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483026f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 | # Copyright 2022 NNAISENSE SA
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from copy import copy, deepcopy
import numpy as np
import pytest
from evotorch.tools import clone
from evotorch.tools import immutable as imm
from evotorch.tools import make_tensor, storage_ptr
from evotorch.tools.objectarray import ObjectArray
def test_making():
# Make a new ObjectArray with the help of `make_tensor(...)`
objs = make_tensor(["a", "b"], dtype=object)
# The result must be an ObjectArray
assert isinstance(objs, ObjectArray)
# The elements must be "a" and "b"
assert len(objs) == 2
assert objs[0] == "a"
assert objs[1] == "b"
def test_sharing_memory():
# Make a new ObjectArray of 10 elements
x = ObjectArray(10)
# Fill the ObjectArray with 0, 1, ... 9.
x[:] = range(10)
# Make a new ObjectArray which is the slice of the first one
y = x[3:5]
# The two tensors should be sharing memory
assert storage_ptr(x) == storage_ptr(y)
# Change the elements of y
y[:] = [0, 0]
# x should be affected by the change as well
assert x[3] == 0
assert x[4] == 0
def test_cloning():
def _got_same_length_same_values(a, b):
n = len(a)
assert n == len(b)
for i in range(n):
assert a[i] == b[i]
def _got_same_length_different_values(a, b):
n = len(a)
assert n == len(b)
for i in range(n):
assert a[i] != b[i]
# Make a new ObjectArray of 10 elements
x = ObjectArray(10)
# Fill the ObjectArray with zeros
x[:] = [0 for _ in range(10)]
# Make a copy of the original tensor
y = copy(x)
_got_same_length_same_values(x, y)
# When we change the copy, the original should NOT be updated
y[:] = [1 for _ in range(10)]
_got_same_length_different_values(x, y)
# Make a deepcopy of the original tensor
y = deepcopy(x)
_got_same_length_same_values(x, y)
# When we change the deepcopy, the original should NOT be updated
y[:] = [1 for _ in range(10)]
_got_same_length_different_values(x, y)
# Make a clone of the original tensor
y = x.clone()
_got_same_length_same_values(x, y)
# When we change the clone, the original should NOT be updated
y[:] = [1 for _ in range(10)]
_got_same_length_different_values(x, y)
def test_cloning2():
# Make a new ObjectArray and fill it with lists
x = ObjectArray(2)
x[0] = [1, 2]
x[1] = [3, 4]
# Make a clone of the original ObjectArray
y = x.clone()
# The elements must be equal
assert x[0] == y[0]
assert x[1] == y[1]
# But those elements must NOT be the same objects in memory
assert x[0] is not y[0]
assert x[1] is not y[0]
def test_immutability():
# Prepare data to put into an ObjectArray
a = set([1, 2])
b = {"x": 3, "y": [4, 5], "z": [6, 7]}
# Make a new ObjectArray
objs = make_tensor([a, b], dtype=object)
# The elements in the ObjectArray instance must be equal to the originals
assert objs[0] == a
assert objs[1] == b
# The elements in the ObjectArray must be the immutable counterparts of their originals
assert isinstance(objs[0], imm.ImmutableSet)
assert isinstance(objs[1], imm.ImmutableDict)
assert isinstance(objs[1]["y"], imm.ImmutableList)
assert isinstance(objs[1]["z"], imm.ImmutableList)
# An ObjectArray can be converted to a numpy array
objs2 = objs.numpy()
assert isinstance(objs2, np.ndarray)
assert objs2.dtype == np.dtype(object)
assert objs2[0] == a
assert objs2[1] == b
# When converted to a numpy array, everything is mutable again
assert isinstance(objs2[0], set)
assert isinstance(objs2[1], dict)
assert isinstance(objs2[1]["y"], list)
assert isinstance(objs2[1]["z"], list)
# The immutable elements in the ObjectArray cannot be modified
with pytest.raises(AttributeError):
objs[0].add(0) # An ImmutableSet does not have an `add` method
with pytest.raises(TypeError):
objs[1]["x"] = 30 # An ImmutableDict does not support item assignment
with pytest.raises(AttributeError):
objs[1]["y"].append(50) # An ImmutableList does not have an `append` method
with pytest.raises(TypeError):
objs[1]["y"][0] = 50 # An ImmutableList does not support item assignment
def test_read_only_object_tensor():
# Make a new ObjectArray
objs = make_tensor([1, 2, 3], dtype=object)
# Create a read-only view to the first ObjectArray
ro = objs.get_read_only_view()
# The two ObjectArray must share memory
assert storage_ptr(objs) == storage_ptr(ro)
# The two ObjectArray instances must be equal, elementwise
assert len(objs) == len(ro)
for i in range(len(objs)):
objs[i] == ro[i]
# The read-only ObjectArray cannot be modified
for i in range(len(ro)):
with pytest.raises(ValueError):
ro[i] = 10
# The original one can be changed and the read-only view will be affected
objs[0] = 10
assert ro[0] == 10
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