Fixing exl2 and other quanize tests again. (#2419)

* Fixing exl2 and other quanize tests again.

* Mark exl2 as non release (so CI tests them, needs to be removed latet).

* Fixing exl2 (by disabling cuda graphs)

* Fix quantization defaults without cuda graphs on exl2 (linked to new
issues with it).

* Removing serde override.

* Go back to released exl2 and remove log.

* Adding warnings for deprecated bitsandbytes + upgrade info to warn.

Dockerfile

@@ -250,6 +250,9 @@ RUN cd server && \
     pip install nvidia-nccl-cu12==2.22.3
 
 ENV LD_PRELOAD=/opt/conda/lib/python3.10/site-packages/nvidia/nccl/lib/libnccl.so.2
+# This is needed because exl2 tries to load flash-attn
+# And fails with our builds.
+ENV EXLLAMA_NO_FLASH_ATTN=1
 
 # Deps before the binaries
 # The binaries change on every build given we burn the SHA into them

integration-tests/models/test_flash_llama_exl2.py

@@ -21,7 +21,6 @@ async def flash_llama_exl2(flash_llama_exl2_handle):
     return flash_llama_exl2_handle.client
 
 
-@pytest.mark.release
 @pytest.mark.asyncio
 @pytest.mark.private
 async def test_flash_llama_exl2(flash_llama_exl2, ignore_logprob_response_snapshot):
@@ -33,7 +32,6 @@ async def test_flash_llama_exl2(flash_llama_exl2, ignore_logprob_response_snapsh
     assert response == ignore_logprob_response_snapshot
 
 
-@pytest.mark.release
 @pytest.mark.asyncio
 @pytest.mark.private
 async def test_flash_llama_exl2_all_params(
@@ -60,7 +58,6 @@ async def test_flash_llama_exl2_all_params(
     assert response == ignore_logprob_response_snapshot
 
 
-@pytest.mark.release
 @pytest.mark.asyncio
 @pytest.mark.private
 async def test_flash_llama_exl2_load(

launcher/src/main.rs

@@ -30,11 +30,18 @@ struct RawConfig {
     n_positions: Option<usize>,
     model_type: Option<String>,
     max_seq_len: Option<usize>,
+    quantization_config: Option<QuantizationConfig>,
+}
+
+#[derive(Deserialize)]
+struct QuantizationConfig {
+    quant_method: Option<Quantization>,
 }
 
 #[derive(Deserialize)]
 struct Config {
     max_position_embeddings: Option<usize>,
+    quantize: Option<Quantization>,
 }
 
 impl From<RawConfig> for Config {
@@ -43,13 +50,16 @@ impl From<RawConfig> for Config {
             .max_position_embeddings
             .or(other.max_seq_len)
             .or(other.n_positions);
+        let quantize = other.quantization_config.and_then(|q| q.quant_method);
         Config {
             max_position_embeddings,
+            quantize,
         }
     }
 }
 
-#[derive(Clone, Copy, Debug, ValueEnum)]
+#[derive(Clone, Copy, Debug, ValueEnum, Deserialize)]
+#[serde(rename_all = "kebab-case")]
 enum Quantization {
     /// 4 bit quantization. Requires a specific AWQ quantized model:
     ///   <https://hf.co/models?search=awq>.
@@ -72,17 +82,17 @@ enum Quantization {
     Marlin,
     /// Bitsandbytes 8bit. Can be applied on any model, will cut the memory requirement in half,
     /// but it is known that the model will be much slower to run than the native f16.
-    #[deprecated(
+    // #[deprecated(
-        since = "1.1.0",
+    //     since = "1.1.0",
-        note = "Use `eetq` instead, which provides better latencies overall and is drop-in in most cases"
+    //     note = "Use `eetq` instead, which provides better latencies overall and is drop-in in most cases"
-    )]
+    // )]
     Bitsandbytes,
     /// Bitsandbytes 4bit. Can be applied on any model, will cut the memory requirement by 4x,
     /// but it is known that the model will be much slower to run than the native f16.
-    BitsandbytesNF4,
+    BitsandbytesNf4,
     /// Bitsandbytes 4bit. nf4 should be preferred in most cases but maybe this one has better
     /// perplexity performance for you model
-    BitsandbytesFP4,
+    BitsandbytesFp4,
     /// [FP8](https://developer.nvidia.com/blog/nvidia-arm-and-intel-publish-fp8-specification-for-standardization-as-an-interchange-format-for-ai/) (e4m3) works on H100 and above
     /// This dtype has native ops should be the fastest if available.
     /// This is currently not the fastest because of local unpacking + padding to satisfy matrix
@@ -99,10 +109,10 @@ impl std::fmt::Display for Quantization {
             Quantization::Bitsandbytes => {
                 write!(f, "bitsandbytes")
             }
-            Quantization::BitsandbytesNF4 => {
+            Quantization::BitsandbytesNf4 => {
                 write!(f, "bitsandbytes-nf4")
             }
-            Quantization::BitsandbytesFP4 => {
+            Quantization::BitsandbytesFp4 => {
                 write!(f, "bitsandbytes-fp4")
             }
             Quantization::Exl2 => {
@@ -1085,6 +1095,7 @@ fn spawn_shards(
     cuda_graphs: Vec<usize>,
     max_total_tokens: usize,
     max_input_tokens: usize,
+    quantize: Option<Quantization>,
     max_log_level: LevelFilter,
     shutdown: Arc<AtomicBool>,
     shutdown_receiver: &mpsc::Receiver<()>,
@@ -1106,7 +1117,6 @@ fn spawn_shards(
         let shutdown_sender = shutdown_sender.clone();
         let otlp_endpoint = args.otlp_endpoint.clone();
         let otlp_service_name = args.otlp_service_name.clone();
-        let quantize = args.quantize;
         let speculate = args.speculate;
         let dtype = args.dtype;
         let trust_remote_code = args.trust_remote_code;
@@ -1429,7 +1439,8 @@ fn main() -> Result<(), LauncherError> {
 
