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# This code is part of a Qiskit project.
#
# (C) Copyright IBM 2022, 2023.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""
Additional optional constants.
"""
from qiskit.utils import LazyImportTester
HAS_TORCH = LazyImportTester(
{
"torch": ("cat", "einsum", "is_tensor", "nn", "optim", "sparse_coo_tensor", "Tensor"),
"torch.autograd": ("Function",),
"torch.autograd.variable": ("Variable",),
"torch.nn": (
"L1Loss",
"Linear",
"Module",
"MSELoss",
"Parameter",
),
"torch.nn.functional": (),
"torch.optim": (
"Adam",
"SGD",
),
"torch.utils.data": ("Dataset",),
},
name="PyTorch",
install="pip install 'qiskit-machine-learning[torch]'",
)
HAS_SPARSE = LazyImportTester(
{
"sparse": ("SparseArray", "COO", "DOK"),
},
name="sparse",
install="pip install 'qiskit-machine-learning[sparse]'",
)
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