ctheodoris madhavanvenkatesh commited on
Commit
b8fda63
1 Parent(s): 6caf480

Config head node runtime via IP (#234)

Browse files

- Config head node runtime via IP (748f48ac03faa90488220eb2f9b5a76e128a6c06)
- Update minor formatting (c48e37c67945c09e6593d45c40c4cbe0df7cc757)


Co-authored-by: Madhavan Venkatesh <madhavanvenkatesh@users.noreply.huggingface.co>

examples/hyperparam_optimiz_for_disease_classifier.py CHANGED
@@ -18,10 +18,42 @@ import ray
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  from ray import tune
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  from ray.tune import ExperimentAnalysis
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  from ray.tune.suggest.hyperopt import HyperOptSearch
 
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  runtime_env = {"conda": "base",
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  "env_vars": {"LD_LIBRARY_PATH": "/path/to/miniconda3/lib:/path/to/sw/lib:/path/to/sw/lib"}}
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  ray.init(runtime_env=runtime_env)
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  import datetime
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  import numpy as np
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  import pandas as pd
@@ -123,6 +155,7 @@ def model_init():
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  return model
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  # define metrics
 
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  def compute_metrics(pred):
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  labels = pred.label_ids
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  preds = pred.predictions.argmax(-1)
 
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  from ray import tune
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  from ray.tune import ExperimentAnalysis
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  from ray.tune.suggest.hyperopt import HyperOptSearch
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+ ray.shutdown() #engage new ray session
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  runtime_env = {"conda": "base",
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  "env_vars": {"LD_LIBRARY_PATH": "/path/to/miniconda3/lib:/path/to/sw/lib:/path/to/sw/lib"}}
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  ray.init(runtime_env=runtime_env)
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+ def initialize_ray_with_check(ip_address):
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+ """
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+ Initialize Ray with a specified IP address and check its status and accessibility.
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+
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+ Args:
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+ - ip_address (str): The IP address (with port) to initialize Ray.
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+
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+ Returns:
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+ - bool: True if initialization was successful and dashboard is accessible, False otherwise.
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+ """
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+ try:
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+ ray.init(address=ip_address)
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+ print(ray.nodes())
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+
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+ services = ray.get_webui_url()
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+ if not services:
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+ raise RuntimeError("Ray dashboard is not accessible.")
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+ else:
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+ print(f"Ray dashboard is accessible at: {services}")
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+ return True
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+ except Exception as e:
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+ print(f"Error initializing Ray: {e}")
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+ return False
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+
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+ # Usage:
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+ ip = 'your_ip:xxxx' # Replace with your actual IP address and port
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+ if initialize_ray_with_check(ip):
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+ print("Ray initialized successfully.")
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+ else:
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+ print("Error during Ray initialization.")
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+
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  import datetime
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  import numpy as np
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  import pandas as pd
 
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  return model
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  # define metrics
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+ # note: macro f1 score recommended for imbalanced multiclass classifiers
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  def compute_metrics(pred):
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  labels = pred.label_ids
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  preds = pred.predictions.argmax(-1)