217217 < div class ="pytorch-left-menu-search ">
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219219 < div class ="version ">
220- < a href ='https://pytorch.org/docs/versions.html '> master (1.12.0a0+gite175065 ) ▼</ a >
220+ < a href ='https://pytorch.org/docs/versions.html '> master (1.12.0a0+gitedffd59 ) ▼</ a >
221221 </ div >
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223223
@@ -764,7 +764,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
764764 < span class ="c1 "> # All strings are unicode in Python 3.</ span >
765765 < span class ="k "> return</ span > < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> _tensor_str</ span > < span class ="o "> .</ span > < span class ="n "> _str</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> tensor_contents</ span > < span class ="o "> =</ span > < span class ="n "> tensor_contents</ span > < span class ="p "> )</ span >
766766
767- < div class =" viewcode-block " id =" Tensor.backward " > < a class =" viewcode-back " href =" ../../generated/torch.Tensor.backward.html#torch.Tensor.backward " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> backward</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> gradient</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="n "> retain_graph</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="n "> create_graph</ span > < span class ="o "> =</ span > < span class ="kc "> False</ span > < span class ="p "> ,</ span > < span class ="n "> inputs</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ):</ span >
767+ < span class ="k "> def</ span > < span class ="nf "> backward</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> gradient</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="n "> retain_graph</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="n "> create_graph</ span > < span class ="o "> =</ span > < span class ="kc "> False</ span > < span class ="p "> ,</ span > < span class ="n "> inputs</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ):</ span >
768768 < span class ="sa "> r</ span > < span class ="sd "> """Computes the gradient of current tensor w.r.t. graph leaves.</ span >
769769
770770< span class ="sd "> The graph is differentiated using the chain rule. If the tensor is</ span >
@@ -820,7 +820,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
820820 < span class ="n "> retain_graph</ span > < span class ="o "> =</ span > < span class ="n "> retain_graph</ span > < span class ="p "> ,</ span >
821821 < span class ="n "> create_graph</ span > < span class ="o "> =</ span > < span class ="n "> create_graph</ span > < span class ="p "> ,</ span >
822822 < span class ="n "> inputs</ span > < span class ="o "> =</ span > < span class ="n "> inputs</ span > < span class ="p "> )</ span >
823- < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> autograd</ span > < span class ="o "> .</ span > < span class ="n "> backward</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> gradient</ span > < span class ="p "> ,</ span > < span class ="n "> retain_graph</ span > < span class ="p "> ,</ span > < span class ="n "> create_graph</ span > < span class ="p "> ,</ span > < span class ="n "> inputs</ span > < span class ="o "> =</ span > < span class ="n "> inputs</ span > < span class ="p "> )</ span > </ div >
823+ < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> autograd</ span > < span class ="o "> .</ span > < span class ="n "> backward</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> gradient</ span > < span class ="p "> ,</ span > < span class ="n "> retain_graph</ span > < span class ="p "> ,</ span > < span class ="n "> create_graph</ span > < span class ="p "> ,</ span > < span class ="n "> inputs</ span > < span class ="o "> =</ span > < span class ="n "> inputs</ span > < span class ="p "> )</ span >
824824
825825 < span class ="k "> def</ span > < span class ="nf "> register_hook</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> hook</ span > < span class ="p "> ):</ span >
826826 < span class ="sa "> r</ span > < span class ="sd "> """Registers a backward hook.</ span >
@@ -922,14 +922,14 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
922922< span class ="s2 "> have forward mode AD gradients.</ span >
923923< span class ="s2 "> """</ span > < span class ="p "> )</ span >
924924
925- < span class ="k "> def</ span > < span class ="nf "> is_shared</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ):</ span >
925+ < div class =" viewcode-block " id =" Tensor.is_shared " > < a class =" viewcode-back " href =" ../../generated/torch.Tensor.is_shared.html#torch.Tensor.is_shared " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> is_shared</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ):</ span >
926926 < span class ="sa "> r</ span > < span class ="sd "> """Checks if tensor is in shared memory.</ span >
927927
