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[Refactor] Deprecate TensorV2 and replace Tensor class with TensorV2
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This commit deprecates the existing TensorV2 class and replaces Tensor class with the new TensorV2 class.
The previous Tensor class has been removed and all its usages have been updated to use the TensorV2 class.
Additionally, all instances of TensorV2 usage within the NNTrainer have been removed.

**Self-evaluation:**
1. Build test: [X]Passed [ ]Failed [ ]Skipped
2. Run test:   [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Donghyeon Jeong <[email protected]>
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@djeong20
djeong20 committed Mar 15, 2024
1 parent 6be8e84 commit c129345
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Showing 61 changed files with 3,232 additions and 11,883 deletions.
4 changes: 2 additions & 2 deletions Applications/LLaMA/jni/rms_norm.h
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Original file line number Diff line number Diff line change
Expand Up @@ -38,8 +38,8 @@ class RMS_NORM_GAMMA_INIT final
/**
* @brief Construct a RMS_NORM_GAMMA_INIT object
*/
RMS_NORM_GAMMA_INIT(nntrainer::Tensor::Initializer value =
nntrainer::Tensor::Initializer::ONES) {
RMS_NORM_GAMMA_INIT(
nntrainer::Initializer value = nntrainer::Initializer::ONES) {
set(value);
};

