fiftyone.brain.internal.models

• fiftyone.brain.internal.models.simple_resnet
  • simple_resnet()
  • Network
    • Network.nodes()
    • Network.forward()
    • Network.half()
    • Network.T_destination
    • Network.add_module()
    • Network.apply()
    • Network.bfloat16()
    • Network.buffers()
    • Network.call_super_init
    • Network.children()
    • Network.compile()
    • Network.cpu()
    • Network.cuda()
    • Network.double()
    • Network.dump_patches
    • Network.eval()
    • Network.extra_repr()
    • Network.float()
    • Network.get_buffer()
    • Network.get_extra_state()
    • Network.get_parameter()
    • Network.get_submodule()
    • Network.ipu()
    • Network.load_state_dict()
    • Network.modules()
    • Network.mtia()
    • Network.named_buffers()
    • Network.named_children()
    • Network.named_modules()
    • Network.named_parameters()
    • Network.parameters()
    • Network.register_backward_hook()
    • Network.register_buffer()
    • Network.register_forward_hook()
    • Network.register_forward_pre_hook()
    • Network.register_full_backward_hook()
    • Network.register_full_backward_pre_hook()
    • Network.register_load_state_dict_post_hook()
    • Network.register_load_state_dict_pre_hook()
    • Network.register_module()
    • Network.register_parameter()
    • Network.register_state_dict_post_hook()
    • Network.register_state_dict_pre_hook()
    • Network.requires_grad_()
    • Network.set_extra_state()
    • Network.set_submodule()
    • Network.share_memory()
    • Network.state_dict()
    • Network.to()
    • Network.to_empty()
    • Network.train()
    • Network.type()
    • Network.xpu()
    • Network.zero_grad()
    • Network.training
  • has_inputs()
  • build_graph()
  • pipeline()
  • Crop
    • Crop.options()
    • Crop.output_shape()
    • Crop.count()
    • Crop.h
    • Crop.index()
    • Crop.w
  • FlipLR
    • FlipLR.options()
    • FlipLR.count()
    • FlipLR.index()
  • Cutout
    • Cutout.options()
    • Cutout.count()
    • Cutout.h
    • Cutout.index()
    • Cutout.w
  • PiecewiseLinear
    • PiecewiseLinear.count()
    • PiecewiseLinear.index()
    • PiecewiseLinear.knots
    • PiecewiseLinear.vals
  • Const
    • Const.count()
    • Const.index()
    • Const.val
  • Identity
    • Identity.count()
    • Identity.index()
  • Add
    • Add.count()
    • Add.index()
  • AddWeighted
    • AddWeighted.count()
    • AddWeighted.index()
    • AddWeighted.wx
    • AddWeighted.wy
  • Mul
    • Mul.T_destination
    • Mul.add_module()
    • Mul.apply()
    • Mul.bfloat16()
    • Mul.buffers()
    • Mul.call_super_init
    • Mul.children()
    • Mul.compile()
    • Mul.cpu()
    • Mul.cuda()
    • Mul.double()
    • Mul.dump_patches
    • Mul.eval()
    • Mul.extra_repr()
    • Mul.float()
    • Mul.forward()
    • Mul.get_buffer()
    • Mul.get_extra_state()
    • Mul.get_parameter()
    • Mul.get_submodule()
    • Mul.half()
    • Mul.ipu()
    • Mul.load_state_dict()
    • Mul.modules()
    • Mul.mtia()
    • Mul.named_buffers()
    • Mul.named_children()
    • Mul.named_modules()
    • Mul.named_parameters()
    • Mul.parameters()
    • Mul.register_backward_hook()
    • Mul.register_buffer()
    • Mul.register_forward_hook()
    • Mul.register_forward_pre_hook()
    • Mul.register_full_backward_hook()
    • Mul.register_full_backward_pre_hook()
    • Mul.register_load_state_dict_post_hook()
    • Mul.register_load_state_dict_pre_hook()
    • Mul.register_module()
    • Mul.register_parameter()
    • Mul.register_state_dict_post_hook()
    • Mul.register_state_dict_pre_hook()
    • Mul.requires_grad_()
    • Mul.set_extra_state()
    • Mul.set_submodule()
    • Mul.share_memory()
    • Mul.state_dict()
    • Mul.to()
    • Mul.to_empty()
    • Mul.train()
    • Mul.type()
    • Mul.xpu()
