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``` Hi, I have a basic similarity search test program creating a collection. ----------------------------------- import time from pymilvus import (Collection, CollectionSchema, DataType, FieldSchema, connections) def connect(host: str, port: int) :...
Can I optimize DeepChem's models using RayTune? Is RayTune compatible with DeepChem?
Latest ray libraries via pip install on python 3.8 code breaking ``` trainer = PPOTrainer(config=config) trainer.restore(checkpoint) ``` **Error** RayActorError: The actor died because of an error raised in its creation...
I am trying to to do large scale hyper-parameter tuning. I have a local setup of 4 GPU's. My model size is small (~ 1GB), so I was thinking of...
in exercise 2 of https://colab.research.google.com/github/ray-project/tutorial/blob/master/exercises/colab01-03.ipynb, in Application: Parallel web-scraping, the data frame is empty after running cells:  I think some changes are needed based on GitHub frontEnd changes.
Copy/paste error it looks like in one of the tutorials
When I'm running the [exercise 3](https://github.com/ray-project/tutorial/tree/master/tune_exercises/exercise_3_pbt.ipynb) after uncommenting the installation cell, I receive the following error: > --------------------------------------------------------------------------- > > ModuleNotFoundError Traceback (most recent call last) > > in ()...
When I am trying to run the exercise01.ipynb I got the following error. Can anyone help me? `from __future__ import absolute_import from __future__ import division from __future__ import print_function import...
My `docker-compose.yml` defines the `shm_size: '32gb'` but when I run `ray.init(num_cpus=4, ignore_reinit_error=True, include_dashboard=False)` I get the log line: `2020-08-26 20:31:09,651 INFO resource_spec.py:231 -- Starting Ray with 37.5 GiB memory available...
ray.__version__ = '0.8.7' ```python # This function is a proxy for a more interesting and computationally # intensive function. @ray.remote def slow_function(i): time.sleep(1) return i # Sleep a little to...