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75 changes: 35 additions & 40 deletions Applications/YOLO/jni/yolo_v2_loss.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -319,141 +319,136 @@ void YoloV2LossLayer::finalize(nntrainer::InitLayerContext &context) {
nntrainer::TensorDim bbox_x_pred_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_x_pred] = context.requestTensor(
bbox_x_pred_dim, "bbox_x_pred", nntrainer::Tensor::Initializer::NONE, true,
bbox_x_pred_dim, "bbox_x_pred", nntrainer::Initializer::NONE, true,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_y_pred_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_y_pred] = context.requestTensor(
bbox_y_pred_dim, "bbox_y_pred", nntrainer::Tensor::Initializer::NONE, true,
bbox_y_pred_dim, "bbox_y_pred", nntrainer::Initializer::NONE, true,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_w_pred_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_w_pred] = context.requestTensor(
bbox_w_pred_dim, "bbox_w_pred", nntrainer::Tensor::Initializer::NONE, true,
bbox_w_pred_dim, "bbox_w_pred", nntrainer::Initializer::NONE, true,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_h_pred_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_h_pred] = context.requestTensor(
bbox_h_pred_dim, "bbox_h_pred", nntrainer::Tensor::Initializer::NONE, true,
bbox_h_pred_dim, "bbox_h_pred", nntrainer::Initializer::NONE, true,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim confidence_pred_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::confidence_pred] =
context.requestTensor(confidence_pred_dim, "confidence_pred",
nntrainer::Tensor::Initializer::NONE, true,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
wt_idx[YoloV2LossParams::confidence_pred] = context.requestTensor(
confidence_pred_dim, "confidence_pred", nntrainer::Initializer::NONE, true,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim class_pred_dim(batch_size,
grid_height_number * grid_width_number,
NUM_ANCHOR, class_number);
wt_idx[YoloV2LossParams::class_pred] = context.requestTensor(
class_pred_dim, "class_pred", nntrainer::Tensor::Initializer::NONE, true,
class_pred_dim, "class_pred", nntrainer::Initializer::NONE, true,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_w_pred_anchor_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_w_pred_anchor] =
context.requestTensor(bbox_w_pred_anchor_dim, "bbox_w_pred_anchor",
nntrainer::Tensor::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
wt_idx[YoloV2LossParams::bbox_w_pred_anchor] = context.requestTensor(
bbox_w_pred_anchor_dim, "bbox_w_pred_anchor", nntrainer::Initializer::NONE,
false, nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_h_pred_anchor_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_h_pred_anchor] =
context.requestTensor(bbox_h_pred_anchor_dim, "bbox_h_pred_anchor",
nntrainer::Tensor::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
wt_idx[YoloV2LossParams::bbox_h_pred_anchor] = context.requestTensor(
bbox_h_pred_anchor_dim, "bbox_h_pred_anchor", nntrainer::Initializer::NONE,
false, nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_x_gt_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_x_gt] = context.requestTensor(
bbox_x_gt_dim, "bbox_x_gt", nntrainer::Tensor::Initializer::NONE, false,
bbox_x_gt_dim, "bbox_x_gt", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_y_gt_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_y_gt] = context.requestTensor(
bbox_y_gt_dim, "bbox_y_gt", nntrainer::Tensor::Initializer::NONE, false,
bbox_y_gt_dim, "bbox_y_gt", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_w_gt_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_w_gt] = context.requestTensor(
bbox_w_gt_dim, "bbox_w_gt", nntrainer::Tensor::Initializer::NONE, false,
bbox_w_gt_dim, "bbox_w_gt", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_h_gt_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_h_gt] = context.requestTensor(
bbox_h_gt_dim, "bbox_h_gt", nntrainer::Tensor::Initializer::NONE, false,
bbox_h_gt_dim, "bbox_h_gt", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim confidence_gt_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::confidence_gt] = context.requestTensor(
confidence_gt_dim, "confidence_gt", nntrainer::Tensor::Initializer::NONE,
false, nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
confidence_gt_dim, "confidence_gt", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim class_gt_dim(batch_size,
grid_height_number * grid_width_number,
NUM_ANCHOR, class_number);
wt_idx[YoloV2LossParams::class_gt] = context.requestTensor(
class_gt_dim, "class_gt", nntrainer::Tensor::Initializer::NONE, false,
class_gt_dim, "class_gt", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox_class_mask_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox_class_mask] =
context.requestTensor(bbox_class_mask_dim, "bbox_class_mask",
nntrainer::Tensor::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
wt_idx[YoloV2LossParams::bbox_class_mask] = context.requestTensor(
bbox_class_mask_dim, "bbox_class_mask", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim iou_mask_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::iou_mask] = context.requestTensor(
iou_mask_dim, "iou_mask", nntrainer::Tensor::Initializer::NONE, false,
iou_mask_dim, "iou_mask", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox1_width_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox1_width] = context.requestTensor(
bbox1_width_dim, "bbox1_width", nntrainer::Tensor::Initializer::NONE, false,
bbox1_width_dim, "bbox1_width", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim bbox1_height_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::bbox1_height] = context.requestTensor(
bbox1_height_dim, "bbox1_height", nntrainer::Tensor::Initializer::NONE,
false, nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
bbox1_height_dim, "bbox1_height", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim is_xy_min_max_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 4);
wt_idx[YoloV2LossParams::is_xy_min_max] = context.requestTensor(
is_xy_min_max_dim, "is_xy_min_max", nntrainer::Tensor::Initializer::NONE,
false, nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
is_xy_min_max_dim, "is_xy_min_max", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim intersection_width_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::intersection_width] =
context.requestTensor(intersection_width_dim, "intersection_width",
nntrainer::Tensor::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
wt_idx[YoloV2LossParams::intersection_width] = context.requestTensor(
intersection_width_dim, "intersection_width", nntrainer::Initializer::NONE,
false, nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim intersection_height_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::intersection_height] =
context.requestTensor(intersection_height_dim, "intersection_height",
nntrainer::Tensor::Initializer::NONE, false,
nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);

nntrainer::TensorDim unions_dim(
batch_size, grid_height_number * grid_width_number, NUM_ANCHOR, 1);
wt_idx[YoloV2LossParams::unions] = context.requestTensor(
unions_dim, "unions", nntrainer::Tensor::Initializer::NONE, false,
unions_dim, "unions", nntrainer::Initializer::NONE, false,
nntrainer::TensorLifespan::FORWARD_DERIV_LIFESPAN);
}

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