192192 < div class ="pytorch-left-menu-search ">
193193
194194 < div class ="version ">
195- < a href ='https://pytorch.org/docs/versions.html '> master (1.10.0a0+git27cbbb8 ) ▼</ a >
195+ < a href ='https://pytorch.org/docs/versions.html '> master (1.10.0a0+git98f637e ) ▼</ a >
196196 </ div >
197197
198198
@@ -656,7 +656,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
656656 < span class ="k "> return</ span > < span class ="n "> module</ span > < span class ="o "> +</ span > < span class ="n "> class_name</ span >
657657
658658
659- < span class ="k "> def</ span > < span class ="nf "> is_tensor</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
659+ < 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 >
660660 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch tensor.</ span >
661661
662662< span class ="sd "> Note that this function is simply doing ``isinstance(obj, Tensor)``.</ span >
@@ -673,19 +673,19 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
673673< span class ="sd "> True</ span >
674674
675675< span class ="sd "> """</ span >
676- < 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 >
676+ < 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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678678
679- < span class ="k "> def</ span > < span class ="nf "> is_storage</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
679+ < 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 >
680680 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch storage object.</ span >
681681
682682< span class ="sd "> Args:</ span >
683683< span class ="sd "> obj (Object): Object to test</ span >
684684< span class ="sd "> """</ span >
685- < 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 >
685+ < 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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688- < div class =" viewcode-block " id =" set_default_tensor_type " > < a class =" viewcode-back " href =" ../generated/torch.set_default_tensor_type.html#torch.set_default_tensor_type " > [docs] </ a > < 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 >
688+ < 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 >
689689 < span class ="sa "> r</ span > < span class ="sd "> """Sets the default ``torch.Tensor`` type to floating point tensor type</ span >
690690< span class ="sd "> ``t``. This type will also be used as default floating point type for</ span >
691691< span class ="sd "> type inference in :func:`torch.tensor`.</ span >
@@ -706,10 +706,10 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
706706< span class ="sd "> """</ span >
707707 < span class ="k "> if</ span > < span class ="nb "> isinstance</ span > < span class ="p "> (</ span > < span class ="n "> t</ span > < span class ="p "> ,</ span > < span class ="n "> _string_classes</ span > < span class ="p "> ):</ span >
708708 < span class ="n "> t</ span > < span class ="o "> =</ span > < span class ="n "> _import_dotted_name</ span > < span class ="p "> (</ span > < span class ="n "> t</ span > < span class ="p "> )</ span >
709- < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_default_tensor_type</ span > < span class ="p "> (</ span > < span class ="n "> t</ span > < span class ="p "> )</ span > </ div >
709+ < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_default_tensor_type</ span > < span class ="p "> (</ span > < span class ="n "> t</ span > < span class ="p "> )</ span >
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712- < div class =" viewcode-block " id =" set_default_dtype " > < a class =" viewcode-back " href =" ../generated/torch.set_default_dtype.html#torch.set_default_dtype " > [docs] </ a > < 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 >
712+ < 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 >
713713 < span class ="sa "> r</ span > < span class ="sd "> """Sets the default floating point dtype to :attr:`d`.</ span >
714714< span class ="sd "> This dtype is:</ span >
715715
@@ -737,9 +737,9 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
737737< span class ="sd "> torch.complex128</ span >
738738
739739< span class ="sd "> """</ span >
740- < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_default_dtype</ span > < span class ="p "> (</ span > < span class ="n "> d</ span > < span class ="p "> )</ span > </ div >
740+ < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_default_dtype</ span > < span class ="p "> (</ span > < span class ="n "> d</ span > < span class ="p "> )</ span >
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742- < span class ="k "> def</ span > < span class ="nf "> use_deterministic_algorithms</ span > < span class ="p "> (</ span > < span class ="n "> mode</ span > < span class ="p "> ):</ span >
