super_gradients.common.data_types package
Subpackages
Module contents
- class super_gradients.common.data_types.StrictLoad(value)[source]
Bases:
enum.Enum
- Wrapper for adding more functionality to torch’s strict_load parameter in load_state_dict().
- Attributes:
OFF - Native torch “strict_load = off” behaviour. See nn.Module.load_state_dict() documentation for more details. ON - Native torch “strict_load = on” behaviour. See nn.Module.load_state_dict() documentation for more details. NO_KEY_MATCHING - Allows the usage of SuperGradient’s adapt_checkpoint function, which loads a checkpoint by matching each
layer’s shapes (and bypasses the strict matching of the names of each layer (ie: disregards the state_dict key matching)).
- OFF = False
- ON = True
- NO_KEY_MATCHING = 'no_key_matching'
- class super_gradients.common.data_types.DeepLearningTask(value)[source]
Bases:
str
,enum.Enum
An enumeration.
- CLASSIFICATION = 'classification'
- SEMANTIC_SEGMENTATION = 'semantic_segmentation'
- OBJECT_DETECTION = 'object_detection'
- DEPTH_ESTIMATION = 'depth_estimation'
- POSE_ESTIMATION = 'pose_estimation'
- NLP = 'nlp'
- OTHER = 'other'
- class super_gradients.common.data_types.EvaluationType(value)[source]
Bases:
str
,enum.Enum
Passed to SgModel.evaluate(..), and controls which phase callbacks should be triggered (if at all).
- Attributes:
TEST VALIDATION
- TEST = 'TEST'
- VALIDATION = 'VALIDATION'
- class super_gradients.common.data_types.MultiGPUMode(value)[source]
Bases:
str
,enum.Enum
- OFF - Single GPU Mode / CPU Mode
- DATA_PARALLEL - Multiple GPUs, Synchronous
- DISTRIBUTED_DATA_PARALLEL - Multiple GPUs, Asynchronous
- OFF = 'Off'
- DATA_PARALLEL = 'DP'
- DISTRIBUTED_DATA_PARALLEL = 'DDP'
- AUTO = 'AUTO'