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from abc import abstractmethod
from dataclasses import asdict
from typing import Generator, List, Optional
from .card import ICLCard, TaskCard
from .common import CommonRecipe
from .operator import SourceOperator, StreamSource
from .random_utils import random
from .stream import MultiStream, Stream
class BaseFusion(SourceOperator):
"""
BaseFusion operator that combines multiple streams into one.
Args:
include_splits: List of splits to include. If None, all splits are included.
"""
include_splits: Optional[List[str]] = None
@abstractmethod
def fusion_generator(self, split) -> Generator:
pass
def splits(self) -> Generator:
splits = []
for origin in self.origins:
for s in origin().keys():
if s not in splits:
if self.include_splits is None or s in self.include_splits:
splits.append(s)
return splits
def process(
self,
) -> MultiStream:
result = {}
for split in self.splits():
result[split] = Stream(self.fusion_generator, gen_kwargs={"split": split})
return MultiStream(result)
class FixedFusion(BaseFusion):
"""
FixedFusion operator that combines multiple streams into one based on a fixed number of examples per task.
Args:
orgins: List of StreamSource objects.
examples_per_task: Number of examples per task. If None, all examples are returned.
splits: List of splits to include. If None, all splits are included.
"""
examples_per_task: Optional[int] = None
def fusion_generator(self, split) -> Generator:
for origin in self.orgins:
iterator = iter(origin()[split])
if self.examples_per_task is not None:
for i in range(self.examples_per_task):
yield next(iterator)
else:
yield from iterator
class WeightedFusion(BaseFusion):
"""
Fusion operator that combines multiple streams based
Args:
orgins: List of StreamSource objects.
weights: List of weights for each origin.
total_examples: Total number of examples to return. If None, all examples are returned.
"""
origins: List[StreamSource] = None
weights: List[float] = None
total_examples: int = None
def verify(self):
super().verify()
assert self.origins is not None, "origins must be specified"
assert self.weights is not None, "weights must be specified"
assert len(self.origins) == len(self.weights), "origins and weights must have the same length"
def fusion_generator(self, split) -> Generator:
iterators = [iter(origin()[split]) for origin in self.origins]
total_examples = 0
while (self.total_examples is None or total_examples <= self.total_examples) and len(iterators) > 0:
iterator = random.choices(population=iterators, weights=self.weights)[0]
try:
yield next(iterator)
total_examples += 1
except StopIteration:
iterators.remove(iterator)
class TasksFusion(SourceOperator):
"""
TasksFusion operator that combines multiple tasks into one.
Args:
tasks: List of TaskCard objects.
config: ICLCard object.
examples_per_task: Number of examples per task. If None, all examples are returned.
include_splits: List of splits to include. If None, all splits are included.
"""
tasks: List[TaskCard]
config: ICLCard
examples_per_task: Optional[int] = None
include_splits: Optional[List[str]] = None
def prepare(self):
self.recipes = []
for task in self.tasks:
recipe = CommonRecipe(card=task, **asdict(self.config))
self.fusion = FixedFusion(
origins=self.recipes, examples_per_task=self.examples_per_task, include_splits=self.include_splits
)
def process(self) -> MultiStream:
return self.fusion()
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