742+ < div class =" viewcode-block " id =" use_deterministic_algorithms " > < a class =" viewcode-back " href =" ../generated/torch.use_deterministic_algorithms.html#torch.use_deterministic_algorithms " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> use_deterministic_algorithms</ span > < span class ="p "> (</ span > < span class ="n "> mode</ span > < span class ="p "> ):</ span >
743743 < span class ="sa "> r</ span > < span class ="sd "> """ Sets whether PyTorch operations must use "deterministic"</ span >
744744< span class ="sd "> algorithms. That is, algorithms which, given the same input, and when</ span >
745745< span class ="sd "> run on the same software and hardware, always produce the same output.</ span >
@@ -854,7 +854,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
854854< span class ="sd "> ...</ span >
855855< span class ="sd "> RuntimeError: index_add_cuda_ does not have a deterministic implementation...</ span >
856856< span class ="sd "> """</ span >
857- < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_deterministic_algorithms</ span > < span class ="p "> (</ span > < span class ="n "> mode</ span > < span class ="p "> )</ span >
857+ < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_deterministic_algorithms</ span > < span class ="p "> (</ span > < span class ="n "> mode</ span > < span class ="p "> )</ span > </ div >
858858
859859< span class ="k "> def</ span > < span class ="nf "> set_deterministic</ span > < span class ="p "> (</ span > < span class ="n "> d</ span > < span class ="p "> ):</ span >
860860 < span class ="sa "> r</ span > < span class ="sd "> """This function is deprecated and will be removed in a future release.</ span >
@@ -882,7 +882,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
882882 < span class ="k "> return</ span > < span class ="n "> are_deterministic_algorithms_enabled</ span > < span class ="p "> ()</ span >
883883
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885- < div class =" viewcode-block " id =" set_warn_always " > < a class =" viewcode-back " href =" ../generated/torch.set_warn_always.html#torch.set_warn_always " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> set_warn_always</ span > < span class ="p "> (</ span > < span class ="n "> b</ span > < span class ="p "> ):</ span >
885+ < span class ="k "> def</ span > < span class ="nf "> set_warn_always</ span > < span class ="p "> (</ span > < span class ="n "> b</ span > < span class ="p "> ):</ span >
886886 < span class ="sa "> r</ span > < span class ="sd "> """When this flag is False (default) then some PyTorch warnings may only</ span >
887887< span class ="sd "> appear once per process. This helps avoid excessive warning information.</ span >
888888< span class ="sd "> Setting it to True causes these warnings to always appear, which may be</ span >
@@ -892,13 +892,13 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
892892< span class ="sd "> b (:class:`bool`): If True, force warnings to always be emitted</ span >
893893< span class ="sd "> If False, set to the default behaviour</ span >
894894< span class ="sd "> """</ span >
895- < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_warnAlways</ span > < span class ="p "> (</ span > < span class ="n "> b</ span > < span class ="p "> )</ span > </ div >
895+ < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _set_warnAlways</ span > < span class ="p "> (</ span > < span class ="n "> b</ span > < span class ="p "> )</ span >
896896
897- < span class ="k "> def</ span > < span class ="nf "> is_warn_always_enabled</ span > < span class ="p "> ():</ span >
897+ < div class =" viewcode-block " id =" is_warn_always_enabled " > < a class =" viewcode-back " href =" ../generated/torch.is_warn_always_enabled.html#torch.is_warn_always_enabled " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> is_warn_always_enabled</ span > < span class ="p "> ():</ span >
898898 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if the global warn_always flag is turned on. Refer to</ span >
899899< span class ="sd "> :func:`torch.set_warn_always` documentation for more details.</ span >
900900< span class ="sd "> """</ span >
901- < span class ="k "> return</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _get_warnAlways</ span > < span class ="p "> ()</ span >
901+ < span class ="k "> return</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _get_warnAlways</ span > < span class ="p "> ()</ span > </ div >
902902
903903< span class ="c1 "> ################################################################################</ span >
904904< span class ="c1 "> # Define numeric constants</ span >
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