From 32862dbb6f91667b605c93a2f5de411bd3bf1e76 Mon Sep 17 00:00:00 2001 From: Kristian Georgiev Date: Thu, 23 Mar 2023 01:05:38 -0400 Subject: [PATCH] update sphinx docs --- docs/conf.py | 2 +- docs/html/.buildinfo | 2 +- docs/html/.doctrees/environment.pickle | Bin 122641 -> 127196 bytes docs/html/.doctrees/trak.doctree | Bin 400710 -> 425550 bytes docs/html/_modules/index.html | 6 +- .../_modules/trak/modelout_functions.html | 51 +++++++++++++ docs/html/_modules/trak/savers.html | 38 ++++++---- docs/html/_modules/trak/traker.html | 18 +++-- docs/html/_static/documentation_options.js | 2 +- docs/html/bert.html | 6 +- docs/html/clip.html | 6 +- docs/html/genindex.html | 20 ++++-- docs/html/index.html | 6 +- docs/html/install.html | 6 +- docs/html/objects.inv | Bin 1332 -> 1353 bytes docs/html/py-modindex.html | 6 +- docs/html/quickstart.html | 8 +-- docs/html/search.html | 6 +- docs/html/searchindex.js | 2 +- docs/html/slurm.html | 6 +- docs/html/trak.html | 68 ++++++++++++++++-- 21 files changed, 195 insertions(+), 64 deletions(-) diff --git a/docs/conf.py b/docs/conf.py index a372a8f..e4a549f 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -22,7 +22,7 @@ author = 'Kristian Georgiev' # The full version, including alpha/beta/rc tags -release = '0.1.0' +release = '0.1.1' # -- General configuration --------------------------------------------------- diff --git a/docs/html/.buildinfo b/docs/html/.buildinfo index 7f9c650..a4d6b90 100644 --- a/docs/html/.buildinfo +++ b/docs/html/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. 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zn}4|B{_O@fBNn>Yj1F+JS?Nz~3Ktg9ZiS3n1j*TVg;O{*(aVMQjxB7=3rCr{e7ojU z#KvO#H)4=6b^whH6`PmKiv@OnGcL7=YUM^K(g2RQnUHgYSClu5XalmrSvtiiGL5n6 z##j_#kh=)mxJ0NBuuNk2>f8 diff --git a/docs/html/_modules/index.html b/docs/html/_modules/index.html index 1a62708..6acb32f 100644 --- a/docs/html/_modules/index.html +++ b/docs/html/_modules/index.html @@ -5,7 +5,7 @@ - Overview: module code - TRAK 0.1.0 documentation + Overview: module code - TRAK 0.1.1 documentation @@ -122,7 +122,7 @@
-
TRAK 0.1.0 documentation
 +
TRAK 0.1.1 documentation
@@ -145,7 +145,7 @@
- TRAK 0.1.0 documentation + TRAK 0.1.1 documentation
+
[docs]class TextClassificationModelOutput(AbstractModelOutput): + """ + Margin for text classification models. This assumes that the model takes in + input_ids, token_type_ids, and attention_mask. + .. math:: + \text{logit}[\text{correct}] - \log\left(\sum_{i \neq \text{correct}} + \exp(\text{logit}[i])\right) + Version of margin proposed in 'Understanding Influence Functions + and Datamodels via Harmonic Analysis' + """ + + def __init__(self, temperature=1.) -> None: + super().__init__() + self.softmax = ch.nn.Softmax(-1) + self.loss_temperature = temperature + +
[docs] @staticmethod + def get_output(func_model, + weights: Iterable[Tensor], + buffers: Iterable[Tensor], + input_id: Tensor, + token_type_id: Tensor, + attention_mask: Tensor, + label: Tensor, + ) -> Tensor: + logits = func_model(weights, buffers, input_id.unsqueeze(0), + token_type_id.unsqueeze(0), + attention_mask.unsqueeze(0)) + bindex = ch.arange(logits.shape[0]).to(logits.device, non_blocking=False) + logits_correct = logits[bindex, label.unsqueeze(0)] + + cloned_logits = logits.clone() + cloned_logits[bindex, label.unsqueeze(0)] = ch.tensor(-ch.inf).to(logits.device) + + margins = logits_correct - cloned_logits.logsumexp(dim=-1) + return margins.sum()
+ +
[docs] def forward(self, model: Module, batch: Iterable[Tensor]) -> Tensor: + input_ids, token_type_ids, attention_mask, _ = batch + return model(input_ids=input_ids, + token_type_ids=token_type_ids, + attention_mask=attention_mask)
+ +
[docs] def get_out_to_loss_grad(self, func_model, weights, buffers, batch: Iterable[Tensor]) -> Tensor: + input_ids, token_type_ids, attention_mask, labels = batch + logits = func_model(weights, buffers, input_ids, token_type_ids, attention_mask) + ps = self.softmax(logits / self.loss_temperature)[ch.arange(logits.size(0)), labels] + return (1 - ps).clone().detach().unsqueeze(-1)
+ + TASK_TO_MODELOUT = { ('image_classification', True): ImageClassificationModelOutput, ('image_classification', False): IterImageClassificationModelOutput, + ('text_classification', True): TextClassificationModelOutput, ('clip', True): CLIPModelOutput, }
diff --git a/docs/html/_modules/trak/savers.html b/docs/html/_modules/trak/savers.html index 6f0fb9c..f450540 100644 --- a/docs/html/_modules/trak/savers.html +++ b/docs/html/_modules/trak/savers.html @@ -220,7 +220,8 @@

