1use std::fs::File;
2use std::io::BufWriter;
3use std::path::{Path, PathBuf};
4
5use anyhow::Context;
6use indicatif::{ProgressBar, ProgressStyle};
7use safetensors::Dtype as StDtype;
8use safetensors::SafeTensors;
9
10use zsfm_gguf::{GGMLType, GGUFMetaValue, GGUFWriter};
11
12use crate::config::TabDptConfig;
13use crate::tensor_map::map_tensor_name;
14
15pub struct ConvertOptions {
16 pub output_dtype: GGMLType,
17}
18
19pub fn convert(
20 shard_paths: &[PathBuf],
21 config: &TabDptConfig,
22 opts: &ConvertOptions,
23 output_path: &Path,
24) -> anyhow::Result<()> {
25 let mut writer = GGUFWriter::new();
26 write_metadata(&mut writer, config);
27
28 let shard_bytes: Vec<Vec<u8>> = shard_paths
29 .iter()
30 .map(|p| std::fs::read(p).with_context(|| format!("read {}", p.display())))
31 .collect::<anyhow::Result<_>>()?;
32 let shard_views: Vec<SafeTensors> = shard_bytes
33 .iter()
34 .map(|b| SafeTensors::deserialize(b).context("deserialize shard"))
35 .collect::<anyhow::Result<_>>()?;
36
37 let total: usize = shard_views.iter().map(|s| s.len()).sum();
38 let pb = ProgressBar::new(total as u64);
39 pb.set_style(
40 ProgressStyle::with_template(
41 "{spinner:.green} [{elapsed_precise}] [{bar:40.cyan/blue}] {pos}/{len} {msg}",
42 )
43 .unwrap()
44 .progress_chars("=>-"),
45 );
46
47 let mut mapped = 0usize;
48 let mut skipped: Vec<String> = Vec::new();
49 let mut fallback_count = 0usize;
50
51 for shard in &shard_views {
52 for (hf_name, tensor_view) in shard.tensors() {
53 pb.set_message(hf_name.to_string());
54
55 let gguf_name = match map_tensor_name(&hf_name) {
56 Some(n) => n,
57 None => {
58 skipped.push(hf_name.to_string());
59 pb.inc(1);
60 continue;
61 }
62 };
63
64 let src_dtype = ggml_type_from_st(tensor_view.dtype())
65 .with_context(|| format!("tensor {hf_name}: unsupported dtype {:?}", tensor_view.dtype()))?;
66
67 let raw_data = tensor_view.data();
68 let py_shape = tensor_view.shape();
69 let n_elems: usize = py_shape.iter().product();
70 let innermost = py_shape.last().copied().unwrap_or(1);
71
72 let (dst_dtype, gguf_shape, tensor_data) =
73 if opts.output_dtype == GGMLType::Q8_0 && (innermost % 32 != 0 || n_elems % 32 != 0) {
74 fallback_count += 1;
75 let data = cast_data(raw_data, src_dtype, GGMLType::F32)
76 .with_context(|| format!("tensor {hf_name}: cast failed"))?;
77 let gs = py_shape.iter().rev().map(|&d| d as u64).collect();
78 (GGMLType::F32, gs, data)
79 } else {
80 let dst = opts.output_dtype;
81 let data = cast_data(raw_data, src_dtype, dst)
82 .with_context(|| format!("tensor {hf_name}: cast failed"))?;
83 let gs = py_shape.iter().rev().map(|&d| d as u64).collect();
84 (dst, gs, data)
85 };
86
87 writer.add_tensor(gguf_name, gguf_shape, dst_dtype, tensor_data);
88 mapped += 1;
89 pb.inc(1);
90 }
91 }
92
93 pb.finish_with_message("tensors processed");
94
95 if !skipped.is_empty() {
96 eprintln!("\nNote: {} tensor(s) skipped (scalar attention-scaling buffers, recomputed from config):", skipped.len());
97 for name in &skipped {
98 eprintln!(" {name}");
99 }
100 }
101 if fallback_count > 0 {
102 eprintln!("\nNote: {fallback_count} tensor(s) fell back to F32.");
103 }
104
105 println!("Writing {mapped} tensors to {} …", output_path.display());
106 let out_file = File::create(output_path).with_context(|| format!("create {}", output_path.display()))?;
