DPT¶
The DPT (Dense Prediction Transformer) is a vision model for dense prediction tasks like depth estimation. It combines Vision Transformer (ViT) features with a specialized decoder for accurate pixel-level predictions. RBLN NPUs can accelerate DPT model inference using Optimum RBLN.
Key Classes¶
RBLNDPTForDepthEstimation
: The main model class for running DPT for depth estimation on RBLN NPURBLNDPTForDepthEstimationConfig
: Configuration class specifically for DPT depth estimation models
API Reference¶
Classes¶
RBLNDPTForDepthEstimation
¶
Bases: RBLNModelForDepthEstimation
DPT (Dense Prediction Transformer) model optimized for depth estimation on RBLN NPUs.
Functions¶
from_pretrained(model_id, export=False, rbln_config=None, **kwargs)
classmethod
¶
The from_pretrained()
function is utilized in its standard form as in the HuggingFace transformers library.
User can use this function to load a pre-trained model from the HuggingFace library and convert it to a RBLN model to be run on RBLN NPUs.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model_id
|
Union[str, Path]
|
The model id of the pre-trained model to be loaded. It can be downloaded from the HuggingFace model hub or a local path, or a model id of a compiled model using the RBLN Compiler. |
required |
export
|
bool
|
A boolean flag to indicate whether the model should be compiled. |
False
|
rbln_config
|
Optional[Union[Dict, RBLNModelConfig]]
|
Configuration for RBLN model compilation and runtime. This can be provided as a dictionary or an instance of the model's configuration class (e.g., |
None
|
kwargs
|
Dict[str, Any]
|
Additional keyword arguments. Arguments with the prefix 'rbln_' are passed to rbln_config, while the remaining arguments are passed to the HuggingFace library. |
{}
|
Returns:
Type | Description |
---|---|
Self
|
A RBLN model instance ready for inference on RBLN NPU devices. |
from_model(model, *, rbln_config=None, **kwargs)
classmethod
¶
Converts and compiles a pre-trained HuggingFace library model into a RBLN model. This method performs the actual model conversion and compilation process.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model
|
PreTrainedModel
|
The PyTorch model to be compiled. The object must be an instance of the HuggingFace transformers PreTrainedModel class. |
required |
rbln_config
|
Optional[Union[Dict, RBLNModelConfig]]
|
Configuration for RBLN model compilation and runtime. This can be provided as a dictionary or an instance of the model's configuration class (e.g., |
None
|
kwargs
|
Dict[str, Any]
|
Additional keyword arguments. Arguments with the prefix 'rbln_' are passed to rbln_config, while the remaining arguments are passed to the HuggingFace library. |
{}
|
The method performs the following steps:
- Compiles the PyTorch model into an optimized RBLN graph
- Configures the model for the specified NPU device
- Creates the necessary runtime objects if requested
- Saves the compiled model and configurations
Returns:
Type | Description |
---|---|
Self
|
A RBLN model instance ready for inference on RBLN NPU devices. |
save_pretrained(save_directory)
¶
Saves a model and its configuration file to a directory, so that it can be re-loaded using the
[from_pretrained
] class method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
save_directory
|
Union[str, PathLike]
|
The directory to save the model and its configuration files. Will be created if it doesn't exist. |
required |
Classes¶
RBLNDPTForDepthEstimationConfig
¶
Bases: RBLNModelForDepthEstimationConfig
Configuration class for RBLNDPTForDepthEstimation models.
This class an alias of RBLNModelForDepthEstimationConfig.
Functions¶
__init__(image_size=None, batch_size=None, **kwargs)
¶
Base configuration class for image models running on RBLN NPUs.
This class extends the RBLNModelConfig to include parameters specific to image models, such as image dimensions and batch sizes for inference.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
image_size
|
Optional[Union[int, Tuple[int, int]]]
|
The size of input images. Can be an integer for square images or a tuple (height, width). |
None
|
batch_size
|
Optional[int]
|
The batch size for inference. Defaults to 1. |
None
|
**kwargs
|
Dict[str, Any]
|
Additional arguments passed to the parent RBLNModelConfig. |
{}
|
Raises:
Type | Description |
---|---|
ValueError
|
If batch_size is not a positive integer. |