Source code for trak.savers

     @abstractmethod
     def __init__(self,
                  save_dir: Union[Path, str],
-                 metadata: Iterable) -> None:
+                 metadata: Iterable,
+                 load_from_save_dir: bool) -> None:
         """ Creates the save directory if it doesn't already exist.
         If the save directory already exists, it validates that the current
         TRAKer class has the same hyperparameters (metadata) as the one
@@ -234,14 +235,19 @@ 
Source code for trak.savers
                 intermediate values, and metadata
             metadata (Iterable): a dictionary containing metadata related to the
                 TRAKer class
+            load_from_save_dir (bool): If True, the Saver instance will attempt
+                to load existing metadata from save_dir. May lead to I/O issues
+                if multiple Saver instances ran in parallel have this flag set
+                to True. See the SLURM tutorial for more details.
         """
         self.metadata = metadata
         self.save_dir = Path(save_dir).resolve()
+        self.load_from_save_dir = load_from_save_dir
         os.makedirs(self.save_dir, exist_ok=True)
 
         # init TRAKer metadata
         self.metadata_file = self.save_dir.joinpath('metadata.json')
-        if os.path.exists(self.metadata_file):
+        if os.path.exists(self.metadata_file) and self.load_from_save_dir:
             with open(self.metadata_file, 'r') as f:
                 existsing_metadata = json.load(f)
             existing_jl_dim = int(existsing_metadata['JL dimension'])
@@ -254,20 +260,22 @@ 
Source code for trak.savers
                    f"In {self.save_dir} there are models using a {existing_matrix_type} JL matrix\
                    , and this TRAKer instance uses a {self.metadata['JL matrix type']} JL matrix."
 
-        else:
+        elif self.load_from_save_dir:
             with open(self.metadata_file, 'w') as f:
                 json.dump(self.metadata, f)
 
         self.model_ids = {}
-        # check if there are existing model ids in the save_dir
-        self.model_ids_files = self.save_dir.rglob('id_*.json')
-
-        for existing_model_id_file in self.model_ids_files:
-            with open(existing_model_id_file, 'r') as f:
-                existing_id = json.load(f)
-                existing_id = {int(model_id): metadata
-                               for model_id, metadata in existing_id.items()}
-            self.model_ids.update(existing_id)
+        if self.load_from_save_dir:
+            # check if there are existing model ids in the save_dir
+            self.model_ids_files = self.save_dir.rglob('id_*.json')
+
+            for existing_model_id_file in self.model_ids_files:
+                with open(existing_model_id_file, 'r') as f:
+                    existing_id = json.load(f)
+                    existing_id = {int(model_id): metadata
+                                   for model_id, metadata in existing_id.items()}
+                self.model_ids.update(existing_id)
+
         # wlog set num_targets to those of a random model_id we could raise an
         # error here if different model_ids have different num_targets but this
         # could be a bit too stringent in some cases
@@ -357,8 +365,10 @@ 
Source code for trak.savers
     into memory.
 
