44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
# Copyright 2024 Bytedance Ltd. and/or its affiliates
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Contains commonly used utilities for ray
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"""
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import ray
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import concurrent.futures
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def parallel_put(data_list, max_workers=None):
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def put_data(index, data):
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return index, ray.put(data)
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if max_workers is None:
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max_workers = min(len(data_list), 16)
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with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
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data_list_f = [executor.submit(put_data, i, data) for i, data in enumerate(data_list)]
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res_lst = []
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for future in concurrent.futures.as_completed(data_list_f):
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res_lst.append(future.result())
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# reorder based on index
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output = [None for _ in range(len(data_list))]
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for res in res_lst:
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index, data_ref = res
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output[index] = data_ref
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return output
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