feat: relax mistral requirements (#1351)

Close #1253 
Close #1279

.github/workflows/build.yaml

@@ -146,11 +146,50 @@ jobs:
           cache-from: type=registry,ref=registry.internal.huggingface.tech/api-inference/community/text-generation-inference:cache,mode=min
           cache-to: type=registry,ref=registry.internal.huggingface.tech/api-inference/community/text-generation-inference:cache,mode=min
 
+  integration-tests:
+    concurrency:
+      group: ${{ github.workflow }}-${{ github.job }}-${{ github.head_ref || github.run_id }}
+      cancel-in-progress: true
+    needs:
+      - start-runner
+      - build-and-push-image # Wait for the docker image to be built
+    runs-on: ${{ needs.start-runner.outputs.label }} # run the job on the newly created runner
+    env:
+      DOCKER_VOLUME: /cache
+    steps:
+      - uses: actions/checkout@v2
+      - name: Inject slug/short variables
+        uses: rlespinasse/github-slug-action@v4.4.1
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: 3.9
+      - name: Tailscale
+        uses: tailscale/github-action@7bd8039bf25c23c4ab1b8d6e2cc2da2280601966
+        with:
+          authkey: ${{ secrets.TAILSCALE_AUTHKEY }}
+      - name: Prepare disks
+        run: |
+          sudo mkfs -t ext4 /dev/nvme1n1
+          sudo mkdir ${{ env.DOCKER_VOLUME }}
+          sudo mount /dev/nvme1n1 ${{ env.DOCKER_VOLUME }}
+      - name: Install
+        run: |
+          make install-integration-tests
+      - name: Run tests
+        run: |
+          export DOCKER_IMAGE=registry.internal.huggingface.tech/api-inference/community/text-generation-inference:sha-${{ env.GITHUB_SHA_SHORT }}
+          export HUGGING_FACE_HUB_TOKEN=${{ secrets.HUGGING_FACE_HUB_TOKEN }}
+          pytest -s -vv integration-tests
+
   build-and-push-image-rocm:
     concurrency:
       group: ${{ github.workflow }}-build-and-push-image-rocm-${{ github.head_ref || github.run_id }}
       cancel-in-progress: true
-    needs: start-runner # required to start the main job when the runner is ready
+    needs:
+      - start-runner
+      - build-and-push-image # Wait for the main docker image to be built
+      - integration-tests # Wait for the main integration-tests
     runs-on: ${{ needs.start-runner.outputs.label }} # run the job on the newly created runner
     permissions:
       contents: write
@@ -235,43 +274,6 @@ jobs:
           cache-from: type=registry,ref=registry.internal.huggingface.tech/api-inference/community/text-generation-inference:cache-rocm,mode=min
           cache-to: type=registry,ref=registry.internal.huggingface.tech/api-inference/community/text-generation-inference:cache-rocm,mode=min
 
-  integration-tests:
-    concurrency:
-      group: ${{ github.workflow }}-${{ github.job }}-${{ github.head_ref || github.run_id }}
-      cancel-in-progress: true
-    needs:
-      - start-runner
-      - build-and-push-image # Wait for the docker image to be built
-      - build-and-push-image-rocm
-    runs-on: ${{ needs.start-runner.outputs.label }} # run the job on the newly created runner
-    env:
-      DOCKER_VOLUME: /cache
-    steps:
-      - uses: actions/checkout@v2
-      - name: Inject slug/short variables
-        uses: rlespinasse/github-slug-action@v4.4.1
-      - name: Set up Python
-        uses: actions/setup-python@v4
-        with:
-          python-version: 3.9
-      - name: Tailscale
-        uses: tailscale/github-action@7bd8039bf25c23c4ab1b8d6e2cc2da2280601966
-        with:
-          authkey: ${{ secrets.TAILSCALE_AUTHKEY }}
-      - name: Prepare disks
-        run: |
-          sudo mkfs -t ext4 /dev/nvme1n1
-          sudo mkdir ${{ env.DOCKER_VOLUME }}
-          sudo mount /dev/nvme1n1 ${{ env.DOCKER_VOLUME }}
-      - name: Install
-        run: |
-          make install-integration-tests
-      - name: Run tests
-        run: |
-          export DOCKER_IMAGE=registry.internal.huggingface.tech/api-inference/community/text-generation-inference:sha-${{ env.GITHUB_SHA_SHORT }}
-          export HUGGING_FACE_HUB_TOKEN=${{ secrets.HUGGING_FACE_HUB_TOKEN }}
-          pytest -s -vv integration-tests
-
   stop-runner:
     name: Stop self-hosted EC2 runner
     needs:

