Better continuous batching tests (#42699)

* No more size 0 cuda graph * Better tests for CB * compile fix for CB test * style * More cleanup and cuda exclusive * Returned to slow tests * Change decorator order * Restore XPU change * Rebase fixes

Author: remi-or

src/transformers/generation/continuous_batching/continuous_api.py

@@ -66,7 +66,7 @@ def pad_by_intervals(size: int, max_value: int, nb_intervals: int) -> int:
  interval_size = max_value // nb_intervals
  if interval_size == 0:
  return max_value
- padded = ceil(size / interval_size) * interval_size
+ padded = ceil(size / interval_size) * interval_size if size > 0 else interval_size
  return min(padded, max_value)
 
 
@@ -713,6 +713,7 @@ def _process_logit(self, batch_data: dict, logits: torch.Tensor, logit_processor
  # Handle shape compatibility: logit processors expect 2D tensors [batch_size, vocab_size]
  # but continuous batching always produces 3D tensors [batch_size, seq_len, vocab_size]
  batch_size, seq_len, vocab_size = logits.shape
+ # NOTE: to be an exact match with generate, we should also convert logits2d to float32 here, but it's not needed in practice
  logits_2d = logits.view(batch_size * seq_len, vocab_size)
  input_ids_2d = batch_data["input_ids"].view(batch_size * seq_len)
  # Process with 2D tensors
@@ -869,7 +870,7 @@ def stop(self, block: bool = True, timeout: float | None = None) -> None:
  logger.warning("\nBatch processor was not initialized.")
  else:
  if self.batch_processor.cache.use_prefix_sharing:
- logger.warning(
+ logger.info(
  f"\nPrefix sharing was on. Total prefix length: {self.batch_processor.cache._total_prefix_length}"
  )