fix tests

router/client/src/client.rs

@@ -8,8 +8,6 @@ use std::time::Duration;
 use tonic::transport::{Channel, Uri};
 use tracing::instrument;
 
-
-
 /// Text Generation Inference gRPC client
 #[derive(Debug, Clone)]
 pub struct Client {
@@ -163,7 +161,11 @@ impl Client {
     ) -> Result<(Vec<Generation>, Option<CachedBatch>, PrefillTimings)> {
         let request = tonic::Request::new(PrefillRequest { batch: Some(batch) }).inject_context();
         let response = self.stub.prefill(request).await?.into_inner();
-        Ok((response.generations, response.batch, PrefillTimings::new(response.forward_ns, response.decode_ns, response.total_ns)))
+        Ok((
+            response.generations,
+            response.batch,
+            PrefillTimings::new(response.forward_ns, response.decode_ns, response.total_ns),
+        ))
     }
 
     /// Generate one token for each request in the given cached batches
@@ -177,7 +179,16 @@ impl Client {
     ) -> Result<(Vec<Generation>, Option<CachedBatch>, DecodeTimings)> {
         let request = tonic::Request::new(DecodeRequest { batches }).inject_context();
         let response = self.stub.decode(request).await?.into_inner();
-        Ok((response.generations, response.batch, DecodeTimings::new(response.concat_ns, response.forward_ns, response.decode_ns, response.total_ns)))
+        Ok((
+            response.generations,
+            response.batch,
+            DecodeTimings::new(
+                response.concat_ns,
+                response.forward_ns,
+                response.decode_ns,
+                response.total_ns,
+            ),
+        ))
     }
 }
 

router/client/src/sharded_client.rs

@@ -1,10 +1,10 @@
+use crate::client::{DecodeTimings, PrefillTimings};
 /// Multi shard Client
 use crate::{Batch, CachedBatch, Client, Generation, HealthResponse, ShardInfo};
 use crate::{ClientError, Result};
 use futures::future::join_all;
 use tonic::transport::Uri;
 use tracing::instrument;
-use crate::client::{DecodeTimings, PrefillTimings};
 
 #[derive(Debug, Clone)]
 /// Text Generation Inference gRPC multi client
@@ -131,7 +131,8 @@ impl ShardedClient {
             join_all(futures).await.into_iter().collect();
         let mut results = results?;
 
-        let (mut generations, next_batch, mut timings) = results.pop().ok_or(ClientError::EmptyResults)?;
+        let (mut generations, next_batch, mut timings) =
+            results.pop().ok_or(ClientError::EmptyResults)?;
 
         // Merge generations from different model shards
         for (mut shard_generations, _, shard_timings) in results.into_iter() {
@@ -162,7 +163,8 @@ impl ShardedClient {
             join_all(futures).await.into_iter().collect();
         let mut results = results?;
 
-        let (mut generations, next_batch, mut timings) = results.pop().ok_or(ClientError::EmptyResults)?;
+        let (mut generations, next_batch, mut timings) =
+            results.pop().ok_or(ClientError::EmptyResults)?;
 
         // Merge generations from different model shards
         for (mut shard_generations, _, shard_timings) in results.into_iter() {

router/src/validation.rs

@@ -229,6 +229,15 @@ impl Validation {
                 stop_sequences.len(),
             ));
         }
+        for s in stop_sequences {
+            if s.chars().len() > 50 {
+                return Err(ValidationError::StopSequence(
+                    self.max_stop_sequences,
+                    stop_sequences.len(),
+                ));
+
+            }
+        }
 
         // If seed is None, assign a random one
         let seed = match seed {

server/text_generation_server/models/flash_causal_lm.py

@@ -943,6 +943,7 @@ class FlashCausalLM(Model):
         # GPU <-> CPU sync
         next_token_logprobs = next_token_logprobs.tolist()
         next_token_ids = next_input_ids.tolist()
+        accepted_ids = accepted_ids.tolist()
         start_decode = time.time_ns()
 
         # Zipped iterator
@@ -980,7 +981,6 @@ class FlashCausalLM(Model):
             # Append next token to all tokens
             next_token_texts = []
             left = 0
-            before = stopping_criteria.current_tokens
 
             current_stopped = False
             for j in range(index, index + n_accepted_ids):
@@ -1095,7 +1095,7 @@ class FlashCausalLM(Model):
                 generations.append(generation)
 
             # Update values
-            batch.input_lengths[i] = input_length + n_accepted_ids.item()
+            batch.input_lengths[i] = input_length + n_accepted_ids
             if batch.input_lengths[i] > batch.max_seqlen:
                 batch.max_seqlen = batch.input_lengths[i]
             batch.prefix_offsets[i] = prefix_offset

server/text_generation_server/utils/tokens.py

@@ -92,7 +92,7 @@ class NextTokenChooser:
 class StopSequenceCriteria:
     def __init__(self, stop_sequence: str):
         stop_sequence = re.escape(stop_sequence)
-        self.regex = re.compile(f".*{stop_sequence}$")
+        self.regex = re.compile(f"{stop_sequence}$")
 
     def __call__(self, output: str) -> bool:
         if self.regex.findall(output):