add deepseek-ocr2 support
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+14
-7
@@ -9,7 +9,7 @@
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// use aha_openai_dive::v1::resources::chat::ChatCompletionParameters;
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use anyhow::Result;
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// use byteorder::{LittleEndian, ReadBytesExt};
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use candle_core::Tensor;
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// use candle_core::Tensor;
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use modelscope::{DownloadOptions, ModelScope};
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// use sentencepiece::SentencePieceProcessor;
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// use zip::ZipArchive;
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@@ -35,12 +35,19 @@ async fn download_test() -> Result<()> {
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#[test]
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fn messy_test() -> Result<()> {
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// RUST_BACKTRACE=1 cargo test -F cuda --test messy_test messy_test -r -- --nocapture
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let device = &candle_core::Device::Cpu;
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let t1 = Tensor::randn(0.0, 1.0, (16, 9, 64, 128), device)?;
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let t2 = Tensor::randn(0.0, 1.0, (16, 9, 128, 64), device)?;
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let out = t1.matmul(&t2)?;
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println!("out shape: {:?}", out);
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let save_dir =
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aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
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let model_path = format!("{}/deepseek-ai/DeepSeek-OCR-2/", save_dir);
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let stem = std::path::Path::new(&model_path)
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.file_stem() // 获取文件名主干(不含扩展名)
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.and_then(|s| s.to_str())
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.unwrap_or("qwen3.5");
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println!("stem: {:?}", stem);
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// let device = &candle_core::Device::Cpu;
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// let t1 = Tensor::randn(0.0, 1.0, (16, 9, 64, 128), device)?;
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// let t2 = Tensor::randn(0.0, 1.0, (16, 9, 128, 64), device)?;
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// let out = t1.matmul(&t2)?;
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// println!("out shape: {:?}", out);
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// let input = Tensor::arange(0.0f32, 25.0f32, device)?.reshape((5, 5))?;
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// println!("input: {}", input);
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