     tracing::info!("{:#?}", args);
 
-    let get_max_position_embeddings = || -> Result<usize, Box<dyn std::error::Error>> {
+    let get_max_positions_quantize =
+        || -> Result<(usize, Option<Quantization>), Box<dyn std::error::Error>> {
             let model_id = args.model_id.clone();
             let mut path = std::path::Path::new(&args.model_id).to_path_buf();
             let filename = if !path.exists() {
@@ -1464,6 +1475,7 @@ fn main() -> Result<(), LauncherError> {
                 std::env::set_var("ATTENTION", "flashdecoding");
             }
             let config: Config = config.into();
+            let quantize = config.quantize;
 
             // Quantization usually means you're even more RAM constrained.
             let max_default = 4096;
@@ -1477,9 +1489,9 @@ fn main() -> Result<(), LauncherError> {
                     {
                         tracing::info!("Model supports up to {max} but tgi will now set its default to {max_default} instead. This is to save VRAM by refusing large prompts in order to allow more users on the same hardware. You can increase that size using `--max-batch-prefill-tokens={} --max-total-tokens={max} --max-input-tokens={}`.", max + 50, max - 1);
                     }
-                Ok(max_default)
+                    Ok((max_default, quantize))
                 } else {
-                Ok(max_position_embeddings)
+                    Ok((max_position_embeddings, quantize))
                 }
             } else {
                 Err(Box::new(LauncherError::ArgumentValidation(
@@ -1487,7 +1499,8 @@ fn main() -> Result<(), LauncherError> {
                 )))
             }
         };
-    let max_position_embeddings: usize = get_max_position_embeddings().unwrap_or(4096);
+    let (max_position_embeddings, quantize): (usize, Option<Quantization>) =
+        get_max_positions_quantize().unwrap_or((4096, None));
 
     let max_input_tokens = {
         match (args.max_input_tokens, args.max_input_length) {
@@ -1544,18 +1557,26 @@ fn main() -> Result<(), LauncherError> {
         )));
     }
 
-    let cuda_graphs = match (&args.cuda_graphs, &args.quantize) {
+    if matches!(args.quantize, Some(Quantization::Bitsandbytes)) {
+        tracing::warn!("Bitsandbytes is deprecated, use `eetq` instead, which provides better latencies overall and is drop-in in most cases.");
+    }
+    let quantize = args.quantize.or(quantize);
+    let cuda_graphs = match (&args.cuda_graphs, &quantize) {
         (Some(cuda_graphs), _) => cuda_graphs.iter().cloned().filter(|&c| c > 0).collect(),
         #[allow(deprecated)]
         (
             None,
             Some(
                 Quantization::Bitsandbytes
-                | Quantization::BitsandbytesNF4
+                | Quantization::BitsandbytesNf4
-                | Quantization::BitsandbytesFP4,
+                | Quantization::BitsandbytesFp4,
             ),
         ) => {
-            tracing::info!("Bitsandbytes doesn't work with cuda graphs, deactivating them");
+            tracing::warn!("Bitsandbytes doesn't work with cuda graphs, deactivating them");
+            vec![]
+        }
+        (None, Some(Quantization::Exl2)) => {
+            tracing::warn!("Exl2 doesn't work with cuda graphs, deactivating them");
             vec![]
         }
         _ => {
@@ -1672,6 +1693,7 @@ fn main() -> Result<(), LauncherError> {
         cuda_graphs,
         max_total_tokens,
         max_input_tokens,
+        quantize,
         max_log_level,
         shutdown.clone(),
         &shutdown_receiver,

