🎨 ⬆️ XP-168 update setup.py

xaynetwork · Dec 18, 2019 · 97c1df4 · 97c1df4
1 parent a60718e
commit 97c1df4
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Showing 2 changed files with 20 additions and 17 deletions.
diff --git a/setup.py b/setup.py
@@ -64,12 +64,12 @@ def run(self):
 # License comments according to `pip-licenses`
 
 install_requires = [
-    "typing-extensions~=3.7",  # PSF
-    "numpy~=1.15",  # BSD
-    "absl-py~=0.8",  # Apache 2.0
-    "grpcio~=1.23",  # Apache License 2.0
-    "protobuf~=3.9",  # 3-Clause BSD License
-    "numproto~=0.3",  # Apache License 2.0
+    "typing-extensions==3.7.4.1",  # PSF
+    "numpy==1.15",  # BSD
+    "absl-py==0.8",  # Apache 2.0
+    "grpcio==1.23",  # Apache License 2.0
+    "protobuf==3.9",  # 3-Clause BSD License
+    "numproto==0.3",  # Apache License 2.0
     "requests==2.22.0",  # Apache 2.0  # TODO(XP-185) remove
     "tensorflow==1.14.0",  # Apache 2.0  # TODO(XP-131) remove
     "structlog==19.2.0",  # Apache License 2.0
@@ -86,24 +86,24 @@ def run(self):
 gpu_require = ["tensorflow-gpu==1.14.0"]  # Apache 2.0
 
 dev_require = [
-    "grpcio-tools~=1.23",  # Apache License 2.0
-    "black==19.3b0",  # MIT
-    "mypy==0.720",  # MIT License
+    "grpcio-tools==1.23",  # Apache License 2.0
+    "black==19.10b0",  # MIT
+    "mypy==0.760",  # MIT License
     "pylint==2.3.1",  # GPL
-    "astroid<=2.2.5",  # LGPL
-    "isort==4.3.20",  # MIT
+    "astroid==2.2.5",  # LGPL
+    "isort==4.3.21",  # MIT
     "rope==0.14.0",  # GNU GPL
     "pip-licenses==1.15.2",  # MIT License
-    "mypy-protobuf==1.15",  # Apache License 2.0
+    "mypy-protobuf==1.16",  # Apache License 2.0
     "twine==2.0.0",  # Apache License 2.0
     "wheel==0.33.6",  # MIT
 ]
 
 examples_require = ["tensorflow==1.14.0"]  # Apache 2.0
 
 tests_require = [
-    "pytest==4.6.2",  # MIT license
-    "pytest-cov==2.7.1",  # MIT
+    "pytest==5.3.2",  # MIT license
+    "pytest-cov==2.8.1",  # MIT
     "pytest-watch==4.2.0",  # MIT
 ]
 

diff --git a/xain_fl/fl/coordinator/coordinator.py b/xain_fl/fl/coordinator/coordinator.py
@@ -143,9 +143,12 @@ def fit_round(
             if str(participant.cid) in indices
         ]
         # Collect training results from the participants of this round
-        theta_updates, histories, opt_configs, train_metrics = self.train_local_concurrently(
-            theta, participants, E
-        )
+        (
+            theta_updates,
+            histories,
+            opt_configs,
+            train_metrics,
+        ) = self.train_local_concurrently(theta, participants, E)
         # Aggregate training results
         theta_prime = self.aggregator.aggregate(theta_updates)
         # Update own model parameters