tckm.yan/aha
0
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

index tts stash save

Browse Source
This commit is contained in:
jhqxxx
2026-01-30 22:04:23 +08:00
parent 53791efa80
commit e3944588fc
39 changed files with 4613 additions and 137 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/weight_test.rs
+39 -1
View File
@@ -1,6 +1,6 @@
use std::collections::HashMap;
use aha::utils::{find_type_files, get_device};
use aha::utils::{find_type_files, get_device, read_pth_tensor_info_cycle};
use anyhow::Result;
use candle_core::{Device, pickle::read_all_with_key, safetensors};
use candle_nn::VarBuilder;
@@ -197,3 +197,41 @@ fn qwen3_weight() -> Result<()> {
println!("model_list: {:?}", model_list);
Ok(())
}
#[test]
fn index_tts2_weight() -> Result<()> {
let save_dir: String =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/IndexTeam/IndexTTS-2/", save_dir);
let s2mel_path = model_path+ "/s2mel.pth";
// let wac2vec2_path = model_path+ "/wav2vec2bert_stats.pt";
// let model_path = format!("{}/iic/speech_campplus_sv_zh-cn_16k-common/", save_dir);
// let campplus_path = model_path+ "/campplus_cn_common.bin";
// let model_list = find_type_files(&model_path, "safetensors")?;
let model_list = vec![s2mel_path];
// let mut dict_to_hashmap = HashMap::new();
// let mut dtype = candle_core::DType::F32;
for m in model_list {
// let dict = read_all_with_key(m, Some("state_dict"))?;
// let dict = read_all_with_key(m, Some("net"))?;
let dict = read_pth_tensor_info_cycle(m, Some("net.cfm"))?;
// dtype = dict[0].1.dtype();
for (k, v) in dict {
// if k.contains("model") {
// println!("key: {}, tensor shape: {:?}", k, v);
// }
// dict_to_hashmap.insert(k, v);
println!("key: {}, tensor shape: {:?}", k, v);
}
}
// let device = Device::Cpu;
// let semantic_codec_path = save_dir.to_string() + "/amphion/MaskGCT/semantic_codec/model.safetensors" ;
// let model_list = vec![semantic_codec_path];
// for m in model_list {
// let weights = safetensors::load(m, &device)?;
// for (key, tensor) in weights.iter() {
// println!("=== {} === {:?}", key, tensor.shape());
// }
// }
Ok(())
}