107 let mut buf_writer = BufWriter::new(out_file);
108 writer.write_to(&mut buf_writer)?;
109 println!("Done.");
110 Ok(())
111}
112
113fn write_metadata(writer: &mut GGUFWriter, config: &TabDptConfig) {
114 writer.add_metadata("general.architecture", GGUFMetaValue::String("tabdpt".into()));
115 writer.add_metadata("general.name", GGUFMetaValue::String("Layer6/TabDPT".into()));
116 writer.add_metadata("tabdpt.dim", GGUFMetaValue::Uint32(config.dim as u32));
117 writer.add_metadata("tabdpt.n_layers", GGUFMetaValue::Uint32(config.n_layers as u32));
118 writer.add_metadata("tabdpt.n_heads", GGUFMetaValue::Uint32(config.n_heads as u32));
119 writer.add_metadata("tabdpt.ff_dim", GGUFMetaValue::Uint32(config.ff_dim as u32));
120 writer.add_metadata("tabdpt.y_encoder_dim", GGUFMetaValue::Uint32(config.y_encoder_dim as u32));
121 writer.add_metadata("tabdpt.max_num_classes", GGUFMetaValue::Uint32(config.max_num_classes as u32));
122 writer.add_metadata("tabdpt.regression_bin_count", GGUFMetaValue::Uint32(config.regression_bin_count as u32));
123 writer.add_metadata("tabdpt.regression_bin_min", GGUFMetaValue::Float32(config.regression_bin_min));
124 writer.add_metadata("tabdpt.regression_bin_max", GGUFMetaValue::Float32(config.regression_bin_max));
125 writer.add_metadata("tabdpt.max_num_features", GGUFMetaValue::Uint32(config.max_num_features as u32));
126 writer.add_metadata("tabdpt.base_len", GGUFMetaValue::Uint32(config.base_len as u32));
127 writer.add_metadata("tabdpt.max_len", GGUFMetaValue::Uint32(config.max_len as u32));
128 writer.add_metadata("tabdpt.n_thinking_rows", GGUFMetaValue::Uint32(config.n_thinking_rows as u32));
129}
130
131fn ggml_type_from_st(dtype: StDtype) -> anyhow::Result<GGMLType> {
132 match dtype {
133 StDtype::F32 => Ok(GGMLType::F32),
134 StDtype::F16 => Ok(GGMLType::F16),
135 StDtype::BF16 => Ok(GGMLType::BF16),
136 other => anyhow::bail!("unsupported safetensors dtype: {other:?}"),
137 }
138}
139
140fn cast_data(data: &[u8], src: GGMLType, dst: GGMLType) -> anyhow::Result<Vec<u8>> {
141 if src == dst {
142 return Ok(data.to_vec());
143 }
144 if dst == GGMLType::Q8_0 {
145 let f32_values = decode_to_f32(data, src)?;
146 return quantize_q8_0(&f32_values);
147 }
148 match (src, dst) {
149 (GGMLType::F32, GGMLType::F16) => {
150 let vals = parse_f32_le(data)?;
151 let mut out = Vec::with_capacity(vals.len() * 2);
152 for v in vals {
153 out.extend_from_slice(&f32_to_f16_bits(v).to_le_bytes());
154 }
155 Ok(out)
156 }
157 (GGMLType::F32, GGMLType::BF16) => {
158 let vals = parse_f32_le(data)?;
159 let mut out = Vec::with_capacity(vals.len() * 2);
160 for v in vals {
161 out.extend_from_slice(&((v.to_bits() >> 16) as u16).to_le_bytes());
162 }
163 Ok(out)
164 }
165 (GGMLType::F16, GGMLType::BF16) => {
166 let mut out = Vec::with_capacity(data.len());
167 for c in data.chunks_exact(2) {
168 let f32_val = f16_to_f32(u16::from_le_bytes([c[0], c[1]]));
169 out.extend_from_slice(&((f32_val.to_bits() >> 16) as u16).to_le_bytes());
170 }
171 Ok(out)
172 }
173 (GGMLType::BF16, GGMLType::F32) => {
174 let mut out = Vec::with_capacity(data.len() * 2);
175 for c in data.chunks_exact(2) {
176 let bits = (u16::from_le_bytes([c[0], c[1]]) as u32) << 16;
177 out.extend_from_slice(&bits.to_le_bytes());
178 }
179 Ok(out)
180 }
181 (GGMLType::BF16, GGMLType::F16) => {
