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3f58dd18dc
**Reopened** to help with merge issues. See #59790 for full context. Fixes #20778. Helps #71688. Finalizes @martinPasen's force argument for `Tensor.numpy()`. It is set to False by default. If it's set to True then we: 1. detatch the Tensor, if requires_grad == True 2. move to cpu, if not on cpu already 3. Uses .resolve_conj() if .is_conj() == True 4. Uses .resolve_neg() if .is_neg() == True cc @albanD Pull Request resolved: https://github.com/pytorch/pytorch/pull/78564 Approved by: https://github.com/albanD
22 lines
600 B
C++
22 lines
600 B
C++
#pragma once
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#include <torch/csrc/python_headers.h>
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#include <ATen/core/Tensor.h>
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namespace torch { namespace utils {
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PyObject* tensor_to_numpy(const at::Tensor& tensor, bool force=false);
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at::Tensor tensor_from_numpy(PyObject* obj, bool warn_if_not_writeable=true);
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int aten_to_numpy_dtype(const at::ScalarType scalar_type);
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at::ScalarType numpy_dtype_to_aten(int dtype);
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bool is_numpy_available();
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bool is_numpy_int(PyObject* obj);
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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(PyObject* obj);
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}} // namespace torch::utils
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