Automatic Formatting.

docs/source/conf.py

@@ -12,9 +12,8 @@
 #
 import os
 import sys
-sys.path.insert(0, os.path.abspath("../../"))
 
-import sphinx_rtd_theme
+sys.path.insert(0, os.path.abspath("../../"))
 
 # -- Project information -----------------------------------------------------
 
@@ -128,15 +127,12 @@ latex_elements = {
     # The paper size ("letterpaper" or "a4paper").
     #
     # "papersize": "letterpaper",
-
     # The font size ("10pt", "11pt" or "12pt").
     #
     # "pointsize": "10pt",
-
     # Additional stuff for the LaTeX preamble.
     #
     # "preamble": "",
-
     # Latex figure (float) alignment
     #
     # "figure_align": "htbp",
@@ -146,15 +142,21 @@ latex_elements = {
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, "prototorch.tex", "ProtoTorch Documentation",
-     "Jensun Ravichandran", "manual"),
+    (
+        master_doc,
+        "prototorch.tex",
+        "ProtoTorch Documentation",
+        "Jensun Ravichandran",
+        "manual",
+    ),
 ]
 
 # -- Options for manual page output ---------------------------------------
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [(master_doc, "ProtoTorch", "ProtoTorch Documentation", [author], 1)]
+man_pages = [(master_doc, "ProtoTorch", "ProtoTorch Documentation", [author],
+              1)]
 
 # -- Options for Texinfo output -------------------------------------------
 
@@ -162,9 +164,15 @@ man_pages = [(master_doc, "ProtoTorch", "ProtoTorch Documentation", [author], 1)
 # (source start file, target name, title, author,
 #  dir menu entry, description, category)
 texinfo_documents = [
-    (master_doc, "prototorch", "ProtoTorch Documentation", author, "prototorch",
-     "Prototype-based machine learning in PyTorch.",
-     "Miscellaneous"),
+    (
+        master_doc,
+        "prototorch",
+        "ProtoTorch Documentation",
+        author,
+        "prototorch",
+        "Prototype-based machine learning in PyTorch.",
+        "Miscellaneous",
+    ),
 ]
 
 # Example configuration for intersphinx: refer to the Python standard library.