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neilisaac / torch   python

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Version: 1.8.0 

/ __future__.py

"""
This global flag controls whether to assign new tensors to the parameters
instead of changing the existing parameters in-place when converting an `nn.Module`
using the following methods:
1. `module.cuda()` / `.cpu()` (for moving `module` between devices)
2. `module.float()` / `.double()` / `.half()` (for converting `module` to a different dtype)
3. `module.to()` / `.type()` (for changing `module`'s device or dtype)
4. `module._apply(fn)` (for generic functions applied to `module`)

Default: False
"""
_overwrite_module_params_on_conversion = False

def set_overwrite_module_params_on_conversion(value):
    global _overwrite_module_params_on_conversion
    _overwrite_module_params_on_conversion = value

def get_overwrite_module_params_on_conversion():
    return _overwrite_module_params_on_conversion