You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: literal_cost.go
    path of file: ./repos/scan4all/vendor/github.com/andybalholm/brotli
    
    the code of the file until where you have to start completion: package brotli

func utf8Position(last uint, c uint, clamp uint) uint {
	if c < 128 {
		return 0 /* Next one is the 'Byte 1' again. */
	} else if c >= 192 { /* Next one is the 'Byte 2' of utf-8 encoding. */
		return brotli_min_size_t(1, clamp)
	} else {
		/* Let's decide over the last byte if this ends the sequence. */
		if last < 0xE0 {
			return 0 /* Completed two or 
    
func estimateBitCostsForLiteralsUTF8(pos uint, len uint, mask uint, data []byte, cost []float32) {
	var max_utf8 uint = decideMultiByteStatsLevel(pos, uint(len), mask, data)
	/* Bootstrap histograms. */
	var histogram = [3][256]uint{[256]uint{0}}
	var window_half uint = 495
	var in_window uint = brotli_min_size_t(window_half, uint(len))
	var in_window_utf8 = [3]uint{0}
	/* max_utf8 is 0 (normal ASCII single byte modeling),
	   1 (for 2-byte UTF-8 modeling), or 2 (for 3-byte UTF-8 modeling). */

	var i uint
	{
		var last_c uint = 0
		var utf8_pos uint = 0
		for i = 0; i < in_window; i++ {
			var c uint = uint(data[(pos+i)&mask])
			histogram[utf8_pos][c]++
			in_window_utf8[utf8_pos]++
			utf8_pos = utf8Position(last_c, c, max_utf8)
			last_c = c
		}
	}

	/* Compute bit costs with sliding window. */
	for i = 0; i < len; i++ {
		if i >= window_half {
			var c uint
			var last_c uint
			if i < window_half+1 {
				c = 0
			} else {
				c = uint(data[(pos+i-window_half-1)&mask])
			}
			if i < window_half+2 {
				last_c = 0
			} else {
				last_c = uint(data[(pos+i-window_half-2)&mask])
			}
			/* Remove a byte in the past. */

			var utf8_pos2 uint = utf8Position(last_c, c, max_utf8)
			histogram[utf8_pos2][data[(pos+i-window_half)&mask]]--
			in_window_utf8[utf8_pos2]--
		}

		if i+window_half < len {
			var c uint = uint(data[(pos+i+window_half-1)&mask])
			var last_c uint = uint(data[(pos+i+window_half-2)&mask])
			/* Add a byte in the future. */

			var utf8_pos2 uint = utf8Position(last_c, c, max_utf8)
			histogram[utf8_pos2][data[(pos+i+window_half)&mask]]++
			in_window_utf8[utf8_pos2]++
		}
		{
			var c uint
			var last_c uint
			if i < 1 {
				c = 0
			} else {
				c = uint(data[(pos+i-1)&mask])
			}
			if i < 2 {
				last_c = 0
			} else {
				last_c = uint(data[(pos+i-2)&mask])
			}
			var utf8_pos uint = utf8Position(last_c, c, max_utf8)
			var masked_pos uint = (pos + i) & mask
			var histo uint = histogram[utf8_pos][data[masked_pos]]
			var lit_cost float64
			if histo == 0 {
				histo = 1
			}

			lit_cost = fastLog2(in_window_utf8[utf8_pos]) - fastLog2(histo)
			lit_cost += 0.02905
			if lit_cost < 1.0 {
				lit_cost *= 0.5
				lit_cost += 0.5
			}

			/* Make the first bytes more expensive -- seems to help, not sure why.
			   Perhaps because the entropy source is changing its properties
			   rapidly in the beginning of the file, perhaps because the beginning
			   of the data is a statistical "anomaly". */
			if i < 2000 {
				lit_cost += 0.7 - (float64(2000-i) / 2000.0 * 0.35)
			}

			cost[i] = float32(lit_cost)
		}
	}
}