server/pyproject.toml

@@ -15,7 +15,7 @@ grpcio-status = "^1.51.1"
 grpcio-reflection = "^1.51.1"
 grpc-interceptor = "^0.15.0"
 typer = "^0.6.1"
-accelerate = { version = "^0.20.0", optional = true }
+accelerate = { version = "^0.25.0", optional = true }
 bitsandbytes = { version = "^0.41.1", optional = true }
 safetensors = "^0.3.2"
 loguru = "^0.6.0"
@@ -24,9 +24,9 @@ opentelemetry-exporter-otlp = "^1.15.0"
 opentelemetry-instrumentation-grpc = "^0.36b0"
 hf-transfer = "^0.1.2"
 sentencepiece = "^0.1.97"
-tokenizers = "^0.13.3"
+tokenizers = "^0.15.0"
-huggingface-hub = "^0.16.4"
+huggingface-hub = "^0.19.3"
-transformers = "^4.32.1"
+transformers = "^4.36.1"
 einops = "^0.6.1"
 texttable = { version = "^1.6.7", optional = true }
 datasets = { version = "^2.14.0", optional = true }

server/requirements_cuda.txt

@@ -1,5 +1,5 @@
 backoff==2.2.1 ; python_version >= "3.9" and python_version < "3.13"
-bitsandbytes==0.41.2.post2 ; python_version >= "3.9" and python_version < "3.13"
+bitsandbytes==0.41.3.post2 ; python_version >= "3.9" and python_version < "3.13"
 certifi==2023.11.17 ; python_version >= "3.9" and python_version < "3.13"
 charset-normalizer==3.3.2 ; python_version >= "3.9" and python_version < "3.13"
 click==8.1.7 ; python_version >= "3.9" and python_version < "3.13"
@@ -8,14 +8,14 @@ deprecated==1.2.14 ; python_version >= "3.9" and python_version < "3.13"
 einops==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
 filelock==3.13.1 ; python_version >= "3.9" and python_version < "3.13"
 fsspec==2023.10.0 ; python_version >= "3.9" and python_version < "3.13"
-googleapis-common-protos==1.61.0 ; python_version >= "3.9" and python_version < "3.13"
+googleapis-common-protos==1.62.0 ; python_version >= "3.9" and python_version < "3.13"
 grpc-interceptor==0.15.4 ; python_version >= "3.9" and python_version < "3.13"
-grpcio-reflection==1.59.3 ; python_version >= "3.9" and python_version < "3.13"
+grpcio-reflection==1.60.0 ; python_version >= "3.9" and python_version < "3.13"
-grpcio-status==1.59.3 ; python_version >= "3.9" and python_version < "3.13"
+grpcio-status==1.60.0 ; python_version >= "3.9" and python_version < "3.13"
-grpcio==1.59.3 ; python_version >= "3.9" and python_version < "3.13"
+grpcio==1.60.0 ; python_version >= "3.9" and python_version < "3.13"
 hf-transfer==0.1.4 ; python_version >= "3.9" and python_version < "3.13"
-huggingface-hub==0.16.4 ; python_version >= "3.9" and python_version < "3.13"
+huggingface-hub==0.19.4 ; python_version >= "3.9" and python_version < "3.13"
-idna==3.4 ; python_version >= "3.9" and python_version < "3.13"
+idna==3.6 ; python_version >= "3.9" and python_version < "3.13"
 loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
 numpy==1.26.2 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "3.13"
@@ -37,11 +37,11 @@ safetensors==0.3.3 ; python_version >= "3.9" and python_version < "3.13"
 scipy==1.11.4 ; python_version >= "3.9" and python_version < "3.13"
 sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"
 setuptools==69.0.2 ; python_version >= "3.9" and python_version < "3.13"
-tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "3.13"
+tokenizers==0.15.0 ; python_version >= "3.9" and python_version < "3.13"
 tqdm==4.66.1 ; python_version >= "3.9" and python_version < "3.13"
-transformers==4.33.3 ; python_version >= "3.9" and python_version < "3.13"
+transformers==4.36.1 ; python_version >= "3.9" and python_version < "3.13"
 typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
-typing-extensions==4.8.0 ; python_version >= "3.9" and python_version < "3.13"
+typing-extensions==4.9.0 ; python_version >= "3.9" and python_version < "3.13"
 urllib3==2.1.0 ; python_version >= "3.9" and python_version < "3.13"
 win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "3.13" and sys_platform == "win32"
 wrapt==1.16.0 ; python_version >= "3.9" and python_version < "3.13"

