reenable xpu for tgi

Dockerfile_intel

@@ -43,6 +43,7 @@ USER root
 RUN wget http://nz2.archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2_amd64.deb && \
     dpkg -i ./libssl1.1_1.1.1f-1ubuntu2_amd64.deb
 
+RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | gpg --dearmor | tee /usr/share/keyrings/intel-graphics.gpg > /dev/null
 
 RUN wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
 | gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null && echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | tee /etc/apt/sources.list.d/oneAPI.list

server/text_generation_server/layers/rotary.py

@@ -9,6 +9,8 @@
     import rotary_emb
 elif SYSTEM == "rocm":
     from vllm._C import ops
+elif SYSTEM == "xpu":
+    import intel_extension_for_pytorch as ipex
 
 
 def _create_inv_freq(dim, base, device):

server/text_generation_server/models/custom_modeling/idefics_modeling.py

@@ -62,7 +62,7 @@
 elif SYSTEM == "rocm":
     from vllm._C import ops
 else:
-    raise RuntimeError(f"Unsupported system {SYSTEM}")
+    dropout_layer_norm = None
 
 
 @dataclass

server/text_generation_server/utils/flash_attn.py

@@ -5,7 +5,9 @@
 import math
 
 from text_generation_server.utils.import_utils import SYSTEM
-from text_generation_server.utils.flash_attn_triton import triton_attention
+
+if SYSTEM != "xpu":
+    from text_generation_server.utils.flash_attn_triton import triton_attention
 
 if os.getenv("USE_FLASH_ATTENTION", "").lower() == "false":
     raise ImportError("`USE_FLASH_ATTENTION` is false.")
@@ -15,43 +17,6 @@
 ROCM_USE_FLASH_ATTN_V2_CK = False
 ROCM_USE_FLASH_ATTN_V2_TRITON = False
 
-if SYSTEM == "xpu":
-    import intel_extension_for_pytorch as ipex
-
-    def attention(
-        q,
-        k,
-        v,
-        out,
-        cu_seqlens,
-        max_s,
-        softmax_scale,
-        window_size_left=-1,
-    ):
-        if window_size_left <= 0 and window_size_left != -1:
-            raise ValueError("`window_size_left` must be > 0 or -1")
-
-        if window_size_left != -1:
-            raise ValueError(
-                f"XPU version of Flash Attention does not support window attention (window_size_left != -1, got window_size_left={window_size_left})."
-            )
-        return ipex.llm.functional.varlen_attention(
-            q,
-            k,
-            v,
-            out,
-            cu_seqlens,
-            cu_seqlens,
-            max_s,
-            max_s,
-            0.0,
-            softmax_scale,
-            False,
-            True,
-            False,
-            None,
-        )
-
 
 if SYSTEM in {"cuda", "rocm"}:
     if not torch.cuda.is_available():
@@ -124,8 +89,44 @@ def attention(
         logger.warning(f"Unable to use Flash Attention V2: {e}")
         HAS_FLASH_ATTN = True
 
+if SYSTEM == "xpu":
+    import intel_extension_for_pytorch as ipex
+
+    def attention(
+        q,
+        k,
+        v,
+        out,
+        cu_seqlens,
+        max_s,
+        softmax_scale,
+        window_size_left=-1,
+    ):
+        if window_size_left <= 0 and window_size_left != -1:
+            raise ValueError("`window_size_left` must be > 0 or -1")
+
+        if window_size_left != -1:
+            raise ValueError(
+                f"XPU version of Flash Attention does not support window attention (window_size_left != -1, got window_size_left={window_size_left})."
+            )
+        return ipex.llm.functional.varlen_attention(
+            q,
+            k,
+            v,
+            out,
+            cu_seqlens,
+            cu_seqlens,
+            max_s,
+            max_s,
+            0.0,
+            softmax_scale,
+            False,
+            True,
+            False,
+            None,
+        )
 
-if HAS_FLASH_ATTN_V2_CUDA:
+elif HAS_FLASH_ATTN_V2_CUDA:
 
     def attention(
         q,

server/text_generation_server/utils/import_utils.py

@@ -17,7 +17,7 @@ def get_cuda_free_memory(device, memory_fraction):
     return free_memory
 
 
-def get_xpu_free_memory(device):
+def get_xpu_free_memory(device, memory_fraction):
     total_gpu_memory = torch.xpu.get_device_properties(device).total_memory
     free_memory = int(total_gpu_memory * 0.5)
     return free_memory