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24,500 | ray-project/ray | python/ray/services.py | create_redis_client | def create_redis_client(redis_address, password=None):
"""Create a Redis client.
Args:
The IP address, port, and password of the Redis server.
Returns:
A Redis client.
"""
redis_ip_address, redis_port = redis_address.split(":")
# For this command to work, some other client (on ... | python | def create_redis_client(redis_address, password=None):
"""Create a Redis client.
Args:
The IP address, port, and password of the Redis server.
Returns:
A Redis client.
"""
redis_ip_address, redis_port = redis_address.split(":")
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24,501 | ray-project/ray | python/ray/services.py | wait_for_redis_to_start | def wait_for_redis_to_start(redis_ip_address,
redis_port,
password=None,
num_retries=5):
"""Wait for a Redis server to be available.
This is accomplished by creating a Redis client and sending a random
command to the server... | python | def wait_for_redis_to_start(redis_ip_address,
redis_port,
password=None,
num_retries=5):
"""Wait for a Redis server to be available.
This is accomplished by creating a Redis client and sending a random
command to the server... | [
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24,502 | ray-project/ray | python/ray/services.py | _autodetect_num_gpus | def _autodetect_num_gpus():
"""Attempt to detect the number of GPUs on this machine.
TODO(rkn): This currently assumes Nvidia GPUs and Linux.
Returns:
The number of GPUs if any were detected, otherwise 0.
"""
proc_gpus_path = "/proc/driver/nvidia/gpus"
if os.path.isdir(proc_gpus_path):... | python | def _autodetect_num_gpus():
"""Attempt to detect the number of GPUs on this machine.
TODO(rkn): This currently assumes Nvidia GPUs and Linux.
Returns:
The number of GPUs if any were detected, otherwise 0.
"""
proc_gpus_path = "/proc/driver/nvidia/gpus"
if os.path.isdir(proc_gpus_path):... | [
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24,503 | ray-project/ray | python/ray/services.py | _compute_version_info | def _compute_version_info():
"""Compute the versions of Python, pyarrow, and Ray.
Returns:
A tuple containing the version information.
"""
ray_version = ray.__version__
python_version = ".".join(map(str, sys.version_info[:3]))
pyarrow_version = pyarrow.__version__
return ray_version... | python | def _compute_version_info():
"""Compute the versions of Python, pyarrow, and Ray.
Returns:
A tuple containing the version information.
"""
ray_version = ray.__version__
python_version = ".".join(map(str, sys.version_info[:3]))
pyarrow_version = pyarrow.__version__
return ray_version... | [
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24,504 | ray-project/ray | python/ray/services.py | check_version_info | def check_version_info(redis_client):
"""Check if various version info of this process is correct.
This will be used to detect if workers or drivers are started using
different versions of Python, pyarrow, or Ray. If the version
information is not present in Redis, then no check is done.
Args:
... | python | def check_version_info(redis_client):
"""Check if various version info of this process is correct.
This will be used to detect if workers or drivers are started using
different versions of Python, pyarrow, or Ray. If the version
information is not present in Redis, then no check is done.
Args:
... | [
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24,505 | ray-project/ray | python/ray/services.py | _start_redis_instance | def _start_redis_instance(executable,
modules,
port=None,
redis_max_clients=None,
num_retries=20,
stdout_file=None,
stderr_file=None,
pass... | python | def _start_redis_instance(executable,
modules,
port=None,
redis_max_clients=None,
num_retries=20,
stdout_file=None,
stderr_file=None,
pass... | [
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executable (str): Full path of the redis-server executable.
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24,506 | ray-project/ray | python/ray/services.py | start_log_monitor | def start_log_monitor(redis_address,
logs_dir,
stdout_file=None,
stderr_file=None,
redis_password=None):
"""Start a log monitor process.
Args:
redis_address (str): The address of the Redis instance.
logs_dir... | python | def start_log_monitor(redis_address,
logs_dir,
stdout_file=None,
stderr_file=None,
redis_password=None):
"""Start a log monitor process.
Args:
redis_address (str): The address of the Redis instance.
logs_dir... | [
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24,507 | ray-project/ray | python/ray/services.py | start_reporter | def start_reporter(redis_address,
stdout_file=None,
stderr_file=None,
redis_password=None):
"""Start a reporter process.
Args:
redis_address (str): The address of the Redis instance.
stdout_file: A file handle opened for writing to redire... | python | def start_reporter(redis_address,
stdout_file=None,
stderr_file=None,
redis_password=None):
"""Start a reporter process.
Args:
redis_address (str): The address of the Redis instance.
stdout_file: A file handle opened for writing to redire... | [
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stdout_file: A file handle opened for writing to redirect stdout to. If
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24,508 | ray-project/ray | python/ray/services.py | start_dashboard | def start_dashboard(redis_address,
temp_dir,
stdout_file=None,
stderr_file=None,
redis_password=None):
"""Start a dashboard process.
Args:
redis_address (str): The address of the Redis instance.
temp_dir (str): The ... | python | def start_dashboard(redis_address,
temp_dir,
stdout_file=None,
stderr_file=None,
redis_password=None):
"""Start a dashboard process.
Args:
redis_address (str): The address of the Redis instance.
temp_dir (str): The ... | [
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24,509 | ray-project/ray | python/ray/services.py | check_and_update_resources | def check_and_update_resources(num_cpus, num_gpus, resources):
"""Sanity check a resource dictionary and add sensible defaults.
Args:
num_cpus: The number of CPUs.
num_gpus: The number of GPUs.
resources: A dictionary mapping resource names to resource quantities.
Returns:
... | python | def check_and_update_resources(num_cpus, num_gpus, resources):
"""Sanity check a resource dictionary and add sensible defaults.
Args:
num_cpus: The number of CPUs.
num_gpus: The number of GPUs.
resources: A dictionary mapping resource names to resource quantities.
