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hub / github.com/InternRobotics/G2VLM / cuda

Method cuda

data/dataset_base.py:714–744  ·  view source on GitHub ↗
(self, device=None, non_blocking=False)

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712 return self
713
714 def cuda(self, device=None, non_blocking=False):
715 self.packed_text_ids = self.packed_text_ids.to(device, non_blocking=non_blocking)
716 self.packed_text_indexes = self.packed_text_indexes.to(device, non_blocking=non_blocking)
717 self.packed_position_ids = self.packed_position_ids.to(device, non_blocking=non_blocking)
718
719 if not self.use_flex:
720 self.nested_attention_masks = [item.to(device, non_blocking=non_blocking) for item in self.nested_attention_masks]
721
722 if hasattr(self, 'packed_dino_image_tensor_list'):
723 self.packed_dino_token_indexes = self.packed_dino_token_indexes.to(device, non_blocking=non_blocking)
724 self.dino_token_seqlens = self.dino_token_seqlens.to(device, non_blocking=non_blocking)
725
726 self.packed_depths = self.packed_depths.to(device, non_blocking=non_blocking)
727 self.packed_extrinsics = self.packed_extrinsics.to(device, non_blocking=non_blocking)
728 self.packed_intrinsics = self.packed_intrinsics.to(device, non_blocking=non_blocking)
729 self.packed_world_points = self.packed_world_points.to(device, non_blocking=non_blocking)
730 self.packed_point_masks = self.packed_point_masks.to(device, non_blocking=non_blocking)
731 self.packed_dino_image_tensor_list = self.packed_dino_image_tensor_list.to(device, non_blocking=non_blocking)
732
733 if hasattr(self, 'packed_vit_images'):
734 self.packed_vit_images = self.packed_vit_images.to(device, non_blocking=non_blocking)
735 self.packed_image_grid_thw = self.packed_image_grid_thw.to(device, non_blocking=non_blocking)
736 self.packed_vit_token_indexes = self.packed_vit_token_indexes.to(device, non_blocking=non_blocking)
737 self.vit_token_seqlens = self.vit_token_seqlens.to(device, non_blocking=non_blocking)
738
739 if hasattr(self, 'packed_label_ids'):
740 self.packed_label_ids = self.packed_label_ids.to(device, non_blocking=non_blocking)
741 self.ce_loss_indexes = self.ce_loss_indexes.to(device, non_blocking=non_blocking)
742 self.ce_loss_weights = self.ce_loss_weights.to(device, non_blocking=non_blocking)
743
744 return self
745
746 def to_dict(self):
747 data = dict(

Callers 6

load_model_and_tokenizerFunction · 0.45
prepare_segformerMethod · 0.45
depth_evaluationFunction · 0.45
mainFunction · 0.45
mainFunction · 0.45

Calls

no outgoing calls

Tested by

no test coverage detected