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- master (2.0.0a0+git5f1ac18 ) ▼ + master (2.0.0a0+git218d4ea ) ▼
diff --git a/docs/master/_modules/torch.html b/docs/master/_modules/torch.html index 4a49a8cc4e4e..a765b7ff3c44 100644 --- a/docs/master/_modules/torch.html +++ b/docs/master/_modules/torch.html @@ -235,7 +235,7 @@
- master (2.0.0a0+git5f1ac18 ) ▼ + master (2.0.0a0+git218d4ea ) ▼
@@ -1772,6 +1772,7 @@

Source code for torch

     solve,
     lstsq,
 )
+from ._linalg_utils import _symeig as symeig  # type: ignore[misc]
 
 class _TorchCompileInductorWrapper:
     compiler_name = "inductor"
diff --git a/docs/master/_modules/torch/__config__.html b/docs/master/_modules/torch/__config__.html
index 7ac6e387f17a..262b1bb84c18 100644
--- a/docs/master/_modules/torch/__config__.html
+++ b/docs/master/_modules/torch/__config__.html
@@ -235,7 +235,7 @@
           

             
     

-      master (2.0.0a0+git5f1ac18 ) ▼
+      master (2.0.0a0+git218d4ea ) ▼
     

     
 
diff --git a/docs/master/_modules/torch/_dynamo.html b/docs/master/_modules/torch/_dynamo.html
index 068f5e964233..5fedb11b38e8 100644
--- a/docs/master/_modules/torch/_dynamo.html
+++ b/docs/master/_modules/torch/_dynamo.html
@@ -235,7 +235,7 @@
           

             
     

-      master (2.0.0a0+git5f1ac18 ) ▼
+      master (2.0.0a0+git218d4ea ) ▼
     

     
 
diff --git a/docs/master/_modules/torch/_dynamo/eval_frame.html b/docs/master/_modules/torch/_dynamo/eval_frame.html
index b44156db2c81..94094c487131 100644
--- a/docs/master/_modules/torch/_dynamo/eval_frame.html
+++ b/docs/master/_modules/torch/_dynamo/eval_frame.html
@@ -235,7 +235,7 @@
           

             
     

-      master (2.0.0a0+git5f1ac18 ) ▼
+      master (2.0.0a0+git218d4ea ) ▼
     

     
 
diff --git a/docs/master/_modules/torch/_jit_internal.html b/docs/master/_modules/torch/_jit_internal.html
index a20b3916d2a1..c09aecdce6cf 100644
--- a/docs/master/_modules/torch/_jit_internal.html
+++ b/docs/master/_modules/torch/_jit_internal.html
@@ -235,7 +235,7 @@
           

             
     

-      master (2.0.0a0+git5f1ac18 ) ▼
+      master (2.0.0a0+git218d4ea ) ▼
     

     
 
diff --git a/docs/master/_modules/torch/_lobpcg.html b/docs/master/_modules/torch/_lobpcg.html
index f23767a2d567..d12fee674808 100644
--- a/docs/master/_modules/torch/_lobpcg.html
+++ b/docs/master/_modules/torch/_lobpcg.html
@@ -235,7 +235,7 @@
           

             
     

-      master (2.0.0a0+git5f1ac18 ) ▼
+      master (2.0.0a0+git218d4ea ) ▼
     

     
 
diff --git a/docs/master/_modules/torch/_lowrank.html b/docs/master/_modules/torch/_lowrank.html
index 4a5c0f09731b..2ef7625bbce3 100644
--- a/docs/master/_modules/torch/_lowrank.html
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diff --git a/docs/master/_modules/torch/_tensor.html b/docs/master/_modules/torch/_tensor.html
index 7115f446fec9..cfae6bf67798 100644
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@@ -1129,6 +1129,11 @@ 
Source code for torch._tensor
 
         return eig(self, eigenvectors=eigenvectors)
 
+    def symeig(self, eigenvectors=False):
+        from ._linalg_utils import _symeig
+
+        return _symeig(self, eigenvectors=eigenvectors)
+
 
[docs]    def lu(self, pivot=True, get_infos=False):
         r"""See :func:`torch.lu`"""
         # If get_infos is True, then we don't need to check for errors and vice versa
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Source code for torch.cuda
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+
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@@ -780,17 +780,10 @@ 
Source code for torch.cuda
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     def __enter__(self):
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-        self.prev_idx = torch.cuda.current_device()
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-        if not torch.jit.is_scripting():
-            _lazy_init()
+        self.prev_idx = torch.cuda._exchange_device(self.idx)
 
     def __exit__(self, type: Any, value: Any, traceback: Any):
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Source code for torch.fx.graph_module
     # we need to define deepcopy otherwise it will call __reduce__
     # and cause symbolic tracing to occur every time we try to copy the object
     def __deepcopy__(self, memo):
+        res = type(self).__new__(type(self))
+        memo[id(self)] = res
         fake_mod = torch.nn.Module()
         fake_mod.__dict__ = copy.deepcopy(self.__dict__, memo)
-        res = GraphModule(fake_mod, fake_mod.__dict__['_graph'])
+        GraphModule.__init__(res, fake_mod, fake_mod.__dict__['_graph'])
         res.meta = copy.deepcopy(getattr(self, 'meta', {}), memo)
         return res
 
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Source code for torch.nn.functional
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Source code for torch.optim.adam
             group.setdefault('foreach', None)
             group.setdefault('capturable', False)
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-            group.setdefault('fused', False)
+            group.setdefault('fused', None)
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Source code for torch.overrides
         Tensor.new_full,
         Tensor._make_subclass,
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Source code for torch.overrides
         torch.svd_lowrank: lambda input, q=6, niter=2, M=None: -1,
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diff --git a/docs/master/_modules/typing.html b/docs/master/_modules/typing.html
index 515ce68820b8..69e554d89aeb 100644
--- a/docs/master/_modules/typing.html
+++ b/docs/master/_modules/typing.html
@@ -235,7 +235,7 @@
           

             
     

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diff --git a/docs/master/_sources/community/governance.rst.txt b/docs/master/_sources/community/governance.rst.txt
index 3aa124846328..7898401d6785 100644
--- a/docs/master/_sources/community/governance.rst.txt
+++ b/docs/master/_sources/community/governance.rst.txt
@@ -128,8 +128,8 @@ The Process for Nomination
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 * Each module has its own process. Please contact module maintainers for more information.
-  However, if there is no process identified, you can file a request to the core maintainers
-  by submitting `this form `__. Core maintainers are
+  However, if there is no process identified, you can file a request to the core
+  maintainers by submitting a proposal form (coming soon). Core maintainers are
   meeting every three months.
 * If you are submitting a request to the core maintainers, the information in your request
   must include the following items:
diff --git a/docs/master/_sources/generated/torch.Tensor.symeig.rst.txt b/docs/master/_sources/generated/torch.Tensor.symeig.rst.txt
deleted file mode 100644
index c56547e8544c..000000000000
--- a/docs/master/_sources/generated/torch.Tensor.symeig.rst.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-ο»Ώtorch.Tensor.symeig
-===================
-
-.. currentmodule:: torch
-
-.. automethod:: Tensor.symeig
\ No newline at end of file
diff --git a/docs/master/_sources/generated/torch.symeig.rst.txt b/docs/master/_sources/generated/torch.symeig.rst.txt
deleted file mode 100644
index 151f63246f78..000000000000
--- a/docs/master/_sources/generated/torch.symeig.rst.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-ο»Ώtorch.symeig
-============
-
-.. currentmodule:: torch
-
-.. autofunction:: symeig
\ No newline at end of file
diff --git a/docs/master/_sources/sparse.rst.txt b/docs/master/_sources/sparse.rst.txt
index 377368e09c78..c273f74b8c0b 100644
--- a/docs/master/_sources/sparse.rst.txt
+++ b/docs/master/_sources/sparse.rst.txt
@@ -38,7 +38,7 @@ performance optimization.
 
