Commit 28f67e1e authored by Zachary Charles's avatar Zachary Charles Committed by tensorflow-copybara
Browse files

Add a `tff.learning.algorithms` component to TFF.

PiperOrigin-RevId: 410538498
parent 7ca8e258
......@@ -37,6 +37,7 @@ py_library(
":model_update_aggregator",
":model_utils",
":personalization_eval",
"//tensorflow_federated/python/learning/algorithms",
"//tensorflow_federated/python/learning/framework",
"//tensorflow_federated/python/learning/framework:optimizer_utils",
"//tensorflow_federated/python/learning/metrics",
......
......@@ -13,6 +13,7 @@
# limitations under the License.
"""Libraries for using Federated Learning algorithms."""
from tensorflow_federated.python.learning import algorithms
from tensorflow_federated.python.learning import framework
from tensorflow_federated.python.learning import metrics
from tensorflow_federated.python.learning import models
......
......@@ -13,6 +13,14 @@ package_group(
licenses(["notice"])
py_library(
name = "algorithms",
srcs = ["__init__.py"],
srcs_version = "PY3",
visibility = ["//tensorflow_federated/python/learning:__pkg__"],
deps = [":client_scheduled_federated_averaging"],
)
py_library(
name = "client_scheduled_federated_averaging",
srcs = ["client_scheduled_federated_averaging.py"],
......
......@@ -11,4 +11,6 @@
# 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.
"""Libraries for building federated learning algorithms."""
"""Libraries providing implementations of federated learning algorithms."""
from tensorflow_federated.python.learning.algorithms.client_scheduled_federated_averaging import build_client_scheduled_federated_averaging_process
......@@ -19,6 +19,10 @@ Communication-Efficient Learning of Deep Networks from Decentralized Data
H. Brendan McMahan, Eider Moore, Daniel Ramage,
Seth Hampson, Blaise Aguera y Arcas. AISTATS 2017.
https://arxiv.org/abs/1602.05629
Currently, this code is intended only as an example of how to use the building
block components of TFF's learning API to implement an algorithm that is
compatible with things like broadcast and aggregation processes.
"""
import collections
......
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