    • Mul.zero_grad()
    • Mul.training
  • Flatten
    • Flatten.forward()
    • Flatten.T_destination
    • Flatten.add_module()
    • Flatten.apply()
    • Flatten.bfloat16()
    • Flatten.buffers()
    • Flatten.call_super_init
    • Flatten.children()
    • Flatten.compile()
    • Flatten.cpu()
    • Flatten.cuda()
    • Flatten.double()
    • Flatten.dump_patches
    • Flatten.eval()
    • Flatten.extra_repr()
    • Flatten.float()
    • Flatten.get_buffer()
    • Flatten.get_extra_state()
    • Flatten.get_parameter()
    • Flatten.get_submodule()
    • Flatten.half()
    • Flatten.ipu()
    • Flatten.load_state_dict()
    • Flatten.modules()
    • Flatten.mtia()
    • Flatten.named_buffers()
    • Flatten.named_children()
    • Flatten.named_modules()
    • Flatten.named_parameters()
    • Flatten.parameters()
    • Flatten.register_backward_hook()
    • Flatten.register_buffer()
    • Flatten.register_forward_hook()
    • Flatten.register_forward_pre_hook()
    • Flatten.register_full_backward_hook()
    • Flatten.register_full_backward_pre_hook()
    • Flatten.register_load_state_dict_post_hook()
    • Flatten.register_load_state_dict_pre_hook()
    • Flatten.register_module()
    • Flatten.register_parameter()
    • Flatten.register_state_dict_post_hook()
    • Flatten.register_state_dict_pre_hook()
    • Flatten.requires_grad_()
    • Flatten.set_extra_state()
    • Flatten.set_submodule()
    • Flatten.share_memory()
    • Flatten.state_dict()
    • Flatten.to()
    • Flatten.to_empty()
    • Flatten.train()
    • Flatten.type()
    • Flatten.xpu()
    • Flatten.zero_grad()
    • Flatten.training
  • Concat
    • Concat.forward()
    • Concat.T_destination
    • Concat.add_module()
    • Concat.apply()
    • Concat.bfloat16()
    • Concat.buffers()
    • Concat.call_super_init
    • Concat.children()
    • Concat.compile()
    • Concat.cpu()
    • Concat.cuda()
    • Concat.double()
    • Concat.dump_patches
    • Concat.eval()
    • Concat.extra_repr()
    • Concat.float()
    • Concat.get_buffer()
    • Concat.get_extra_state()
    • Concat.get_parameter()
    • Concat.get_submodule()
    • Concat.half()
    • Concat.ipu()
    • Concat.load_state_dict()
    • Concat.modules()
    • Concat.mtia()
    • Concat.named_buffers()
    • Concat.named_children()
    • Concat.named_modules()
    • Concat.named_parameters()
    • Concat.parameters()
    • Concat.register_backward_hook()
    • Concat.register_buffer()
    • Concat.register_forward_hook()
    • Concat.register_forward_pre_hook()
    • Concat.register_full_backward_hook()
    • Concat.register_full_backward_pre_hook()
    • Concat.register_load_state_dict_post_hook()
    • Concat.register_load_state_dict_pre_hook()
    • Concat.register_module()
    • Concat.register_parameter()
    • Concat.register_state_dict_post_hook()
    • Concat.register_state_dict_pre_hook()
    • Concat.requires_grad_()
    • Concat.set_extra_state()
    • Concat.set_submodule()
    • Concat.share_memory()
    • Concat.state_dict()
    • Concat.to()
    • Concat.to_empty()
    • Concat.train()
    • Concat.type()
    • Concat.xpu()
    • Concat.zero_grad()
    • Concat.training
  • BatchNorm
    • BatchNorm.T_destination
    • BatchNorm.add_module()
    • BatchNorm.apply()
    • BatchNorm.bfloat16()
    • BatchNorm.buffers()
    • BatchNorm.call_super_init
    • BatchNorm.children()
    • BatchNorm.compile()
    • BatchNorm.cpu()
    • BatchNorm.cuda()
    • BatchNorm.double()
    • BatchNorm.dump_patches
    • BatchNorm.eval()
    • BatchNorm.extra_repr()
    • BatchNorm.float()
    • BatchNorm.forward()
    • BatchNorm.get_buffer()
    • BatchNorm.get_extra_state()
    • BatchNorm.get_parameter()
    • BatchNorm.get_submodule()
    • BatchNorm.half()
    • BatchNorm.ipu()
    • BatchNorm.load_state_dict()
