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59f9b25f3c
This is an improvement over https://github.com/pytorch/pytorch/pull/132595 . That PR improves the case where `device` is not given. This PR tries to improve the case where `device` is given but the first step of auto-infer device from `cudaPointerGetAttributes` can be wrong (undesired). See https://github.com/pytorch/pytorch/issues/158316 for more details on when this can happen. I think this is a reasonable improvement, as people expect `torch.as_tensor` + cupy should be zero-copy as much as possible. However, it does change some behaviors, because previously it might incur a device-to-device copy. I will leave it to pytorch developers to see if the improvement is worthwhile. Pull Request resolved: https://github.com/pytorch/pytorch/pull/158320 Approved by: https://github.com/ezyang
33 lines
875 B
C++
33 lines
875 B
C++
#pragma once
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#include <ATen/core/Tensor.h>
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#include <torch/csrc/python_headers.h>
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namespace torch::utils {
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TORCH_API PyObject* tensor_to_numpy(
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const at::Tensor& tensor,
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bool force = false);
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TORCH_API at::Tensor tensor_from_numpy(
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PyObject* obj,
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bool warn_if_not_writeable = true);
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TORCH_API int aten_to_numpy_dtype(const at::ScalarType scalar_type);
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TORCH_API at::ScalarType numpy_dtype_to_aten(int dtype);
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TORCH_API bool is_numpy_available();
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TORCH_API bool is_numpy_int(PyObject* obj);
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TORCH_API bool is_numpy_bool(PyObject* obj);
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TORCH_API bool is_numpy_scalar(PyObject* obj);
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void warn_numpy_not_writeable();
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at::Tensor tensor_from_cuda_array_interface(
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PyObject* obj,
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std::optional<c10::Device> device_opt = std::nullopt);
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void validate_numpy_for_dlpack_deleter_bug();
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bool is_numpy_dlpack_deleter_bugged();
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} // namespace torch::utils
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