wehub-resource-sync
145 lines
3.5 KiB
Python
145 lines
3.5 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 unittest
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import numpy
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from dygraph_to_static_utils import (
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Dy2StTestBase,
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enable_to_static_guard,
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)
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import paddle
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# 1. print Tensor
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def dyfunc_print_variable(x):
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# NOTE: transform to static code, var name will be changed
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x_t = paddle.to_tensor(x)
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print(x_t)
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# 2. print ndarray
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def dyfunc_print_ndarray(x):
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print(x)
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# 3. print Tensor with format
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def dyfunc_print_with_format(x):
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x_t = paddle.to_tensor(x)
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print(f"PrintTensor: {x_t}")
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# 4. print Tensor with format 2
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def dyfunc_print_with_format2(x):
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x_t = paddle.to_tensor(x)
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print("PrintTensor: %s" % x_t) # noqa: UP031
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# 5. print Tensor in control flow1
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def dyfunc_print_with_ifelse(x):
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x_t = paddle.to_tensor(x)
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if len(x_t.shape) > 1:
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print(x_t)
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else:
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print(x_t)
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# 6. print multiple Tensor
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def dyfunc_print_multi_tensor(x):
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x_t = paddle.to_tensor(x)
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y_t = x_t * 2
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print(x_t)
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print(y_t)
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# 7. print continue Tensor
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def dyfunc_print_continue_vars(x):
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x_t = paddle.to_tensor(x)
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y_t = x_t * 2
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print(x_t, y_t)
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# 8. print with kwargs
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def dyfunc_print_with_kwargs(x):
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x_t = paddle.to_tensor(x)
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print("Tensor", x_t, end='\n\n', sep=': ')
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class TestPrintBase(Dy2StTestBase):
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def setUp(self):
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self.input = numpy.ones(5).astype("int32")
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self.set_test_func()
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def set_test_func(self):
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raise NotImplementedError("Print test should implement set_test_func")
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def _run(self, to_static: bool):
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with enable_to_static_guard(to_static):
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paddle.jit.to_static(self.dygraph_func)(self.input)
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def get_dygraph_output(self):
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self._run(to_static=False)
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def get_static_output(self):
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self._run(to_static=True)
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class TestPrintVariable(TestPrintBase):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_variable
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def test_transformed_static_result(self):
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self.get_dygraph_output()
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self.get_static_output()
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class TestPrintNdArray(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_ndarray
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class TestPrintWithFormat(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_with_format
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class TestPrintWithFormat2(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_with_format2
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class TestPrintWithIfElse(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_with_ifelse
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class TestPrintMultipleTensor(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_multi_tensor
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class TestPrintContinueVar(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_continue_vars
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class TestPrintWithKwargs(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_with_kwargs
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if __name__ == '__main__':
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unittest.main()
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