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Summary: Close https://github.com/pytorch/pytorch/issues/51108 Related https://github.com/pytorch/pytorch/issues/38349 This PR implements the `cpu_kernel_multiple_outputs` to support returning multiple values in a CPU kernel. ```c++ auto iter = at::TensorIteratorConfig() .add_output(out1) .add_output(out2) .add_input(in1) .add_input(in2) .build(); at::native::cpu_kernel_multiple_outputs(iter, [=](float a, float b) -> std::tuple<float, float> { float add = a + b; float mul = a * b; return std::tuple<float, float>(add, mul); } ); ``` The `out1` will equal to `torch.add(in1, in2)`, while the result of `out2` will be `torch.mul(in1, in2)`. It helps developers implement new torch functions that return two tensors more conveniently, such as NumPy-like functions [divmod](https://numpy.org/doc/1.18/reference/generated/numpy.divmod.html?highlight=divmod#numpy.divmod) and [frexp](https://numpy.org/doc/stable/reference/generated/numpy.frexp.html#numpy.frexp). This PR adds `torch.frexp` function to exercise the new functionality provided by `cpu_kernel_multiple_outputs`. Pull Request resolved: https://github.com/pytorch/pytorch/pull/51097 Reviewed By: albanD Differential Revision: D26982619 Pulled By: heitorschueroff fbshipit-source-id: cb61c7f2c79873ab72ab5a61cbdb9203531ad469 |
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| .. | ||
| _static | ||
| _templates | ||
| _templates-stable | ||
| community | ||
| notes | ||
| rpc | ||
| scripts | ||
| __config__.rst | ||
| amp.rst | ||
| autograd.rst | ||
| backends.rst | ||
| benchmark_utils.rst | ||
| bottleneck.rst | ||
| checkpoint.rst | ||
| complex_numbers.rst | ||
| conf.py | ||
| cpp_extension.rst | ||
| cpp_index.rst | ||
| cuda.rst | ||
| cudnn_persistent_rnn.rst | ||
| cudnn_rnn_determinism.rst | ||
| data.rst | ||
| ddp_comm_hooks.rst | ||
| distributed.optim.rst | ||
| distributed.rst | ||
| distributions.rst | ||
| dlpack.rst | ||
| docutils.conf | ||
| fft.rst | ||
| futures.rst | ||
| fx.rst | ||
| hub.rst | ||
| index.rst | ||
| jit.rst | ||
| jit_builtin_functions.rst | ||
| jit_language_reference.rst | ||
| jit_language_reference_v2.rst | ||
| jit_python_reference.rst | ||
| jit_unsupported.rst | ||
| linalg.rst | ||
| math-quantizer-equation.png | ||
| mobile_optimizer.rst | ||
| model_zoo.rst | ||
| multiprocessing.rst | ||
| name_inference.rst | ||
| named_tensor.rst | ||
| nn.functional.rst | ||
| nn.init.rst | ||
| nn.rst | ||
| onnx.rst | ||
| optim.rst | ||
| pipeline.rst | ||
| profiler.rst | ||
| quantization-support.rst | ||
| quantization.rst | ||
| random.rst | ||
| rpc.rst | ||
| sparse.rst | ||
| special.rst | ||
| storage.rst | ||
| tensor_attributes.rst | ||
| tensor_view.rst | ||
| tensorboard.rst | ||
| tensors.rst | ||
| torch.nn.intrinsic.qat.rst | ||
| torch.nn.intrinsic.quantized.rst | ||
| torch.nn.intrinsic.rst | ||
| torch.nn.qat.rst | ||
| torch.nn.quantized.dynamic.rst | ||
| torch.nn.quantized.rst | ||
| torch.overrides.rst | ||
| torch.quantization.rst | ||
| torch.rst | ||
| type_info.rst | ||