server/poetry.lock

@@ -1070,6 +1070,30 @@ win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""}
 [package.extras]
 dev = ["Sphinx (>=4.1.1)", "black (>=19.10b0)", "colorama (>=0.3.4)", "docutils (==0.16)", "flake8 (>=3.7.7)", "isort (>=5.1.1)", "pytest (>=4.6.2)", "pytest-cov (>=2.7.1)", "sphinx-autobuild (>=0.7.1)", "sphinx-rtd-theme (>=0.4.3)", "tox (>=3.9.0)"]
 
+[[package]]
+name = "markdown-it-py"
+version = "3.0.0"
+description = "Python port of markdown-it. Markdown parsing, done right!"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"},
+    {file = "markdown_it_py-3.0.0-py3-none-any.whl", hash = "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1"},
+]
+
+[package.dependencies]
+mdurl = ">=0.1,<1.0"
+
+[package.extras]
+benchmarking = ["psutil", "pytest", "pytest-benchmark"]
+code-style = ["pre-commit (>=3.0,<4.0)"]
+compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
+linkify = ["linkify-it-py (>=1,<3)"]
+plugins = ["mdit-py-plugins"]
+profiling = ["gprof2dot"]
+rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
+
 [[package]]
 name = "markupsafe"
 version = "2.1.5"
@@ -1207,6 +1231,17 @@ torch = "*"
 type = "url"
 url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp39-cp39-linux_x86_64.whl"
 
+[[package]]
+name = "mdurl"
+version = "0.1.2"
+description = "Markdown URL utilities"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"},
+    {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
+]
+
 [[package]]
 name = "mpmath"
 version = "1.3.0"
@@ -2277,6 +2312,20 @@ files = [
 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[package]]
+name = "pygments"
+version = "2.18.0"
+description = "Pygments is a syntax highlighting package written in Python."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pygments-2.18.0-py3-none-any.whl", hash = "sha256:b8e6aca0523f3ab76fee51799c488e38782ac06eafcf95e7ba832985c8e7b13a"},
+    {file = "pygments-2.18.0.tar.gz", hash = "sha256:786ff802f32e91311bff3889f6e9a86e81505fe99f2735bb6d60ae0c5004f199"},
+]
+
+[package.extras]
+windows-terminal = ["colorama (>=0.4.6)"]
+
 [[package]]
 name = "pytest"
 version = "7.4.4"
@@ -2508,6 +2557,24 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "rich"
+version = "13.7.1"
+description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "rich-13.7.1-py3-none-any.whl", hash = "sha256:4edbae314f59eb482f54e9e30bf00d33350aaa94f4bfcd4e9e3110e64d0d7222"},
+    {file = "rich-13.7.1.tar.gz", hash = "sha256:9be308cb1fe2f1f57d67ce99e95af38a1e2bc71ad9813b0e247cf7ffbcc3a432"},
+]
+
+[package.dependencies]
+markdown-it-py = ">=2.2.0"
+pygments = ">=2.13.0,<3.0.0"
+
+[package.extras]
+jupyter = ["ipywidgets (>=7.5.1,<9)"]
+
 [[package]]
 name = "rpds-py"
 version = "0.19.0"
@@ -3584,4 +3651,4 @@ torch = ["torch"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.13"
-content-hash = "a89867b23017d2efa8a7aa14d4764bcbd3b4dea9bfbf06a7a68464cb184ac6a1"
+content-hash = "0ff7a244a409b616490cb238995bbe28dedf67ccb8855edafa2b71ee2e777dbd"

server/pyproject.toml

@@ -46,6 +46,7 @@ marlin-kernels = [
   { url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp311-cp311-linux_x86_64.whl", python = "~3.11", optional = true },
   { url = "https://github.com/danieldk/marlin-kernels/releases/download/v0.2.0/marlin_kernels-0.2.0+cu123torch2.4-cp312-cp312-linux_x86_64.whl", python = "~3.12", optional = true },
 ]
+rich = "^13.7.1"
 
