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3a5bf0bc36
Fixes #144302 After checking the code of my third-party devices, I think these APIs are also relied on by us, so I exposed them according to the discussion in the issue. Pull Request resolved: https://github.com/pytorch/pytorch/pull/144746 Approved by: https://github.com/albanD
35 lines
1.1 KiB
C++
35 lines
1.1 KiB
C++
#pragma once
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#include <c10/core/Device.h>
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#include <c10/core/DispatchKey.h>
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#include <c10/core/ScalarType.h>
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#include <torch/csrc/Export.h>
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#include <torch/csrc/python_headers.h>
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namespace at {
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class Tensor;
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} // namespace at
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namespace torch::tensors {
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// Initializes the Python tensor type objects: torch.FloatTensor,
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// torch.DoubleTensor, etc. and binds them in their containing modules.
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TORCH_PYTHON_API void initialize_python_bindings();
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// Same as set_default_tensor_type() but takes a PyObject*
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TORCH_PYTHON_API void py_set_default_tensor_type(PyObject* type_obj);
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// Same as py_set_default_tensor_type, but only changes the dtype (ScalarType).
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TORCH_PYTHON_API void py_set_default_dtype(PyObject* dtype_obj);
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// Gets the DispatchKey for the default tensor type.
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//
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// TODO: This is nuts! There is no reason to let the default tensor type id
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// change. Probably only store ScalarType, as that's the only flex point
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// we support.
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TORCH_API c10::DispatchKey get_default_dispatch_key();
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TORCH_PYTHON_API at::Device get_default_device();
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// Gets the ScalarType for the default tensor type.
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at::ScalarType get_default_scalar_type();
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} // namespace torch::tensors
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