Upload standard.py with huggingface_hub
Browse files- standard.py +10 -14
standard.py
CHANGED
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@@ -3,7 +3,6 @@ from typing import List
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from .card import TaskCard
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from .dataclass import Field, InternalField, OptionalField
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from .formats import Format, SystemFormat
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from .instructions import EmptyInstruction, Instruction
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from .logging_utils import get_logger
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from .operator import SourceSequentialOperator, StreamingOperator
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from .operators import (
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@@ -14,6 +13,7 @@ from .operators import (
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from .recipe import Recipe
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from .schema import ToUnitxtGroup
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from .splitters import Sampler, SeparateSplit, SpreadSplit
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from .templates import Template
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logger = get_logger()
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@@ -31,7 +31,7 @@ class AddDemosField(SpreadSplit):
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class BaseRecipe(Recipe, SourceSequentialOperator):
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card: TaskCard
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template: Template = None
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-
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format: Format = Field(default_factory=SystemFormat)
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loader_limit: int = None
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@@ -46,6 +46,7 @@ class BaseRecipe(Recipe, SourceSequentialOperator):
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demos_pool_size: int = None
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num_demos: int = 0
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demos_pool_name: str = "demos_pool"
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demos_taken_from: str = "train"
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@@ -135,6 +136,7 @@ class BaseRecipe(Recipe, SourceSequentialOperator):
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from_split=self.demos_taken_from,
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to_split_names=[self.demos_pool_name, self.demos_taken_from],
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to_split_sizes=[int(self.demos_pool_size)],
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)
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)
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@@ -160,7 +162,7 @@ class BaseRecipe(Recipe, SourceSequentialOperator):
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sampler=self.sampler,
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)
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)
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self.steps.append(self.
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self.steps.append(self.format)
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if self.augmentor.augment_model_input:
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self.steps.append(self.augmentor)
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@@ -177,7 +179,6 @@ class BaseRecipe(Recipe, SourceSequentialOperator):
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class StandardRecipeWithIndexes(BaseRecipe):
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instruction_card_index: int = None
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template_card_index: int = None
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def prepare(self):
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@@ -192,17 +193,12 @@ class StandardRecipeWithIndexes(BaseRecipe):
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self.template = self.card.templates[self.template_card_index]
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except Exception as e:
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if isinstance(self.card.templates, dict):
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options = self.card.templates.keys()
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else:
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options = list(range(0, len(self.card.templates)))
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raise ValueError(
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f"card_template_index '{self.template_card_index}' is not in card.
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) from e
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assert (
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self.instruction_card_index is None or self.instruction is None
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), "Specify either instruction or instruction_card_index"
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if self.instruction_card_index is not None:
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self.instruction = self.card.instructions[int(self.instruction_card_index)]
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super().prepare()
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@@ -217,7 +213,7 @@ class StandardRecipe(StandardRecipeWithIndexes):
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Attributes:
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card (TaskCard): TaskCard object associated with the recipe.
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template (Template, optional): Template object to be used for the recipe.
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-
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loader_limit (int, optional): Specifies the maximum number of instances per stream to be returned from the loader (used to reduce loading time in large datasets)
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format (SystemFormat, optional): SystemFormat object to be used for the recipe.
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train_refiner (StreamRefiner, optional): Train refiner to be used in the recipe.
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@@ -231,6 +227,7 @@ class StandardRecipe(StandardRecipeWithIndexes):
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demos_pool_name (str, optional): Name of the demos pool. Default is "demos_pool".
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demos_taken_from (str, optional): Specifies from where the demos are taken. Default is "train".
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demos_field (str, optional): Field name for demos. Default is "demos".
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sampler (Sampler, optional): Sampler object to be used in the recipe.
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steps (List[StreamingOperator], optional): List of StreamingOperator objects to be used in the recipe.
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augmentor (Augmentor) : Augmentor to be used to pseudo randomly augment the source text
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@@ -244,8 +241,7 @@ class StandardRecipe(StandardRecipeWithIndexes):
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by arranging all the steps, refiners, and renderers in a sequential manner.
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Raises:
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AssertionError: If both template and template_card_index
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are specified at the same time.
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"""
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pass
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from .card import TaskCard
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from .dataclass import Field, InternalField, OptionalField
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from .formats import Format, SystemFormat
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from .logging_utils import get_logger
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from .operator import SourceSequentialOperator, StreamingOperator
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from .operators import (
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from .recipe import Recipe
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from .schema import ToUnitxtGroup
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from .splitters import Sampler, SeparateSplit, SpreadSplit
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+
from .system_prompts import EmptySystemPrompt, SystemPrompt
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from .templates import Template
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logger = get_logger()
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class BaseRecipe(Recipe, SourceSequentialOperator):
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card: TaskCard
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template: Template = None
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system_prompt: SystemPrompt = Field(default_factory=EmptySystemPrompt)
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format: Format = Field(default_factory=SystemFormat)
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loader_limit: int = None
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demos_pool_size: int = None
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num_demos: int = 0
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demos_removed_from_data: bool = True
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demos_pool_name: str = "demos_pool"
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demos_taken_from: str = "train"
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from_split=self.demos_taken_from,
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to_split_names=[self.demos_pool_name, self.demos_taken_from],
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to_split_sizes=[int(self.demos_pool_size)],
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remove_targets_from_source_split=self.demos_removed_from_data,
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)
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)
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sampler=self.sampler,
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)
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)
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self.steps.append(self.system_prompt)
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self.steps.append(self.format)
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if self.augmentor.augment_model_input:
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self.steps.append(self.augmentor)
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class StandardRecipeWithIndexes(BaseRecipe):
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template_card_index: int = None
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def prepare(self):
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self.template = self.card.templates[self.template_card_index]
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except Exception as e:
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if isinstance(self.card.templates, dict):
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options = list(self.card.templates.keys())
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else:
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options = list(range(0, len(self.card.templates)))
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raise ValueError(
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f"card_template_index '{self.template_card_index}' is not defined in card. Possible card_template_index options: {options}"
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) from e
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super().prepare()
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Attributes:
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card (TaskCard): TaskCard object associated with the recipe.
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template (Template, optional): Template object to be used for the recipe.
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system_prompt (SystemPrompt, optional): SystemPrompt object to be used for the recipe.
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loader_limit (int, optional): Specifies the maximum number of instances per stream to be returned from the loader (used to reduce loading time in large datasets)
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format (SystemFormat, optional): SystemFormat object to be used for the recipe.
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train_refiner (StreamRefiner, optional): Train refiner to be used in the recipe.
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demos_pool_name (str, optional): Name of the demos pool. Default is "demos_pool".
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demos_taken_from (str, optional): Specifies from where the demos are taken. Default is "train".
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demos_field (str, optional): Field name for demos. Default is "demos".
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demos_removed_from_data (bool, optional): whether to remove the demos from the source data, Default is True
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sampler (Sampler, optional): Sampler object to be used in the recipe.
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steps (List[StreamingOperator], optional): List of StreamingOperator objects to be used in the recipe.
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augmentor (Augmentor) : Augmentor to be used to pseudo randomly augment the source text
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by arranging all the steps, refiners, and renderers in a sequential manner.
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Raises:
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AssertionError: If both template and template_card_index are specified at the same time.
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"""
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pass
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