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160160 < div class ="version ">
161- < a href ='http://pytorch.org/docs/versions.html '> 1.7.0a0+b87f0e5 ▼</ a >
161+ < a href ='http://pytorch.org/docs/versions.html '> 1.7.0a0+fa9ae67 ▼</ a >
162162 </ div >
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164164
256256< ul >
257257< li class ="toctree-l1 "> < a class ="reference external " href ="https://pytorch.org/audio "> torchaudio</ a > </ li >
258258< li class ="toctree-l1 "> < a class ="reference external " href ="https://pytorch.org/text "> torchtext</ a > </ li >
259- < li class ="toctree-l1 "> < a class ="reference internal " href ="../torchvision/index.html "> torchvision</ a > </ li >
259+ < li class ="toctree-l1 "> < a class ="reference external " href ="https://pytorch.org/vision "> torchvision</ a > </ li >
260260< li class ="toctree-l1 "> < a class ="reference external " href ="https://pytorch.org/elastic/ "> TorchElastic</ a > </ li >
261261< li class ="toctree-l1 "> < a class ="reference external " href ="https://pytorch.org/serve "> TorchServe</ a > </ li >
262262< li class ="toctree-l1 "> < a class ="reference external " href ="http://pytorch.org/xla/ "> PyTorch on XLA Devices</ a > </ li >
@@ -341,7 +341,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
341341< span > </ span >
342342< span class ="sa "> r</ span > < span class ="sd "> """</ span >
343343< span class ="sd "> The torch package contains data structures for multi-dimensional</ span >
344- < span class ="sd "> tensors. It also defines mathematical operations that can be performed over these tensors.</ span >
344+ < span class ="sd "> tensors and defines mathematical operations over these tensors.</ span >
345345< span class ="sd "> Additionally, it provides many utilities for efficient serializing of</ span >
346346< span class ="sd "> Tensors and arbitrary types, and other useful utilities.</ span >
347347
@@ -562,7 +562,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
562562 < span class ="k "> return</ span > < span class ="n "> module</ span > < span class ="o "> +</ span > < span class ="n "> class_name</ span >
563563
564564
565- < span class ="k "> def</ span > < span class ="nf "> is_tensor</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
565+ < div class =" viewcode-block " id =" is_tensor " > < a class =" viewcode-back " href =" ../generated/torch.is_tensor.html#torch.is_tensor " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> is_tensor</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
566566 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch tensor.</ span >
567567
568568< span class ="sd "> Note that this function is simply doing ``isinstance(obj, Tensor)``.</ span >
@@ -573,16 +573,16 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
573573< span class ="sd "> Args:</ span >
574574< span class ="sd "> obj (Object): Object to test</ span >
575575< span class ="sd "> """</ span >
576- < span class ="k "> return</ span > < span class ="nb "> isinstance</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ,</ span > < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> Tensor</ span > < span class ="p "> )</ span >
576+ < span class ="k "> return</ span > < span class ="nb "> isinstance</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ,</ span > < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> Tensor</ span > < span class ="p "> )</ span > </ div >
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579- < span class ="k "> def</ span > < span class ="nf "> is_storage</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
579+ < div class =" viewcode-block " id =" is_storage " > < a class =" viewcode-back " href =" ../generated/torch.is_storage.html#torch.is_storage " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> is_storage</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
580580 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch storage object.</ span >
581581
582582< span class ="sd "> Args:</ span >
583583< span class ="sd "> obj (Object): Object to test</ span >
584584< span class ="sd "> """</ span >
585- < span class ="k "> return</ span > < span class ="nb "> type</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> )</ span > < span class ="ow "> in</ span > < span class ="n "> _storage_classes</ span >
585+ < span class ="k "> return</ span > < span class ="nb "> type</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> )</ span > < span class ="ow "> in</ span > < span class ="n "> _storage_classes</ span > </ div >
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588588< span class ="k "> def</ span > < span class ="nf "> set_default_tensor_type</ span > < span class ="p "> (</ span > < span class ="n "> t</ span > < span class ="p "> ):</ span >
@@ -612,6 +612,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
612612< span class ="k "> def</ span > < span class ="nf "> set_default_dtype</ span > < span class ="p "> (</ span > < span class ="n "> d</ span > < span class ="p "> ):</ span >
613613 < span class ="sa "> r</ span > < span class ="sd "> """Sets the default floating point dtype to :attr:`d`.</ span >
614614< span class ="sd "> This dtype is:</ span >
615+
615616< span class ="sd "> 1. The inferred dtype for python floats in :func:`torch.tensor`.</ span >
616617< span class ="sd "> 2. Used to infer dtype for python complex numbers. The default complex dtype is set to</ span >
617618< span class ="sd "> ``torch.complex128`` if default floating point dtype is ``torch.float64``,</ span >
@@ -622,7 +623,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
622623< span class ="sd "> Args:</ span >
623624< span class ="sd "> d (:class:`torch.dtype`): the floating point dtype to make the default</ span >
624625
625- < span class ="sd "> Example:: </ span >
626+ < span class ="sd "> Example:</ span >
626627< span class ="sd "> >>> # initial default for floating point is torch.float32</ span >
627628< span class ="sd "> >>> torch.tensor([1.2, 3]).dtype</ span >
628629< span class ="sd "> torch.float32</ span >
@@ -671,8 +672,8 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
671672 < span class ="k "> pass</ span >
672673
673674
674- < div class =" viewcode-block " id =" FloatStorage " > < a class =" viewcode-back " href =" ../storage.html#torch.FloatStorage " > [docs] </ a > < span class ="k "> class</ span > < span class ="nc "> FloatStorage</ span > < span class ="p "> (</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> FloatStorageBase</ span > < span class ="p "> ,</ span > < span class ="n "> _StorageBase</ span > < span class ="p "> ):</ span >
675- < span class ="k "> pass</ span > </ div >
675+ < span class ="k "> class</ span > < span class ="nc "> FloatStorage</ span > < span class ="p "> (</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> FloatStorageBase</ span > < span class ="p "> ,</ span > < span class ="n "> _StorageBase</ span > < span class ="p "> ):</ span >
676+ < span class ="k "> pass</ span >
676677
677678
678679< span class ="k "> class</ span > < span class ="nc "> HalfStorage</ span > < span class ="p "> (</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> HalfStorageBase</ span > < span class ="p "> ,</ span > < span class ="n "> _StorageBase</ span > < span class ="p "> ):</ span >
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