    • BatchNorm.modules()
    • BatchNorm.mtia()
    • BatchNorm.named_buffers()
    • BatchNorm.named_children()
    • BatchNorm.named_modules()
    • BatchNorm.named_parameters()
    • BatchNorm.parameters()
    • BatchNorm.register_backward_hook()
    • BatchNorm.register_buffer()
    • BatchNorm.register_forward_hook()
    • BatchNorm.register_forward_pre_hook()
    • BatchNorm.register_full_backward_hook()
    • BatchNorm.register_full_backward_pre_hook()
    • BatchNorm.register_load_state_dict_post_hook()
    • BatchNorm.register_load_state_dict_pre_hook()
    • BatchNorm.register_module()
    • BatchNorm.register_parameter()
    • BatchNorm.register_state_dict_post_hook()
    • BatchNorm.register_state_dict_pre_hook()
    • BatchNorm.requires_grad_()
    • BatchNorm.reset_parameters()
    • BatchNorm.reset_running_stats()
    • BatchNorm.set_extra_state()
    • BatchNorm.set_submodule()
    • BatchNorm.share_memory()
    • BatchNorm.state_dict()
    • BatchNorm.to()
    • BatchNorm.to_empty()
    • BatchNorm.train()
    • BatchNorm.type()
    • BatchNorm.xpu()
    • BatchNorm.zero_grad()
    • BatchNorm.num_features
    • BatchNorm.eps
    • BatchNorm.momentum
    • BatchNorm.affine
    • BatchNorm.track_running_stats
    • BatchNorm.running_mean
    • BatchNorm.running_var
    • BatchNorm.num_batches_tracked
    • BatchNorm.training
  • conv_bn()
  • residual()
  • path_iter()
• fiftyone.brain.internal.models.torch
  • TorchImageModelConfig
    • TorchImageModelConfig.attributes()
    • TorchImageModelConfig.builder()
    • TorchImageModelConfig.copy()
    • TorchImageModelConfig.custom_attributes()
    • TorchImageModelConfig.default()
    • TorchImageModelConfig.download_model_if_necessary()
    • TorchImageModelConfig.from_dict()
    • TorchImageModelConfig.from_json()
    • TorchImageModelConfig.from_kwargs()
    • TorchImageModelConfig.from_str()
    • TorchImageModelConfig.get_class_name()
    • TorchImageModelConfig.init()
    • TorchImageModelConfig.load_default()
    • TorchImageModelConfig.parse_array()
    • TorchImageModelConfig.parse_bool()
    • TorchImageModelConfig.parse_categorical()
    • TorchImageModelConfig.parse_dict()
    • TorchImageModelConfig.parse_int()
    • TorchImageModelConfig.parse_mutually_exclusive_fields()
    • TorchImageModelConfig.parse_number()
    • TorchImageModelConfig.parse_object()
    • TorchImageModelConfig.parse_object_array()
    • TorchImageModelConfig.parse_object_dict()
    • TorchImageModelConfig.parse_path()
    • TorchImageModelConfig.parse_raw()
    • TorchImageModelConfig.parse_string()
    • TorchImageModelConfig.serialize()
    • TorchImageModelConfig.to_str()
    • TorchImageModelConfig.validate_all_or_nothing_fields()
    • TorchImageModelConfig.write_json()
  • TorchImageModel
    • TorchImageModel.build_get_item()
    • TorchImageModel.can_embed_prompts
    • TorchImageModel.classes
    • TorchImageModel.collate_fn()
    • TorchImageModel.device
    • TorchImageModel.embed()
    • TorchImageModel.embed_all()
    • TorchImageModel.from_config()
    • TorchImageModel.from_dict()
    • TorchImageModel.from_json()
    • TorchImageModel.from_kwargs()
    • TorchImageModel.get_embeddings()
    • TorchImageModel.has_collate_fn
    • TorchImageModel.has_embeddings
    • TorchImageModel.has_logits
    • TorchImageModel.mask_targets
    • TorchImageModel.media_type
    • TorchImageModel.num_classes
    • TorchImageModel.parse()
    • TorchImageModel.predict()
    • TorchImageModel.predict_all()
    • TorchImageModel.preprocess
    • TorchImageModel.ragged_batches
    • TorchImageModel.required_keys
    • TorchImageModel.skeleton
    • TorchImageModel.store_logits
    • TorchImageModel.transforms
    • TorchImageModel.using_gpu
    • TorchImageModel.using_half_precision
    • TorchImageModel.validate()