Returns:
... | [
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24,510 | ray-project/ray | python/ray/services.py | start_raylet | def start_raylet(redis_address,
node_ip_address,
raylet_name,
plasma_store_name,
worker_path,
temp_dir,
num_cpus=None,
num_gpus=None,
resources=None,
object_manager_po... | python | def start_raylet(redis_address,
node_ip_address,
raylet_name,
plasma_store_name,
worker_path,
temp_dir,
num_cpus=None,
num_gpus=None,
resources=None,
object_manager_po... | [
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24,511 | ray-project/ray | python/ray/services.py | build_java_worker_command | def build_java_worker_command(
java_worker_options,
redis_address,
plasma_store_name,
raylet_name,
redis_password,
temp_dir,
):
"""This method assembles the command used to start a Java worker.
Args:
java_worker_options (str): The command options for Java... | python | def build_java_worker_command(
java_worker_options,
redis_address,
plasma_store_name,
raylet_name,
redis_password,
temp_dir,
):
"""This method assembles the command used to start a Java worker.
Args:
java_worker_options (str): The command options for Java... | [
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redis_address (str): Redis address of GCS.
plasma_store_name (str): The name of the plasma store socket to connect
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24,512 | ray-project/ray | python/ray/services.py | determine_plasma_store_config | def determine_plasma_store_config(object_store_memory=None,
plasma_directory=None,
huge_pages=False):
"""Figure out how to configure the plasma object store.
This will determine which directory to use for the plasma store (e.g.,
/tmp or /d... | python | def determine_plasma_store_config(object_store_memory=None,
plasma_directory=None,
huge_pages=False):
"""Figure out how to configure the plasma object store.
This will determine which directory to use for the plasma store (e.g.,
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24,513 | ray-project/ray | python/ray/services.py | _start_plasma_store | def _start_plasma_store(plasma_store_memory,
use_valgrind=False,
use_profiler=False,
stdout_file=None,
stderr_file=None,
plasma_directory=None,
huge_pages=False,
... | python | def _start_plasma_store(plasma_store_memory,
use_valgrind=False,
use_profiler=False,
stdout_file=None,
stderr_file=None,
plasma_directory=None,
huge_pages=False,
... | [
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24,514 | ray-project/ray | python/ray/services.py | start_plasma_store | def start_plasma_store(stdout_file=None,
stderr_file=None,
object_store_memory=None,
plasma_directory=None,
huge_pages=False,
plasma_store_socket_name=None):
"""This method starts an object store proce... | python | def start_plasma_store(stdout_file=None,
stderr_file=None,
object_store_memory=None,
plasma_directory=None,
huge_pages=False,
plasma_store_socket_name=None):
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24,515 | ray-project/ray | python/ray/services.py | start_worker | def start_worker(node_ip_address,
object_store_name,
raylet_name,
redis_address,
worker_path,
temp_dir,
stdout_file=None,
stderr_file=None):
"""This method starts a worker process.
Args:
... | python | def start_worker(node_ip_address,
object_store_name,
raylet_name,
redis_address,
worker_path,
temp_dir,
stdout_file=None,
stderr_file=None):
"""This method starts a worker process.
Args:
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raylet_name (str): The socket name of the raylet server.
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24,516 | ray-project/ray | python/ray/rllib/models/model.py | restore_original_dimensions | def restore_original_dimensions(obs, obs_space, tensorlib=tf):
"""Unpacks Dict and Tuple space observations into their original form.
This is needed since we flatten Dict and Tuple observations in transit.
Before sending them to the model though, we should unflatten them into
Dicts or Tuples of tensors... | python | def restore_original_dimensions(obs, obs_space, tensorlib=tf):
"""Unpacks Dict and Tuple space observations into their original form.
This is needed since we flatten Dict and Tuple observations in transit.
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24,517 | ray-project/ray | python/ray/autoscaler/aws/node_provider.py | to_aws_format | def to_aws_format(tags):
"""Convert the Ray node name tag to the AWS-specific 'Name' tag."""
if TAG_RAY_NODE_NAME in tags:
tags["Name"] = tags[TAG_RAY_NODE_NAME]
del tags[TAG_RAY_NODE_NAME]
return tags | python | def to_aws_format(tags):
"""Convert the Ray node name tag to the AWS-specific 'Name' tag."""
if TAG_RAY_NODE_NAME in tags:
tags["Name"] = tags[TAG_RAY_NODE_NAME]
del tags[TAG_RAY_NODE_NAME]
return tags | [
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24,518 | ray-project/ray | python/ray/autoscaler/aws/node_provider.py | AWSNodeProvider._node_tag_update_loop | def _node_tag_update_loop(self):
""" Update the AWS tags for a cluster periodically.
The purpose of this loop is to avoid excessive EC2 calls when a large
number of nodes are being launched simultaneously.
"""
while True:
self.tag_cache_update_event.wait()
... | python | def _node_tag_update_loop(self):
""" Update the AWS tags for a cluster periodically.
The purpose of this loop is to avoid excessive EC2 calls when a large
number of nodes are being launched simultaneously.
"""
while True:
self.tag_cache_update_event.wait()
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24,519 | ray-project/ray | python/ray/autoscaler/aws/node_provider.py | AWSNodeProvider._get_node | def _get_node(self, node_id):
"""Refresh and get info for this node, updating the cache."""
self.non_terminated_nodes({}) # Side effect: updates cache
if node_id in self.cached_nodes:
return self.cached_nodes[node_id]
# Node not in {pending, running} -- retry with a point ... | python | def _get_node(self, node_id):
"""Refresh and get info for this node, updating the cache."""
self.non_terminated_nodes({}) # Side effect: updates cache
if node_id in self.cached_nodes:
return self.cached_nodes[node_id]
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24,520 | ray-project/ray | python/ray/tune/trial.py | ExportFormat.validate | def validate(export_formats):
"""Validates export_formats.
Raises:
ValueError if the format is unknown.
"""
for i in range(len(export_formats)):
export_formats[i] = export_formats[i].strip().lower()
if export_formats[i] not in [
Ex... | python | def validate(export_formats):
"""Validates export_formats.
Raises:
ValueError if the format is unknown.