server/requirements_rocm.txt

@@ -7,14 +7,14 @@ deprecated==1.2.14 ; python_version >= "3.9" and python_version < "3.13"
 einops==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
 filelock==3.13.1 ; python_version >= "3.9" and python_version < "3.13"
 fsspec==2023.10.0 ; python_version >= "3.9" and python_version < "3.13"
-googleapis-common-protos==1.61.0 ; python_version >= "3.9" and python_version < "3.13"
+googleapis-common-protos==1.62.0 ; python_version >= "3.9" and python_version < "3.13"
 grpc-interceptor==0.15.4 ; python_version >= "3.9" and python_version < "3.13"
-grpcio-reflection==1.59.3 ; python_version >= "3.9" and python_version < "3.13"
+grpcio-reflection==1.60.0 ; python_version >= "3.9" and python_version < "3.13"
-grpcio-status==1.59.3 ; python_version >= "3.9" and python_version < "3.13"
+grpcio-status==1.60.0 ; python_version >= "3.9" and python_version < "3.13"
-grpcio==1.59.3 ; python_version >= "3.9" and python_version < "3.13"
+grpcio==1.60.0 ; python_version >= "3.9" and python_version < "3.13"
 hf-transfer==0.1.4 ; python_version >= "3.9" and python_version < "3.13"
-huggingface-hub==0.16.4 ; python_version >= "3.9" and python_version < "3.13"
+huggingface-hub==0.19.4 ; python_version >= "3.9" and python_version < "3.13"
-idna==3.4 ; python_version >= "3.9" and python_version < "3.13"
+idna==3.6 ; python_version >= "3.9" and python_version < "3.13"
 loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
 numpy==1.26.2 ; python_version >= "3.9" and python_version < "3.13"
 opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "3.13"
@@ -36,11 +36,11 @@ safetensors==0.3.3 ; python_version >= "3.9" and python_version < "3.13"
 scipy==1.11.4 ; python_version >= "3.9" and python_version < "3.13"
 sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13"
 setuptools==69.0.2 ; python_version >= "3.9" and python_version < "3.13"
-tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "3.13"
+tokenizers==0.15.0 ; python_version >= "3.9" and python_version < "3.13"
 tqdm==4.66.1 ; python_version >= "3.9" and python_version < "3.13"
-transformers==4.33.3 ; python_version >= "3.9" and python_version < "3.13"
+transformers==4.36.1 ; python_version >= "3.9" and python_version < "3.13"
 typer==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
-typing-extensions==4.8.0 ; python_version >= "3.9" and python_version < "3.13"
+typing-extensions==4.9.0 ; python_version >= "3.9" and python_version < "3.13"
 urllib3==2.1.0 ; python_version >= "3.9" and python_version < "3.13"
 win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "3.13" and sys_platform == "win32"
 wrapt==1.16.0 ; python_version >= "3.9" and python_version < "3.13"

server/text_generation_server/models/__init__.py

@@ -55,10 +55,14 @@ try:
         FlashSantacoderSharded,
     )
     from text_generation_server.models.idefics import IDEFICSSharded
+    from text_generation_server.models.flash_mistral import FlashMistral
+    from text_generation_server.models.flash_mixtral import FlashMixtral
+    from text_generation_server.utils.flash_attn import HAS_FLASH_ATTN_V2_CUDA
 
 except ImportError as e:
     logger.warning(f"Could not import Flash Attention enabled models: {e}")
     FLASH_ATTENTION = False
+    HAS_FLASH_ATTN_V2_CUDA = False
 
 if FLASH_ATTENTION:
     __all__.append(FlashNeoXSharded)
@@ -66,25 +70,7 @@ if FLASH_ATTENTION:
     __all__.append(FlashSantacoderSharded)
     __all__.append(FlashLlama)
     __all__.append(IDEFICSSharded)
-
-MISTRAL = True
-try:
-    from text_generation_server.models.flash_mistral import FlashMistral
-except ImportError as e:
-    logger.warning(f"Could not import Mistral model: {e}")
-    MISTRAL = False
-
-if MISTRAL:
     __all__.append(FlashMistral)
-
-MIXTRAL = True
-try:
-    from text_generation_server.models.flash_mixtral import FlashMixtral
-except ImportError as e:
-    logger.warning(f"Could not import Mixtral model: {e}")
-    MIXTRAL = False
-
-if MIXTRAL:
     __all__.append(FlashMixtral)
 
