211
211
< div class ="pytorch-left-menu-search ">
212
212
213
213
< div class ="version ">
214
- < a href ='https://pytorch.org/docs/versions.html '> master (1.12.0a0+gitc088c8f ) ▼</ a >
214
+ < a href ='https://pytorch.org/docs/versions.html '> master (1.12.0a0+git1d49711 ) ▼</ a >
215
215
</ div >
216
216
217
217
@@ -755,7 +755,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
755
755
< span class ="c1 "> # All strings are unicode in Python 3.</ span >
756
756
< 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 >
757
757
758
- < 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 >
758
+ < 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 >
759
759
< span class ="sa "> r</ span > < span class ="sd "> """Computes the gradient of current tensor w.r.t. graph leaves.</ span >
760
760
761
761
< span class ="sd "> The graph is differentiated using the chain rule. If the tensor is</ span >
@@ -811,7 +811,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
811
811
< span class ="n "> retain_graph</ span > < span class ="o "> =</ span > < span class ="n "> retain_graph</ span > < span class ="p "> ,</ span >
812
812
< span class ="n "> create_graph</ span > < span class ="o "> =</ span > < span class ="n "> create_graph</ span > < span class ="p "> ,</ span >
813
813
< span class ="n "> inputs</ span > < span class ="o "> =</ span > < span class ="n "> inputs</ span > < span class ="p "> )</ span >
814
- < 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 >
814
+ < 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 >
815
815
816
816
< 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 >
817
817
< span class ="sa "> r</ span > < span class ="sd "> """Registers a backward hook.</ span >
@@ -913,14 +913,14 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
913
913
< span class ="s2 "> have forward mode AD gradients.</ span >
914
914
< span class ="s2 "> """</ span > < span class ="p "> )</ span >
915
915
916
- < 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 >
916
+ < span class ="k "> def</ span > < span class ="nf "> is_shared</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ):</ span >
917
917
< span class ="sa "> r</ span > < span class ="sd "> """Checks if tensor is in shared memory.</ span >
918
918
919
919
< span class ="sd "> This is always ``True`` for CUDA tensors.</ span >
920
920
< span class ="sd "> """</ span >
921
921
< 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 >
922
922
< 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 >
923
- < 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 >
923
+ < 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 >
924
924
925
925
< span class ="k "> def</ span > < span class ="nf "> share_memory_</ span > < span class ="p "> (</ span > < span class ="bp "> self</ span > < span class ="p "> ):</ span >
926
926
< span class ="sa "> r</ span > < span class ="sd "> """Moves the underlying storage to shared memory.</ span >
@@ -979,7 +979,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
979
979
< 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 >
980
980
< 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 >
981
981
982
- < 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 >
982
+ < 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 >
983
983
< 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 >
984
984
< 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 >
985
985
< 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 >
@@ -992,7 +992,7 @@ <h1>Source code for torch._tensor</h1><div class="highlight"><pre>
992
992
< span class ="n "> return_complex</ span > < span class ="o "> =</ span > < span class ="n "> return_complex</ span >
993
993
< span class ="p "> )</ span >
994
994
< 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 >
995
- < 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 >
995
+ < 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 >
996
996
997
997
< 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 >
998
998
< 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 >
0 commit comments