Module contents

Brain models.

Copyright 2017-2025, Voxel51, Inc.

voxel51.com

Functions:

list_models()	Returns the list of available models.
list_downloaded_models()	Returns information about the models that have been downloaded.
is_model_downloaded(name)	Determines whether the model of the given name is downloaded.
download_model(name[, overwrite])	Downloads the model of the given name.
install_model_requirements(name[, error_level])	Installs any package requirements for the model with the given name.
ensure_model_requirements(name[, error_level])	Ensures that the package requirements for the model with the given name are satisfied.
load_model(name[, download_if_necessary, ...])	Loads the model of the given name.
find_model(name)	Returns the path to the model on disk.
get_model(name)	Returns the eta.core.models.Model instance for the model with the given name.
delete_model(name)	Deletes the model from local disk, if necessary.

Classes:

HasBrainModel()

Mixin class for Config classes of fiftyone.core.models.Model instances whose models are stored privately by the FiftyOne Brain.

fiftyone.brain.internal.models.list_models()

Returns the list of available models.

Returns:

a list of model names

fiftyone.brain.internal.models.list_downloaded_models()

Returns information about the models that have been downloaded.

Returns:

a dict mapping model names to (model path, eta.core.models.Model) tuples

fiftyone.brain.internal.models.is_model_downloaded(name)

Determines whether the model of the given name is downloaded.

Parameters:

name – the name of the model, which can have @<ver> appended to refer to a specific version of the model. If no version is specified, the latest version of the model is used

Returns:

True/False

fiftyone.brain.internal.models.download_model(name, overwrite=False)

Downloads the model of the given name.

If the model is already downloaded, it is not re-downloaded unless overwrite == True is specified.

Parameters:

• name – the name of the model, which can have @<ver> appended to refer to a specific version of the model. If no version is specified, the latest version of the model is used. Call list_models() to see the available models

• overwrite (False) – whether to overwrite any existing files

Returns:

tuple of

• model: the eta.core.models.Model instance for the model

• model_path: the path to the downloaded model on disk

fiftyone.brain.internal.models.install_model_requirements(name, error_level=0)

Installs any package requirements for the model with the given name.

Parameters:

• name – the name of the model, which can have @<ver> appended to refer to a specific version of the model. If no version is specified, the latest version of the model is used. Call list_models() to see the available models

• error_level –

  the error level to use, defined as:

  0: raise error if a requirement install fails 1: log warning if a requirement install fails 2: ignore install fails

fiftyone.brain.internal.models.ensure_model_requirements(name, error_level=0)

Ensures that the package requirements for the model with the given name are satisfied.

Parameters:

• name – the name of the model, which can have @<ver> appended to refer to a specific version of the model. If no version is specified, the latest version of the model is used. Call list_models() to see the available models

• error_level –

  the error level to use, defined as:

  0: raise error if a requirement is not satisfied 1: log warning if a requirement is not satisifed 2: ignore unsatisifed requirements

fiftyone.brain.internal.models.load_model(name, download_if_necessary=True, install_requirements=False, error_level=0, **kwargs)

Loads the model of the given name.

By default, the model will be downloaded if necessary.

Parameters:

• name – the name of the model, which can have @<ver> appended to refer to a specific version of the model. If no version is specified, the latest version of the model is used. Call list_models() to see the available models

• download_if_necessary (True) – whether to download the model if it is not found in the specified directory

• install_requirements – whether to install any requirements before loading the model. By default, this is False

• error_level –

  the error level to use, defined as:

  0: raise error if a requirement is not satisfied 1: log warning if a requirement is not satisifed 2: ignore unsatisifed requirements

• **kwargs – keyword arguments to inject into the model’s Config instance

Returns:

a fiftyone.core.models.Model

fiftyone.brain.internal.models.find_model(name)

Returns the path to the model on disk.

The model must be downloaded. Use download_model() to download models.

Parameters:

name – the name of the model, which can have @<ver> appended to refer to a specific version of the model. If no version is specified, the latest version of the model is used

Returns:

the path to the model on disk

Raises:

ValueError – if the model does not exist or has not been downloaded

fiftyone.brain.internal.models.get_model(name)

Returns the eta.core.models.Model instance for the model with the given name.

Parameters:

name – the name of the model

Returnsn eta.core.models.ModelZooModel

fiftyone.brain.internal.models.delete_model(name)

Deletes the model from local disk, if necessary.

Parameters:

name – the name of the model, which can have @<ver> appended to refer to a specific version of the model. If no version is specified, the latest version of the model is used

class fiftyone.brain.internal.models.HasBrainModel

Bases: HasPublishedModel

Mixin class for Config classes of fiftyone.core.models.Model instances whose models are stored privately by the FiftyOne Brain.

Methods:

download_model_if_necessary()	Downloads the published model specified by the config, if necessary.
init(d)	Initializes the published model config.

download_model_if_necessary()

Downloads the published model specified by the config, if necessary.

After this method is called, the model_path attribute will always contain the path to the model on disk.

init(d)

Initializes the published model config.

This method should be called by ModelConfig.__init__(), and it performs the following tasks:

• Parses the model_name and model_path parameters

• Populates any default parameters in the provided ModelConfig dict

Parameters:

d – a ModelConfig dict

Returns:

a ModelConfig dict with any default parameters populated