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06aaf8c20d
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/42637 This commit enables sending non-CPU tensors through RPC using TensorPipe backend. Users can configure device mappings by calling set_map_location on `TensorPipeRpcBackendOptions`. Internally, the `init_rpc` API verifies the correctness of device mappings. It will shutdown RPC if the check failed, or proceed and pass global mappings to `TensorPipeAgent` if the check was successful. For serde, we added a device indices field to TensorPipe read and write buffers, which should be either empty (all tensors must be on CPU) or match the tensors in order and number in the RPC message. This commit does not yet avoid zero-copy, the tensor is always moved to CPU on the sender and then moved to the specified device on the receiver. Test Plan: Imported from OSS Reviewed By: izdeby Differential Revision: D23011572 Pulled By: mrshenli fbshipit-source-id: 62b617eed91237d4e9926bc8551db78b822a1187 |
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| .. | ||
| _C | ||
| autograd | ||
| backends | ||
| contrib | ||
| csrc | ||
| cuda | ||
| distributed | ||
| distributions | ||
| fft | ||
| for_onnx | ||
| futures | ||
| fx | ||
| jit | ||
| legacy | ||
| lib | ||
| linalg | ||
| multiprocessing | ||
| nn | ||
| onnx | ||
| optim | ||
| quantization | ||
| sparse | ||
| testing | ||
| utils | ||
| __config__.py | ||
| __future__.py | ||
| __init__.py | ||
| _appdirs.py | ||
| _classes.py | ||
| _jit_internal.py | ||
| _linalg_utils.py | ||
| _lobpcg.py | ||
| _lowrank.py | ||
| _namedtensor_internals.py | ||
| _ops.py | ||
| _six.py | ||
| _storage_docs.py | ||
| _tensor_docs.py | ||
| _tensor_str.py | ||
| _torch_docs.py | ||
| _utils_internal.py | ||
| _utils.py | ||
| _VF.py | ||
| _vmap_internals.py | ||
| abi-check.cpp | ||
| CMakeLists.txt | ||
| custom_class_detail.h | ||
| custom_class.h | ||
| extension.h | ||
| functional.py | ||
| hub.py | ||
| library.h | ||
| overrides.py | ||
| py.typed | ||
| quasirandom.py | ||
| random.py | ||
| README.txt | ||
| script.h | ||
| serialization.py | ||
| storage.py | ||
| tensor.py | ||
| types.py | ||
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.