188188 < div class ="pytorch-left-menu-search ">
189189
190190 < div class ="version ">
191- < a href ='https://pytorch.org/docs/versions.html '> master (1.9.0a0+gitadfc9a3 ) ▼</ a >
191+ < a href ='https://pytorch.org/docs/versions.html '> master (1.9.0a0+git4ee630a ) ▼</ a >
192192 </ div >
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@@ -650,7 +650,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
650650 < span class ="k "> return</ span > < span class ="n "> module</ span > < span class ="o "> +</ span > < span class ="n "> class_name</ span >
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653- < 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 >
653+ < span class ="k "> def</ span > < span class ="nf "> is_tensor</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
654654 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch tensor.</ span >
655655
656656< span class ="sd "> Note that this function is simply doing ``isinstance(obj, Tensor)``.</ span >
@@ -667,19 +667,19 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
667667< span class ="sd "> True</ span >
668668
669669< span class ="sd "> """</ span >
670- < 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 >
670+ < 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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673- < 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 >
673+ < span class ="k "> def</ span > < span class ="nf "> is_storage</ span > < span class ="p "> (</ span > < span class ="n "> obj</ span > < span class ="p "> ):</ span >
674674 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if `obj` is a PyTorch storage object.</ span >
675675
676676< span class ="sd "> Args:</ span >
677677< span class ="sd "> obj (Object): Object to test</ span >
678678< span class ="sd "> """</ span >
679- < 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 >
679+ < 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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682- < 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 >
682+ < 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 >
683683 < span class ="sa "> r</ span > < span class ="sd "> """Sets the default ``torch.Tensor`` type to floating point tensor type</ span >
684684< span class ="sd "> ``t``. This type will also be used as default floating point type for</ span >
685685< span class ="sd "> type inference in :func:`torch.tensor`.</ span >
@@ -700,10 +700,10 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
700700< span class ="sd "> """</ span >
701701 < 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 >
702702 < 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 >
703- < 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 >
703+ < 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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706- < 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 >
706+ < 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 >
707707 < span class ="sa "> r</ span > < span class ="sd "> """Sets the default floating point dtype to :attr:`d`.</ span >
708708< span class ="sd "> This dtype is:</ span >
709709
@@ -731,9 +731,9 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
731731< span class ="sd "> torch.complex128</ span >
732732
733733< span class ="sd "> """</ span >
734- < 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 >
734+ < 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 >
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736- < 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 >
736+ < 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 >
737737 < span class ="sa "> r</ span > < span class ="sd "> """ Sets whether PyTorch operations must use "deterministic"</ span >
738738< span class ="sd "> algorithms. That is, algorithms which, given the same input, and when</ span >
739739< span class ="sd "> run on the same software and hardware, always produce the same output.</ span >
@@ -849,7 +849,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
849849< span class ="sd "> ...</ span >
850850< span class ="sd "> RuntimeError: index_add_cuda_ does not have a deterministic implementation...</ span >
851851< span class ="sd "> """</ span >
852- < 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 >
852+ < 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 >
853853
854854< span class ="k "> def</ span > < span class ="nf "> set_deterministic</ span > < span class ="p "> (</ span > < span class ="n "> d</ span > < span class ="p "> ):</ span >
855855 < span class ="sa "> r</ span > < span class ="sd "> """This function is deprecated and will be removed in a future release.</ span >
@@ -877,7 +877,7 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
877877 < span class ="k "> return</ span > < span class ="n "> are_deterministic_algorithms_enabled</ span > < span class ="p "> ()</ span >
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880- < 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 >
880+ < 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 >
881881 < span class ="sa "> r</ span > < span class ="sd "> """When this flag is False (default) then some PyTorch warnings may only</ span >
882882< span class ="sd "> appear once per process. This helps avoid excessive warning information.</ span >
883883< span class ="sd "> Setting it to True causes these warnings to always appear, which may be</ span >
@@ -887,13 +887,13 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
887887< span class ="sd "> b (:class:`bool`): If True, force warnings to always be emitted</ span >
888888< span class ="sd "> If False, set to the default behaviour</ span >
889889< span class ="sd "> """</ span >
890- < 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 >
890+ < 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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892- < 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 >
892+ < span class ="k "> def</ span > < span class ="nf "> is_warn_always_enabled</ span > < span class ="p "> ():</ span >
893893 < span class ="sa "> r</ span > < span class ="sd "> """Returns True if the global warn_always flag is turned on. Refer to</ span >
894894< span class ="sd "> :func:`torch.set_warn_always` documentation for more details.</ span >
895895< span class ="sd "> """</ span >
896- < 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 >
896+ < span class ="k "> return</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _get_warnAlways</ span > < span class ="p "> ()</ span >
897897
898898< span class ="c1 "> ################################################################################</ span >
899899< span class ="c1 "> # Define Storage and Tensor classes</ span >
@@ -1039,14 +1039,14 @@ <h1>Source code for torch</h1><div class="highlight"><pre>
10391039< span class ="c1 "> ################################################################################</ span >
10401040
10411041< span class ="c1 "> # needs to be before the submodule imports to avoid circular dependencies</ span >
1042- < span class ="k "> def</ span > < span class ="nf "> _assert</ span > < span class ="p "> (</ span > < span class ="n "> condition</ span > < span class ="p "> ,</ span > < span class ="n "> message</ span > < span class ="p "> ):</ span >
1042+ < div class =" viewcode-block " id =" _assert " > < a class =" viewcode-back " href =" ../generated/torch._assert.html#torch._assert " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> _assert</ span > < span class ="p "> (</ span > < span class ="n "> condition</ span > < span class ="p "> ,</ span > < span class ="n "> message</ span > < span class ="p "> ):</ span >
10431043 < span class ="sa "> r</ span > < span class ="sd "> """A wrapper around Python's assert which is symbolically traceable.</ span >
10441044< span class ="sd "> """</ span >
10451045 < span class ="kn "> from</ span > < span class ="nn "> .overrides</ span > < span class ="kn "> import</ span > < span class ="n "> has_torch_function</ span > < span class ="p "> ,</ span > < span class ="n "> handle_torch_function</ span >
10461046
10471047 < span class ="k "> if</ span > < span class ="nb "> type</ span > < span class ="p "> (</ span > < span class ="n "> condition</ span > < span class ="p "> )</ span > < span class ="ow "> is</ span > < span class ="ow "> not</ span > < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> Tensor</ span > < span class ="ow "> and</ span > < span class ="n "> has_torch_function</ span > < span class ="p "> ((</ span > < span class ="n "> condition</ span > < span class ="p "> ,)):</ span >
10481048 < span class ="k "> return</ span > < span class ="n "> handle_torch_function</ span > < span class ="p "> (</ span > < span class ="n "> _assert</ span > < span class ="p "> ,</ span > < span class ="p "> (</ span > < span class ="n "> condition</ span > < span class ="p "> ,),</ span > < span class ="n "> condition</ span > < span class ="p "> ,</ span > < span class ="n "> message</ span > < span class ="p "> )</ span >
1049- < span class ="k "> assert</ span > < span class ="n "> condition</ span > < span class ="p "> ,</ span > < span class ="n "> message</ span >
1049+ < span class ="k "> assert</ span > < span class ="n "> condition</ span > < span class ="p "> ,</ span > < span class ="n "> message</ span > </ div >
10501050
10511051< span class ="c1 "> ################################################################################</ span >
10521052< span class ="c1 "> # Import most common subpackages</ span >
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