"""
for i in range(len(export_formats)):
export_formats[i] = export_formats[i].strip().lower()
if export_formats[i] not in [
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24,521 | ray-project/ray | python/ray/tune/trial.py | Trial.init_logger | def init_logger(self):
"""Init logger."""
if not self.result_logger:
if not os.path.exists(self.local_dir):
os.makedirs(self.local_dir)
if not self.logdir:
self.logdir = tempfile.mkdtemp(
prefix="{}_{}".format(
... | python | def init_logger(self):
"""Init logger."""
if not self.result_logger:
if not os.path.exists(self.local_dir):
os.makedirs(self.local_dir)
if not self.logdir:
self.logdir = tempfile.mkdtemp(
prefix="{}_{}".format(
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24,522 | ray-project/ray | python/ray/tune/trial.py | Trial.should_stop | def should_stop(self, result):
"""Whether the given result meets this trial's stopping criteria."""
if result.get(DONE):
return True
for criteria, stop_value in self.stopping_criterion.items():
if criteria not in result:
raise TuneError(
... | python | def should_stop(self, result):
"""Whether the given result meets this trial's stopping criteria."""
if result.get(DONE):
return True
for criteria, stop_value in self.stopping_criterion.items():
if criteria not in result:
raise TuneError(
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24,523 | ray-project/ray | python/ray/tune/trial.py | Trial.should_checkpoint | def should_checkpoint(self):
"""Whether this trial is due for checkpointing."""
result = self.last_result or {}
if result.get(DONE) and self.checkpoint_at_end:
return True
if self.checkpoint_freq:
return result.get(TRAINING_ITERATION,
... | python | def should_checkpoint(self):
"""Whether this trial is due for checkpointing."""
result = self.last_result or {}
if result.get(DONE) and self.checkpoint_at_end:
return True
if self.checkpoint_freq:
return result.get(TRAINING_ITERATION,
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24,524 | ray-project/ray | python/ray/tune/trial.py | Trial.progress_string | def progress_string(self):
"""Returns a progress message for printing out to the console."""
if not self.last_result:
return self._status_string()
def location_string(hostname, pid):
if hostname == os.uname()[1]:
return "pid={}".format(pid)
e... | python | def progress_string(self):
"""Returns a progress message for printing out to the console."""
if not self.last_result:
return self._status_string()
def location_string(hostname, pid):
if hostname == os.uname()[1]:
return "pid={}".format(pid)
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24,525 | ray-project/ray | python/ray/tune/trial.py | Trial.should_recover | def should_recover(self):
"""Returns whether the trial qualifies for restoring.
This is if a checkpoint frequency is set and has not failed more than
max_failures. This may return true even when there may not yet
be a checkpoint.
"""
return (self.checkpoint_freq > 0
... | python | def should_recover(self):
"""Returns whether the trial qualifies for restoring.
This is if a checkpoint frequency is set and has not failed more than
max_failures. This may return true even when there may not yet
be a checkpoint.
"""
return (self.checkpoint_freq > 0
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24,526 | ray-project/ray | python/ray/tune/trial.py | Trial.compare_checkpoints | def compare_checkpoints(self, attr_mean):
"""Compares two checkpoints based on the attribute attr_mean param.
Greater than is used by default. If command-line parameter
checkpoint_score_attr starts with "min-" less than is used.
Arguments:
attr_mean: mean of attribute value... | python | def compare_checkpoints(self, attr_mean):
"""Compares two checkpoints based on the attribute attr_mean param.
Greater than is used by default. If command-line parameter
checkpoint_score_attr starts with "min-" less than is used.
Arguments:
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24,527 | ray-project/ray | examples/rl_pong/driver.py | discount_rewards | def discount_rewards(r):
"""take 1D float array of rewards and compute discounted reward"""
discounted_r = np.zeros_like(r)
running_add = 0
for t in reversed(range(0, r.size)):
# Reset the sum, since this was a game boundary (pong specific!).
if r[t] != 0:
running_add = 0
... | python | def discount_rewards(r):
"""take 1D float array of rewards and compute discounted reward"""
discounted_r = np.zeros_like(r)
running_add = 0
for t in reversed(range(0, r.size)):
# Reset the sum, since this was a game boundary (pong specific!).
if r[t] != 0:
running_add = 0
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24,528 | ray-project/ray | python/ray/autoscaler/node_provider.py | load_class | def load_class(path):
"""
Load a class at runtime given a full path.
Example of the path: mypkg.mysubpkg.myclass
"""
class_data = path.split(".")
if len(class_data) < 2:
raise ValueError(
"You need to pass a valid path like mymodule.provider_class")
module_path = ".".joi... | python | def load_class(path):
"""
Load a class at runtime given a full path.
Example of the path: mypkg.mysubpkg.myclass
"""
class_data = path.split(".")
if len(class_data) < 2:
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24,529 | ray-project/ray | python/ray/autoscaler/node_provider.py | NodeProvider.terminate_nodes | def terminate_nodes(self, node_ids):
"""Terminates a set of nodes. May be overridden with a batch method."""
for node_id in node_ids:
logger.info("NodeProvider: "
"{}: Terminating node".format(node_id))
self.terminate_node(node_id) | python | def terminate_nodes(self, node_ids):
"""Terminates a set of nodes. May be overridden with a batch method."""
for node_id in node_ids:
logger.info("NodeProvider: "
"{}: Terminating node".format(node_id))
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24,530 | ray-project/ray | python/ray/tune/suggest/bayesopt.py | BayesOptSearch.on_trial_complete | def on_trial_complete(self,
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error=False,
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"""Passes the result to BayesOpt unless early terminated or errored"""
if result:
self.optimizer.re... | python | def on_trial_complete(self,
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error=False,
early_terminated=False):
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24,531 | ray-project/ray | python/ray/experimental/serve/mixin.py | _execute_and_seal_error | def _execute_and_seal_error(method, arg, method_name):
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24,532 | ray-project/ray | python/ray/experimental/serve/mixin.py | RayServeMixin._dispatch | def _dispatch(self, input_batch: List[SingleQuery]):
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24,533 | ray-project/ray | python/ray/rllib/env/atari_wrappers.py | get_wrapper_by_cls | def get_wrapper_by_cls(env, cls):
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currentenv = env
while True:
if isinstance(currentenv, cls):
return currentenv
elif isinstance(currentenv, gym.Wrapper):
currentenv = currentenv.env
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"""Returns the gym env wrapper of the given class, or None."""
currentenv = env
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return currentenv
elif isinstance(currentenv, gym.Wrapper):
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24,534 | ray-project/ray | python/ray/rllib/env/atari_wrappers.py | wrap_deepmind | def wrap_deepmind(env, dim=84, framestack=True):
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Note that we assume reward clipping is done outside the wrapper.
