Run flake8 in Travis and make code PEP8 compliant. (#387)

python/ray/experimental/array/remote/core.py

@@ -5,82 +5,97 @@ from __future__ import print_function
 import numpy as np
 import ray
 
-__all__ = ["zeros", "zeros_like", "ones", "eye", "dot", "vstack", "hstack", "subarray", "copy", "tril", "triu", "diag", "transpose", "add", "subtract", "sum", "shape", "sum_list"]
 
 @ray.remote
 def zeros(shape, dtype_name="float", order="C"):
   return np.zeros(shape, dtype=np.dtype(dtype_name), order=order)
 
+
 @ray.remote
 def zeros_like(a, dtype_name="None", order="K", subok=True):
   dtype_val = None if dtype_name == "None" else np.dtype(dtype_name)
   return np.zeros_like(a, dtype=dtype_val, order=order, subok=subok)
 
+
 @ray.remote
 def ones(shape, dtype_name="float", order="C"):
   return np.ones(shape, dtype=np.dtype(dtype_name), order=order)
 
+
 @ray.remote
 def eye(N, M=-1, k=0, dtype_name="float"):
   M = N if M == -1 else M
   return np.eye(N, M=M, k=k, dtype=np.dtype(dtype_name))
 
+
 @ray.remote
 def dot(a, b):
   return np.dot(a, b)
 
+
 @ray.remote
 def vstack(*xs):
   return np.vstack(xs)
 
+
 @ray.remote
 def hstack(*xs):
   return np.hstack(xs)
 
-# TODO(rkn): instead of this, consider implementing slicing
+
+# TODO(rkn): Instead of this, consider implementing slicing.
+# TODO(rkn): Be consistent about using "index" versus "indices".
 @ray.remote
-def subarray(a, lower_indices, upper_indices): # TODO(rkn): be consistent about using "index" versus "indices"
+def subarray(a, lower_indices, upper_indices):
   return a[[slice(l, u) for (l, u) in zip(lower_indices, upper_indices)]]
 
+
 @ray.remote
 def copy(a, order="K"):
   return np.copy(a, order=order)
 
+
 @ray.remote
 def tril(m, k=0):
   return np.tril(m, k=k)
 
+
 @ray.remote
 def triu(m, k=0):
   return np.triu(m, k=k)
 
+
 @ray.remote
 def diag(v, k=0):
   return np.diag(v, k=k)
 
+
 @ray.remote
 def transpose(a, axes=[]):
   axes = None if axes == [] else axes
   return np.transpose(a, axes=axes)
 
+
 @ray.remote
 def add(x1, x2):
   return np.add(x1, x2)
 
+
 @ray.remote
 def subtract(x1, x2):
   return np.subtract(x1, x2)
 
+
 @ray.remote
 def sum(x, axis=-1):
   return np.sum(x, axis=axis if axis != -1 else None)
 
+
 @ray.remote
 def shape(a):
   return np.shape(a)
 
-# We use Any to allow different numerical types as well as numpy arrays.
-# TODO(rkn):this isn't in the numpy API, so be careful about exposing this.
+
 @ray.remote
 def sum_list(*xs):
   return np.sum(xs, axis=0)