 [tool.poetry.extras]
 torch = ["torch"]

server/requirements_cuda.txt

@@ -16,6 +16,8 @@ huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13"
 idna==3.7 ; python_version >= "3.9" and python_version < "3.13"
 importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13"
 loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
+markdown-it-py==3.0.0 ; python_version >= "3.9" and python_version < "3.13"
+mdurl==0.1.2 ; python_version >= "3.9" and python_version < "3.13"
 numpy==1.26.4 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
@@ -32,9 +34,11 @@ pillow==10.4.0 ; python_version >= "3.9" and python_version < "3.13"
 prometheus-client==0.20.0 ; python_version >= "3.9" and python_version < "3.13"
 protobuf==4.25.3 ; python_version >= "3.9" and python_version < "3.13"
 py-cpuinfo==9.0.0 ; python_version >= "3.9" and python_version < "3.13"
+pygments==2.18.0 ; python_version >= "3.9" and python_version < "3.13"
 pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "3.13"
 regex==2024.5.15 ; python_version >= "3.9" and python_version < "3.13"
 requests==2.32.3 ; python_version >= "3.9" and python_version < "3.13"
+rich==13.7.1 ; python_version >= "3.9" and python_version < "3.13"
 safetensors==0.4.3 ; python_version >= "3.9" and python_version < "3.13"
 scipy==1.13.1 ; python_version >= "3.9" and python_version < "3.13"
 sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"

server/requirements_intel.txt

@@ -16,6 +16,8 @@ huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13"
 idna==3.7 ; python_version >= "3.9" and python_version < "3.13"
 importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13"
 loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
+markdown-it-py==3.0.0 ; python_version >= "3.9" and python_version < "3.13"
+mdurl==0.1.2 ; python_version >= "3.9" and python_version < "3.13"
 numpy==1.26.4 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
@@ -32,9 +34,11 @@ pillow==10.4.0 ; python_version >= "3.9" and python_version < "3.13"
 prometheus-client==0.20.0 ; python_version >= "3.9" and python_version < "3.13"
 protobuf==4.25.3 ; python_version >= "3.9" and python_version < "3.13"
 py-cpuinfo==9.0.0 ; python_version >= "3.9" and python_version < "3.13"
+pygments==2.18.0 ; python_version >= "3.9" and python_version < "3.13"
 pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "3.13"
 regex==2024.5.15 ; python_version >= "3.9" and python_version < "3.13"
 requests==2.32.3 ; python_version >= "3.9" and python_version < "3.13"
+rich==13.7.1 ; python_version >= "3.9" and python_version < "3.13"
 safetensors==0.4.3 ; python_version >= "3.9" and python_version < "3.13"
 scipy==1.13.1 ; python_version >= "3.9" and python_version < "3.13"
 sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"

server/requirements_rocm.txt

@@ -16,6 +16,8 @@ huggingface-hub==0.23.5 ; python_version >= "3.9" and python_version < "3.13"
 idna==3.7 ; python_version >= "3.9" and python_version < "3.13"
 importlib-metadata==7.1.0 ; python_version >= "3.9" and python_version < "3.13"
 loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
+markdown-it-py==3.0.0 ; python_version >= "3.9" and python_version < "3.13"
+mdurl==0.1.2 ; python_version >= "3.9" and python_version < "3.13"
 numpy==1.26.4 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-api==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-exporter-otlp-proto-common==1.25.0 ; python_version >= "3.9" and python_version < "3.13"
@@ -32,9 +34,11 @@ pillow==10.4.0 ; python_version >= "3.9" and python_version < "3.13"
 prometheus-client==0.20.0 ; python_version >= "3.9" and python_version < "3.13"
 protobuf==4.25.3 ; python_version >= "3.9" and python_version < "3.13"
 py-cpuinfo==9.0.0 ; python_version >= "3.9" and python_version < "3.13"
+pygments==2.18.0 ; python_version >= "3.9" and python_version < "3.13"
 pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "3.13"
 regex==2024.5.15 ; python_version >= "3.9" and python_version < "3.13"
 requests==2.32.3 ; python_version >= "3.9" and python_version < "3.13"
+rich==13.7.1 ; python_version >= "3.9" and python_version < "3.13"
 safetensors==0.4.3 ; python_version >= "3.9" and python_version < "3.13"
 scipy==1.13.1 ; python_version >= "3.9" and python_version < "3.13"
 sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"

server/text_generation_server/models/causal_lm.py

@@ -652,6 +652,7 @@ class CausalLM(Model):
             dtype=dtype,
             device=device,
         )
+        self.quantize = quantize
         return self
 
     @property

server/text_generation_server/models/mamba.py

@@ -412,6 +412,7 @@ class Mamba(Model):
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
+        self.quantize = quantize
         self.process_group, _rank, world_size = initialize_torch_distributed()
         if world_size > 1:
             raise RuntimeError("Mamba does not support Tensor Parallelism (TP)")

server/text_generation_server/models/seq2seq_lm.py

@@ -676,6 +676,7 @@ class Seq2SeqLM(Model):
             dtype=dtype,
             device=device,
         )
+        self.quantize = quantize
         return self
 
     @property