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033b7ae3ef
Summary: Related to https://github.com/pytorch/pytorch/issues/38349 Implement NumPy-like functions `maximum` and `minimum`. The `maximum` and `minimum` functions compute input tensors element-wise, returning a new array with the element-wise maxima/minima. If one of the elements being compared is a NaN, then that element is returned, both `maximum` and `minimum` functions do not support complex inputs. This PR also promotes the overloaded versions of torch.max and torch.min, by re-dispatching binary `torch.max` and `torch.min` to `torch.maximum` and `torch.minimum`. Pull Request resolved: https://github.com/pytorch/pytorch/pull/42579 Reviewed By: mrshenli Differential Revision: D23153081 Pulled By: mruberry fbshipit-source-id: 803506c912440326d06faa1b71964ec06775eac1 |
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| .. | ||
| _static | ||
| _templates | ||
| _templates-stable | ||
| community | ||
| notes | ||
| rpc | ||
| scripts | ||
| __config__.rst | ||
| amp.rst | ||
| autograd.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 | ||
| distributed.rst | ||
| distributions.rst | ||
| dlpack.rst | ||
| docutils.conf | ||
| fft.rst | ||
| futures.rst | ||
| hub.rst | ||
| index.rst | ||
| jit.rst | ||
| jit_builtin_functions.rst | ||
| jit_language_reference.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 | ||
| quantization-support.rst | ||
| quantization.rst | ||
| random.rst | ||
| rpc.rst | ||
| sparse.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.quantization.rst | ||
| torch.rst | ||
| type_info.rst | ||
