get_valid_program_error(self):
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# case 1: CompiledProgram no program
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graph = core.Graph(core.ProgramDesc())
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compiled_program = base.CompiledProgram(graph)
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with self.assertRaises(TypeError):
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paddle.static.io._get_valid_program(compiled_program)
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# case 2: main_program type error
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with self.assertRaises(TypeError):
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paddle.static.io._get_valid_program("program")
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def test_load_vars_error(self):
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place = base.CPUPlace()
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exe = base.Executor(place)
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# case 1: main_program type error when vars None
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with self.assertRaises(TypeError):
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static.io.load_vars(
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executor=exe, dirname=self.save_dir, main_program="program"
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)
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# case 2: main_program type error when vars not None
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with self.assertRaises(TypeError):
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static.io.load_vars(
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executor=exe,
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dirname=self.save_dir,
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main_program="program",
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vars="vars",
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)
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class TestSaveInferenceModelAPIError(unittest.TestCase):
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def setUp(self):
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self.temp_dir = tempfile.TemporaryDirectory()
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def tearDown(self):
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self.temp_dir.cleanup()
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def test_useless_feeded_var_names(self):
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start_prog = base.Program()
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main_prog = base.Program()
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with base.program_guard(main_prog, start_prog):
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x = paddle.static.data(name='x', shape=[10, 16], dtype='float32')
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y = paddle.static.data(name='y', shape=[10, 16], dtype='float32')
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z = paddle.static.nn.fc(x, 4)
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exe = base.Executor(base.CPUPlace())
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exe.run(start_prog)
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with self.assertRaisesRegex(
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ValueError, "not involved in the target_vars calculation"
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):
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paddle.static.io.save_inference_model(
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path_prefix=os.path.join(self.temp_dir.name, 'model'),
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feed_vars=[x, y],
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fetch_vars=[z],
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executor=exe,
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program=main_prog,
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)
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class TestWhenTrainWithNoGrad(unittest.TestCase):
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def setUp(self):
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self.temp_dir = tempfile.TemporaryDirectory()
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def tearDown(self):
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self.temp_dir.cleanup()
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def test_when_train_with_no_grad(self):
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paddle.disable_static()
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net = paddle.nn.Linear(1024, 1)
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net = paddle.jit.to_static(net, full_graph=True)
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x = paddle.rand([1024], 'float32')
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x.stop_gradient = False
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out = net(x)
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out.backward()
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x_grad = x.grad.mean()
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x.clear_grad()
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# jit.save
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save_path = os.path.join(self.temp_dir.name, 'train_with_no_grad')
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paddle.jit.save(net, save_path)
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# test eval mode
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net1 = paddle.jit.load(save_path)
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net1.eval()
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with paddle.no_grad():
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out1 = net1(x)
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self.assertEqual(out, out1)
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# test train mode
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net2 = paddle.jit.load(save_path)
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net2.train()
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out2 = net2(x)
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out2.backward()
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self.assertEqual(out, out2)
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x_grad2 = x.grad.mean()
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if paddle.framework.in_pir_mode():
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self.assertEqual(x_grad, x_grad2)
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if __name__ == '__main__':
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paddle.enable_static()
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unittest.main()
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