     """
-    def __init__(self, save_dir, metadata, train_set_size, proj_dim) -> None:
-        super().__init__(save_dir=save_dir, metadata=metadata)
+    def __init__(self, save_dir, metadata, train_set_size, proj_dim, load_from_save_dir) -> None:
+        super().__init__(save_dir=save_dir,
+                         metadata=metadata,
+                         load_from_save_dir=load_from_save_dir)
         self.train_set_size = train_set_size
         self.proj_dim = proj_dim
 
diff --git a/docs/html/_modules/trak/traker.html b/docs/html/_modules/trak/traker.html
index 85ef668..d20e42c 100644
--- a/docs/html/_modules/trak/traker.html
+++ b/docs/html/_modules/trak/traker.html
@@ -218,6 +218,7 @@ 
Source code for trak.traker
                  task: Union[AbstractModelOutput, str],
                  train_set_size: int,
                  save_dir: str = './trak_results',
+                 load_from_save_dir: bool = True,
                  device: Union[str, torch.device] = 'cuda',
                  gradient_computer: AbstractGradientComputer = FunctionalGradientComputer,
                  projector: Optional[AbstractProjector] = None,
@@ -237,6 +238,10 @@ 
Source code for trak.traker
             train_set_size (int): Size of the train set that TRAK is featurizing
             save_dir (str, optional): Directory to save final TRAK scores,
                 intermediate results, and metadata. Defaults to './trak_results'.
+            load_from_save_dir (bool, optional): If True, the TRAKer instance
+                will attempt to load existing metadata from save_dir. May lead
+                to I/O issues if multiple TRAKer instances ran in parallel have
+                this flag set to True. See the SLURM tutorial for more details.
             device (Union[str, torch.device], optional): torch device on which
                 to do computations. Defaults to 'cuda'.
             gradient_computer (AbstractGradientComputer, optional):
@@ -261,6 +266,7 @@ 
Source code for trak.traker
         self.init_projector(projector, proj_dim)  # inits self.projector
 
         self.save_dir = Path(save_dir).resolve()
+        self.load_from_save_dir = load_from_save_dir
 
         if type(self.task) is str:
             self.modelout_fn = TASK_TO_MODELOUT[(self.task, gradient_computer.is_functional)]
@@ -278,7 +284,8 @@ 
Source code for trak.traker
         self.saver = MmapSaver(save_dir=self.save_dir,
                                metadata=metadata,
                                train_set_size=self.train_set_size,
-                               proj_dim=self.proj_dim)
+                               proj_dim=self.proj_dim,
+                               load_from_save_dir=self.load_from_save_dir)
 
 
[docs]    def init_projector(self, projector, proj_dim) -> None:
         """ Initialize the projector for a traker class
@@ -511,8 +518,7 @@ 
Source code for trak.traker
             model_ids = self.saver.model_ids
 
         _completed = [False] * len(model_ids)
-        _scores = ch.empty(len(model_ids),
-                           self.train_set_size,
+        _scores = ch.zeros(self.train_set_size,
                            self.saver.num_targets,
                            device=self.device)
         _avg_out_to_losses = ch.zeros(self.saver.train_set_size, 1, device=self.device)
@@ -530,7 +536,7 @@ 
Source code for trak.traker
             g = ch.as_tensor(self.saver.current_features, device=self.device)
             g_target = ch.as_tensor(self.saver.current_target_grads, device=self.device)
 
-            _scores[j] = self.score_computer.get_scores(g, g_target)
+            _scores += self.score_computer.get_scores(g, g_target)
             _avg_out_to_losses += ch.as_tensor(self.saver.current_out_to_loss, device=self.device)
             _completed[j] = True
 
@@ -539,10 +545,8 @@ 
Source code for trak.traker
             else:
                 self.saver.clear_target_grad_count(model_id)
 
