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Switch Python indentation from 2 spaces to 4 spaces. (#726)

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* 4 space indentation for actor.py.

* 4 space indentation for worker.py.

* 4 space indentation for more files.

* 4 space indentation for some test files.

* Check indentation in Travis.

* 4 space indentation for some rl files.

* Fix failure test.

* Fix multi_node_test.

* 4 space indentation for more files.

* 4 space indentation for remaining files.

* Fixes.
This commit is contained in:
Robert Nishihara
2017-07-13 14:53:57 -07:00
committed by Philipp Moritz
parent 310ba82131
commit e0867c8845
100 changed files with 16686 additions and 16189 deletions
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python/ray/utils.py
+31 -30
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@@ -11,51 +11,52 @@ import ray.local_scheduler
def random_string():
"""Generate a random string to use as an ID.
"""Generate a random string to use as an ID.
Note that users may seed numpy, which could cause this function to generate
duplicate IDs. Therefore, we need to seed numpy ourselves, but we can't
interfere with the state of the user's random number generator, so we extract
the state of the random number generator and reset it after we are done.
Note that users may seed numpy, which could cause this function to generate
duplicate IDs. Therefore, we need to seed numpy ourselves, but we can't
interfere with the state of the user's random number generator, so we
extract the state of the random number generator and reset it after we are
done.
TODO(rkn): If we want to later guarantee that these are generated in a
deterministic manner, then we will need to make some changes here.
TODO(rkn): If we want to later guarantee that these are generated in a
deterministic manner, then we will need to make some changes here.
Returns:
A random byte string of length 20.
"""
# Get the state of the numpy random number generator.
numpy_state = np.random.get_state()
# Try to use true randomness.
np.random.seed(None)
# Generate the random ID.
random_id = np.random.bytes(20)
# Reset the state of the numpy random number generator.
np.random.set_state(numpy_state)
return random_id
Returns:
A random byte string of length 20.
"""
# Get the state of the numpy random number generator.
numpy_state = np.random.get_state()
# Try to use true randomness.
np.random.seed(None)
# Generate the random ID.
random_id = np.random.bytes(20)
# Reset the state of the numpy random number generator.
np.random.set_state(numpy_state)
return random_id
def decode(byte_str):
"""Make this unicode in Python 3, otherwise leave it as bytes."""
if sys.version_info >= (3, 0):
return byte_str.decode("ascii")
else:
return byte_str
"""Make this unicode in Python 3, otherwise leave it as bytes."""
if sys.version_info >= (3, 0):
return byte_str.decode("ascii")
else:
return byte_str
def binary_to_object_id(binary_object_id):
return ray.local_scheduler.ObjectID(binary_object_id)
return ray.local_scheduler.ObjectID(binary_object_id)
def binary_to_hex(identifier):
hex_identifier = binascii.hexlify(identifier)
if sys.version_info >= (3, 0):
hex_identifier = hex_identifier.decode()
return hex_identifier
hex_identifier = binascii.hexlify(identifier)
if sys.version_info >= (3, 0):
hex_identifier = hex_identifier.decode()
return hex_identifier
def hex_to_binary(hex_identifier):
return binascii.unhexlify(hex_identifier)
return binascii.unhexlify(hex_identifier)
FunctionProperties = collections.namedtuple("FunctionProperties",