makarna/pkg/backend/cpu/ops/repeat.go

package ops

import (
	"makarna/pkg/backend/cpu"
	"makarna/pkg/tensor"
)

// Repeat repeats tensor n times along dimension dim
func Repeat(t *cpu.Tensor, dim, n int) *cpu.Tensor {
	shape := t.Shape()
	data := t.DataFloat32()
	
	newShape := make(tensor.Shape, len(shape))
	copy(newShape, shape)
	newShape[dim] *= n
	
	// Simple case: repeat along first dimension
	if dim == 0 {
		newData := make([]float32, 0, newShape.NumElements())
		for i := 0; i < n; i++ {
			newData = append(newData, data...)
		}
		return cpu.NewTensor(newShape, newData)
	}
	
	// Simple case: repeat along last dimension
	if dim == len(shape)-1 {
		newData := make([]float32, newShape.NumElements())
		rowSize := shape[dim]
		newRowSize := newShape[dim]
		numRows := len(data) / rowSize
		
		for row := 0; row < numRows; row++ {
			srcStart := row * rowSize
			dstStart := row * newRowSize
			for rep := 0; rep < n; rep++ {
				copy(newData[dstStart+rep*rowSize:], data[srcStart:srcStart+rowSize])
			}
		}
		return cpu.NewTensor(newShape, newData)
	}
	
	// General case: repeat along middle dimension
	// Calculate outer (before dim), inner (after dim) sizes
	outerSize := 1
	for i := 0; i < dim; i++ {
		outerSize *= shape[i]
	}
	innerSize := 1
	for i := dim + 1; i < len(shape); i++ {
		innerSize *= shape[i]
	}
	dimSize := shape[dim]
	sliceSize := dimSize * innerSize
	
	newData := make([]float32, newShape.NumElements())
	dstIdx := 0
	
	for outer := 0; outer < outerSize; outer++ {
		srcStart := outer * sliceSize
		srcSlice := data[srcStart : srcStart+sliceSize]
		for rep := 0; rep < n; rep++ {
			copy(newData[dstIdx:], srcSlice)
			dstIdx += sliceSize
		}
	}
	
	return cpu.NewTensor(newShape, newData)
}

// RepeatInterleave repeats each element n times along dimension
func RepeatInterleave(t *cpu.Tensor, dim, n int) *cpu.Tensor {
	shape := t.Shape()
	data := t.DataFloat32()
	
	newShape := make(tensor.Shape, len(shape))
	copy(newShape, shape)
	newShape[dim] *= n
	
	// Handle 2D case with dim=0
	if len(shape) == 2 && dim == 0 {
		newData := make([]float32, newShape.NumElements())
		rowSize := shape[1]
		for row := 0; row < shape[0]; row++ {
			srcRow := data[row*rowSize : (row+1)*rowSize]
			for rep := 0; rep < n; rep++ {
				dstStart := (row*n + rep) * rowSize
				copy(newData[dstStart:], srcRow)
			}
		}
		return cpu.NewTensor(newShape, newData)
	}
	
	return nil
}