928928< span class ="sd "> This is always ``True`` for CUDA tensors.</ span >
929929< span class ="sd "> """</ span >
930930 < span class ="k "> if</ span > < span class ="n "> has_torch_function_unary</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ):</ span >
931931 < span class ="k "> return</ span > < span class ="n "> handle_torch_function</ span > < span class ="p "> (</ span > < span class ="n "> Tensor</ span > < span class ="o "> .</ span > < span class ="n "> is_shared</ span > < span class ="p "> ,</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,),</ span > < span class ="bp "> self</ span > < span class ="p "> )</ span >
932- < span class ="k "> return</ span > < span class ="bp "> self</ span > < span class ="o "> .</ span > < span class ="n "> storage</ span > < span class ="p "> ()</ span > < span class ="o "> .</ span > < span class ="n "> is_shared</ span > < span class ="p "> ()</ span >
932+ < span class ="k "> return</ span > < span class ="bp "> self</ span > < span class ="o "> .</ span > < span class ="n "> storage</ span > < span class ="p "> ()</ span > < span class ="o "> .</ span > < span class ="n "> is_shared</ span > < span class ="p "> ()</ span > </ div >
933933
934934 < span class ="k "> def</ span > < span class ="nf "> share_memory_</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ):</ span >
935935 < span class ="sa "> r</ span > < span class ="sd "> """Moves the underlying storage to shared memory.</ span >
@@ -992,7 +992,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
992992 < span class ="k "> return</ span > < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> stft</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> n_fft</ span > < span class ="p "> ,</ span > < span class ="n "> hop_length</ span > < span class ="p "> ,</ span > < span class ="n "> win_length</ span > < span class ="p "> ,</ span > < span class ="n "> window</ span > < span class ="p "> ,</ span > < span class ="n "> center</ span > < span class ="p "> ,</ span >
993993 < span class ="n "> pad_mode</ span > < span class ="p "> ,</ span > < span class ="n "> normalized</ span > < span class ="p "> ,</ span > < span class ="n "> onesided</ span > < span class ="p "> ,</ span > < span class ="n "> return_complex</ span > < span class ="o "> =</ span > < span class ="n "> return_complex</ span > < span class ="p "> )</ span >
994994
995- < span class ="k "> def</ span > < span class ="nf "> istft</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> n_fft</ span > < span class ="p "> :</ span > < span class ="nb "> int</ span > < span class ="p "> ,</ span > < span class ="n "> hop_length</ span > < span class ="p "> :</ span > < span class ="n "> Optional</ span > < span class ="p "> [</ span > < span class ="nb "> int</ span > < span class ="p "> ]</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span >
995+ < div class =" viewcode-block " id =" Tensor.istft " > < a class =" viewcode-back " href =" ../../generated/torch.Tensor.istft.html#torch.Tensor.istft " > [docs] </ a > < span class ="k "> def</ span > < span class ="nf "> istft</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> n_fft</ span > < span class ="p "> :</ span > < span class ="nb "> int</ span > < span class ="p "> ,</ span > < span class ="n "> hop_length</ span > < span class ="p "> :</ span > < span class ="n "> Optional</ span > < span class ="p "> [</ span > < span class ="nb "> int</ span > < span class ="p "> ]</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span >
996996 < span class ="n "> win_length</ span > < span class ="p "> :</ span > < span class ="n "> Optional</ span > < span class ="p "> [</ span > < span class ="nb "> int</ span > < span class ="p "> ]</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="n "> window</ span > < span class ="p "> :</ span > < span class ="s1 "> 'Optional[Tensor]'</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span >
997997 < span class ="n "> center</ span > < span class ="p "> :</ span > < span class ="nb "> bool</ span > < span class ="o "> =</ span > < span class ="kc "> True</ span > < span class ="p "> ,</ span > < span class ="n "> normalized</ span > < span class ="p "> :</ span > < span class ="nb "> bool</ span > < span class ="o "> =</ span > < span class ="kc "> False</ span > < span class ="p "> ,</ span >
998998 < span class ="n "> onesided</ span > < span class ="p "> :</ span > < span class ="n "> Optional</ span > < span class ="p "> [</ span > < span class ="nb "> bool</ span > < span class ="p "> ]</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="n "> length</ span > < span class ="p "> :</ span > < span class ="n "> Optional</ span > < span class ="p "> [</ span > < span class ="nb "> int</ span > < span class ="p "> ]</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span >
@@ -1005,7 +1005,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
