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523 lines
15 KiB
523 lines
15 KiB
# 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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# Test set_value op in static mode
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from __future__ import print_function
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import unittest
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import numpy as np
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import paddle
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class TestSetValueBase(unittest.TestCase):
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def setUp(self):
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paddle.enable_static()
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self.set_dtype()
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self.set_value()
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self.shape = [2, 3, 4]
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self.data = np.ones(self.shape).astype(self.dtype)
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self.program = paddle.static.Program()
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def set_value(self):
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self.value = 6
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def set_dtype(self):
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self.dtype = "float32"
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def _call_setitem(self, x):
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x[0, 0] = self.value
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def _get_answer(self):
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self.data[0, 0] = self.value
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class TestSetValueApi(TestSetValueBase):
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def test_api(self):
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with paddle.static.program_guard(self.program):
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x = paddle.ones(shape=self.shape, dtype=self.dtype)
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self._call_setitem(x)
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exe = paddle.static.Executor(paddle.CPUPlace())
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out = exe.run(self.program, fetch_list=[x])
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self._get_answer()
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self.assertTrue(
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(self.data == out).all(),
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msg="\nExpected res = \n{}, \n\nbut received : \n{}".format(
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self.data, out))
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# 1. Test different type of item: int, python slice
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class TestSetValueItemInt(TestSetValueApi):
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def _call_setitem(self, x):
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x[0] = self.value
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def _get_answer(self):
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self.data[0] = self.value
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class TestSetValueItemSlice(TestSetValueApi):
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def _call_setitem(self, x):
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x[0:2] = self.value
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def _get_answer(self):
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self.data[0:2] = self.value
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class TestSetValueItemSlice2(TestSetValueApi):
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def _call_setitem(self, x):
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x[0:-1] = self.value
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def _get_answer(self):
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self.data[0:-1] = self.value
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class TestSetValueItemSlice3(TestSetValueApi):
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def _call_setitem(self, x):
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x[0:-1, 0:2] = self.value
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def _get_answer(self):
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self.data[0:-1, 0:2] = self.value
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class TestSetValueItemSlice4(TestSetValueApi):
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def _call_setitem(self, x):
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x[0:, 1:2, :] = self.value
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def _get_answer(self):
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self.data[0:, 1:2, :] = self.value
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# 2. Test different type of value: int, float, numpy.ndarray, Tensor
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# 2.1 value is int32, int64, float32, float64, bool
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def create_test_value_int32(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = 7
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def set_dtype(self):
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self.dtype = "int32"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueInt32")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_int32(TestSetValueItemInt)
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create_test_value_int32(TestSetValueItemSlice)
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create_test_value_int32(TestSetValueItemSlice2)
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create_test_value_int32(TestSetValueItemSlice3)
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create_test_value_int32(TestSetValueItemSlice4)
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def create_test_value_int64(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = 7
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def set_dtype(self):
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self.dtype = "int64"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueInt64")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_int64(TestSetValueItemInt)
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create_test_value_int64(TestSetValueItemSlice)
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create_test_value_int64(TestSetValueItemSlice2)
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create_test_value_int64(TestSetValueItemSlice3)
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create_test_value_int64(TestSetValueItemSlice4)
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def create_test_value_fp32(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = 3.3
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def set_dtype(self):
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self.dtype = "float32"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueFp32")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_fp32(TestSetValueItemInt)
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create_test_value_fp32(TestSetValueItemSlice)
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create_test_value_fp32(TestSetValueItemSlice2)
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create_test_value_fp32(TestSetValueItemSlice3)
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create_test_value_fp32(TestSetValueItemSlice4)
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def create_test_value_fp64(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = 2.0**127 # float32:[-2^128, 2^128)
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def set_dtype(self):
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self.dtype = "float64"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueFp64")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_fp64(TestSetValueItemInt)
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create_test_value_fp64(TestSetValueItemSlice)
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create_test_value_fp64(TestSetValueItemSlice2)
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create_test_value_fp64(TestSetValueItemSlice3)
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create_test_value_fp64(TestSetValueItemSlice4)
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def create_test_value_bool(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = 0
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def set_dtype(self):