 Like many other performance optimization sparse storage formats are not
 always advantageous. When trying sparse formats for your use case
-you might find your execution time to decrease rather than increase.
+you might find your execution time to increase rather than decrease.
 
 Please feel encouraged to open a GitHub issue if you analytically
 expected to see a stark increase in performance but measured a
diff --git a/docs/master/_sources/tensors.rst.txt b/docs/master/_sources/tensors.rst.txt
index 2700e613ad4c..4f6de6f62d53 100644
--- a/docs/master/_sources/tensors.rst.txt
+++ b/docs/master/_sources/tensors.rst.txt
@@ -650,7 +650,6 @@ Tensor class reference
     Tensor.svd
     Tensor.swapaxes
     Tensor.swapdims
-    Tensor.symeig
     Tensor.t
     Tensor.t_
     Tensor.tensor_split
diff --git a/docs/master/_sources/torch.rst.txt b/docs/master/_sources/torch.rst.txt
index bbec47f69404..a4f0a2c721e1 100644
--- a/docs/master/_sources/torch.rst.txt
+++ b/docs/master/_sources/torch.rst.txt
@@ -589,7 +589,6 @@ BLAS and LAPACK Operations
     svd
     svd_lowrank
     pca_lowrank
-    symeig
     lobpcg
     trapz
     trapezoid
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@@ -585,8 +585,8 @@ 
The PrinciplesΒΆ

 
+  
+  
-  
    
       
  • smm() (in module torch)
 
       
      
@@ -8588,12 +8588,6 @@ 
      S
      
 
       
    • SymBool (class in torch)
 
      • 
-      
    • symeig() (in module torch)
-
-      
      • 
       
    • SymFloat (class in torch)
 
      • 
       
    • SymInt (class in torch)
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@@ -3416,14 +3416,6 @@
 Tensor.swapdims_(dim0 : int,
                  dim1 : int) -> Tensor
 
-Tensor.symeig(eigenvectors : bool=False,
-              upper : bool=True) -> Tuple[Tensor, Tensor]
-
-Tensor.symeig(eigenvectors : bool=False,
-              upper : bool=True,
-              e : Tensor,
-              V : Tensor) -> Tuple[Tensor, Tensor]
-
 Tensor.t() -> Tensor
 
 Tensor.t_() -> Tensor
@@ -10534,16 +10526,6 @@
                dim0 : int,
                dim1 : int) -> Tensor
 
-torch.symeig(self : Tensor,
-             eigenvectors : bool=False,
-             upper : bool=True) -> Tuple[Tensor, Tensor]
-
-torch.symeig(self : Tensor,
-             eigenvectors : bool=False,
-             upper : bool=True,
-             e : Tensor,
-             V : Tensor) -> Tuple[Tensor, Tensor]
-
 torch.t(self : Tensor) -> Tensor
 
 torch.t_copy(self : Tensor,
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index 2bcc9f321f9a..2d1c00dafea2 100644
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diff --git a/docs/master/notes/extending.func.html b/docs/master/notes/extending.func.html
index dd6360994af6..1ffee4c1f3ab 100644
--- a/docs/master/notes/extending.func.html
+++ b/docs/master/notes/extending.func.html
@@ -237,7 +237,7 @@
           
      
             
     
      
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diff --git a/docs/master/notes/extending.html b/docs/master/notes/extending.html
index 8088939756b8..034f877490a4 100644
--- a/docs/master/notes/extending.html
+++ b/docs/master/notes/extending.html
@@ -237,7 +237,7 @@
           
      
             
     
      
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@@ -469,13 +469,13 @@
   
      
 
      Extending PyTorchΒΆ
      
 
      In this note we’ll cover ways of extending torch.nn,
-torch.autograd, torch, and writing custom C extensions utilizing our C
+torch.autograd, torch, and writing custom C extensions utilizing our C
 libraries.
      
 
      
-
      Extending torch.autogradΒΆ
      
-
      Adding operations to autograd requires implementing a new
+
      Extending torch.autogradΒΆ
      
+
      Adding operations to autograd requires implementing a new
 Function subclass for each operation. Recall that Functions
-are what autograd uses to encode the operation history and compute
+are what autograd uses to encode the operation history and compute
 gradients.
      
 
      The first part of this doc is focused on backward mode AD as it is the most widely used
 feature. A section at the end discusses the extensions for forward mode AD.
      
@@ -837,7 +837,7 @@ 
      Extending 
 
      
 
      Adding a ModuleΒΆ
      
-
      Since nn heavily utilizes autograd, adding a new
+
      Since nn heavily utilizes autograd, adding a new
 Module requires implementing a Function
 that performs the operation and can compute the gradient. From now on let’s
 assume that we want to implement a Linear module and we have the function
diff --git a/docs/master/notes/faq.html b/docs/master/notes/faq.html
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diff --git a/docs/master/notes/randomness.html b/docs/master/notes/randomness.html
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diff --git a/docs/master/notes/windows.html b/docs/master/notes/windows.html
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-      master (2.0.0a0+git5f1ac18 ) ▼
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diff --git a/docs/master/onnx_diagnostics.html b/docs/master/onnx_diagnostics.html
index c3a98d16fd70..064da2329f12 100644
--- a/docs/master/onnx_diagnostics.html
+++ b/docs/master/onnx_diagnostics.html
@@ -237,7 +237,7 @@
           
      
             
     
      
-      master (2.0.0a0+git5f1ac18 ) ▼
+      master (2.0.0a0+git218d4ea ) ▼
     
      
     
 
diff --git a/docs/master/onnx_supported_aten_ops.html b/docs/master/onnx_supported_aten_ops.html
index 39edc04cbfbb..c96b81a569a4 100644
--- a/docs/master/onnx_supported_aten_ops.html
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@@ -235,7 +235,7 @@
           
      
             
     
      
-      master (2.0.0a0+git5f1ac18 ) ▼
+      master (2.0.0a0+git218d4ea ) ▼
     
      
     
 
@@ -2347,1867 +2347,1861 @@ 
      Unsupported operators
      aten::_standard_gamma_grad
      
 
      Not yet supported
      
 
-
      aten::_symeig_helper
      
+
      aten::_tensor_to_list
      
 
      Not yet supported
      
 
-
      aten::_tensor_to_list
      
+
      aten::_test_ambiguous_defaults
      
 
      Not yet supported
      
 
-
      aten::_test_ambiguous_defaults
      
+
      aten::_test_autograd_multiple_dispatch
      
 
      Not yet supported
      
 
-
      aten::_test_autograd_multiple_dispatch
      
+
      aten::_test_autograd_multiple_dispatch_view
      
 
      Not yet supported
      
 
-
      aten::_test_autograd_multiple_dispatch_view
      
+
      aten::_test_autograd_multiple_dispatch_view_copy
      
 
      Not yet supported
      
 
-
      aten::_test_autograd_multiple_dispatch_view_copy
      
+
      aten::_test_check_tensor
      
 
      Not yet supported
      
 
-
      aten::_test_check_tensor
      
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      aten::_test_optional_filled_intlist
      
 
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      aten::_test_optional_floatlist
      
 
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      aten::_test_serialization_subcmul
      
 
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      aten::_test_string_default
      
 
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      aten::_test_warn_in_autograd
      
 
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      aten::_thnn_fused_gru_cell
      
 
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      aten::_thnn_fused_lstm_cell
      
 
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      aten::_to_copy
      
 
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      aten::_transformer_decoder_only_layer_fwd
      
 
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      aten::_transformer_encoder_layer_fwd
      
 
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      aten::_upsample_bicubic2d_aa
      
 
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      aten::_use_cudnn_ctc_loss
      