-        _scores = _scores[_completed].mean(dim=0)
-
         _num_models_used = float(sum(_completed))
-        self.scores = _scores * (_avg_out_to_losses / _num_models_used)
+        self.scores = (_scores / _num_models_used) * (_avg_out_to_losses / _num_models_used)
         self.saver.save_scores(self.scores.cpu().numpy(), exp_name)
 
         return self.scores

diff --git a/docs/html/_static/documentation_options.js b/docs/html/_static/documentation_options.js
index 87d8188..1f7b0d1 100644
--- a/docs/html/_static/documentation_options.js
+++ b/docs/html/_static/documentation_options.js
@@ -1,6 +1,6 @@
 var DOCUMENTATION_OPTIONS = {
     URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
-    VERSION: '0.1.0',
+    VERSION: '0.1.1',
     LANGUAGE: 'None',
     COLLAPSE_INDEX: false,
     BUILDER: 'html',
diff --git a/docs/html/bert.html b/docs/html/bert.html
index 913d52c..3d47df4 100644
--- a/docs/html/bert.html
+++ b/docs/html/bert.html
@@ -6,7 +6,7 @@
 
 
     
-        Add a task to TRAKer (subclassing ModelOutput) — BERT-base - TRAK 0.1.0 documentation
+        Add a task to TRAKer (subclassing ModelOutput) — BERT-base - TRAK 0.1.1 documentation
       
     
     
@@ -123,7 +123,7 @@
       
     

     

-      
TRAK 0.1.0 documentation

+      
TRAK 0.1.1 documentation

     

     

       

@@ -146,7 +146,7 @@
       

   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
diff --git a/docs/html/clip.html b/docs/html/clip.html
index db19338..60071e9 100644
--- a/docs/html/clip.html
+++ b/docs/html/clip.html
@@ -6,7 +6,7 @@
 
 
     
-        Add a task to TRAKer (subclassing ModelOutput) — CLIP - TRAK 0.1.0 documentation
+        Add a task to TRAKer (subclassing ModelOutput) — CLIP - TRAK 0.1.1 documentation
       
     
     
@@ -123,7 +123,7 @@
       
     

     

-      
TRAK 0.1.0 documentation

+      
TRAK 0.1.1 documentation

     

     

       

@@ -146,7 +146,7 @@
       

   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
diff --git a/docs/html/genindex.html b/docs/html/genindex.html
index 83a9199..c0ca7eb 100644
--- a/docs/html/genindex.html
+++ b/docs/html/genindex.html
@@ -4,7 +4,7 @@
     
     
 
-    Index - TRAK 0.1.0 documentation
+    Index - TRAK 0.1.1 documentation
 
     
     
@@ -121,7 +121,7 @@
       
     

     

-      
TRAK 0.1.0 documentation

+      
TRAK 0.1.1 documentation

     

     

       

@@ -144,7 +144,7 @@
       

   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
@@ -293,12 +293,16 @@ 
F

 
         
  • finalize_features() (trak.traker.TRAKer method)
 
    • 
-    
-    
+    
@@ -329,6 +333,8 @@ 
    G
    
           
  • (trak.modelout_functions.ImageClassificationModelOutput method)
 
    • 
           
  • (trak.modelout_functions.IterImageClassificationModelOutput method)
+
    • 
+          
  • (trak.modelout_functions.TextClassificationModelOutput method)
 
    • 
         
         
  • get_output() (trak.modelout_functions.AbstractModelOutput method)
@@ -339,6 +345,8 @@ 
    G
    
           
  • (trak.modelout_functions.ImageClassificationModelOutput static method)
 
    • 
           
  • (trak.modelout_functions.IterImageClassificationModelOutput method)
+
    • 
+          
  • (trak.modelout_functions.TextClassificationModelOutput static method)
 
    • 
         
     
@@ -553,6 +561,8 @@ 
    T
    
   
    
     
      
         
    • text_embeddings (trak.modelout_functions.CLIPModelOutput attribute)
+
      • 
+        
    • TextClassificationModelOutput (class in trak.modelout_functions)
 
      • 
         
    • 
     trak
diff --git a/docs/html/index.html b/docs/html/index.html
index 13dd132..4293a1f 100644
--- a/docs/html/index.html
+++ b/docs/html/index.html
@@ -6,7 +6,7 @@
 
 
     
-        TRAK 0.1.0 documentation
+        TRAK 0.1.1 documentation
       
     
     
@@ -123,7 +123,7 @@
       
     
     
      
-      
      TRAK 0.1.0 documentation
      
+      
      TRAK 0.1.1 documentation
      
     
      
     
      
       
      