10051005 < span class ="n "> return_complex</ span > < span class ="o "> =</ span > < span class ="n "> return_complex</ span >
10061006 < span class ="p "> )</ span >
10071007 < span class ="k "> return</ span > < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> istft</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> n_fft</ span > < span class ="p "> ,</ span > < span class ="n "> hop_length</ span > < span class ="p "> ,</ span > < span class ="n "> win_length</ span > < span class ="p "> ,</ span > < span class ="n "> window</ span > < span class ="p "> ,</ span > < span class ="n "> center</ span > < span class ="p "> ,</ span >
1008- < span class ="n "> normalized</ span > < span class ="p "> ,</ span > < span class ="n "> onesided</ span > < span class ="p "> ,</ span > < span class ="n "> length</ span > < span class ="p "> ,</ span > < span class ="n "> return_complex</ span > < span class ="o "> =</ span > < span class ="n "> return_complex</ span > < span class ="p "> )</ span >
1008+ < span class ="n "> normalized</ span > < span class ="p "> ,</ span > < span class ="n "> onesided</ span > < span class ="p "> ,</ span > < span class ="n "> length</ span > < span class ="p "> ,</ span > < span class ="n "> return_complex</ span > < span class ="o "> =</ span > < span class ="n "> return_complex</ span > < span class ="p "> )</ span > </ div >
10091009
10101010 < span class ="k "> def</ span > < span class ="nf "> resize</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="o "> *</ span > < span class ="n "> sizes</ span > < span class ="p "> ):</ span >
10111011 < span class ="k "> if</ span > < span class ="n "> has_torch_function_unary</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ):</ span >
@@ -1073,6 +1073,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
10731073 < span class ="fm "> __itruediv__</ span > < span class ="o "> =</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _TensorBase</ span > < span class ="o "> .</ span > < span class ="n "> __idiv__</ span >
10741074
10751075 < span class ="fm "> __pow__</ span > < span class ="o "> =</ span > < span class ="n "> _handle_torch_function_and_wrap_type_error_to_not_implemented</ span > < span class ="p "> (</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _TensorBase</ span > < span class ="o "> .</ span > < span class ="n "> pow</ span > < span class ="p "> )</ span >
1076+ < span class ="fm "> __ipow__</ span > < span class ="o "> =</ span > < span class ="n "> _handle_torch_function_and_wrap_type_error_to_not_implemented</ span > < span class ="p "> (</ span > < span class ="n "> _C</ span > < span class ="o "> .</ span > < span class ="n "> _TensorBase</ span > < span class ="o "> .</ span > < span class ="n "> pow_</ span > < span class ="p "> )</ span >
10761077
10771078 < span class ="nd "> @_handle_torch_function_and_wrap_type_error_to_not_implemented</ span >
10781079 < span class ="k "> def</ span > < span class ="fm "> __rmod__</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> other</ span > < span class ="p "> ):</ span >
@@ -1085,10 +1086,6 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
10851086 < span class ="k "> return</ span > < span class ="bp "> self</ span > < span class ="o "> .</ span > < span class ="n "> item</ span > < span class ="p "> ()</ span > < span class ="o "> .</ span > < span class ="fm "> __format__</ span > < span class ="p "> (</ span > < span class ="n "> format_spec</ span > < span class ="p "> )</ span >
10861087 < span class ="k "> return</ span > < span class ="nb "> object</ span > < span class ="o "> .</ span > < span class ="fm "> __format__</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> format_spec</ span > < span class ="p "> )</ span >
10871088
1088- < span class ="nd "> @_handle_torch_function_and_wrap_type_error_to_not_implemented</ span >
1089- < span class ="k "> def</ span > < span class ="fm "> __ipow__</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> other</ span > < span class ="p "> ):</ span > < span class ="c1 "> # type: ignore[misc]</ span >
1090- < span class ="k "> return</ span > < span class ="bp "> NotImplemented</ span >
1091-
10921089 < span class ="nd "> @_handle_torch_function_and_wrap_type_error_to_not_implemented</ span >
10931090 < span class ="k "> def</ span > < span class ="fm "> __rpow__</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ,</ span > < span class ="n "> other</ span > < span class ="p "> ):</ span >
10941091 < span class ="n "> dtype</ span > < span class ="o "> =</ span > < span class ="n "> torch</ span > < span class ="o "> .</ span > < span class ="n "> result_type</ span > < span class ="p "> (</ span > < span class ="n "> other</ span > < span class ="p "> ,</ span > < span class ="bp "> self</ span > < span class ="p "> )</ span >
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