 
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      aten::_use_cudnn_rnn_flatten_weight
      
 
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      aten::_validate_compressed_sparse_indices
      
 
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      aten::float_power
      
 
      Not yet supported
      
 
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      aten::float_power
      
+
      aten::fmax
      
 
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      aten::fmax
      
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      aten::fractional_max_pool2d
      
 
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      aten::fractional_max_pool3d
      
 
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      aten::frexp
      
 
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      aten::frexp
      
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      aten::from_file
      
 
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-
      aten::from_file
      
+
      aten::fused_moving_avg_obs_fake_quant
      
 
      Not yet supported
      
 
-
      aten::fused_moving_avg_obs_fake_quant
      
+
      aten::gamma
      
 
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      aten::gcd
      
 
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      aten::geometric
      
 
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      aten::get
      
 
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      aten::get
      
+
      aten::get_device
      
 
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      aten::get_device
      
+
      aten::get_gradients
      
 
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-
      aten::get_gradients
      
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      aten::glu_jvp
      
 
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      aten::grad
      
 
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      aten::greater_equal
      
 
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      aten::greater_equal
      
+
      aten::grid_sampler_2d
      
 
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-
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      aten::grid_sampler_3d
      
 
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      aten::gru_cell
      
 
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      aten::has_torch_function
      
 
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      aten::hash
      
 
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      aten::hinge_embedding_loss
      
 
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      aten::histc
      
 
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      aten::hstack
      
 
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+
      aten::huber_loss
      
 
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      aten::index_reduce
      
 
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      aten::indices
      
 
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      aten::indices_copy
      
 
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      aten::inner
      
 
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      aten::int_repr
      
 
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      aten::int_repr
      
+
      aten::inverse
      
 
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      aten::is_autocast_cpu_enabled
      
 
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-
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+
      aten::is_autocast_enabled
      
 
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-
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+
      aten::is_coalesced
      
 
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      aten::is_complex
      
 
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      aten::is_conj
      
 
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      aten::is_contiguous
      
 
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-
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+
      aten::is_distributed
      
 
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-
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+
      aten::is_grad_enabled
      
 
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-
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+
      aten::is_inference
      
 
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-
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+
      aten::is_leaf
      
 
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+
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+
      aten::is_non_overlapping_and_dense
      
 
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+
      aten::is_nonzero
      
 
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+
      aten::is_owner
      
 
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+
      aten::is_same_size
      
 
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-
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+
      aten::is_scripting
      
 
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-
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+
      aten::is_set_to
      
 
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-
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+
      aten::is_signed
      
 
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-
      aten::is_signed
      
+
      aten::is_strides_like_format
      
 
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-
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+
      aten::is_vulkan_available
      
 
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-
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+
      aten::isalnum
      
 
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+
      aten::isdecimal
      
 
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+
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+
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+
      aten::isprintable
      
 
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      aten::join
      
 
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+
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      aten::kthvalue
      
 
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+
      aten::l1_loss
      
 
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+
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      aten::lift_fresh
      
 
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+
      aten::lift_fresh_copy
      
 
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-
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+
      aten::linalg_cholesky
      
 
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+
      aten::linalg_cholesky_ex
      
 
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-
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+
      aten::linalg_cond
      
 
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-
      aten::linalg_cond
      
+
      aten::linalg_diagonal
      
 
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-
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+
      aten::linalg_eig
      
 
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-
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      aten::linalg_eigh
      
 
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      aten::linalg_eigvals
      
 
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      aten::linalg_eigvals
      
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      aten::linalg_eigvalsh
      
 
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      aten::linalg_eigvalsh
      
+
      aten::linalg_householder_product
      
 
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-
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+
      aten::linalg_inv
      
 
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-
      aten::linalg_inv
      
+
      aten::linalg_inv_ex
      
 
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-
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+
      aten::linalg_ldl_factor
      
 
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-
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+
      aten::linalg_ldl_factor_ex
      
 
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-
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+
      aten::linalg_ldl_solve
      
 
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-
      aten::linalg_ldl_solve
      
+
      aten::linalg_lstsq
      
 
      Not yet supported
      
 
-
      aten::linalg_lstsq
      
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      aten::linalg_lu
      
 
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-
      aten::linalg_lu
      
+
      aten::linalg_lu_factor
      
 
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      aten::linalg_lu_factor
      
+
      aten::linalg_lu_factor_ex
      
 
      Not yet supported
      
 
-
      aten::linalg_lu_factor_ex
      
+
      aten::linalg_lu_solve
      
 
      Not yet supported
      
 
-
      aten::linalg_lu_solve
      
+
      aten::linalg_matmul
      
 
      Not yet supported
      
 
-
      aten::linalg_matmul
      
+
      aten::linalg_matrix_exp
      
 
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-
      aten::linalg_matrix_exp
      
+
      aten::linalg_matrix_power
      
 
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      aten::linalg_matrix_power
      
+
      aten::linalg_matrix_rank
      
 
      Not yet supported
      
 
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      aten::linalg_matrix_rank
      
+
      aten::linalg_multi_dot
      
 
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      aten::linalg_multi_dot
      
+
      aten::linalg_pinv
      
 
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+
      aten::linalg_qr
      
 
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      aten::linalg_slogdet
      
 
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      aten::linalg_solve
      
 
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      aten::linalg_solve_ex
      
 
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+
      aten::linalg_solve_triangular
      
 
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+
      aten::linalg_svd
      
 
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      aten::linalg_svdvals
      
 
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      aten::linalg_tensorinv
      
 
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      aten::linalg_tensorsolve
      
 
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+
      aten::linalg_vander
      
 
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      aten::linalg_vecdot
      
 
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      aten::ljust
      
 
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      aten::ljust
      
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      aten::local_value
      
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      aten::log_normal
      
 
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      aten::log_sigmoid_forward
      
 
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      aten::logaddexp
      
 
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      aten::logcumsumexp
      
 
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      aten::logical_not
      
 
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      aten::lu_unpack
      
 
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      aten::manual_seed
      
 
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+
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+
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      aten::max_unpool3d
      
 
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      aten::median
      
 
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      aten::miopen_batch_norm
      
 
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      aten::miopen_convolution
      
 
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      aten::miopen_convolution_transpose
      
 
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+
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+
      aten::promote_types
      
 
      Not yet supported
      
 
-
      aten::promote_types
      
+
      aten::put
      
 
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-
      aten::put
      
+
      aten::q_per_channel_axis
      
 
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-
      aten::q_per_channel_axis
      
+
      aten::q_per_channel_scales
      
 
      Not yet supported
      
 
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      aten::q_per_channel_scales
      
+
      aten::q_per_channel_zero_points
      
 
      Not yet supported
      
 
-
      aten::q_per_channel_zero_points
      
+
      aten::q_scale
      
 
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-
      aten::q_scale
      
+
      aten::q_zero_point
      
 
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-
      aten::q_zero_point
      
+
      aten::qr
      
 
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-
      aten::qr
      
+
      aten::qscheme
      
 
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-
      aten::qscheme
      
+
      aten::quantile
      
 
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      aten::quantile
      
+
      aten::quantize_per_channel
      
 
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-
      aten::quantize_per_channel
      
+
      aten::quantize_per_tensor_dynamic
      
 
      Not yet supported
      
 
-
      aten::quantize_per_tensor_dynamic
      
+
      aten::quantized_batch_norm
      
 
      Not yet supported
      
 
-
      aten::quantized_batch_norm
      
+
      aten::quantized_gru
      
 
      Not yet supported
      
 
-
      aten::quantized_gru
      
+
      aten::quantized_gru_cell
      
 
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-
      aten::quantized_gru_cell
      