Args:
dim (int): Dimension to resize observations to (dim x dim).
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"""Configure environment for DeepMind-style Atari.
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dim (int): Dimension to resize observations to (dim x dim).
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24,535 | ray-project/ray | python/ray/rllib/utils/memory.py | ray_get_and_free | def ray_get_and_free(object_ids):
"""Call ray.get and then queue the object ids for deletion.
This function should be used whenever possible in RLlib, to optimize
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Args:
object_ids (ObjectID|List[ObjectI... | python | def ray_get_and_free(object_ids):
"""Call ray.get and then queue the object ids for deletion.
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24,536 | ray-project/ray | python/ray/rllib/utils/memory.py | aligned_array | def aligned_array(size, dtype, align=64):
"""Returns an array of a given size that is 64-byte aligned.
The returned array can be efficiently copied into GPU memory by TensorFlow.
"""
n = size * dtype.itemsize
empty = np.empty(n + (align - 1), dtype=np.uint8)
data_align = empty.ctypes.data % al... | python | def aligned_array(size, dtype, align=64):
"""Returns an array of a given size that is 64-byte aligned.
The returned array can be efficiently copied into GPU memory by TensorFlow.
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24,537 | ray-project/ray | python/ray/rllib/utils/memory.py | concat_aligned | def concat_aligned(items):
"""Concatenate arrays, ensuring the output is 64-byte aligned.
We only align float arrays; other arrays are concatenated as normal.
This should be used instead of np.concatenate() to improve performance
when the output array is likely to be fed into TensorFlow.
"""
... | python | def concat_aligned(items):
"""Concatenate arrays, ensuring the output is 64-byte aligned.
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This should be used instead of np.concatenate() to improve performance
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24,538 | ray-project/ray | python/ray/experimental/queue.py | Queue.get | def get(self, block=True, timeout=None):
"""Gets an item from the queue.
Uses polling if block=True, so there is no guarantee of order if
multiple consumers get from the same empty queue.
Returns:
The next item in the queue.
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"""Gets an item from the queue.
Uses polling if block=True, so there is no guarantee of order if
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24,539 | ray-project/ray | python/ray/rllib/utils/annotations.py | override | def override(cls):
"""Annotation for documenting method overrides.
Arguments:
cls (type): The superclass that provides the overriden method. If this
cls does not actually have the method, an error is raised.
"""
def check_override(method):
if method.__name__ not in dir(cls)... | python | def override(cls):
"""Annotation for documenting method overrides.
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cls (type): The superclass that provides the overriden method. If this
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24,540 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | HyperBandScheduler.on_trial_add | def on_trial_add(self, trial_runner, trial):
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24,541 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | HyperBandScheduler._cur_band_filled | def _cur_band_filled(self):
"""Checks if the current band is filled.
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cur_band = self._hyperbands[self._state["band_idx"]]
return len(cur_band) == self._s_max_1 | python | def _cur_band_filled(self):
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24,542 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | HyperBandScheduler.on_trial_result | def on_trial_result(self, trial_runner, trial, result):
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24,543 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | HyperBandScheduler._process_bracket | def _process_bracket(self, trial_runner, bracket, trial):
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24,544 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | HyperBandScheduler.on_trial_remove | def on_trial_remove(self, trial_runner, trial):
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bracket, _ = self._trial_info[trial]
bracket.cleanup_trial(trial)
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24,545 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | HyperBandScheduler.choose_trial_to_run | def choose_trial_to_run(self, trial_runner):
"""Fair scheduling within iteration by completion percentage.
List of trials not used since all trials are tracked as state
of scheduler. If iteration is occupied (ie, no trials to run),
then look into next iteration.
"""
for... | python | def choose_trial_to_run(self, trial_runner):
"""Fair scheduling within iteration by completion percentage.
List of trials not used since all trials are tracked as state
of scheduler. If iteration is occupied (ie, no trials to run),
then look into next iteration.
"""
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24,546 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | HyperBandScheduler.debug_string | def debug_string(self):
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Bracket(Max Size (n)=5, Milestone (r)=33, completed=14.6%):
{PENDING: 2, RUNNING: 3, TERMINATED: 2}
"Max Size" indicates... | python | def debug_string(self):
"""This provides a progress notification for the algorithm.
For each bracket, the algorithm will output a string as follows:
Bracket(Max Size (n)=5, Milestone (r)=33, completed=14.6%):
{PENDING: 2, RUNNING: 3, TERMINATED: 2}
"Max Size" indicates... | [
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24,547 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | Bracket.add_trial | def add_trial(self, trial):
"""Add trial to bracket assuming bracket is not filled.
At a later iteration, a newly added trial will be given equal
opportunity to catch up."""
assert not self.filled(), "Cannot add trial to filled bracket!"
self._live_trials[trial] = None
s... | python | def add_trial(self, trial):
"""Add trial to bracket assuming bracket is not filled.
At a later iteration, a newly added trial will be given equal
opportunity to catch up."""
assert not self.filled(), "Cannot add trial to filled bracket!"
self._live_trials[trial] = None
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24,548 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | Bracket.cur_iter_done | def cur_iter_done(self):
"""Checks if all iterations have completed.
