forked from 626_privacy/tensorflow_privacy
Move TensorFlow v1 imports to their own __init__.py file in a new subdirectory.
PiperOrigin-RevId: 383485268
This commit is contained in:
Steve Chien
A. Unique TensorFlower
parent
beed219d20
commit
4326014a0e
6 changed files with 53 additions and 36 deletions
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@ -26,6 +26,9 @@ from tensorflow_privacy.version import __version__ # pylint: disable=g-bad-impo
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if hasattr(sys, 'skip_tf_privacy_import'): # Useful for standalone scripts.
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pass
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else:
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# TensorFlow v1 imports
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import tensorflow_privacy.v1
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# Analysis
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from tensorflow_privacy.privacy.analysis.compute_dp_sgd_privacy_lib import compute_dp_sgd_privacy
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from tensorflow_privacy.privacy.analysis.privacy_ledger import GaussianSumQueryEntry
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@ -54,7 +57,6 @@ else:
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# Estimators
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from tensorflow_privacy.privacy.estimators.dnn import DNNClassifier
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from tensorflow_privacy.privacy.estimators.v1.dnn import DNNClassifier as DNNClassifierV1
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# Keras Models
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from tensorflow_privacy.privacy.keras_models.dp_keras_model import DPModel
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@ -62,14 +64,6 @@ else:
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from tensorflow_privacy.privacy.keras_models.dp_keras_model import make_dp_model_class
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# Optimizers
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdagradGaussianOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdagradOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdamGaussianOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdamOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPGradientDescentGaussianOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPGradientDescentOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import make_optimizer_class
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_keras import DPKerasAdagradOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_keras import DPKerasAdamOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_keras import DPKerasSGDOptimizer
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@ -80,15 +74,6 @@ else:
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_keras_vectorized import VectorizedDPKerasSGDOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_keras_vectorized import make_vectorized_keras_optimizer_class
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdagradOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdamOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPSGDOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdagrad
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdam
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPSGD
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import make_vectorized_optimizer_class
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try:
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from tensorflow_privacy.privacy.bolt_on.models import BoltOnModel
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from tensorflow_privacy.privacy.bolt_on.optimizers import BoltOn
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@ -32,16 +32,11 @@ 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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import sys
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from absl import app
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from absl import flags
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from tensorflow_privacy.privacy.analysis.compute_dp_sgd_privacy_lib import compute_dp_sgd_privacy
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# Opting out of loading all sibling packages and their dependencies.
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sys.skip_tf_privacy_import = True
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FLAGS = flags.FLAGS
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flags.DEFINE_integer('N', None, 'Total number of examples')
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@ -19,13 +19,9 @@ from __future__ import division
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from __future__ import print_function
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import math
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import sys
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from absl import app
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# Opting out of loading all sibling packages and their dependencies.
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sys.skip_tf_privacy_import = True
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from tensorflow_privacy.privacy.analysis.rdp_accountant import compute_rdp # pylint: disable=g-import-not-at-top
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from tensorflow_privacy.privacy.analysis.rdp_accountant import get_privacy_spent
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@ -34,16 +34,11 @@ 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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import sys
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from absl import app
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from absl import flags
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from tensorflow_privacy.privacy.analysis.compute_noise_from_budget_lib import compute_noise
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# Opting out of loading all sibling packages and their dependencies.
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sys.skip_tf_privacy_import = True
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FLAGS = flags.FLAGS
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flags.DEFINE_integer('N', None, 'Total number of examples')
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@ -19,7 +19,6 @@ from __future__ import division
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from __future__ import print_function
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import math
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import sys
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from absl import app
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from scipy.optimize import bisect
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@ -27,9 +26,6 @@ from scipy.optimize import bisect
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from tensorflow_privacy.privacy.analysis.rdp_accountant import compute_rdp # pylint: disable=g-import-not-at-top
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from tensorflow_privacy.privacy.analysis.rdp_accountant import get_privacy_spent
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# Opting out of loading all sibling packages and their dependencies.
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sys.skip_tf_privacy_import = True
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def apply_dp_sgd_analysis(q, sigma, steps, orders, delta):
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"""Compute and print results of DP-SGD analysis."""
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50
tensorflow_privacy/v1/__init__.py
Normal file
50
tensorflow_privacy/v1/__init__.py
Normal file
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@ -0,0 +1,50 @@
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# Copyright 2020, The TensorFlow Privacy Authors.
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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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"""TensorFlow Privacy library v1 imports.
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This module includes classes designed to be compatible with TF1, based on
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`tf.compat.v1.train.Optimizer` and `tf.estimator.Estimator`.
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"""
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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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import sys
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# pylint: disable=g-import-not-at-top
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if hasattr(sys, 'skip_tf_privacy_import'): # Useful for standalone scripts.
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pass
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else:
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# Estimators
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from tensorflow_privacy.privacy.estimators.v1.dnn import DNNClassifier as DNNClassifierV1
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# Optimizers
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdagradGaussianOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdagradOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdamGaussianOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPAdamOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPGradientDescentGaussianOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import DPGradientDescentOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer import make_optimizer_class
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdagradOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdamOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPSGDOptimizer
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdagrad
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPAdam
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import VectorizedDPSGD
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from tensorflow_privacy.privacy.optimizers.dp_optimizer_vectorized import make_vectorized_optimizer_class
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