+
      aten::quantized_lstm
      
 
      Not yet supported
      
 
-
      aten::quantized_lstm
      
+
      aten::quantized_lstm_cell
      
 
      Not yet supported
      
 
-
      aten::quantized_lstm_cell
      
+
      aten::quantized_max_pool1d
      
 
      Not yet supported
      
 
-
      aten::quantized_max_pool1d
      
+
      aten::quantized_max_pool2d
      
 
      Not yet supported
      
 
-
      aten::quantized_max_pool2d
      
+
      aten::quantized_rnn_relu_cell
      
 
      Not yet supported
      
 
-
      aten::quantized_rnn_relu_cell
      
+
      aten::quantized_rnn_tanh_cell
      
 
      Not yet supported
      
 
-
      aten::quantized_rnn_tanh_cell
      
+
      aten::rad2deg
      
 
      Not yet supported
      
 
-
      aten::rad2deg
      
+
      aten::radians
      
 
      Not yet supported
      
 
-
      aten::radians
      
+
      aten::randint
      
 
      Not yet supported
      
 
-
      aten::randint
      
+
      aten::randint_like
      
 
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-
      aten::randint_like
      
+
      aten::random
      
 
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-
      aten::random
      
+
      aten::randperm
      
 
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      aten::randperm
      
+
      aten::range
      
 
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+
      aten::ravel
      
 
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-
      aten::ravel
      
+
      aten::real
      
 
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      aten::real
      
+
      aten::record_stream
      
 
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-
      aten::record_stream
      
+
      aten::refine_names
      
 
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-
      aten::refine_names
      
+
      aten::remove
      
 
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-
      aten::remove
      
+
      aten::rename
      
 
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      aten::rename
      
+
      aten::renorm
      
 
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      aten::renorm
      
+
      aten::replace
      
 
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      aten::replace
      
+
      aten::requires_grad
      
 
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      aten::requires_grad
      
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      aten::resize
      
 
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      aten::resize
      
+
      aten::resize_as
      
 
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      aten::resize_as
      
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      aten::resize_as_sparse
      
 
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      aten::resize_as_sparse
      
+
      aten::result_type
      
 
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      aten::retain_grad
      
 
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+
      aten::retains_grad
      
 
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-
      aten::retains_grad
      
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      aten::reverse
      
 
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-
      aten::reverse
      
+
      aten::rfind
      
 
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-
      aten::rfind
      
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      aten::rindex
      
 
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      aten::rindex
      
+
      aten::rjust
      
 
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      aten::rjust
      
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      aten::rnn_relu_cell
      
 
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-
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+
      aten::rnn_tanh_cell
      
 
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-
      aten::rnn_tanh_cell
      
+
      aten::rot90
      
 
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-
      aten::rot90
      
+
      aten::row_indices
      
 
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-
      aten::row_indices
      
+
      aten::row_indices_copy
      
 
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-
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+
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-
      aten::row_stack
      
+
      aten::rpartition
      
 
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-
      aten::rpartition
      
+
      aten::rrelu_with_noise
      
 
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-
      aten::rrelu_with_noise
      
+
      aten::rsplit
      
 
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-
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+
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-
      aten::rstrip
      
+
      aten::save
      
 
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      aten::scaled_dot_product_attention
      
 
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-
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+
      aten::scatter_reduce
      
 
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-
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      aten::searchsorted
      
 
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-
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+
      aten::segment_reduce
      
 
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      aten::segment_reduce
      
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      aten::select_copy
      
 
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-
      aten::select_copy
      
+
      aten::select_scatter
      
 
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-
      aten::select_scatter
      
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      aten::set
      
 
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-
      aten::set
      
+
      aten::set_data
      
 
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-
      aten::set_data
      
+
      aten::set_grad_enabled
      
 
      Not yet supported
      
 
-
      aten::set_grad_enabled
      
+
      aten::setdefault
      
 
      Not yet supported
      
 
-
      aten::setdefault
      
+
      aten::sgn
      
 
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-
      aten::sgn
      
+
      aten::signbit
      
 
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-
      aten::signbit
      
+
      aten::sinc
      
 
      Not yet supported
      
 
-
      aten::sinc
      
+
      aten::sinh
      
 
      Not yet supported
      
 
-
      aten::sinh
      
+
      aten::slice_copy
      
 
      Not yet supported
      
 
-
      aten::slice_copy
      
+
      aten::slice_scatter
      
 
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      aten::slice_scatter
      
+
      aten::slogdet
      
 
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-
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+
      aten::slow_conv3d
      
 
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-
      aten::slow_conv3d
      
+
      aten::slow_conv3d_forward
      
 
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-
      aten::slow_conv3d_forward
      
+
      aten::slow_conv_dilated2d
      
 
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-
      aten::slow_conv_dilated2d
      
+
      aten::slow_conv_dilated3d
      
 
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      aten::slow_conv_dilated3d
      
+
      aten::slow_conv_transpose2d
      
 
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      aten::slow_conv_transpose2d
      
+
      aten::slow_conv_transpose3d
      
 
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-
      aten::slow_conv_transpose3d
      
+
      aten::smm
      
 
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-
      aten::smm
      
+
      aten::smooth_l1_loss
      
 
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      aten::smooth_l1_loss
      
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      aten::soft_margin_loss
      
 
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      aten::sorted
      
 
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      aten::sparse_bsc_tensor
      
 
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      aten::sparse_bsr_tensor
      
 
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      aten::sparse_compressed_tensor
      
 
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      aten::sparse_coo_tensor
      
 
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      aten::sparse_csc_tensor
      
 
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      aten::sparse_csr_tensor
      
 
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      aten::sparse_csr_tensor
      
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      aten::sparse_dim
      
 
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      aten::sparse_dim
      
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      aten::sparse_mask
      
 
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      aten::sparse_resize
      
 
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      aten::sparse_resize_and_clear
      
 
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      aten::sparse_resize_and_clear
      
+
      aten::sparse_sampled_addmm
      
 
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      aten::sparse_sampled_addmm
      
+
      aten::special_airy_ai
      
 
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      aten::special_airy_ai
      
+
      aten::special_bessel_j0
      
 
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      aten::special_bessel_j0
      
+
      aten::special_bessel_j1
      
 
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      aten::special_bessel_j1
      
+
      aten::special_bessel_y0
      
 
      Not yet supported
      
 
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      aten::special_bessel_y0
      
+
      aten::special_bessel_y1
      
 
      Not yet supported
      
 
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      aten::special_bessel_y1
      
+
      aten::special_chebyshev_polynomial_t
      
 
      Not yet supported
      
 
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      aten::special_chebyshev_polynomial_t
      
+
      aten::special_chebyshev_polynomial_u
      
 
      Not yet supported
      
 
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      aten::special_chebyshev_polynomial_u
      
+
      aten::special_chebyshev_polynomial_v
      
 
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      aten::special_chebyshev_polynomial_v
      
+
      aten::special_chebyshev_polynomial_w
      
 
      Not yet supported
      
 
-
      aten::special_chebyshev_polynomial_w
      
+
      aten::special_digamma
      
 
      Not yet supported
      
 
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      aten::special_digamma
      
+
      aten::special_entr
      
 
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-
      aten::special_entr
      
+
      aten::special_erf
      
 
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+
      aten::special_erfc
      
 
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+
      aten::special_erfcx
      
 
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      aten::special_erfcx
      
+
      aten::special_erfinv
      
 
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      aten::special_erfinv
      
+
      aten::special_exp2
      
 
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+
      aten::special_expit
      
 
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-
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+
      aten::special_expm1
      
 
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-
      aten::special_expm1
      
+
      aten::special_gammainc
      
 
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+
      aten::special_gammaincc
      
 
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+
      aten::special_gammaln
      
 
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-
      aten::special_gammaln
      
+
      aten::special_hermite_polynomial_h
      
 
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+
      aten::special_hermite_polynomial_he
      
 
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+
      aten::special_i0
      
 
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+
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+
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+
      aten::special_i1e
      
