U <cX@sddlZddlZddlmZmZmZmZmZGdddZddZ ddZ d d Z d d Z ej d dZGdddZGdddeZdS)N)_len_torch_dispatch_stack_get_dispatch_stack_at_pop_torch_dispatch_stack_push_on_torch_dispatch_stack_set_torch_dispatch_modec@s6eZdZdZd ddZddZdd Zed d ZdS) TorchDispatchModea A ``TorchDispatchMode`` allows you to override the meaning of all ``__torch_dispatch__`` overrideable functions within a dynamic scope, without having to actually create a tensor subclass or manually monkey-patch functions in the PyTorch API. Some common situations where you should use a mode: * You want to override the meaning of factory functions, or other functions that do not otherwise take a tensor as an argument (these cannot be overridden with tensor subclasses). * You want to override the behavior of all functions without needing to wrap your inputs in tensor subclasses; e.g., if you are just interested in logging intermediate computations. * You want to control the order of execution of various tensor subclasses explicitly, rather than implicitly via the return of ``NotImplemented``. Independent subclasses of :class:`TorchDispatchMode` are compositional: modes can be pushed onto a stack using ``with MyMode():``. When you call functions in the PyTorch API inside your ``__torch_dispatch__`` implementation, by default, they will forward on to the next mode on the mode stack. If you want recursively call back into your current ``__torch_dispatch__`` implementation, either explicitly invoke ``self.__torch_dispatch__(...)``, or use the context manager ``__torch_dispatch__(self)`` to make PyTorch API self-referential (beware of infinite loops, in this case!) NcCs tdSN)NotImplementedErrorselffunctypesargskwargsrr@/tmp/pip-unpacked-wheel-gikjz4vx/torch/utils/_python_dispatch.py__torch_dispatch__,sz$TorchDispatchMode.__torch_dispatch__cCs t||Sr ) _push_mode)r rrr __enter__/szTorchDispatchMode.__enter__cCs tdSr ) _pop_mode)r exc_typeexc_valexc_tbrrr__exit__3szTorchDispatchMode.__exit__cOstd|||}|S)NzP`Mode.push()` is no longer necessary and can be replaced with just `with Mode()`)warningswarn)clsrrinstancerrrpush6s  zTorchDispatchMode.push)rN) __name__ __module__ __qualname____doc__rrr classmethodrrrrrrs  rcCst}|dkrt|dSdS)Nr)rrZ stack_lenrrr_get_current_dispatch_mode<sr&cCst}ddt|DS)NcSsg|] }t|qSr)r).0irrr Csz4_get_current_dispatch_mode_stack..)rranger%rrr _get_current_dispatch_mode_stackAsr+cCs tdkrttt|dSNr)rr_TorchDispatchStackModer)moderrrrEs  rcCst}tdkrtd|Sr,)rrroldrrrrKs rccs t}z |VW5t|XdSr )rrr/rrr_pop_mode_temporarilyRs r1c@seZdZdddZdS)r-rNc CsftV}tdkrt||jjt|kr@tt|dd|||||W5QRSQRXdS)Nrz's torch_dispatch function z,should be a normal method not a class method)r1rrr__self__type RuntimeError)r r rrrr0rrrr]s z*_TorchDispatchStackMode.__torch_dispatch__)rNrr r!rrrrrr-\sr-c@seZdZdddZdS)BaseTorchDispatchModerNcCs|dkr i}|||Sr rr rrrrhsz(BaseTorchDispatchMode.__torch_dispatch__)rNr5rrrrr6gsr6) contextlibrZtorch._Crrrrrrr&r+rrcontextmanagerr1r-r6rrrrs .