TODO(rliaw): also check that `t.iterations == self._r`"""
return all(
self._get_result_time(result) >= self._cumul_r
for result in self._live_trials.values()) | python | def cur_iter_done(self):
"""Checks if all iterations have completed.
TODO(rliaw): also check that `t.iterations == self._r`"""
return all(
self._get_result_time(result) >= self._cumul_r
for result in self._live_trials.values()) | [
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24,549 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | Bracket.update_trial_stats | def update_trial_stats(self, trial, result):
"""Update result for trial. Called after trial has finished
an iteration - will decrement iteration count.
TODO(rliaw): The other alternative is to keep the trials
in and make sure they're not set as pending later."""
assert trial in... | python | def update_trial_stats(self, trial, result):
"""Update result for trial. Called after trial has finished
an iteration - will decrement iteration count.
TODO(rliaw): The other alternative is to keep the trials
in and make sure they're not set as pending later."""
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24,550 | ray-project/ray | python/ray/tune/schedulers/hyperband.py | Bracket.cleanup_full | def cleanup_full(self, trial_runner):
"""Cleans up bracket after bracket is completely finished.
Lets the last trial continue to run until termination condition
kicks in."""
for trial in self.current_trials():
if (trial.status == Trial.PAUSED):
trial_runner.s... | python | def cleanup_full(self, trial_runner):
"""Cleans up bracket after bracket is completely finished.
Lets the last trial continue to run until termination condition
kicks in."""
for trial in self.current_trials():
if (trial.status == Trial.PAUSED):
trial_runner.s... | [
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24,551 | ray-project/ray | python/ray/experimental/state.py | parse_client_table | def parse_client_table(redis_client):
"""Read the client table.
Args:
redis_client: A client to the primary Redis shard.
Returns:
A list of information about the nodes in the cluster.
"""
NIL_CLIENT_ID = ray.ObjectID.nil().binary()
message = redis_client.execute_command("RAY.TA... | python | def parse_client_table(redis_client):
"""Read the client table.
Args:
redis_client: A client to the primary Redis shard.
Returns:
A list of information about the nodes in the cluster.
"""
NIL_CLIENT_ID = ray.ObjectID.nil().binary()
message = redis_client.execute_command("RAY.TA... | [
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24,552 | ray-project/ray | python/ray/experimental/state.py | GlobalState._initialize_global_state | def _initialize_global_state(self,
redis_address,
redis_password=None,
timeout=20):
"""Initialize the GlobalState object by connecting to Redis.
It's possible that certain keys in Redis may not have been ... | python | def _initialize_global_state(self,
redis_address,
redis_password=None,
timeout=20):
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24,553 | ray-project/ray | python/ray/experimental/state.py | GlobalState._execute_command | def _execute_command(self, key, *args):
"""Execute a Redis command on the appropriate Redis shard based on key.
Args:
key: The object ID or the task ID that the query is about.
args: The command to run.
Returns:
The value returned by the Redis command.
... | python | def _execute_command(self, key, *args):
"""Execute a Redis command on the appropriate Redis shard based on key.
Args:
key: The object ID or the task ID that the query is about.
args: The command to run.
Returns:
The value returned by the Redis command.
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24,554 | ray-project/ray | python/ray/experimental/state.py | GlobalState._keys | def _keys(self, pattern):
"""Execute the KEYS command on all Redis shards.
Args:
pattern: The KEYS pattern to query.
Returns:
The concatenated list of results from all shards.
"""
result = []
for client in self.redis_clients:
result.e... | python | def _keys(self, pattern):
"""Execute the KEYS command on all Redis shards.
Args:
pattern: The KEYS pattern to query.
Returns:
The concatenated list of results from all shards.
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24,555 | ray-project/ray | python/ray/experimental/state.py | GlobalState._object_table | def _object_table(self, object_id):
"""Fetch and parse the object table information for a single object ID.
Args:
object_id: An object ID to get information about.
Returns:
A dictionary with information about the object ID in question.
"""
# Allow the ar... | python | def _object_table(self, object_id):
"""Fetch and parse the object table information for a single object ID.
Args:
object_id: An object ID to get information about.
Returns:
A dictionary with information about the object ID in question.
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24,556 | ray-project/ray | python/ray/experimental/state.py | GlobalState.object_table | def object_table(self, object_id=None):
"""Fetch and parse the object table info for one or more object IDs.
Args:
object_id: An object ID to fetch information about. If this is
None, then the entire object table is fetched.
Returns:
Information from the... | python | def object_table(self, object_id=None):
"""Fetch and parse the object table info for one or more object IDs.
Args:
object_id: An object ID to fetch information about. If this is
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24,557 | ray-project/ray | python/ray/experimental/state.py | GlobalState._task_table | def _task_table(self, task_id):
"""Fetch and parse the task table information for a single task ID.
Args:
task_id: A task ID to get information about.
Returns:
A dictionary with information about the task ID in question.
"""
assert isinstance(task_id, ra... | python | def _task_table(self, task_id):
"""Fetch and parse the task table information for a single task ID.
Args:
task_id: A task ID to get information about.
Returns:
A dictionary with information about the task ID in question.
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24,558 | ray-project/ray | python/ray/experimental/state.py | GlobalState.task_table | def task_table(self, task_id=None):
"""Fetch and parse the task table information for one or more task IDs.
Args:
task_id: A hex string of the task ID to fetch information about. If
this is None, then the task object table is fetched.
Returns:
Informatio... | python | def task_table(self, task_id=None):
"""Fetch and parse the task table information for one or more task IDs.
Args:
task_id: A hex string of the task ID to fetch information about. If
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24,559 | ray-project/ray | python/ray/experimental/state.py | GlobalState.function_table | def function_table(self, function_id=None):
"""Fetch and parse the function table.
Returns:
A dictionary that maps function IDs to information about the
function.
"""
self._check_connected()
function_table_keys = self.redis_client.keys(
ra... | python | def function_table(self, function_id=None):
"""Fetch and parse the function table.
Returns:
A dictionary that maps function IDs to information about the
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"""
self._check_connected()
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24,560 | ray-project/ray | python/ray/experimental/state.py | GlobalState._profile_table | def _profile_table(self, batch_id):
"""Get the profile events for a given batch of profile events.
