forked from 626_privacy/tensorflow_privacy
Update to allow bazel on tensorflow_privacy to work out of the box.
PiperOrigin-RevId: 225605386
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6 changed files with 6 additions and 60 deletions
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@ -1,55 +0,0 @@
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licenses(["notice"]) # Apache 2.0
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py_library(
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name = "gaussian_average_query",
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srcs = ["gaussian_average_query.py"],
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deps = [
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":private_queries",
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"@org_tensorflow//tensorflow:tensorflow_py",
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],
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)
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py_library(
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name = "dp_optimizers",
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deps = [
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":dp_adam",
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":dp_gradient_descent",
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],
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)
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py_library(
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name = "dp_adam",
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srcs = [
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"dp_adam.py",
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],
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deps = [
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":gaussian_average_query",
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"@org_tensorflow//tensorflow:tensorflow_py",
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],
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)
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py_library(
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name = "dp_gradient_descent",
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srcs = [
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"dp_gradient_descent.py",
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],
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deps = [
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":gaussian_average_query",
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"@org_tensorflow//tensorflow:tensorflow_py",
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],
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)
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py_test(
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name = "dp_optimizer_test",
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srcs = ["dp_optimizer_test.py"],
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deps = [
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":dp_optimizers",
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"@absl_py//absl/testing:parameterized",
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"@org_tensorflow//tensorflow:tensorflow_py",
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],
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)
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py_library(
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name = "private_queries",
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srcs = ["private_queries.py"],
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)
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@ -20,7 +20,7 @@ from __future__ import print_function
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import tensorflow as tf
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import tensorflow_privacy.privacy.optimizers.gaussian_average_query as ph
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import privacy.optimizers.gaussian_average_query as ph
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class DPAdamOptimizer(tf.train.AdamOptimizer):
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@ -20,7 +20,7 @@ from __future__ import print_function
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import tensorflow as tf
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import tensorflow_privacy.privacy.optimizers.gaussian_average_query as ph
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import privacy.optimizers.gaussian_average_query as ph
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class DPGradientDescentOptimizer(tf.train.GradientDescentOptimizer):
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@ -22,8 +22,8 @@ from absl.testing import parameterized
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import numpy as np
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import tensorflow as tf
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from tensorflow_privacy.privacy.optimizers import dp_adam
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from tensorflow_privacy.privacy.optimizers import dp_gradient_descent
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from privacy.optimizers import dp_adam
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from privacy.optimizers import dp_gradient_descent
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def loss(val0, val1):
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@ -23,7 +23,7 @@ import collections
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import tensorflow as tf
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from tensorflow_privacy.privacy.optimizers import private_queries
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from privacy.optimizers import private_queries
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class GaussianAverageQuery(private_queries.PrivateAverageQuery):
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1
requirements.txt
Normal file
1
requirements.txt
Normal file
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@ -0,0 +1 @@
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tensorflow
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