codespell commit

benchmarks/benchmark.py

@@ -8,10 +8,12 @@
 def setup_backends():
     if jax:
         from jax.config import config
+
         config.update("jax_enable_x64", True)
 
     if tf:
         from tensorflow.python.ops.numpy_ops import np_config
+
         np_config.enable_numpy_behavior()
 
 
@@ -36,10 +38,7 @@ def exec_bench(setup, tested_function, param_list, n_runs, warmup_runs):
             print(nx, param_list[i])
             args = inputs[i]
             results_nx = nx._bench(
-                tested_function,
-                *args,
-                n_runs=n_runs,
-                warmup_runs=warmup_runs
+                tested_function, *args, n_runs=n_runs, warmup_runs=warmup_runs
             )
             gc.collect()
             results_nx_with_param_in_key = dict()
@@ -64,10 +63,11 @@ def convert_to_html_table(results, param_name, main_title=None, comments=None):
     assert cpus_cols + gpus_cols == len(devices_names)
 
     if main_title is not None:
-        string += f'<tr><th align="center" colspan="{length}">{str(main_title)}</th></tr>\n'
+        string += (
+            f'<tr><th align="center" colspan="{length}">{str(main_title)}</th></tr>\n'
+        )
 
     for i, bitsize in enumerate(bitsizes):
-
         if i != 0:
             string += f'<tr><td colspan="{length}">&nbsp;</td></tr>\n'
 

benchmarks/emd.py

@@ -3,11 +3,7 @@
 
 import numpy as np
 import ot
-from .benchmark import (
-    setup_backends,
-    exec_bench,
-    convert_to_html_table
-)
+from .benchmark import setup_backends, exec_bench, convert_to_html_table
 
 
 def setup(n_samples):
@@ -31,10 +27,12 @@ def setup(n_samples):
         tested_function=lambda a, M: ot.emd(a, a, M),
         param_list=param_list,
         n_runs=n_runs,
-        warmup_runs=warmup_runs
+        warmup_runs=warmup_runs,
+    )
+    print(
+        convert_to_html_table(
+            results,
+            param_name="Sample size",
+            main_title=f"EMD - Averaged on {n_runs} runs",
+        )
     )
-    print(convert_to_html_table(
-        results,
-        param_name="Sample size",
-        main_title=f"EMD - Averaged on {n_runs} runs"
-    ))

benchmarks/sinkhorn_knopp.py

@@ -3,11 +3,7 @@
 
 import numpy as np
 import ot
-from .benchmark import (
-    setup_backends,
-    exec_bench,
-    convert_to_html_table
-)
+from .benchmark import setup_backends, exec_bench, convert_to_html_table
 
 
 def setup(n_samples):
@@ -33,10 +29,12 @@ def setup(n_samples):
         tested_function=lambda *args: ot.bregman.sinkhorn(*args, reg=1, stopThr=1e-7),
         param_list=param_list,
         n_runs=n_runs,
-        warmup_runs=warmup_runs
+        warmup_runs=warmup_runs,
+    )
+    print(
+        convert_to_html_table(
+            results,
+            param_name="Sample size",
+            main_title=f"Sinkhorn Knopp - Averaged on {n_runs} runs",
+        )
     )
-    print(convert_to_html_table(
-        results,
-        param_name="Sample size",
-        main_title=f"Sinkhorn Knopp - Averaged on {n_runs} runs"
-    ))

docs/nb_run_conv

@@ -9,18 +9,17 @@ Created on Fri Sep  1 16:43:45 2017
 @author: rflamary
 """
 
-import sys
 import json
 import glob
 import hashlib
 import subprocess
 
 import os
 
-cache_file = 'cache_nbrun'
+cache_file = "cache_nbrun"
 
-path_doc = 'source/auto_examples/'
-path_nb = '../notebooks/'
+path_doc = "source/auto_examples/"
+path_nb = "../notebooks/"
 
 
 def load_json(fname):
@@ -34,7 +33,7 @@ def load_json(fname):
 
 
 def save_json(fname, nb):
-    f = open(fname, 'w')
+    f = open(fname, "w")
     f.write(json.dumps(nb))
     f.close()
 
@@ -60,22 +59,45 @@ def to_update(fname, cache):
 
 
 def update(fname, cache):
-
-    # jupyter nbconvert --to notebook --execute mynotebook.ipynb --output targte
-    subprocess.check_call(['cp', path_doc + fname, path_nb])
-    print(' '.join(['jupyter', 'nbconvert', '--to', 'notebook', '--ExecutePreprocessor.timeout=600', '--execute', path_nb + fname, '--inplace']))
-    subprocess.check_call(['jupyter', 'nbconvert', '--to', 'notebook', '--ExecutePreprocessor.timeout=600', '--execute', path_nb + fname, '--inplace'])
+    # jupyter nbconvert --to notebook --execute mynotebook.ipynb --output target
+    subprocess.check_call(["cp", path_doc + fname, path_nb])
+    print(
+        " ".join(
+            [
+                "jupyter",
+                "nbconvert",
+                "--to",
+                "notebook",
+                "--ExecutePreprocessor.timeout=600",
+                "--execute",
+                path_nb + fname,
+                "--inplace",
+            ]
+        )
+    )
+    subprocess.check_call(
+        [
+            "jupyter",
+            "nbconvert",
+            "--to",
+            "notebook",
+            "--ExecutePreprocessor.timeout=600",
+            "--execute",
+            path_nb + fname,
+            "--inplace",
+        ]
+    )
     cache[fname] = md5(path_doc + fname)
 
 
 cache = load_json(cache_file)
 
-lst_file = glob.glob(path_doc + '*.ipynb')
+lst_file = glob.glob(path_doc + "*.ipynb")
 
 lst_file = [os.path.basename(name) for name in lst_file]
 
 for fname in lst_file:
     if to_update(fname, cache):
-        print('Updating file: {}'.format(fname))
+        print("Updating file: {}".format(fname))
         update(fname, cache)
         save_json(cache_file, cache)

docs/rtd/conf.py

@@ -1,6 +1,6 @@
 from recommonmark.parser import CommonMarkParser
 
-source_parsers = {'.md': CommonMarkParser}
+source_parsers = {".md": CommonMarkParser}
 
-source_suffix = ['.md']
-master_doc = 'index'
+source_suffix = [".md"]
+master_doc = "index"