 
@@ -295,7 +281,9 @@ def get_model(
                 )
 
     if model_type == "mistral":
-        if MISTRAL:
+        if (config_dict["sliding_window"] is None and FLASH_ATTENTION) or (
+            config_dict["sliding_window"] > 0 and HAS_FLASH_ATTN_V2_CUDA
+        ):
             return FlashMistral(
                 model_id,
                 revision,
@@ -303,10 +291,11 @@ def get_model(
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
-        raise NotImplementedError("Mistral models requires flash attention v2")
 
     if model_type == "mixtral":
-        if MIXTRAL:
+        if (config_dict["sliding_window"] is None and FLASH_ATTENTION) or (
+            config_dict["sliding_window"] > 0 and HAS_FLASH_ATTN_V2_CUDA
+        ):
             return FlashMixtral(
                 model_id,
                 revision,
@@ -314,9 +303,6 @@ def get_model(
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
-        raise NotImplementedError(
-            "Mixtral models requires flash attention v2, stk and megablocks"
-        )
 
     if model_type == "opt":
         return OPTSharded(
@@ -348,17 +334,17 @@ def get_model(
             raise NotImplementedError(FLASH_ATT_ERROR_MESSAGE.format("Idefics"))
 
     if sharded:
-        raise ValueError("sharded is not supported for AutoModel")
+        raise NotImplementedError("sharded is not supported for AutoModel")
     if quantize == "gptq":
-        raise ValueError(
+        raise NotImplementedError(
             "gptq quantization is not supported for AutoModel, you can try to quantize it with `text-generation-server quantize ORIGINAL_MODEL_ID NEW_MODEL_ID`"
         )
     if quantize == "awq":
-        raise ValueError("awq quantization is not supported for AutoModel")
+        raise NotImplementedError("awq quantization is not supported for AutoModel")
     elif (quantize == "bitsandbytes-fp4") or (quantize == "bitsandbytes-nf4"):
-        raise ValueError("4bit quantization is not supported for AutoModel")
+        raise NotImplementedError("4bit quantization is not supported for AutoModel")
     elif quantize == "eetq":
-        raise ValueError("Eetq quantization is not supported for AutoModel")
+        raise NotImplementedError("Eetq quantization is not supported for AutoModel")
     if model_type in modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES:
         return CausalLM(
             model_id,

server/text_generation_server/models/custom_modeling/flash_mistral_modeling.py

@@ -27,11 +27,6 @@ from transformers.configuration_utils import PretrainedConfig
 from typing import Optional, List, Tuple
 
 from text_generation_server.utils import paged_attention, flash_attn
-from text_generation_server.utils.flash_attn import (
-    attention,
-    HAS_FLASH_ATTN_V2_ROCM,
-    HAS_FLASH_ATTN_V2_CUDA,
-)
 from text_generation_server.utils.layers import (
     TensorParallelRowLinear,
     TensorParallelColumnLinear,
@@ -43,10 +38,6 @@ from text_generation_server.utils.layers import (
 )
 
 
-if not HAS_FLASH_ATTN_V2_CUDA and not HAS_FLASH_ATTN_V2_ROCM:
-    raise ImportError("Mistral model requires flash attn v2")
-
-
 class MistralConfig(PretrainedConfig):
     model_type = "mistral"
 

server/text_generation_server/models/custom_modeling/flash_mixtral_modeling.py

@@ -27,12 +27,9 @@ from torch import nn
 from transformers.activations import ACT2FN
 from transformers.configuration_utils import PretrainedConfig
 from typing import Optional, List, Tuple
+from loguru import logger
 
 from text_generation_server.utils import paged_attention, flash_attn
-from text_generation_server.utils.flash_attn import (
-    HAS_FLASH_ATTN_V2_ROCM,
-    HAS_FLASH_ATTN_V2_CUDA,
-)
 from text_generation_server.utils.layers import (
     FastLinear,
     FastRMSNorm,
@@ -44,18 +41,13 @@ from text_generation_server.utils.layers import (
     get_linear,
 )
 
-if not HAS_FLASH_ATTN_V2_CUDA and not HAS_FLASH_ATTN_V2_ROCM:
+HAS_MEGABLOCKS = True
-    raise ImportError("Mixtral model requires flash attn v2")
-
-try:
-    import megablocks.ops as ops
-except ImportError:
-    raise ImportError("Mixtral model requires megablocks to be installed")
-
 try:
     import stk
+    import megablocks.ops as ops
 except ImportError:
-    raise ImportError("Mixtral model requires stk to be installed")
+    logger.warning("Mixtral: megablocks is not installed")
+    HAS_MEGABLOCKS = False
 
 
 class MixtralConfig(PretrainedConfig):
@@ -590,7 +582,7 @@ class BlockSparseMoE(nn.Module):
         return out
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
-        if len(x) > 256:
+        if len(x) > 256 and HAS_MEGABLOCKS:
             return self.sparse_forward(x)
         # This is faster when there is not a lot of tokens
         return self.dense_forward(x)