fix: pass model_id for all flash causal lms

server/text_generation_server/models/flash_causal_lm.py

@@ -953,12 +953,13 @@ class FlashCausalLM(Model):
         total_cache_size = self.num_layers * cache_block_size * 2 * dtype_size
 
         free_memory = get_free_memory(self.device, MEMORY_FRACTION)
+        batch_num_blocks = batch.num_blocks if batch is not None else 0
 
         num_blocks = (
             # Leave 5% for some wiggle room
             int((free_memory * 0.95) // total_cache_size)
             # Add batch.num_blocks as we allocated it above, so it is included in the peak memory.
-            + batch.num_blocks
+            + batch_num_blocks
         )
 
         del batch

server/text_generation_server/models/flash_cohere.py

@@ -62,6 +62,7 @@ class FlashCohere(FlashCausalLM):
 
         torch.distributed.barrier(group=self.process_group)
         super(FlashCohere, self).__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=len(model.model.layers),

server/text_generation_server/models/flash_dbrx.py

@@ -87,6 +87,7 @@ class FlashDbrx(FlashCausalLM):
 
         torch.distributed.barrier(group=self.process_group)
         super(FlashDbrx, self).__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=len(model.model.layers),

server/text_generation_server/models/flash_gemma.py

@@ -62,6 +62,7 @@ class FlashGemma(FlashCausalLM):
 
         torch.distributed.barrier(group=self.process_group)
         super(FlashGemma, self).__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=len(model.model.layers),

server/text_generation_server/models/flash_gpt2.py

@@ -65,6 +65,7 @@ class FlashGPT2(FlashCausalLM):
         model = FlashGPT2ForCausalLM(prefix, config, weights)
         torch.distributed.barrier(group=self.process_group)
         super(FlashGPT2, self).__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=len(model.model.layers),

server/text_generation_server/models/flash_mistral.py

@@ -79,6 +79,7 @@ class BaseFlashMistral(FlashCausalLM):
         torch.distributed.barrier(group=self.process_group)
         num_layers, num_kv_heads, head_size = self.get_layer_config(model)
         super().__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=num_layers,
@@ -110,6 +111,7 @@ class FlashMistral(BaseFlashMistral):
         trust_remote_code: bool = False,
     ):
         super(FlashMistral, self).__init__(
+            model_id=model_id,
             config_cls=MistralConfig,
             model_cls=FlashMistralForCausalLM,
             model_id=model_id,

server/text_generation_server/models/flash_mixtral.py

@@ -20,6 +20,7 @@ class FlashMixtral(BaseFlashMistral):
         trust_remote_code: bool = False,
     ):
         super(FlashMixtral, self).__init__(
+            model_id=model_id,
             config_cls=MixtralConfig,
             model_cls=FlashMixtralForCausalLM,
             model_id=model_id,

server/text_generation_server/models/flash_neox.py

@@ -65,6 +65,7 @@ class FlashNeoXSharded(FlashCausalLM):
 
         torch.distributed.barrier(group=self.process_group)
         super(FlashNeoXSharded, self).__init__(
+            model_id=model_id,
             model=model.to(device),
             tokenizer=tokenizer,
             num_layers=len(model.gpt_neox.layers),

server/text_generation_server/models/flash_phi.py

@@ -91,6 +91,7 @@ class FlashPhi(FlashCausalLM):
 
         torch.distributed.barrier(group=self.process_group)
         super(FlashPhi, self).__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=len(model.model.layers),

server/text_generation_server/models/flash_qwen2.py

@@ -71,6 +71,7 @@ class FlashQwen2(BaseFlashMistral):
 
         torch.distributed.barrier(group=self.process_group)
         super(BaseFlashMistral, self).__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=len(model.model.layers),

server/text_generation_server/models/flash_rw.py

@@ -74,6 +74,7 @@ class FlashRWSharded(FlashCausalLM):
 
         torch.distributed.barrier(group=self.process_group)
         super(FlashRWSharded, self).__init__(
+            model_id=model_id,
             model=model.to(device),
             tokenizer=tokenizer,
             num_layers=len(model.transformer.h),

server/text_generation_server/models/flash_santacoder.py

@@ -76,6 +76,7 @@ class FlashSantacoderSharded(FlashCausalLM):
 
         torch.distributed.barrier(group=self.process_group)
         super(FlashSantacoderSharded, self).__init__(
+            model_id=model_id,
             model=model.to(device),
             tokenizer=tokenizer,
             num_layers=len(model.transformer.h),

server/text_generation_server/models/flash_starcoder2.py

@@ -70,6 +70,7 @@ class FlashStarcoder2(BaseFlashMistral):
 
         torch.distributed.barrier(group=self.process_group)
         super(BaseFlashMistral, self).__init__(
+            model_id=model_id,
             model=model,
             tokenizer=tokenizer,
             num_layers=len(model.model.layers),