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self.dtype = "bool"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueBool")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_bool(TestSetValueItemInt)
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create_test_value_bool(TestSetValueItemSlice)
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create_test_value_bool(TestSetValueItemSlice2)
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create_test_value_bool(TestSetValueItemSlice3)
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create_test_value_bool(TestSetValueItemSlice4)
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# 2.2 value is numpy.array (int32, int64, float32, float64, bool)
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def create_test_value_numpy_int32(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = np.array([5])
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def set_dtype(self):
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self.dtype = "int32"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyInt32")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_numpy_int32(TestSetValueItemInt)
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create_test_value_numpy_int32(TestSetValueItemSlice)
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create_test_value_numpy_int32(TestSetValueItemSlice2)
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create_test_value_numpy_int32(TestSetValueItemSlice3)
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create_test_value_numpy_int32(TestSetValueItemSlice4)
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def create_test_value_numpy_int64(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = np.array([1])
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def set_dtype(self):
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self.dtype = "int64"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyInt64")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_numpy_int64(TestSetValueItemInt)
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create_test_value_numpy_int64(TestSetValueItemSlice)
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create_test_value_numpy_int64(TestSetValueItemSlice2)
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create_test_value_numpy_int64(TestSetValueItemSlice3)
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create_test_value_numpy_int64(TestSetValueItemSlice4)
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def create_test_value_numpy_fp32(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = np.array([1])
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def set_dtype(self):
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self.dtype = "float32"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyFp32")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_numpy_fp32(TestSetValueItemInt)
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create_test_value_numpy_fp32(TestSetValueItemSlice)
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create_test_value_numpy_fp32(TestSetValueItemSlice2)
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create_test_value_numpy_fp32(TestSetValueItemSlice3)
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create_test_value_numpy_fp32(TestSetValueItemSlice4)
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def create_test_value_numpy_fp64(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = np.array([2**127]).astype("float64")
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def set_dtype(self):
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self.dtype = "float64"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyFp64")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_numpy_fp64(TestSetValueItemInt)
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create_test_value_numpy_fp64(TestSetValueItemSlice)
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create_test_value_numpy_fp64(TestSetValueItemSlice2)
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create_test_value_numpy_fp64(TestSetValueItemSlice3)
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create_test_value_numpy_fp64(TestSetValueItemSlice4)
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def create_test_value_numpy_bool(parent):
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class TestValueInt(parent):
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def set_value(self):
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self.value = np.array([0])
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def set_dtype(self):
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self.dtype = "bool"
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cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyBool")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_numpy_bool(TestSetValueItemInt)
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create_test_value_numpy_bool(TestSetValueItemSlice)
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create_test_value_numpy_bool(TestSetValueItemSlice2)
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create_test_value_numpy_bool(TestSetValueItemSlice3)
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create_test_value_numpy_bool(TestSetValueItemSlice4)
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# 2.3 value is a Paddle Tensor (int32, int64, float32, float64, bool)
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def create_test_value_tensor_int32(parent):
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class TestValueInt(parent):
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def set_dtype(self):
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self.dtype = "int32"
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def _call_setitem(self, x):
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value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
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x[0, 1] = value
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def _get_answer(self):
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self.data[0, 1] = 3
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cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorInt32")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_tensor_int32(TestSetValueItemInt)
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create_test_value_tensor_int32(TestSetValueItemSlice)
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create_test_value_tensor_int32(TestSetValueItemSlice2)
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create_test_value_tensor_int32(TestSetValueItemSlice3)
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create_test_value_tensor_int32(TestSetValueItemSlice4)
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def create_test_value_tensor_int64(parent):
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class TestValueInt(parent):
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def set_dtype(self):
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self.dtype = "int64"
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def _call_setitem(self, x):
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value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
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x[0, 1] = value
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def _get_answer(self):
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self.data[0, 1] = 3
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cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorInt64")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_tensor_int64(TestSetValueItemInt)
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create_test_value_tensor_int64(TestSetValueItemSlice)
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create_test_value_tensor_int64(TestSetValueItemSlice2)
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create_test_value_tensor_int64(TestSetValueItemSlice3)
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create_test_value_tensor_int64(TestSetValueItemSlice4)
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def create_test_value_tensor_fp32(parent):
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class TestValueInt(parent):
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def set_dtype(self):
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self.dtype = "float32"
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def _call_setitem(self, x):
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value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
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x[0, 1] = value
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def _get_answer(self):