Args:
batch_id: An identifier for a batch of profile events.
Returns:
A list of the profile events for the specified batch.
"""
# TODO(rkn): This method sh... | python | def _profile_table(self, batch_id):
"""Get the profile events for a given batch of profile events.
Args:
batch_id: An identifier for a batch of profile events.
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A list of the profile events for the specified batch.
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24,561 | ray-project/ray | python/ray/experimental/state.py | GlobalState.chrome_tracing_dump | def chrome_tracing_dump(self, filename=None):
"""Return a list of profiling events that can viewed as a timeline.
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by passing in "filename" or using using json.dump, and then load go to
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24,562 | ray-project/ray | python/ray/experimental/state.py | GlobalState.chrome_tracing_object_transfer_dump | def chrome_tracing_object_transfer_dump(self, filename=None):
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To view this information as a timeline, simply dump it as a json file
by passing in "filename" or using using json.dump, and then load go to
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24,563 | ray-project/ray | python/ray/experimental/state.py | GlobalState.workers | def workers(self):
"""Get a dictionary mapping worker ID to worker information."""
worker_keys = self.redis_client.keys("Worker*")
workers_data = {}
for worker_key in worker_keys:
worker_info = self.redis_client.hgetall(worker_key)
worker_id = binary_to_hex(worke... | python | def workers(self):
"""Get a dictionary mapping worker ID to worker information."""
worker_keys = self.redis_client.keys("Worker*")
workers_data = {}
for worker_key in worker_keys:
worker_info = self.redis_client.hgetall(worker_key)
worker_id = binary_to_hex(worke... | [
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24,564 | ray-project/ray | python/ray/experimental/state.py | GlobalState.cluster_resources | def cluster_resources(self):
"""Get the current total cluster resources.
Note that this information can grow stale as nodes are added to or
removed from the cluster.
Returns:
A dictionary mapping resource name to the total quantity of that
resource in the cl... | python | def cluster_resources(self):
"""Get the current total cluster resources.
Note that this information can grow stale as nodes are added to or
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24,565 | ray-project/ray | python/ray/experimental/state.py | GlobalState.available_resources | def available_resources(self):
"""Get the current available cluster resources.
This is different from `cluster_resources` in that this will return
idle (available) resources rather than total resources.
Note that this information can grow stale as tasks start and finish.
Retur... | python | def available_resources(self):
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24,566 | ray-project/ray | python/ray/experimental/state.py | GlobalState._error_messages | def _error_messages(self, driver_id):
"""Get the error messages for a specific driver.
Args:
driver_id: The ID of the driver to get the errors for.
Returns:
A list of the error messages for this driver.
"""
assert isinstance(driver_id, ray.DriverID)
... | python | def _error_messages(self, driver_id):
"""Get the error messages for a specific driver.
Args:
driver_id: The ID of the driver to get the errors for.
Returns:
A list of the error messages for this driver.
"""
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24,567 | ray-project/ray | python/ray/experimental/state.py | GlobalState.error_messages | def error_messages(self, driver_id=None):
"""Get the error messages for all drivers or a specific driver.
Args:
driver_id: The specific driver to get the errors for. If this is
None, then this method retrieves the errors for all drivers.
Returns:
A dicti... | python | def error_messages(self, driver_id=None):
"""Get the error messages for all drivers or a specific driver.
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driver_id: The specific driver to get the errors for. If this is
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24,568 | ray-project/ray | python/ray/experimental/tf_utils.py | TensorFlowVariables.get_flat_size | def get_flat_size(self):
"""Returns the total length of all of the flattened variables.
Returns:
The length of all flattened variables concatenated.
"""
return sum(
np.prod(v.get_shape().as_list()) for v in self.variables.values()) | python | def get_flat_size(self):
"""Returns the total length of all of the flattened variables.
Returns:
The length of all flattened variables concatenated.
"""
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24,569 | ray-project/ray | python/ray/experimental/tf_utils.py | TensorFlowVariables.get_flat | def get_flat(self):
"""Gets the weights and returns them as a flat array.
Returns:
1D Array containing the flattened weights.
"""
self._check_sess()
return np.concatenate([
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"""Gets the weights and returns them as a flat array.
Returns:
1D Array containing the flattened weights.
"""
self._check_sess()
return np.concatenate([
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24,570 | ray-project/ray | python/ray/experimental/tf_utils.py | TensorFlowVariables.set_flat | def set_flat(self, new_weights):
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24,571 | ray-project/ray | python/ray/experimental/tf_utils.py | TensorFlowVariables.get_weights | def get_weights(self):
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24,572 | ray-project/ray | python/ray/experimental/tf_utils.py | TensorFlowVariables.set_weights | def set_weights(self, new_weights):
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Args:
new_weights (Dict): Dictionary mapping variable names to their
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24,573 | ray-project/ray | python/ray/gcs_utils.py | construct_error_message | def construct_error_message(driver_id, error_type, message, timestamp):
"""Construct a serialized ErrorTableData object.
Args:
driver_id: The ID of the driver that the error should go to. If this is
nil, then the error will go to all drivers.
error_type: The type of the error.
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"""Construct a serialized ErrorTableData object.
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driver_id: The ID of the driver that the error should go to. If this is
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error_type: The type of the error.
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24,574 | ray-project/ray | python/ray/experimental/async_api.py | init | def init():
"""
Initialize synchronously.
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loop = asyncio.get_event_loop()
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"""
Initialize synchronously.
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24,575 | ray-project/ray | python/ray/experimental/async_api.py | shutdown | def shutdown():
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protocol = None | python | def shutdown():
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24,576 | ray-project/ray | python/ray/experimental/features.py | flush_redis_unsafe | def flush_redis_unsafe(redis_client=None):
"""This removes some non-critical state from the primary Redis shard.
This removes the log files as well as the event log from Redis. This can
be used to try to address out-of-memory errors caused by the accumulation
of metadata in Redis. However, it will only... | python | def flush_redis_unsafe(redis_client=None):
"""This removes some non-critical state from the primary Redis shard.