@@ -146,7 +146,7 @@
       
      
   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
diff --git a/docs/html/install.html b/docs/html/install.html
index 464d9a8..91668cf 100644
--- a/docs/html/install.html
+++ b/docs/html/install.html
@@ -6,7 +6,7 @@
 
 
     
-        Installation FAQs - TRAK 0.1.0 documentation
+        Installation FAQs - TRAK 0.1.1 documentation
       
     
     
@@ -123,7 +123,7 @@
       
     
      
     
      
-      
      TRAK 0.1.0 documentation
      
+      
      TRAK 0.1.1 documentation
      
     
      
     
      
       
      
@@ -146,7 +146,7 @@
       
      
   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
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index 7f0c75b4872eda16df56d1490ceac873d72c2ac9..11be779126fd2a153c6dacb55d758fde471bd830 100644
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-    Python Module Index - TRAK 0.1.0 documentation
+    Python Module Index - TRAK 0.1.1 documentation
 
     
     
@@ -121,7 +121,7 @@
       
     
      
     
      
-      
      TRAK 0.1.0 documentation
      
+      
      TRAK 0.1.1 documentation
      
     
      
     
      
       
      
@@ -144,7 +144,7 @@
       
      
   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
diff --git a/docs/html/quickstart.html b/docs/html/quickstart.html
index 626ee06..5c1c6a7 100644
--- a/docs/html/quickstart.html
+++ b/docs/html/quickstart.html
@@ -3,10 +3,10 @@
   
     
     
-
+
 
     
-        Quickstart — get TRAK scores for CIFAR-10 - TRAK 0.1.0 documentation
+        Quickstart — get TRAK scores for CIFAR-10 - TRAK 0.1.1 documentation
       
     
     
@@ -123,7 +123,7 @@
       
     
      
     
      
-      
      TRAK 0.1.0 documentation
      
+      
      TRAK 0.1.1 documentation
      
     
      
     
      
       
      
@@ -146,7 +146,7 @@
       
      
   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
diff --git a/docs/html/search.html b/docs/html/search.html
index b2381eb..e6f9633 100644
--- a/docs/html/search.html
+++ b/docs/html/search.html
@@ -4,7 +4,7 @@
     
     
 
-    Search - TRAK 0.1.0 documentation
+    Search - TRAK 0.1.1 documentation
     
     
     
@@ -120,7 +120,7 @@
       
     
      
     
      
-      
      TRAK 0.1.0 documentation
      
+      
      TRAK 0.1.1 documentation
      
     
      
     
      
       
      
@@ -143,7 +143,7 @@
       
      
   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
diff --git a/docs/html/searchindex.js b/docs/html/searchindex.js
index f2f7a0b..d60b0a1 100644
--- a/docs/html/searchindex.js
+++ b/docs/html/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/docs/html/slurm.html b/docs/html/slurm.html
index 6dd6a5f..2ead939 100644
--- a/docs/html/slurm.html
+++ b/docs/html/slurm.html
@@ -6,7 +6,7 @@
 
 
     
-        Parallelize TRAK scoring with SLURM - TRAK 0.1.0 documentation
+        Parallelize TRAK scoring with SLURM - TRAK 0.1.1 documentation
       
     
     
@@ -123,7 +123,7 @@
       
     
      
     
      
-      
      TRAK 0.1.0 documentation
      
+      
      TRAK 0.1.1 documentation
      
     
      
     
      
       
      
@@ -146,7 +146,7 @@
       
      
   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
diff --git a/docs/html/trak.html b/docs/html/trak.html
index 235c991..14e78e3 100644
--- a/docs/html/trak.html
+++ b/docs/html/trak.html
@@ -6,7 +6,7 @@
 
 
     
-        API reference - TRAK 0.1.0 documentation
+        API reference - TRAK 0.1.1 documentation
       
     
     
@@ -123,7 +123,7 @@
       
     
      
     
      
-      
      TRAK 0.1.0 documentation
      
+      
      TRAK 0.1.1 documentation
      
     
      
     
      
       
      
@@ -146,7 +146,7 @@
       
      
   
   
-  TRAK 0.1.0 documentation
+  TRAK 0.1.1 documentation
   
 
   
@@ -201,7 +201,7 @@
 
      trak.traker module#
      
 
      
 
      
