# Copyright (c) 2020, Fabio Muratore, Honda Research Institute Europe GmbH, and
# Technical University of Darmstadt.
# All rights reserved.
#
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# notice, this list of conditions and the following disclaimer.
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# documentation and/or other materials provided with the distribution.
# 3. Neither the name of Fabio Muratore, Honda Research Institute Europe GmbH,
# or Technical University of Darmstadt, nor the names of its contributors may
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#
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import pytest
import torch as to
from pyrado.utils.tensor import insert_tensor_col, stack_tensor_dict_list, stack_tensor_list
[docs]def test_stack_tensors():
tensors = [
to.tensor([1, 2, 3]),
to.tensor([2, 3, 4]),
to.tensor([4, 5, 6]),
]
stack = stack_tensor_list(tensors)
to.testing.assert_allclose(
stack,
to.tensor(
[
[1, 2, 3],
[2, 3, 4],
[4, 5, 6],
]
),
)
[docs]def test_stack_tensors_scalar():
tensors = [1, 2, 3]
stack = stack_tensor_list(tensors)
to.testing.assert_allclose(stack, to.tensor([1, 2, 3]))
[docs]def test_stack_tensor_dicts():
tensors = [
{"multi": [1, 2], "single": 1},
{"multi": [3, 4], "single": 2},
{"multi": [5, 6], "single": 3},
]
stack = stack_tensor_dict_list(tensors)
to.testing.assert_allclose(stack["single"], to.tensor([1, 2, 3]))
to.testing.assert_allclose(stack["multi"], to.tensor([[1, 2], [3, 4], [5, 6]]))
[docs]@pytest.mark.parametrize(
"orig, col",
[
(to.rand((1, 1)), to.zeros(1, 1)),
(to.rand((3, 3)), to.zeros(3, 1)),
],
ids=["1x1", "3x3"],
)
def test_insert_tensor_col(orig, col):
for col_idx in range(orig.shape[1] + 1): # also check appending case
result = insert_tensor_col(orig, col_idx, col)
# Check number of rows and columns
assert orig.shape[0] == result.shape[0]
assert orig.shape[1] == result.shape[1] - 1
# Check the values
assert to.all(result[:, col_idx] == col)