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self.data[0, 1] = 3
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cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorFp32")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_tensor_fp32(TestSetValueItemInt)
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create_test_value_tensor_fp32(TestSetValueItemSlice)
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create_test_value_tensor_fp32(TestSetValueItemSlice2)
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create_test_value_tensor_fp32(TestSetValueItemSlice3)
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create_test_value_tensor_fp32(TestSetValueItemSlice4)
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def create_test_value_tensor_fp64(parent):
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class TestValueInt(parent):
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def set_dtype(self):
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self.dtype = "float64"
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def _call_setitem(self, x):
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value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
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x[0, 1] = value
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def _get_answer(self):
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self.data[0, 1] = 3
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cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorFp64")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_tensor_fp64(TestSetValueItemInt)
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create_test_value_tensor_fp64(TestSetValueItemSlice)
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create_test_value_tensor_fp64(TestSetValueItemSlice2)
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create_test_value_tensor_fp64(TestSetValueItemSlice3)
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create_test_value_tensor_fp64(TestSetValueItemSlice4)
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def create_test_value_tensor_bool(parent):
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class TestValueInt(parent):
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def set_dtype(self):
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self.dtype = "bool"
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def _call_setitem(self, x):
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value = paddle.full(shape=[1], fill_value=False, dtype=self.dtype)
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x[0, 1] = value
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def _get_answer(self):
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self.data[0, 1] = False
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cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorBool")
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TestValueInt.__name__ = cls_name
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globals()[cls_name] = TestValueInt
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create_test_value_tensor_bool(TestSetValueItemInt)
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create_test_value_tensor_bool(TestSetValueItemSlice)
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create_test_value_tensor_bool(TestSetValueItemSlice2)
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create_test_value_tensor_bool(TestSetValueItemSlice3)
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create_test_value_tensor_bool(TestSetValueItemSlice4)
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# 3. Test different shape of value
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class TestSetValueValueShape1(TestSetValueApi):
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def set_value(self):
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self.value = np.array([3, 4, 5, 6]) # shape is (4,)
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def _call_setitem(self, x):
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x[0] = self.value
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def _get_answer(self):
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self.data[0] = self.value
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class TestSetValueValueShape2(TestSetValueApi):
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def set_value(self):
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self.value = np.array([[3, 4, 5, 6]]) # shape is (1,4)
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def _call_setitem(self, x):
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x[0:1] = self.value
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def _get_answer(self):
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self.data[0:1] = self.value
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class TestSetValueValueShape3(TestSetValueApi):
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def set_value(self):
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self.value = np.array(
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[[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]]) # shape is (3,4)
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def _call_setitem(self, x):
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x[0] = self.value
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def _get_answer(self):
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self.data[0] = self.value
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class TestSetValueValueShape4(TestSetValueApi):
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def set_value(self):
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self.value = np.array(
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[[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]]).astype(
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self.dtype) # shape is (3,4)
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def _call_setitem(self, x):
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x[0] = paddle.assign(self.value) # x is Paddle.Tensor
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def _get_answer(self):
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self.data[0] = self.value
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# 4. Test error
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class TestError(TestSetValueBase):
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def _value_type_error(self):
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with self.assertRaisesRegexp(
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TypeError,
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"Only support to assign an integer, float, numpy.ndarray or paddle.Tensor"
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):
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x = paddle.ones(shape=self.shape, dtype=self.dtype)
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value = [1]
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x[0] = value
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def _dtype_error(self):
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with self.assertRaisesRegexp(
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TypeError,
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"When assign a numpy.ndarray, integer or float to a paddle.Tensor, "
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):
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y = paddle.ones(shape=self.shape, dtype="float16")
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y[0] = 1
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def _step_error(self):
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with self.assertRaisesRegexp(ValueError, "only support step is 1"):
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x = paddle.ones(shape=self.shape, dtype=self.dtype)
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x[0:1:2] = self.value
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def _broadcast_mismatch(self):
|
|
program = paddle.static.Program()
|
|
with paddle.static.program_guard(program):
|
|
x = paddle.ones(shape=self.shape, dtype=self.dtype)
|
|
value = np.array([3, 4, 5, 6, 7])
|
|
x[0] = value
|
|
exe = paddle.static.Executor(paddle.CPUPlace())
|
|
with self.assertRaisesRegexp(ValueError,
|
|
"Broadcast dimension mismatch."):
|
|
exe.run(program)
|
|
|
|
def test_error(self):
|
|
with paddle.static.program_guard(self.program):
|
|
self._value_type_error()
|
|
self._dtype_error()
|
|
self._step_error()
|
|
self._broadcast_mismatch()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|