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8a2000fd42
A test was failing in inductor (`test_pointwise_zeta`) -- and I realized the operation was missing also from eager. Implemented for both, leveraging the kernel. Happy to split in two (one PR for eager, one for inductor) if folks prefer. Pull Request resolved: https://github.com/pytorch/pytorch/pull/146465 Approved by: https://github.com/malfet |
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| _awaits | ||
| _C | ||
| _C_flatbuffer | ||
| _custom_op | ||
| _decomp | ||
| _dispatch | ||
| _dynamo | ||
| _export | ||
| _functorch | ||
| _higher_order_ops | ||
| _inductor | ||
| _lazy | ||
| _library | ||
| _logging | ||
| _numpy | ||
| _prims | ||
| _prims_common | ||
| _refs | ||
| _strobelight | ||
| _subclasses | ||
| _vendor | ||
| accelerator | ||
| amp | ||
| ao | ||
| autograd | ||
| backends | ||
| compiler | ||
| contrib | ||
| cpu | ||
| csrc | ||
| cuda | ||
| distributed | ||
| distributions | ||
| export | ||
| fft | ||
| func | ||
| futures | ||
| fx | ||
| jit | ||
| legacy | ||
| lib | ||
| linalg | ||
| masked | ||
| monitor | ||
| mps | ||
| mtia | ||
| multiprocessing | ||
| nested | ||
| nn | ||
| onnx | ||
| optim | ||
| package | ||
| profiler | ||
| quantization | ||
| signal | ||
| sparse | ||
| special | ||
| testing | ||
| utils | ||
| xpu | ||
| __config__.py | ||
| __future__.py | ||
| __init__.py | ||
| _appdirs.py | ||
| _classes.py | ||
| _compile.py | ||
| _custom_ops.py | ||
| _deploy.py | ||
| _environment.py | ||
| _guards.py | ||
| _jit_internal.py | ||
| _linalg_utils.py | ||
| _lobpcg.py | ||
| _lowrank.py | ||
| _meta_registrations.py | ||
| _namedtensor_internals.py | ||
| _ops.py | ||
| _python_dispatcher.py | ||
| _size_docs.py | ||
| _sources.py | ||
| _storage_docs.py | ||
| _streambase.py | ||
| _tensor.py | ||
| _tensor_docs.py | ||
| _tensor_str.py | ||
| _thread_safe_fork.py | ||
| _torch_docs.py | ||
| _utils.py | ||
| _utils_internal.py | ||
| _VF.py | ||
| _vmap_internals.py | ||
| _weights_only_unpickler.py | ||
| abi-check.cpp | ||
| CMakeLists.txt | ||
| custom_class.h | ||
| custom_class_detail.h | ||
| extension.h | ||
| functional.py | ||
| hub.py | ||
| library.h | ||
| library.py | ||
| overrides.py | ||
| py.typed | ||
| quasirandom.py | ||
| random.py | ||
| README.txt | ||
| return_types.py | ||
| script.h | ||
| serialization.py | ||
| storage.py | ||
| torch_version.py | ||
| types.py | ||
| version.py.tpl | ||
Note [TH abstraction violation] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TH/THC provide some hpp headers, which are proper C++ headers rather than C headers. These headers serve double duty as *internal implementation detail* headers, whose contents should largely not be used by external clients. Ideally, we would not install these headers at all; instead, you should use public functions (in headers like `THTensor.h`, NOT `THTensor.hpp`) to manipulate these structs. However, there are a few places in torch/csrc where we violate this abstraction. They are marked with a pointer to this note. Each of those sites will have to be refactored when we refactor the guts of THTensor and related structures.