 
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+
      aten::special_laguerre_polynomial_l
      
 
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+
      aten::special_legendre_polynomial_p
      
 
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-
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+
      aten::special_log1p
      
 
      Not yet supported
      
 
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      aten::special_log1p
      
+
      aten::special_log_ndtr
      
 
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+
      aten::special_log_softmax
      
 
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+
      aten::special_logit
      
 
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+
      aten::special_logsumexp
      
 
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+
      aten::special_modified_bessel_i0
      
 
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+
      aten::special_modified_bessel_i1
      
 
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+
      aten::special_modified_bessel_k0
      
 
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+
      aten::special_modified_bessel_k1
      
 
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+
      aten::special_multigammaln
      
 
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+
      aten::special_ndtr
      
 
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+
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+
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+
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+
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+
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+
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+
      aten::special_shifted_chebyshev_polynomial_t
      
 
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+
      aten::special_shifted_chebyshev_polynomial_u
      
 
      Not yet supported
      
 
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      aten::special_shifted_chebyshev_polynomial_u
      
+
      aten::special_shifted_chebyshev_polynomial_v
      
 
      Not yet supported
      
 
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      aten::special_shifted_chebyshev_polynomial_v
      
+
      aten::special_shifted_chebyshev_polynomial_w
      
 
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+
      aten::special_sinc
      
 
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+
      aten::special_softmax
      
 
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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      Not yet supported
      
 
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+
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+
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      Not yet supported
      
 
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+
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+
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+
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+
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      aten::sym_stride
      
-
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-
      aten::symeig
      
+
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      Not yet supported
      
 
 
      aten::t_copy
      
@@ -4417,7 +4411,13 @@ 
      Unsupported operators
      mkldnn::_convolution_pointwise
      
 
      Not yet supported
      
 
-
      mkldnn::_linear_pointwise
      
+
      mkldnn::_convolution_transpose_pointwise
      
+
      Not yet supported
      
+
+
      mkldnn::_linear_pointwise
      
+
      Not yet supported
      
+
+
      mkldnn::_reorder_convolution_transpose_weight
      
 
      Not yet supported
      
 
 
      mkldnn_prepacked::conv2d_prepack
      
@@ -5341,370 +5341,373 @@ 
      Unsupported operators
      quantized::conv2d_add
      
 
      Not yet supported
      
 
-
      quantized::conv2d_dilation
      
+
      quantized::conv2d_add_relu
      
+
      Not yet supported
      
+
+
      quantized::conv2d_dilation
      
 
      Not yet supported
      
 
-
      quantized::conv2d_dynamic
      
+
      quantized::conv2d_dynamic
      
 
      Not yet supported
      
 
-
      quantized::conv2d_groups
      
+
      quantized::conv2d_groups
      
 
      Not yet supported
      
 
-
      quantized::conv2d_output_padding
      
+
      quantized::conv2d_output_padding
      
 
      Not yet supported
      
 
-
      quantized::conv2d_padding
      
+
      quantized::conv2d_padding
      
 
      Not yet supported
      
 
-
      quantized::conv2d_prepack
      
+
      quantized::conv2d_prepack
      
 
      Not yet supported
      
 
-
      quantized::conv2d_stride
      
+
      quantized::conv2d_stride
      
 
      Not yet supported
      
 
-
      quantized::conv2d_transpose
      
+
      quantized::conv2d_transpose
      
 
      Not yet supported
      
 
-
      quantized::conv2d_unpack
      
+
      quantized::conv2d_unpack
      
 
      Not yet supported
      
 
-
      quantized::conv2d_unpack_sizes
      
+
      quantized::conv2d_unpack_sizes
      
 
      Not yet supported
      
 
-
      quantized::conv3d
      
+
      quantized::conv3d
      
 
      Not yet supported
      
 
-
      quantized::conv3d_dilation
      
+
      quantized::conv3d_dilation
      
 
      Not yet supported
      
 
-
      quantized::conv3d_dynamic
      
+
      quantized::conv3d_dynamic
      
 
      Not yet supported
      
 
-
      quantized::conv3d_groups
      
+
      quantized::conv3d_groups
      
 
      Not yet supported
      
 
-
      quantized::conv3d_output_padding
      
+
      quantized::conv3d_output_padding
      
 
      Not yet supported
      
 
-
      quantized::conv3d_padding
      
+
      quantized::conv3d_padding
      
 
      Not yet supported
      
 
-
      quantized::conv3d_prepack
      
+
      quantized::conv3d_prepack
      
 
      Not yet supported
      
 
-
      quantized::conv3d_relu
      
+
      quantized::conv3d_relu
      
 
      Not yet supported
      
 
-
      quantized::conv3d_stride
      
+
      quantized::conv3d_stride
      
 
      Not yet supported
      
 
-
      quantized::conv3d_transpose
      
+
      quantized::conv3d_transpose
      
 
      Not yet supported
      
 
-
      quantized::conv3d_unpack
      
+
      quantized::conv3d_unpack
      
 
      Not yet supported
      
 
-
      quantized::conv_prepack
      
+
      quantized::conv_prepack
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose1d
      
+
      quantized::conv_transpose1d
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose1d_dynamic
      
+
      quantized::conv_transpose1d_dynamic
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose1d_prepack
      
+
      quantized::conv_transpose1d_prepack
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose1d_unpack
      
+
      quantized::conv_transpose1d_unpack
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose2d
      
+
      quantized::conv_transpose2d
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose2d_dilation
      
+
      quantized::conv_transpose2d_dilation
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose2d_dynamic
      
+
      quantized::conv_transpose2d_dynamic
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose2d_groups
      
+
      quantized::conv_transpose2d_groups
      
 
      Not yet supported
      
 
-
      quantized::conv_transpose2d_output_padding
      
+
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-
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+
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+
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+
      quantized::conv_transpose2d_transpose
      
 
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+
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-
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+
      quantized::conv_transpose3d
      
 
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+
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+
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      quantized::conv_transpose3d_groups
      
 
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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-
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+
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+
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+
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+
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+
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+
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+
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+
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      Not yet supported
      
 
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+
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      Not yet supported
      
 
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+
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+
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      Not yet supported
      
 
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+
      quantized::mul_scalar_out
      
 
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+
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+
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+
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-
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+
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-
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+
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      Not yet supported
      
 
-
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+
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-
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+
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      Not yet supported
      
 
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+
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+
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+
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+
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+
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+
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+
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+
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-
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+
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      Not yet supported
      
 
-
      static_runtime::VarTupleUnpack
      
+
      static_runtime::VarTupleUnpack
      
 
      Not yet supported
      
 
-
      static_runtime::clamp_nan_to_num
      
+
      static_runtime::clamp_nan_to_num
      
 
      Not yet supported
      
 
-
      static_runtime::create_owned_ref
      
+
      static_runtime::create_owned_ref
      
 
      Not yet supported
      
 
-
      static_runtime::dequantize_copy
      
+
      static_runtime::dequantize_copy
      
 
      Not yet supported
      
 
-
      static_runtime::dict_unpack
      
+
      static_runtime::dict_unpack
      
 
      Not yet supported
      
 
-
      static_runtime::embedding_bag
      
+
      static_runtime::embedding_bag
      
 
      Not yet supported
      
 
-
      static_runtime::expand_dims_copy
      
+
      static_runtime::expand_dims_copy
      
 
      Not yet supported
      
 
-
      static_runtime::flatten_copy
      
+
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      Not yet supported
      
 
-
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+
      static_runtime::fused_equally_split
      
 
      Not yet supported
      
 
-
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+
      static_runtime::layer_norm
      