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24,577 | ray-project/ray | python/ray/rllib/agents/ppo/ppo_policy_graph.py | PPOPolicyGraph.copy | def copy(self, existing_inputs):
"""Creates a copy of self using existing input placeholders."""
return PPOPolicyGraph(
self.observation_space,
self.action_space,
self.config,
existing_inputs=existing_inputs) | python | def copy(self, existing_inputs):
"""Creates a copy of self using existing input placeholders."""
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24,578 | ray-project/ray | examples/parameter_server/model.py | deepnn | def deepnn(x):
"""deepnn builds the graph for a deep net for classifying digits.
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x: an input tensor with the dimensions (N_examples, 784), where 784 is
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x: an input tensor with the dimensions (N_examples, 784), where 784 is
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24,579 | ray-project/ray | python/ray/signature.py | get_signature_params | def get_signature_params(func):
"""Get signature parameters
Support Cython functions by grabbing relevant attributes from the Cython
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funcsigs may change, but given that funcsigs is written to a PEP, we hope
it is relatively... | python | def get_signature_params(func):
"""Get signature parameters
Support Cython functions by grabbing relevant attributes from the Cython
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24,580 | ray-project/ray | python/ray/signature.py | check_signature_supported | def check_signature_supported(func, warn=False):
"""Check if we support the signature of this function.
We currently do not allow remote functions to have **kwargs. We also do not
support keyword arguments in conjunction with a *args argument.
Args:
func: The function whose signature should be... | python | def check_signature_supported(func, warn=False):
"""Check if we support the signature of this function.
We currently do not allow remote functions to have **kwargs. We also do not
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24,581 | ray-project/ray | python/ray/signature.py | extract_signature | def extract_signature(func, ignore_first=False):
"""Extract the function signature from the function.
Args:
func: The function whose signature should be extracted.
ignore_first: True if the first argument should be ignored. This should
be used when func is a method of a class.
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"""Extract the function signature from the function.
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func: The function whose signature should be extracted.
ignore_first: True if the first argument should be ignored. This should
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24,582 | ray-project/ray | python/ray/signature.py | extend_args | def extend_args(function_signature, args, kwargs):
"""Extend the arguments that were passed into a function.
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Args:
function_signature: The function signature of the funct... | python | def extend_args(function_signature, args, kwargs):
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24,583 | ray-project/ray | python/ray/autoscaler/gcp/config.py | wait_for_crm_operation | def wait_for_crm_operation(operation):
"""Poll for cloud resource manager operation until finished."""
logger.info("wait_for_crm_operation: "
"Waiting for operation {} to finish...".format(operation))
for _ in range(MAX_POLLS):
result = crm.operations().get(name=operation["name"]).e... | python | def wait_for_crm_operation(operation):
"""Poll for cloud resource manager operation until finished."""
logger.info("wait_for_crm_operation: "
"Waiting for operation {} to finish...".format(operation))
for _ in range(MAX_POLLS):
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24,584 | ray-project/ray | python/ray/autoscaler/gcp/config.py | wait_for_compute_global_operation | def wait_for_compute_global_operation(project_name, operation):
"""Poll for global compute operation until finished."""
logger.info("wait_for_compute_global_operation: "
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operation["name"]))
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... | python | def wait_for_compute_global_operation(project_name, operation):
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24,585 | ray-project/ray | python/ray/autoscaler/gcp/config.py | key_pair_name | def key_pair_name(i, region, project_id, ssh_user):
"""Returns the ith default gcp_key_pair_name."""
key_name = "{}_gcp_{}_{}_{}".format(RAY, region, project_id, ssh_user, i)
return key_name | python | def key_pair_name(i, region, project_id, ssh_user):
"""Returns the ith default gcp_key_pair_name."""
key_name = "{}_gcp_{}_{}_{}".format(RAY, region, project_id, ssh_user, i)
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24,586 | ray-project/ray | python/ray/autoscaler/gcp/config.py | key_pair_paths | def key_pair_paths(key_name):
"""Returns public and private key paths for a given key_name."""
public_key_path = os.path.expanduser("~/.ssh/{}.pub".format(key_name))
private_key_path = os.path.expanduser("~/.ssh/{}.pem".format(key_name))
return public_key_path, private_key_path | python | def key_pair_paths(key_name):
"""Returns public and private key paths for a given key_name."""
public_key_path = os.path.expanduser("~/.ssh/{}.pub".format(key_name))
private_key_path = os.path.expanduser("~/.ssh/{}.pem".format(key_name))
return public_key_path, private_key_path | [
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24,587 | ray-project/ray | python/ray/autoscaler/gcp/config.py | generate_rsa_key_pair | def generate_rsa_key_pair():
"""Create public and private ssh-keys."""
key = rsa.generate_private_key(
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public_key = key.public_key().public_bytes(
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"""Create public and private ssh-keys."""
key = rsa.generate_private_key(
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24,588 | ray-project/ray | python/ray/autoscaler/gcp/config.py | _configure_project | def _configure_project(config):
"""Setup a Google Cloud Platform Project.
Google Compute Platform organizes all the resources, such as storage
buckets, users, and instances under projects. This is different from
aws ec2 where everything is global.
"""
project_id = config["provider"].get("projec... | python | def _configure_project(config):
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24,589 | ray-project/ray | python/ray/autoscaler/gcp/config.py | _configure_iam_role | def _configure_iam_role(config):
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24,590 | ray-project/ray | python/ray/autoscaler/gcp/config.py | _configure_key_pair | def _configure_key_pair(config):
"""Configure SSH access, using an existing key pair if possible.
Creates a project-wide ssh key that can be used to access all the instances
unless explicitly prohibited by instance config.
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[USERNAME]:ssh-rsa [KEY_VALUE... | python | def _configure_key_pair(config):
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/autoscaler/gcp/config.py#L186-L269 |
24,591 | ray-project/ray | python/ray/autoscaler/gcp/config.py | _configure_subnet | def _configure_subnet(config):
"""Pick a reasonable subnet if not specified by the config."""
