135 lines
5.2 KiB
Python
135 lines
5.2 KiB
Python
# Copyright 2019 The TensorFlow 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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# ==============================================================================
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"""Registrations for LinearOperator.adjoint."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from tensorflow.python.ops import math_ops
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from tensorflow.python.ops.linalg import linear_operator
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from tensorflow.python.ops.linalg import linear_operator_adjoint
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from tensorflow.python.ops.linalg import linear_operator_algebra
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from tensorflow.python.ops.linalg import linear_operator_block_diag
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from tensorflow.python.ops.linalg import linear_operator_circulant
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from tensorflow.python.ops.linalg import linear_operator_diag
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from tensorflow.python.ops.linalg import linear_operator_householder
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from tensorflow.python.ops.linalg import linear_operator_identity
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from tensorflow.python.ops.linalg import linear_operator_kronecker
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# By default, return LinearOperatorAdjoint which switched the .matmul
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# and .solve methods.
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@linear_operator_algebra.RegisterAdjoint(linear_operator.LinearOperator)
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def _adjoint_linear_operator(linop):
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return linear_operator_adjoint.LinearOperatorAdjoint(
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linop,
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is_non_singular=linop.is_non_singular,
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is_self_adjoint=linop.is_self_adjoint,
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is_positive_definite=linop.is_positive_definite,
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is_square=linop.is_square)
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_adjoint.LinearOperatorAdjoint)
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def _adjoint_adjoint_linear_operator(linop):
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return linop.operator
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_identity.LinearOperatorIdentity)
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def _adjoint_identity(identity_operator):
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return identity_operator
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_identity.LinearOperatorScaledIdentity)
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def _adjoint_scaled_identity(identity_operator):
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multiplier = identity_operator.multiplier
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if multiplier.dtype.is_complex:
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multiplier = math_ops.conj(multiplier)
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return linear_operator_identity.LinearOperatorScaledIdentity(
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num_rows=identity_operator._num_rows, # pylint: disable=protected-access
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multiplier=multiplier,
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is_non_singular=identity_operator.is_non_singular,
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is_self_adjoint=identity_operator.is_self_adjoint,
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is_positive_definite=identity_operator.is_positive_definite,
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is_square=True)
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_diag.LinearOperatorDiag)
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def _adjoint_diag(diag_operator):
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diag = diag_operator.diag
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if diag.dtype.is_complex:
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diag = math_ops.conj(diag)
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return linear_operator_diag.LinearOperatorDiag(
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diag=diag,
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is_non_singular=diag_operator.is_non_singular,
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is_self_adjoint=diag_operator.is_self_adjoint,
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is_positive_definite=diag_operator.is_positive_definite,
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is_square=True)
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_block_diag.LinearOperatorBlockDiag)
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def _adjoint_block_diag(block_diag_operator):
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# We take the adjoint of each block on the diagonal.
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return linear_operator_block_diag.LinearOperatorBlockDiag(
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operators=[
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operator.adjoint() for operator in block_diag_operator.operators],
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is_non_singular=block_diag_operator.is_non_singular,
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is_self_adjoint=block_diag_operator.is_self_adjoint,
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is_positive_definite=block_diag_operator.is_positive_definite,
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is_square=True)
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_kronecker.LinearOperatorKronecker)
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def _adjoint_kronecker(kronecker_operator):
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# Adjoint of a Kronecker product is the Kronecker product
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# of adjoints.
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return linear_operator_kronecker.LinearOperatorKronecker(
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operators=[
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operator.adjoint() for operator in kronecker_operator.operators],
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is_non_singular=kronecker_operator.is_non_singular,
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is_self_adjoint=kronecker_operator.is_self_adjoint,
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is_positive_definite=kronecker_operator.is_positive_definite,
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is_square=True)
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_circulant.LinearOperatorCirculant)
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def _adjoint_circulant(circulant_operator):
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spectrum = circulant_operator.spectrum
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if spectrum.dtype.is_complex:
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spectrum = math_ops.conj(spectrum)
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# Conjugating the spectrum is sufficient to get the adjoint.
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return linear_operator_circulant.LinearOperatorCirculant(
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spectrum=spectrum,
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is_non_singular=circulant_operator.is_non_singular,
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is_self_adjoint=circulant_operator.is_self_adjoint,
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is_positive_definite=circulant_operator.is_positive_definite,
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is_square=True)
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@linear_operator_algebra.RegisterAdjoint(
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linear_operator_householder.LinearOperatorHouseholder)
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def _adjoint_householder(householder_operator):
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return householder_operator
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