 
      Not yet supported
      
 
-
      static_runtime::permute_copy
      
+
      static_runtime::permute_copy
      
 
      Not yet supported
      
 
-
      static_runtime::reshape_copy
      
+
      static_runtime::reshape_copy
      
 
      Not yet supported
      
 
-
      static_runtime::select_tensor
      
+
      static_runtime::select_tensor
      
 
      Not yet supported
      
 
-
      static_runtime::signed_log1p
      
+
      static_runtime::signed_log1p
      
 
      Not yet supported
      
 
-
      static_runtime::to_copy
      
+
      static_runtime::to_copy
      
 
      Not yet supported
      
 
-
      static_runtime::to_maybe_copy_out
      
+
      static_runtime::to_maybe_copy_out
      
 
      Not yet supported
      
 
 
diff --git a/docs/master/optim.html b/docs/master/optim.html
index 8101a921aa12..0de2a3c6e7cc 100644
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52, 1834, 1853, 1860, 1861], "localhost": [22, 24, 49, 50, 1834, 1853, 1860, 1861], "master_port": [22, 24, 40, 50, 52, 1834, 1853, 1860, 1861], "12355": 22, "init_process_group": [22, 24, 25, 28, 40, 50, 52, 1488, 1833, 1834, 1860], "cleanup": 22, "destroy_process_group": 22, "run_demo": 22, "demo_fn": 22, "mp": [22, 24, 25, 51, 1488, 1807, 1834, 1843, 1855, 1861, 1866, 1867, 1874], "nproc": [22, 24, 47, 1822, 1834, 1861], "demo_seri": 22, "gettempdir": 22, "device_id": [22, 24, 25, 28, 50, 54, 1166, 1252, 1354, 1476, 1488, 1834], "powersgd_st": 22, "lr": [22, 25, 28, 54, 1483, 1488, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1833, 1834, 1841, 1851, 1861, 1869], "001": [22, 814, 815, 1104, 1543, 1547, 1548, 1557, 1561, 1573, 1834, 1848], "comm_hook": 22, "comm_hook_st": 22, "hook_stat": 22, "barrier": [22, 40, 49, 1850], "map_loc": [22, 1099, 1102, 1166, 1488, 1806, 1820, 1852], "n_gpu": 22, "device_count": [22, 24, 1807], "got": [22, 24, 797, 1835], "thank": [22, 30, 1835, 1853], "author": [22, 33, 35, 39, 49, 50, 1036, 1557, 1662, 1799, 1829], "thij": 22, "par": 22, "home": [23, 1833], "brief": [24, 1488, 1822, 1860], "introduct": [24, 30, 906, 1488, 1807, 1809, 1813, 1823, 1831, 1841, 1848, 1860, 1864, 1869], "mpi": [24, 1488], "gloo": [24, 50, 1488, 1834, 1839, 1860], "recv": [24, 1488, 1850, 1861], "broadcast": [24, 28, 30, 34, 54, 59, 76, 175, 375, 377, 379, 487, 489, 491, 539, 658, 659, 660, 661, 662, 663, 664, 670, 790, 827, 832, 835, 839, 840, 841, 842, 866, 885, 963, 964, 969, 974, 1014, 1015, 1016, 1017, 1037, 1039, 1051, 1061, 1119, 1120, 1127, 1140, 1144, 1149, 1150, 1152, 1155, 1163, 1183, 1188, 1189, 1199, 1204, 1207, 1216, 1219, 1250, 1269, 1321, 1394, 1456, 1488, 1493, 1543, 1579, 1587, 1675, 1677, 1753, 1773, 1778, 1802, 1807, 1808, 1812, 1823, 1824, 1825, 1834, 1848, 1850, 1865], "all_reduc": [24, 51, 1488], "all_gath": 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1833, 1839, 1845, 1853, 1860], "version": [4, 7, 10, 15, 20, 22, 24, 26, 30, 38, 39, 50, 54, 57, 58, 62, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 100, 102, 104, 106, 109, 110, 112, 120, 122, 125, 126, 128, 131, 137, 139, 141, 143, 145, 147, 156, 165, 173, 177, 180, 182, 192, 194, 210, 214, 216, 222, 225, 227, 229, 231, 235, 240, 247, 249, 251, 255, 257, 261, 263, 270, 272, 274, 282, 284, 286, 288, 290, 292, 294, 296, 333, 335, 337, 339, 341, 343, 345, 348, 350, 352, 353, 360, 362, 364, 366, 368, 372, 376, 378, 396, 399, 402, 404, 414, 416, 418, 426, 431, 441, 444, 460, 464, 466, 482, 485, 486, 488, 490, 496, 500, 502, 505, 507, 509, 522, 524, 526, 529, 535, 537, 544, 548, 550, 566, 569, 571, 573, 575, 585, 595, 706, 707, 719, 720, 721, 722, 723, 724, 745, 746, 747, 748, 750, 754, 755, 768, 769, 877, 916, 1024, 1051, 1069, 1091, 1094, 1097, 1098, 1101, 1104, 1123, 1136, 1137, 1141, 1142, 1155, 1188, 1213, 1231, 1284, 1314, 1315, 1329, 1366, 1376, 1401, 1411, 1418, 1427, 1458, 1460, 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1826, 1830, 1863], "fc2": [22, 1482, 1851], "master_addr": [22, 24, 40, 50, 52, 1832, 1851, 1858, 1859], "localhost": [22, 24, 49, 50, 1832, 1851, 1858, 1859], "master_port": [22, 24, 40, 50, 52, 1832, 1851, 1858, 1859], "12355": 22, "init_process_group": [22, 24, 25, 28, 40, 50, 52, 1487, 1831, 1832, 1858], "cleanup": 22, "destroy_process_group": 22, "run_demo": 22, "demo_fn": 22, "mp": [22, 24, 25, 51, 1487, 1805, 1832, 1841, 1853, 1859, 1864, 1865, 1872], "nproc": [22, 24, 47, 1820, 1832, 1859], "demo_seri": 22, "gettempdir": 22, "device_id": [22, 24, 25, 28, 50, 54, 1165, 1251, 1353, 1475, 1487, 1832], "powersgd_st": 22, "lr": [22, 25, 28, 54, 1482, 1487, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1831, 1832, 1839, 1849, 1859, 1867], "001": [22, 813, 814, 1103, 1542, 1546, 1547, 1556, 1560, 1572, 1832, 1846], "comm_hook": 22, "comm_hook_st": 22, "hook_stat": 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1823, 1832, 1846, 1848, 1863], "all_reduc": [24, 51, 1487], "all_gath": 24, "scatter": [24, 28, 54, 487, 489, 491, 1251, 1808, 1835, 1848, 1858], "reduce_scatt": [24, 1848], "all_to_al": 24, "v1": [24, 54, 1162, 1578, 1804, 1832, 1858], "init_method": [24, 1487, 1858], "adher": [24, 1810], "some_fil": 24, "machine_nam": 24, "share_folder_nam": 24, "tcpstore": [24, 49], "past": [24, 35, 62, 929, 946, 1487, 1835], "ask": [24, 58, 59, 1804, 1805, 1834, 1836], "infiniband": [24, 1487, 1858], "interconnect": 24, "gpudirect": 24, "ethernet": 24, "encount": [24, 32, 34, 36, 39, 59, 61, 62, 1487, 1807, 1810, 1812, 1830, 1842, 1850, 1853], "ip": [24, 49], "ib": 24, "upcom": [24, 34, 39, 54, 1827], "nccl_socket_ifnam": 24, "eth0": 24, "gloo_socket_ifnam": 24, "comma": [24, 968, 1810], "eth1": 24, "eth2": 24, "eth3": 24, "imper": 24, "nccl_debug": 24, "info": [24, 33, 34, 39, 40, 43, 47, 797, 874, 875, 877, 1124, 1135, 1137, 1138, 1142, 1155, 1183, 1540, 1805, 1808, 1832, 1833, 1834, 1846, 1850], 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1380, 1383, 1384, 1394, 1408, 1423, 1432, 1433, 1446, 1454, 1487, 1492, 1543, 1544, 1546, 1547, 1548, 1550, 1556, 1557, 1560, 1615, 1616, 1776, 1805, 1832, 1852], "elimin": [24, 35, 62, 583, 1787, 1788, 1843], "thrash": 24, "recurr": [24, 730, 731, 1109, 1237, 1251, 1266, 1267, 1284, 1329, 1499, 1525, 1557, 1805, 1831], "use_distribut": 24, "datetim": [24, 1819], "timedelta": [24, 49, 1819], "1800": 24, "group_nam": [24, 46], "pg_option": 24, "url": [24, 38, 49, 821, 1804, 1818, 1858], "discov": [24, 1858], "encod": [24, 40, 46, 49, 62, 1141, 1165, 1230, 1231, 1357, 1358, 1359, 1360, 1361, 1487, 1737, 1738, 1739, 1741, 1742, 1807, 1810, 1811, 1833, 1844, 1850, 1859, 1862], "ucc": 24, "lowercas": 24, "deadlock": [24, 1487], "job": [24, 40, 42, 43, 45, 46, 48, 49, 50, 51, 1487, 1565, 1571, 1838, 1852, 1867], "exchang": [24, 49, 875, 956, 1831, 1846], "nccl_blocking_wait": 24, "nccl_async_error_handl": [24, 1831], "throw": [24, 25, 34, 35, 39, 54, 61, 62, 169, 301, 306, 518, 587, 1079, 1094, 1134, 1183, 1314, 1487, 1489, 1490, 1525, 1534, 1585, 1790, 1823, 1828, 1843, 1858, 1868], "abort": [24, 1831], "crash": [24, 42, 49, 1820, 1828, 1858, 1860, 1867], "caught": [24, 1487, 1820], "littl": [24, 36, 1833, 1860], "watch": 24, "dog": 24, "deprec": [24, 40, 49, 50, 54, 58, 383, 530, 576, 755, 756, 757, 759, 812, 848, 849, 920, 924, 1040, 1094, 1148, 1151, 1183, 1184, 1230, 1231, 1248, 1250, 1273, 1274, 1280, 1281, 1305, 1306, 1314, 1317, 1318, 1319, 1321, 1328, 1345, 1346, 1362, 1367, 1368, 1383, 1384, 1394, 1423, 1446, 1454, 1479, 1480, 1481, 1483, 1487, 1528, 1529, 1534, 1589, 1620, 1670, 1751, 1755, 1778, 1805, 1807, 1812, 1820, 1829, 1852, 1864, 1868, 1869], "processgroupopt": 24, "processgroupnccl": [24, 1832], "is_high_priority_stream": 24, "is_initi": [24, 1805], "is_mpi_avail": 24, "is_nccl_avail": 24, "is_gloo_avail": 24, "is_torchelastic_launch": 24, "elast": [24, 41, 42, 43, 44, 45, 46, 47, 48, 49, 51, 52, 1805], "aka": [24, 822, 1275, 1828, 1865], 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"get_backend": [24, 49], "get_rank": [24, 1353], "uniqu": [24, 40, 46, 49, 50, 51, 487, 491, 1085, 1129, 1130, 1134, 1140, 1141, 1143, 1152, 1154, 1156, 1157, 1194, 1201, 1755, 1788, 1804, 1807, 1818, 1833, 1850, 1852, 1858, 1859, 1860, 1862, 1867], "get_world_s": 24, "filestor": [24, 49], "hashstor": 24, "client": [24, 28, 34, 49, 1850], "host_nam": 24, "hostnam": [24, 40, 49, 1852], "listen": 24, "is_mast": 24, "300": [24, 40, 1171, 1231, 1526, 1849], "wait_for_work": 24, "server_stor": 24, "127": [24, 760, 1603, 1604, 1606, 1607, 1625, 1626, 1639, 1640, 1641, 1642, 1643, 1822, 1853, 1867], "1234": [24, 49, 1071], "client_stor": 24, "first_kei": 24, "first_valu": 24, "underli": [24, 26, 28, 30, 36, 40, 59, 62, 76, 289, 304, 354, 377, 379, 448, 449, 450, 451, 458, 473, 494, 497, 530, 531, 532, 586, 718, 727, 783, 874, 1064, 1068, 1094, 1165, 1213, 1454, 1672, 1775, 1789, 1807, 1810, 1823, 1831, 1835, 1837, 1851, 1858, 1866], "hashmap": 24, "file_nam": [24, 1804, 1818, 1850], "store1": 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\ No newline at end of file
diff --git a/docs/master/signal.html b/docs/master/signal.html
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@@ -494,7 +494,7 @@ 
      Why and when to use sparsity
             
