edbe8e45-68ad-41d5-8021-29d38e2f9712
commented
4 years ago Currently, in order to share numpy array between processes via multiprocessing.SharedMemory object, it is required to copy the memory content with: input = np.ones((1,10,10,10)) shm = shared_memory.SharedMemory(create=True, size=input.nbytes) write_array = np.ndarray(input.shape, dtype=input.dtype,buffer=shm.buf) write_array1[:] = input[:] In result the original numpy array is duplicated in RAM. It also adds extra cpu cycles to copy the content.
I would like to recommend adding an option to create shared memory object by pointing it to existing memoryview object, beside current method of using shared memory name. Is that doable?
Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.
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GitHub fields: ```python assignee = None closed_at = None created_at =
labels = ['3.8', 'library', 'performance']
title = 'create multiprocessing.SharedMemory by pointing to existing memoryview'
updated_at =
user = 'https://bugs.python.org/DariuszTrawinski'
```
bugs.python.org fields:
```python
activity =
actor = 'petr.viktorin'
assignee = 'none'
closed = False
closed_date = None
closer = None
components = ['Library (Lib)']
creation =
creator = 'Dariusz Trawinski'
dependencies = []
files = []
hgrepos = []
issue_num = 39767
keywords = []
message_count = 1.0
messages = ['362754']
nosy_count = 1.0
nosy_names = ['Dariusz Trawinski']
pr_nums = []
priority = 'normal'
resolution = None
stage = None
status = 'open'
superseder = None
type = 'performance'
url = 'https://bugs.python.org/issue39767'
versions = ['Python 3.8']
```