# Rationale: avoid subnet lookup if the network is already
# completely manually configured
if ("networkInterfaces" in config["head_node"]
and "networkInterfaces" in config["worker_nodes"]):
... | python | def _configure_subnet(config):
"""Pick a reasonable subnet if not specified by the config."""
# Rationale: avoid subnet lookup if the network is already
# completely manually configured
if ("networkInterfaces" in config["head_node"]
and "networkInterfaces" in config["worker_nodes"]):
... | [
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24,592 | ray-project/ray | python/ray/autoscaler/gcp/config.py | _add_iam_policy_binding | def _add_iam_policy_binding(service_account, roles):
"""Add new IAM roles for the service account."""
project_id = service_account["projectId"]
email = service_account["email"]
member_id = "serviceAccount:" + email
policy = crm.projects().getIamPolicy(resource=project_id).execute()
already_con... | python | def _add_iam_policy_binding(service_account, roles):
"""Add new IAM roles for the service account."""
project_id = service_account["projectId"]
email = service_account["email"]
member_id = "serviceAccount:" + email
policy = crm.projects().getIamPolicy(resource=project_id).execute()
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24,593 | ray-project/ray | python/ray/autoscaler/gcp/config.py | _create_project_ssh_key_pair | def _create_project_ssh_key_pair(project, public_key, ssh_user):
"""Inserts an ssh-key into project commonInstanceMetadata"""
key_parts = public_key.split(" ")
# Sanity checks to make sure that the generated key matches expectation
assert len(key_parts) == 2, key_parts
assert key_parts[0] == "ssh-... | python | def _create_project_ssh_key_pair(project, public_key, ssh_user):
"""Inserts an ssh-key into project commonInstanceMetadata"""
key_parts = public_key.split(" ")
# Sanity checks to make sure that the generated key matches expectation
assert len(key_parts) == 2, key_parts
assert key_parts[0] == "ssh-... | [
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/autoscaler/gcp/config.py#L419-L451 |
24,594 | ray-project/ray | python/ray/remote_function.py | RemoteFunction._remote | def _remote(self,
args=None,
kwargs=None,
num_return_vals=None,
num_cpus=None,
num_gpus=None,
resources=None):
"""An experimental alternate way to submit remote functions."""
worker = ray.worker.get_global_wo... | python | def _remote(self,
args=None,
kwargs=None,
num_return_vals=None,
num_cpus=None,
num_gpus=None,
resources=None):
"""An experimental alternate way to submit remote functions."""
worker = ray.worker.get_global_wo... | [
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/remote_function.py#L92-L135 |
24,595 | ray-project/ray | python/ray/experimental/async_plasma.py | PlasmaObjectLinkedList.append | def append(self, future):
"""Append an object to the linked list.
Args:
future (PlasmaObjectFuture): A PlasmaObjectFuture instance.
"""
future.prev = self.tail
if self.tail is None:
assert self.head is None
self.head = future
else:
... | python | def append(self, future):
"""Append an object to the linked list.
Args:
future (PlasmaObjectFuture): A PlasmaObjectFuture instance.
"""
future.prev = self.tail
if self.tail is None:
assert self.head is None
self.head = future
else:
... | [
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/experimental/async_plasma.py#L97-L111 |
24,596 | ray-project/ray | python/ray/experimental/async_plasma.py | PlasmaObjectLinkedList.remove | def remove(self, future):
"""Remove an object from the linked list.
Args:
future (PlasmaObjectFuture): A PlasmaObjectFuture instance.
"""
if self._loop.get_debug():
logger.debug("Removing %s from the linked list.", future)
if future.prev is None:
... | python | def remove(self, future):
"""Remove an object from the linked list.
Args:
future (PlasmaObjectFuture): A PlasmaObjectFuture instance.
"""
if self._loop.get_debug():
logger.debug("Removing %s from the linked list.", future)
if future.prev is None:
... | [
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/experimental/async_plasma.py#L113-L138 |
24,597 | ray-project/ray | python/ray/experimental/async_plasma.py | PlasmaObjectLinkedList.cancel | def cancel(self, *args, **kwargs):
"""Manually cancel all tasks assigned to this event loop."""
# Because remove all futures will trigger `set_result`,
# we cancel itself first.
super().cancel()
for future in self.traverse():
# All cancelled futures should have callba... | python | def cancel(self, *args, **kwargs):
"""Manually cancel all tasks assigned to this event loop."""
# Because remove all futures will trigger `set_result`,
# we cancel itself first.
super().cancel()
for future in self.traverse():
# All cancelled futures should have callba... | [
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/experimental/async_plasma.py#L140-L150 |
24,598 | ray-project/ray | python/ray/experimental/async_plasma.py | PlasmaObjectLinkedList.set_result | def set_result(self, result):
"""Complete all tasks. """
for future in self.traverse():
# All cancelled futures should have callbacks to removed itself
# from this linked list. However, these callbacks are scheduled in
# an event loop, so we could still find them in o... | python | def set_result(self, result):
"""Complete all tasks. """
for future in self.traverse():
# All cancelled futures should have callbacks to removed itself
# from this linked list. However, these callbacks are scheduled in
# an event loop, so we could still find them in o... | [
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/experimental/async_plasma.py#L152-L160 |
24,599 | ray-project/ray | python/ray/experimental/async_plasma.py | PlasmaObjectLinkedList.traverse | def traverse(self):
"""Traverse this linked list.
Yields:
PlasmaObjectFuture: PlasmaObjectFuture instances.
"""
current = self.head
while current is not None:
yield current
current = current.next | python | def traverse(self):
"""Traverse this linked list.
Yields:
PlasmaObjectFuture: PlasmaObjectFuture instances.
"""
current = self.head
while current is not None:
yield current
current = current.next | [
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Yields:
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] | 4eade036a0505e244c976f36aaa2d64386b5129b | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/experimental/async_plasma.py#L162-L171 |
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