     
      
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diff --git a/docs/master/storage.html b/docs/master/storage.html
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diff --git a/docs/master/tensor_attributes.html b/docs/master/tensor_attributes.html
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diff --git a/docs/master/tensor_view.html b/docs/master/tensor_view.html
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diff --git a/docs/master/tensorboard.html b/docs/master/tensorboard.html
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@@ -237,7 +237,7 @@
           
      
             
     
      
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diff --git a/docs/master/tensors.html b/docs/master/tensors.html
index 38a4e9a55b53..448e020ca8e2 100644
--- a/docs/master/tensors.html
+++ b/docs/master/tensors.html
@@ -237,7 +237,7 @@
           
      
             
     
      
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@@ -647,7 +647,7 @@ 
      Initializing and basic operationsIndexing, Slicing, Joining, Mutating Ops
      
 
      A tensor can be created with requires_grad=True so that
-torch.autograd records operations on them for automatic differentiation.
      
+torch.autograd records operations on them for automatic differentiation.
      
 
      >>> x = torch.tensor([[1., -1.], [1., 1.]], requires_grad=True)
 >>> out = x.pow(2).sum()
 >>> out.backward()
@@ -2141,175 +2141,172 @@ 
      Tensor class reference
      Tensor.swapdims
      
 
      See torch.swapdims()
      
 
-
      Tensor.symeig
      
-
      See torch.symeig()
      
-
-
      Tensor.t
      
+
      Tensor.t
      
 
      See torch.t()
      
 
-
      Tensor.t_
      
+
      Tensor.t_
      
 
      In-place version of t()
      
 
-
      Tensor.tensor_split
      
+
      Tensor.tensor_split
      
 
      See torch.tensor_split()
      
 
-
      Tensor.tile
      
+
      Tensor.tile
      
 
      See torch.tile()
      
 
-
      Tensor.to
      
+
      Tensor.to
      
 
      Performs Tensor dtype and/or device conversion.
      
 
-
      Tensor.to_mkldnn
      
+
      Tensor.to_mkldnn
      
 
      Returns a copy of the tensor in torch.mkldnn layout.
      
 
-
      Tensor.take
      
+
      Tensor.take
      
 
      See torch.take()
      
 
-
      Tensor.take_along_dim
      
+
      Tensor.take_along_dim
      
 
      See torch.take_along_dim()
      
 
-
      Tensor.tan
      
+
      Tensor.tan
      
 
      See torch.tan()
      
 
-
      Tensor.tan_
      
+
      Tensor.tan_
      
 
      In-place version of tan()
      
 
-
      Tensor.tanh
      
+
      Tensor.tanh
      
 
      See torch.tanh()
      
 
-
      Tensor.tanh_
      
+
      Tensor.tanh_
      
 
      In-place version of tanh()
      
 
-
      Tensor.atanh
      
+
      Tensor.atanh
      
 
      See torch.atanh()
      
 
-
      Tensor.atanh_
      
+
      Tensor.atanh_
      
 
      In-place version of atanh()
      
 
-
      Tensor.arctanh
      
+
      Tensor.arctanh
      
 
      See torch.arctanh()
      
 
-
      Tensor.arctanh_
      
+
      Tensor.arctanh_
      
 
      In-place version of arctanh()
      
 
-
      Tensor.tolist
      
+
      Tensor.tolist
      
 
      Returns the tensor as a (nested) list.
      
