scvi.model.base.BaseMinifiedModeModelClass#
- class scvi.model.base.BaseMinifiedModeModelClass(adata=None)[source]#
Abstract base class for scvi-tools models that can handle minified data.
Attributes table#
Data attached to model instance. |
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Manager instance associated with self.adata. |
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The current device that the module's params are on. |
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Returns computed metrics during training. |
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Whether the model has been trained. |
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The type of minified data associated with this model, if applicable. |
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Observations that are in test set. |
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Observations that are in train set. |
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Observations that are in validation set. |
Methods table#
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Converts a legacy saved model (<v0.15.0) to the updated save format. |
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Retrieves the |
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Returns the object in AnnData associated with the key in the data registry. |
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Instantiate a model from the saved output. |
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Return the full registry saved with the model. |
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Minifies the model's adata. |
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Registers an |
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Save the state of the model. |
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Sets up the |
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Move model to device. |
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Trains the model. |
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Print summary of the setup for the initial AnnData or a given AnnData object. |
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Print args used to setup a saved model. |
Attributes#
adata
adata_manager
device
history
is_trained
minified_data_type
- BaseMinifiedModeModelClass.minified_data_type[source]#
The type of minified data associated with this model, if applicable.
test_indices
train_indices
validation_indices
Methods#
convert_legacy_save
- classmethod BaseMinifiedModeModelClass.convert_legacy_save(dir_path, output_dir_path, overwrite=False, prefix=None)[source]#
Converts a legacy saved model (<v0.15.0) to the updated save format.
get_anndata_manager
- BaseMinifiedModeModelClass.get_anndata_manager(adata, required=False)[source]#
Retrieves the
AnnDataManager
for a given AnnData object specific to this model instance.Requires
self.id
has been set. Checks for anAnnDataManager
specific to this model instance.
get_from_registry
- BaseMinifiedModeModelClass.get_from_registry(adata, registry_key)[source]#
Returns the object in AnnData associated with the key in the data registry.
AnnData object should be registered with the model prior to calling this function via the
self._validate_anndata
method.
load
- classmethod BaseMinifiedModeModelClass.load(dir_path, adata=None, use_gpu=None, prefix=None, backup_url=None)[source]#
Instantiate a model from the saved output.
- Parameters:
dir_path (str) – Path to saved outputs.
adata (Optional[Union[AnnData, MuData]]) – AnnData organized in the same way as data used to train model. It is not necessary to run setup_anndata, as AnnData is validated against the saved
scvi
setup dictionary. If None, will check for and load anndata saved with the model.use_gpu (Optional[Union[str, int, bool]]) – Load model on default GPU if available (if None or True), or index of GPU to use (if int), or name of GPU (if str), or use CPU (if False).
backup_url (Optional[str]) – URL to retrieve saved outputs from if not present on disk.
- Returns:
Model with loaded state dictionaries.
Examples
>>> model = ModelClass.load(save_path, adata) # use the name of the model class used to save >>> model.get_....
load_registry
- static BaseMinifiedModeModelClass.load_registry(dir_path, prefix=None)[source]#
Return the full registry saved with the model.
minify_adata
- abstract BaseMinifiedModeModelClass.minify_adata(*args, **kwargs)[source]#
Minifies the model’s adata.
Minifies the adata, and registers new anndata fields as required (can be model-specific). This also sets the appropriate property on the module to indicate that the adata is minified.
Notes
The modification is not done inplace – instead the model is assigned a new (minified) version of the adata.
register_manager
- classmethod BaseMinifiedModeModelClass.register_manager(adata_manager)[source]#
Registers an
AnnDataManager
instance with this model class.Stores the
AnnDataManager
reference in a class-specific manager store. Intended for use in thesetup_anndata()
class method followed up by retrieval of theAnnDataManager
via the_get_most_recent_anndata_manager()
method in the model init method.Notes
Subsequent calls to this method with an
AnnDataManager
instance referring to the same underlying AnnData object will overwrite the reference to previousAnnDataManager
.- Parameters:
adata_manager (AnnDataManager) –
save
- BaseMinifiedModeModelClass.save(dir_path, prefix=None, overwrite=False, save_anndata=False, **anndata_write_kwargs)[source]#
Save the state of the model.
Neither the trainer optimizer state nor the trainer history are saved. Model files are not expected to be reproducibly saved and loaded across versions until we reach version 1.0.
- Parameters:
dir_path (str) – Path to a directory.
prefix (Optional[str]) – Prefix to prepend to saved file names.
overwrite (bool) – Overwrite existing data or not. If
False
and directory already exists atdir_path
, error will be raised.save_anndata (bool) – If True, also saves the anndata
anndata_write_kwargs – Kwargs for
write()
setup_anndata
- abstract classmethod BaseMinifiedModeModelClass.setup_anndata(adata, *args, **kwargs)[source]#
Sets up the
AnnData
object for this model.A mapping will be created between data fields used by this model to their respective locations in adata. None of the data in adata are modified. Only adds fields to adata.
Each model class deriving from this class provides parameters to this method according to its needs. To operate correctly with the model initialization, the implementation must call
register_manager()
on a model-specific instance ofAnnDataManager
.- Parameters:
adata (AnnData) –
to_device
- BaseMinifiedModeModelClass.to_device(device)[source]#
Move model to device.
- Parameters:
device (Union[str, int]) – Device to move model to. Options: ‘cpu’ for CPU, integer GPU index (eg. 0), or ‘cuda:X’ where X is the GPU index (eg. ‘cuda:0’). See torch.device for more info.
Examples
>>> adata = scvi.data.synthetic_iid() >>> model = scvi.model.SCVI(adata) >>> model.to_device('cpu') # moves model to CPU >>> model.to_device('cuda:0') # moves model to GPU 0 >>> model.to_device(0) # also moves model to GPU 0
train
view_anndata_setup
- BaseMinifiedModeModelClass.view_anndata_setup(adata=None, hide_state_registries=False)[source]#
Print summary of the setup for the initial AnnData or a given AnnData object.
view_setup_args