Refactor system architecture (#109)

cacheflow/outputs.py

@@ -0,0 +1,79 @@
+from typing import Dict, List, Union
+
+from transformers import PreTrainedTokenizer, PreTrainedTokenizerFast
+
+from cacheflow.sequence import SequenceGroup
+
+
+class CompletionOutput:
+
+    def __init__(
+        self,
+        text: str,
+        token_ids: List[int],
+        cumulative_logprobs: float,
+        logprobs: List[Dict[int, float]],
+    ) -> None:
+        self.text = text
+        self.token_ids = token_ids
+        self.cumulative_logprobs = cumulative_logprobs
+        self.logprobs = logprobs
+
+    def __repr__(self) -> str:
+        return (f"CompletionOutput(output={self.text!r}, "
+                f"token_ids={self.token_ids}, "
+                f"cumulative_logprobs={self.cumulative_logprobs}, "
+                f"logprobs={self.logprobs})")
+
+
+class RequestOutput:
+
+    def __init__(
+        self,
+        request_id: int,
+        prompt: str,
+        prompt_token_ids: List[int],
+        outputs: List[CompletionOutput],
+        done: bool = False,
+    ) -> None:
+        self.request_id = request_id
+        self.prompt = prompt
+        self.prompt_token_ids = prompt_token_ids
+        self.outputs = outputs
+        self.done = done
+
+    @staticmethod
+    def from_seq_group(
+        seq_group: SequenceGroup,
+        tokenizer: Union[PreTrainedTokenizer, PreTrainedTokenizerFast],
+    ) -> "RequestOutput":
+        outputs: List[CompletionOutput] = []
+        seqs = seq_group.get_seqs()
+        for seq in seqs:
+            output_token_ids = seq.data.output_token_ids
+            output_str = tokenizer.decode(output_token_ids,
+                                          skip_special_tokens=True)
+            seq_logprobs = seq.data.cumulative_logprobs
+
+            logprobs = seq.output_logprobs
+            if seq_group.sampling_params.logprobs == 0:
+                # NOTE: We need to take care of this case because the sequence
+                # always has the logprobs of the sampled tokens even if the
+                # logprobs are not requested.
+                logprobs = {}
+            output = CompletionOutput(output_str, output_token_ids,
+                                      seq_logprobs, logprobs)
+            outputs.append(output)
+
+        # Every sequence in the sequence group should have the same prompt.
+        prompt = seqs[0].prompt
+        prompt_token_ids = seqs[0].data.prompt_token_ids
+        return RequestOutput(seq_group.request_id, prompt, prompt_token_ids,
+                             outputs, seq_group.is_finished())
+
+    def __repr__(self) -> str:
+        return (f"RequestOutput(request_id={self.request_id}, "
+                f"prompt={self.prompt!r}, "
+                f"prompt_token_ids={self.prompt_token_ids}, "
+                f"outputs={self.outputs}, "
+                f"done={self.done})")