182 let mut out = Vec::with_capacity(data.len());
183 for c in data.chunks_exact(2) {
184 let bits = (u16::from_le_bytes([c[0], c[1]]) as u32) << 16;
185 out.extend_from_slice(&f32_to_f16_bits(f32::from_bits(bits)).to_le_bytes());
186 }
187 Ok(out)
188 }
189 (GGMLType::F16, GGMLType::F32) => {
190 let mut out = Vec::with_capacity(data.len() * 2);
191 for c in data.chunks_exact(2) {
192 out.extend_from_slice(&f16_to_f32(u16::from_le_bytes([c[0], c[1]])).to_bits().to_le_bytes());
193 }
194 Ok(out)
195 }
196 _ => anyhow::bail!("unsupported cast: {src:?} → {dst:?}"),
197 }
198}
199
200fn decode_to_f32(data: &[u8], src: GGMLType) -> anyhow::Result<Vec<f32>> {
201 match src {
202 GGMLType::F32 => parse_f32_le(data),
203 GGMLType::F16 => data
204 .chunks_exact(2)
205 .map(|c| Ok(f16_to_f32(u16::from_le_bytes([c[0], c[1]]))))
206 .collect(),
207 GGMLType::BF16 => data
208 .chunks_exact(2)
209 .map(|c| Ok(f32::from_bits((u16::from_le_bytes([c[0], c[1]]) as u32) << 16)))
210 .collect(),
211 GGMLType::Q8_0 => anyhow::bail!("Q8_0 as source not supported"),
212 }
213}
214
215fn quantize_q8_0(values: &[f32]) -> anyhow::Result<Vec<u8>> {
216 const BLOCK: usize = 32;
217 if values.len() % BLOCK != 0 {
218 anyhow::bail!("Q8_0 requires count divisible by {BLOCK}");
219 }
220 let n_blocks = values.len() / BLOCK;
221 let mut out = vec![0u8; n_blocks * 34];
222 for b in 0..n_blocks {
223 let blk = &values[b * BLOCK..(b + 1) * BLOCK];
224 let amax = blk.iter().copied().map(f32::abs).fold(0.0f32, f32::max);
225 let d = if amax == 0.0 { 0.0f32 } else { amax / 127.0 };
226 let d_inv = if d == 0.0 { 0.0f32 } else { 1.0 / d };
227 let base = b * 34;
228 out[base..base + 2].copy_from_slice(&f32_to_f16_bits(d).to_le_bytes());
229 for i in 0..BLOCK {
230 out[base + 2 + i] = (blk[i] * d_inv).round().clamp(-127.0, 127.0) as i8 as u8;
231 }
232 }
233 Ok(out)
234}
235
236fn parse_f32_le(data: &[u8]) -> anyhow::Result<Vec<f32>> {
237 if data.len() % 4 != 0 {
238 anyhow::bail!("f32 data length not divisible by 4");
239 }
240 Ok(data.chunks_exact(4).map(|c| f32::from_le_bytes([c[0], c[1], c[2], c[3]])).collect())
241}
242
243fn f32_to_f16_bits(v: f32) -> u16 {
244 let bits = v.to_bits();
245 let sign = ((bits >> 16) & 0x8000) as u16;
246 let exp = ((bits >> 23) & 0xFF) as i32;
247 let mantissa = bits & 0x007F_FFFF;
248 if exp == 0xFF {
249 return sign | 0x7C00 | if mantissa != 0 { 0x0200 } else { 0 };
250 }
251 let new_exp = exp - 127 + 15;
252 if new_exp >= 31 {
253 return sign | 0x7C00;
254 }
255 if new_exp <= 0 {
256 if new_exp < -10 {
257 return sign;
258 }
259 let m = (mantissa | 0x0080_0000) >> (1 - new_exp);
260 return sign | (m >> 13) as u16;
261 }
262 sign | ((new_exp as u16) << 10) | (mantissa >> 13) as u16
263}
264
265fn f16_to_f32(bits: u16) -> f32 {
266 let sign = ((bits & 0x8000) as u32) << 16;
267 let exp = ((bits >> 10) & 0x1F) as i32;
268 let mantissa = (bits & 0x03FF) as u32;
269 let f32_bits = if exp == 0 {
270 if mantissa == 0 {
271 sign
272 } else {
273 let mut m = mantissa;
274 let mut e = 0i32;
275 while m & 0x0400 == 0 {
276 m <<= 1;
277 e += 1;
278 }
279 sign | ((127 - 15 - e + 1) as u32) << 23 | (m & 0x03FF) << 13
280 }
281 } else if exp == 31 {
282 sign | 0x7F80_0000 | (mantissa << 13)
283 } else {
284 sign | ((exp + 127 - 15) as u32) << 23 | (mantissa << 13)
285 };
286 f32::from_bits(f32_bits)
287}