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@michaelreneer @krzys-ostrowski @jkr26
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# Lint as: python3
# Copyright 2019, The TensorFlow Federated Authors.
#
# 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.
"""TensorFlow Federated Library."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow_federated.version import __version__ # pylint: disable=g-bad-import-order
from tensorflow_federated.python.core.api.computation_base import Computation
from tensorflow_federated.python.core.api.computation_types import FederatedType
from tensorflow_federated.python.core.api.computation_types import FunctionType
from tensorflow_federated.python.core.api.computation_types import NamedTupleType
from tensorflow_federated.python.core.api.computation_types import SequenceType
from tensorflow_federated.python.core.api.computation_types import TensorType
from tensorflow_federated.python.core.api.computation_types import to_type
from tensorflow_federated.python.core.api.computation_types import Type
from tensorflow_federated.python.core.api.computations import federated_computation
from tensorflow_federated.python.core.api.computations import tf_computation
from tensorflow_federated.python.core.api.intrinsics import federated_aggregate
from tensorflow_federated.python.core.api.intrinsics import federated_apply
from tensorflow_federated.python.core.api.intrinsics import federated_broadcast
from tensorflow_federated.python.core.api.intrinsics import federated_collect
from tensorflow_federated.python.core.api.intrinsics import federated_map
from tensorflow_federated.python.core.api.intrinsics import federated_mean
from tensorflow_federated.python.core.api.intrinsics import federated_reduce
from tensorflow_federated.python.core.api.intrinsics import federated_sum
from tensorflow_federated.python.core.api.intrinsics import federated_value
from tensorflow_federated.python.core.api.intrinsics import federated_zip
from tensorflow_federated.python.core.api.intrinsics import sequence_map
from tensorflow_federated.python.core.api.intrinsics import sequence_reduce
from tensorflow_federated.python.core.api.intrinsics import sequence_sum
from tensorflow_federated.python.core.api.placements import CLIENTS
from tensorflow_federated.python.core.api.placements import SERVER
from tensorflow_federated.python.core.api.typed_object import TypedObject
from tensorflow_federated.python.core.api.value_base import Value
from tensorflow_federated.python.core.api.values import to_value
# NOTE: These imports must happen after the API imports.
# pylint: disable=g-bad-import-order
from tensorflow_federated.python.core import framework
from tensorflow_federated.python.core import backends
from tensorflow_federated.python.core import utils
# pylint: enable=g-bad-import-order
# NOTE: These imports must happen after the Core imports.
# pylint: disable=g-bad-import-order
from tensorflow_federated.python import learning
from tensorflow_federated.python import simulation
# pylint: enable=g-bad-import-order,wildcard-import
# Used by doc generation script.
_allowed_symbols = [
"backends",
"CLIENTS",
"Computation",
"FederatedType",
"FunctionType",
"NamedTupleType",
"SERVER",
"SequenceType",
"TensorType",
"Type",
"TypedObject",
"Value",
"federated_aggregate",
"federated_apply",
"federated_broadcast",
"federated_collect",
"federated_computation",
"federated_map",
"federated_mean",
"federated_reduce",
"federated_sum",
"federated_value",
"federated_zip",
"framework",
"learning",
"sequence_map",
"sequence_reduce",
"sequence_sum",
"simulation",
"tf_computation",
"to_type",
"to_value",
"utils",
]
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