 
-
      Tensor.topk
      
+
      Tensor.topk
      
 
      See torch.topk()
      
 
-
      Tensor.to_dense
      
+
      Tensor.to_dense
      
 
      Creates a strided copy of self if self is not a strided tensor, otherwise returns self.
      
 
-
      Tensor.to_sparse
      
+
      Tensor.to_sparse
      
 
      Returns a sparse copy of the tensor.
      
 
-
      Tensor.to_sparse_csr
      
+
      Tensor.to_sparse_csr
      
 
      Convert a tensor to compressed row storage format (CSR).
      
 
-
      Tensor.to_sparse_csc
      
+
      Tensor.to_sparse_csc
      
 
      Convert a tensor to compressed column storage (CSC) format.
      
 
-
      Tensor.to_sparse_bsr
      
+
      Tensor.to_sparse_bsr
      
 
      Convert a tensor to a block sparse row (BSR) storage format of given blocksize.
      
 
-
      Tensor.to_sparse_bsc
      
+
      Tensor.to_sparse_bsc
      
 
      Convert a tensor to a block sparse column (BSC) storage format of given blocksize.
      
 
-
      Tensor.trace
      
+
      Tensor.trace
      
 
      See torch.trace()
      
 
-
      Tensor.transpose
      
+
      Tensor.transpose
      
 
      See torch.transpose()
      
 
-
      Tensor.transpose_
      
+
      Tensor.transpose_
      
 
      In-place version of transpose()
      
 
-
      Tensor.triangular_solve
      
+
      Tensor.triangular_solve
      
 
      See torch.triangular_solve()
      
 
-
      Tensor.tril
      
+
      Tensor.tril
      
 
      See torch.tril()
      
 
-
      Tensor.tril_
      
+
      Tensor.tril_
      
 
      In-place version of tril()
      
 
-
      Tensor.triu
      
+
      Tensor.triu
      
 
      See torch.triu()
      
 
-
      Tensor.triu_
      
+
      Tensor.triu_
      
 
      In-place version of triu()
      
 
-
      Tensor.true_divide
      
+
      Tensor.true_divide
      
 
      See torch.true_divide()
      
 
-
      Tensor.true_divide_
      
+
      Tensor.true_divide_
      
 
      In-place version of true_divide_()
      
 
-
      Tensor.trunc
      
+
      Tensor.trunc
      
 
      See torch.trunc()
      
 
-
      Tensor.trunc_
      
+
      Tensor.trunc_
      
 
      In-place version of trunc()
      
 
-
      Tensor.type
      
+
      Tensor.type
      
 
      Returns the type if dtype is not provided, else casts this object to the specified type.
      
 
-
      Tensor.type_as
      
+
      Tensor.type_as
      
 
      Returns this tensor cast to the type of the given tensor.
      
 
-
      Tensor.unbind
      
+
      Tensor.unbind
      
 
      See torch.unbind()
      
 
-
      Tensor.unflatten
      
+
      Tensor.unflatten
      
 
      See torch.unflatten().
      
 
-
      Tensor.unfold
      
+
      Tensor.unfold
      
 
      Returns a view of the original tensor which contains all slices of size size from self tensor in the dimension dimension.
      
 
-
      Tensor.uniform_
      
+
      Tensor.uniform_
      
 
      Fills self tensor with numbers sampled from the continuous uniform distribution:
      
 
-
      Tensor.unique
      
+
      Tensor.unique
      
 
      Returns the unique elements of the input tensor.
      
 
-
      Tensor.unique_consecutive
      
+
      Tensor.unique_consecutive
      
 
      Eliminates all but the first element from every consecutive group of equivalent elements.
      
 
-
      Tensor.unsqueeze
      
+
      Tensor.unsqueeze
      
 
      See torch.unsqueeze()
      
 
-
      Tensor.unsqueeze_
      
+
      Tensor.unsqueeze_
      
 
      In-place version of unsqueeze()
      
 
-
      Tensor.values
      
+
      Tensor.values
      
 
      Return the values tensor of a sparse COO tensor.
      
 
-
      Tensor.var
      
+
      Tensor.var
      
 
      See torch.var()
      
 
-
      Tensor.vdot
      
+
      Tensor.vdot
      
 
      See torch.vdot()
      
 
-
      Tensor.view
      
+
      Tensor.view
      
 
      Returns a new tensor with the same data as the self tensor but of a different shape.
      
 
-
      Tensor.view_as
      
+
      Tensor.view_as
      
 
      View this tensor as the same size as other.
      
 
-
      Tensor.vsplit
      
+
      Tensor.vsplit
      
 
      See torch.vsplit()
      
 
-
      Tensor.where
      
+
      Tensor.where
      
 
      self.where(condition, y) is equivalent to torch.where(condition, self, y).
      
 
-
      Tensor.xlogy
      
+
      Tensor.xlogy
      
 
      See torch.xlogy()
      
 
-
      Tensor.xlogy_
      
+
      Tensor.xlogy_
      
 
      In-place version of xlogy()
      
 
-
      Tensor.zero_
      
+
      Tensor.zero_
      
 
      Fills self tensor with zeros.
      
 
 
diff --git a/docs/master/testing.html b/docs/master/testing.html
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diff --git a/docs/master/torch.ao.ns._numeric_suite.html b/docs/master/torch.ao.ns._numeric_suite.html
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index 1b3baf8a06b9..24e3e57b17d6 100644
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diff --git a/docs/master/torch.html b/docs/master/torch.html
index 999918d43313..35dffc9967bb 100644
--- a/docs/master/torch.html
+++ b/docs/master/torch.html
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@@ -1815,26 +1815,23 @@ 
      BLAS and LAPACK Operations
      pca_lowrank
      
 
      Performs linear Principal Component Analysis (PCA) on a low-rank matrix, batches of such matrices, or sparse matrix.
      
 
-
      symeig
      
-
      This function returns eigenvalues and eigenvectors of a real symmetric or complex Hermitian matrix input or a batch thereof, represented by a namedtuple (eigenvalues, eigenvectors).
      
-
-
      lobpcg
      
+
      lobpcg
      
 
      Find the k largest (or smallest) eigenvalues and the corresponding eigenvectors of a symmetric positive definite generalized eigenvalue problem using matrix-free LOBPCG methods.
      
 
-
      trapz
      
+
      trapz
      
 
      Alias for torch.trapezoid().
      
 
-
      trapezoid
      
+
      trapezoid
      
 
      Computes the trapezoidal rule along dim.
      
 
-
      cumulative_trapezoid
      
+
      cumulative_trapezoid
      
 
      Cumulatively computes the trapezoidal rule along dim.
      
 
      
 
-
      triangular_solve
      
+
      triangular_solve
      
 
      Solves a system of equations with a square upper or lower triangular invertible matrix AA and multiple right-hand sides bb.
      
 
-
      vdot
      
+
      vdot
      
 
      Computes the dot product of two 1D vectors along a dimension.
      
 
 
@@ -2134,14 +2131,14 @@ 
      Operator Tags
 class torch.TagΒΆ
 
      Members:
      
+
      generated
      
 
      nondeterministic_seeded
      
-
      data_dependent_output
      
-
      core
      
 
      view_copy
      
+
      inplace_view
      
 
      pointwise
      
-
      generated
      
 
      nondeterministic_bitwise
      
-
      inplace_view
      
+
      data_dependent_output
      
+
      core
      
 
      dynamic_output_shape
      
 
      
 
      
diff --git a/docs/master/torch.overrides.html b/docs/master/torch.overrides.html
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