193193 < div class ="pytorch-left-menu-search ">
194194
195195 < div class ="version ">
196- < a href ='https://pytorch.org/docs/versions.html '> master (1.10.0a0+git6cf311c ) ▼</ a >
196+ < a href ='https://pytorch.org/docs/versions.html '> master (1.10.0a0+git701771a ) ▼</ a >
197197 </ div >
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@@ -658,7 +658,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
658658 < span class ="k "> return</ span > < span class ="n "> module</ span > < span class ="o "> +</ span > < span class ="n "> class_name</ span >
659659
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661- < 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 >
661+ < span class ="k "> def</ span > < span class ="nf "> is_tensor</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
662662 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch tensor.</ span >
663663
664664< span class ="sd "> Note that this function is simply doing ``isinstance(obj, Tensor)``.</ span >
@@ -675,19 +675,19 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
675675< span class ="sd "> True</ span >
676676
677677< span class ="sd "> """</ span >
678- < 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 >
678+ < 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 >
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681- < 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 >
681+ < span class ="k "> def</ span > < span class ="nf "> is_storage</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
682682 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch storage object.</ span >
683683
684684< span class ="sd "> Args:</ span >
685685< span class ="sd "> obj (Object): Object to test</ span >
686686< span class ="sd "> """</ span >
687- < 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 >
687+ < 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 >
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690- < 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 >
690+ < 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 >
691691 < span class ="sa "> r</ span > < span class ="sd "> """Sets the default ``torch.Tensor`` type to floating point tensor type</ span >
692692< span class ="sd "> ``t``. This type will also be used as default floating point type for</ span >
693693< span class ="sd "> type inference in :func:`torch.tensor`.</ span >
@@ -708,10 +708,10 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
708708< span class ="sd "> """</ span >
709709 < 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 >
710710 < 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 >
711- < 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 >
711+ < 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 >
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714- < 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 >
714+ < 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 >
715715 < span class ="sa "> r</ span > < span class ="sd "> """</ span >
716716
717717< span class ="sd "> Sets the default floating point dtype to :attr:`d`. Supports torch.float32</ span >
@@ -754,9 +754,9 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
754754< span class ="sd "> torch.complex128</ span >
755755
756756< span class ="sd "> """</ span >
757- < 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 >
757+ < 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 >
758758
759- < 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 >
759+ < 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 >
760760 < span class ="sa "> r</ span > < span class ="sd "> """ Sets whether PyTorch operations must use "deterministic"</ span >
761761< span class ="sd "> algorithms. That is, algorithms which, given the same input, and when</ span >
762762< span class ="sd "> run on the same software and hardware, always produce the same output.</ span >
@@ -871,15 +871,15 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
871871< span class ="sd "> ...</ span >
872872< span class ="sd "> RuntimeError: index_add_cuda_ does not have a deterministic implementation...</ span >
873873< span class ="sd "> """</ span >
874- < 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 >
874+ < 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 >
875875
876876< span class ="k "> def</ span > < span class ="nf "> are_deterministic_algorithms_enabled</ span > < span class ="p "> ():</ span >
877877 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if the global deterministic flag is turned on. Refer to</ span >
878878< span class ="sd "> :func:`torch.use_deterministic_algorithms` documentation for more details.</ span >
879879< span class ="sd "> """</ span >
880880 < span class ="k "> return</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _get_deterministic_algorithms</ span > < span class ="p "> ()</ span >
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882- < 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 >
882+ < 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 >
883883 < span class ="sa "> r</ span > < span class ="sd "> """When this flag is False (default) then some PyTorch warnings may only</ span >
884884< span class ="sd "> appear once per process. This helps avoid excessive warning information.</ span >
885885< span class ="sd "> Setting it to True causes these warnings to always appear, which may be</ span >
@@ -889,13 +889,13 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
889889< span class ="sd "> b (:class:`bool`): If True, force warnings to always be emitted</ span >
890890< span class ="sd "> If False, set to the default behaviour</ span >
891891< span class ="sd "> """</ span >
892- < 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 >
892+ < 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 >
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894- < 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 >
894+ < span class ="k "> def</ span > < span class ="nf "> is_warn_always_enabled</ span > < span class ="p "> ():</ span >
895895 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if the global warn_always flag is turned on. Refer to</ span >
896896< span class ="sd "> :func:`torch.set_warn_always` documentation for more details.</ span >
897897< span class ="sd "> """</ span >
898- < 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 >
898+ < span class ="k "> return</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _get_warnAlways</ span > < span class ="p "> ()</ span >
899899
900900< span class ="c1 "> ################################################################################</ span >
901901< span class ="c1 "> # Define numeric constants</ span >
@@ -1120,9 +1120,9 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
11201120< span class ="k "> del</ span > < span class ="n "> _torch_docs</ span > < span class ="p "> ,</ span > < span class ="n "> _tensor_docs</ span > < span class ="p "> ,</ span > < span class ="n "> _storage_docs</ span >
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1123- < span class ="k "> def</ span > < span class ="nf "> compiled_with_cxx11_abi</ span > < span class ="p "> ():</ span >
1123+ < div class =" viewcode-block " id =" compiled_with_cxx11_abi " > < a class =" viewcode-back " href =" ../generated/torch.compiled_with_cxx11_abi.html#torch.compiled_with_cxx11_abi " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> compiled_with_cxx11_abi</ span > < span class ="p "> ():</ span >
11241124 < span class ="sa "> r</ span > < span class ="sd "> """Returns whether PyTorch was built with _GLIBCXX_USE_CXX11_ABI=1"""</ span >
1125- < span class ="k "> return</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _GLIBCXX_USE_CXX11_ABI</ span >
1125+ < span class ="k "> return</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _GLIBCXX_USE_CXX11_ABI</ span > </ div >
11261126
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11281128< span class ="c1 "> # Import the ops "namespace"</ span >
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