black

evil.py

@@ -10,14 +10,17 @@ def ccall(func, pass_name=False):
         key = "word"
         def arguments(): pass
     """
+
     class metaclass(type):
         def __new__(cls, name, a, d):
             d.pop("__module__", 0)
             if pass_name:
                 d["__name__"] = name
             return func(*a[1:], **d)
+
         def __call__(*a, **d):
             return func(*a, **d)
+
     return type.__new__(metaclass, func.__name__, (), {})
 
 
@@ -31,9 +34,13 @@ def pin(loc, *skip):
         these = 2
     """
     loc = dict(loc)
-    loc.pop("self").__dict__.update({k: v for k, v in loc.items() if not any(
-        s is k or
-        s is True and k.startswith("_") or
-        s is v and isinstance(s, object)
-        for s in skip
-    )})
+    loc.pop("self").__dict__.update(
+        {
+            k: v
+            for k, v in loc.items()
+            if not any(
+                s is k or s is True and k.startswith("_") or s is v and isinstance(s, object)
+                for s in skip
+            )
+        }
+    )

tf.py

@@ -5,25 +5,32 @@ from time import time
 from analysis.util import atq
 from io import BytesIO
 import h5py
-from tensorflow.python.keras.engine.saving import save_weights_to_hdf5_group, load_weights_from_hdf5_group
+from tensorflow.python.keras.engine.saving import (
+    save_weights_to_hdf5_group,
+    load_weights_from_hdf5_group,
+)
 
 from evil import pin, ccall
 
 
 from tensorflow.python.util import deprecation
+
 deprecation._PRINT_DEPRECATION_WARNINGS = False
 
 
 def last_map(func, obj, order=1):
-    return tf.concat([
-        obj[..., :-1],
-        tf.expand_dims(
-            last_map(func=func, obj=obj[..., -1], order=order - 1)
-            if 1 < order else
-            func(obj[..., -1]),
-            axis=-1
-        ),
-    ], axis=-1)
+    return tf.concat(
+        [
+            obj[..., :-1],
+            tf.expand_dims(
+                last_map(func=func, obj=obj[..., -1], order=order - 1)
+                if 1 < order
+                else func(obj[..., -1]),
+                axis=-1,
+            ),
+        ],
+        axis=-1,
+    )
 
 
 def tf_meanstd(val, **kwargs):
@@ -34,6 +41,7 @@ def tf_meanstd(val, **kwargs):
 
 # this is mostly unused ...
 
+
 class FD(dict):
     def add(self, data, dtype=None, shape=None, **kwargs):
         if shape is True:
@@ -48,7 +56,17 @@ class FD(dict):
 
 
 class Chain(object):
-    def __init__(self, __name__, loss, sumnbs=(), step=None, opt=None, train=None, ema=(1, 2, 3, 4, 5), **kwargs):
+    def __init__(
+        self,
+        __name__,
+        loss,
+        sumnbs=(),
+        step=None,
+        opt=None,
+        train=None,
+        ema=(1, 2, 3, 4, 5),
+        **kwargs
+    ):
         if step is None:
             step = tf.Variable(0, trainable=False, name="%s_step" % __name__)
         if opt is None:
@@ -88,9 +106,13 @@ class Chain(object):
             reset_ema = ema_step.initializer
             for i in ema:
                 with tf.name_scope("%s_%d" % (__name__, i)):
-                    ema = tf.train.ExponentialMovingAverage(decay=1. - tf.maximum(
-                        0.1**i, tf.exp((np.log(0.1**i) / 10.) * tf.cast(ema_step, tf.float32))
-                    ))
+                    ema = tf.train.ExponentialMovingAverage(
+                        decay=1.0
+                        - tf.maximum(
+                            0.1 ** i,
+                            tf.exp((np.log(0.1 ** i) / 10.0) * tf.cast(ema_step, tf.float32)),
+                        )
+                    )
                     _ema_ops.append(ema.apply(_ema_val.values()))
                     for key, val in _ema_val.items():
                         val = ema.average(val)
@@ -139,7 +161,9 @@ class Runner(object):
     @contextmanager
     def make(cls, path, gpuOpts={}, flush_secs=20):
         with cls.make_session(gpuOpts=gpuOpts) as sess:
-            with tf.summary.FileWriter(path, session=sess, flush_secs=flush_secs, graph=sess.graph) as writer:
+            with tf.summary.FileWriter(
+                path, session=sess, flush_secs=flush_secs, graph=sess.graph
+            ) as writer:
                 yield cls(sess, writer)
 
     @classmethod
@@ -168,11 +192,12 @@ class Confirmer(object):
                         break
                     if tnext < time():
                         tnext = time() + self.tdelay
-                        pTotal = 100. * i / its
+                        pTotal = 100.0 * i / its
                         self.task.set_progress_percentage(pTotal)
-                        self.task.set_status_message("total=%.1f%% conf=%.1f%% best=%.2e" % (
-                            pTotal, 100. * self.conf / target, self.best
-                        ))
+                        self.task.set_status_message(
+                            "total=%.1f%% conf=%.1f%% best=%.2e"
+                            % (pTotal, 100.0 * self.conf / target, self.best)
+                        )
                 if not (self.conf < target):
                     break
                 self.step += 1
@@ -216,11 +241,7 @@ class Confirmer(object):
         }
 
     def __repr__(self):
-        return "Confirmer(step=%d, best=%.3e, conf=%d)" % (
-            self.step,
-            self.best,
-            self.conf
-        )
+        return "Confirmer(step=%d, best=%.3e, conf=%d)" % (self.step, self.best, self.conf)
 
 
 class Bestie(object):