-class trak.traker.TRAKer(model: torch.nn.modules.module.Module, task: typing.Union[trak.modelout_functions.AbstractModelOutput, str], train_set_size: int, save_dir: str = './trak_results', device: typing.Union[str, torch.device] = 'cuda', gradient_computer: trak.gradient_computers.AbstractGradientComputer = <class 'trak.gradient_computers.FunctionalGradientComputer'>, projector: typing.Optional[trak.projectors.AbstractProjector] = None, proj_dim: int = 2048)[source]#
      
+class trak.traker.TRAKer(model: torch.nn.modules.module.Module, task: typing.Union[trak.modelout_functions.AbstractModelOutput, str], train_set_size: int, save_dir: str = './trak_results', load_from_save_dir: bool = True, device: typing.Union[str, torch.device] = 'cuda', gradient_computer: trak.gradient_computers.AbstractGradientComputer = <class 'trak.gradient_computers.FunctionalGradientComputer'>, projector: typing.Optional[trak.projectors.AbstractProjector] = None, proj_dim: int = 2048)[source]#
 
      Bases: object
      
 
      
 
      
@@ -769,6 +769,62 @@
 
 
      
 
+
      
+
      
+class trak.modelout_functions.TextClassificationModelOutput(temperature=1.0)[source]#
      
+
      Bases: trak.modelout_functions.AbstractModelOutput
      
+
      
+
      Margin for text classification models. This assumes that the model takes in
+input_ids, token_type_ids, and attention_mask.
+.. math:
      
+
      ext{logit}[     ext{correct}] - \log\left(\sum_{i 
+
      
+
      
+
      
+
      
+
      eq      ext{correct}}
      exp(   ext{logit}[i])
      
+
      
+
      ight)
      Version of margin proposed in ‘Understanding Influence Functions
+and Datamodels via Harmonic Analysis’
      
+
      
+
      
+
      
+
      
+forward(model: torch.nn.modules.module.Module, batch: Iterable[torch.Tensor]) → torch.Tensor[source]#
      
+
      
+
+
      
+
      
+get_out_to_loss_grad(func_model, weights, buffers, batch: Iterable[torch.Tensor]) → torch.Tensor[source]#
      
+
      See Sections 2 & 3 of (TODO: link)[our paper] for more details on
+what the out-to-loss functions (in the notation of the paper, \(Q\))
+are in the context of TRAK and how to use & design them.
      
+
      
+
      Args:
      model (torch.nn.Module): model
+batch (Iterable[Tensor]): input batch
      
+
      
+
      Returns:
      Tensor: gradient of the out-to-loss function
      
+
      
+
      
+
      
+
+
      
+
      
+static get_output(func_model, weights: Iterable[torch.Tensor], buffers: Iterable[torch.Tensor], input_id: torch.Tensor, token_type_id: torch.Tensor, attention_mask: torch.Tensor, label: torch.Tensor) → torch.Tensor[source]#
      
+
      See Sections 2 & 3 of (TODO: link)[our paper] for more details on
+what model output functions are in the context of TRAK and how to use &
+design them.
      
+
      
+
      Args:
      model (torch.nn.Module): model
+batch (Iterable[Tensor]): input batch
      
+
      
+
      Returns:
      Tensor: model output function
      
+
      
+
      
+
      
+
+
      
+
 
 
      
 
      trak.projectors module#
      
@@ -912,7 +968,7 @@
 
      trak.savers module#
      
 
      
 
      
-class trak.savers.AbstractSaver(save_dir: Union[pathlib.Path, str], metadata: Iterable)[source]#
      
+class trak.savers.AbstractSaver(save_dir: Union[pathlib.Path, str], metadata: Iterable, load_from_save_dir: bool)[source]#
 
      Bases: abc.ABC
      
 
      Implementations of Saver class must implement getters and setters for TRAK
 features and scores, as well as intermediate values like gradients and
@@ -993,7 +1049,7 @@
 
 
      
 
      
-class trak.savers.MmapSaver(save_dir, metadata, train_set_size, proj_dim)[source]#
      
+class trak.savers.MmapSaver(save_dir, metadata, train_set_size, proj_dim, load_from_save_dir)[source]#
 
      Bases: trak.savers.AbstractSaver
      
 
      A saver that uses memory-mapped numpy arrays. This makes small reads and
 writes (e.g.) during featurizing feasible without loading the entire file