Upload formats.py with huggingface_hub
Browse files- formats.py +101 -72
formats.py
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pass
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class
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)
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)
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instruction = ""
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if "instruction" in instance:
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assert (
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), f"
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+ self.demo_separator
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)
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if self.size_limiter is not None:
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if not self.size_limiter.check(
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source + demo_str + query_str + instance["target"]
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):
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continue
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source += demo_str
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source += query_str
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source += self.suffix
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return source
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from typing import (
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Any,
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Dict,
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List,
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Optional,
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)
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from .operator import StreamInstanceOperator
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from .type_utils import isoftype
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class Format(StreamInstanceOperator):
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pass
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class SystemFormat(Format):
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r"""Generates the whole input to the model, from constant strings that are given as args, and from values found in specified fields of the instance.
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SystemFormat expects the input instance to contain:
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1. A field named "source" whose value is a string verbalizing the original values in the instance (as read
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from the source dataset), in the context of the underlying task.
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2. A field named "instruction" that contains a (non-None) string.
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3. A field named with the value in arg 'demos_field', containing a list of dicts, each dict with fields "source"
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and "target", representing a single demo.
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SystemFormat formats the above fields into a single string to be inputted to the model. This string overwrites
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field "source" of the instance. Formatting is driven by two args: 'demo_format' and 'model_input_format'.
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SystemFormat also pops field "instruction" and the field containing the demos out from the input instance.
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Args:
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demos_field (str): the name of the field that contains the demos, being a list of dicts, each with "source" and "target" keys
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demo_format (str): formatting string for a single demo, combining fields "source" and "target"
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model_input_format (str) overall product format, combining instruction and source (as read from fields "instruction"
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and "source" of the input instance), together with demos (as formatted into one string)
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Example:
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when input instance:
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{
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"source": "1+1",
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"target": "2",
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"instruction": "Solve the math exercises.",
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"demos": [{"source": "1+2", "target": "3"}, {"source": "4-2", "target": "2"}]
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}
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is process-ed by
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system_format = SystemFormat(
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demos_field="demos",
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demo_format="Input: {source}\nOutput: {target}\n\n",
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model_input_format="Instruction: {instruction}\n\n{demos}Input: {source}\nOutput: ",
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)
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the resulting instance is:
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{
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"target": "2",
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"source": "Instruction: Solve the math exercises.\n\nInput: 1+2\nOutput: 3\n\nInput: 4-2\nOutput: 2\n\nInput: 1+1\nOutput: ",
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}
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"""
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demos_field: str = "demos"
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demo_format: str = (
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"{source}\n{target}\n\n" # example: "User: {source}\nAgent: {target}\n\n"
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)
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model_input_format: str = "{instruction}{demos}{source}\n"
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@staticmethod
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def _retrieve_field_and_assert_not_none(instance, field_name) -> str:
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if field_name is not None and field_name in instance:
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field_value = instance[field_name]
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assert (
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field_value is not None
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), f"Value in field '{field_name}' should not be none. Received instance: {instance}"
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return field_value
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return ""
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def process(
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self, instance: Dict[str, Any], stream_name: Optional[str] = None
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) -> Dict[str, Any]:
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assert (
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"source" in instance
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), f"field 'source' is expected to be in the input instance. Received instance: {instance}"
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source = self._retrieve_field_and_assert_not_none(
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instance=instance, field_name="source"
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)
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instruction = self._retrieve_field_and_assert_not_none(
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instance=instance, field_name="instruction"
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)
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# pop "instruction" from instance
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if "instruction" in instance:
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instance.pop("instruction")
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demo_instances = []
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if self.demos_field is not None and self.demos_field in instance:
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demos = instance[self.demos_field]
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assert (
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demos is not None and isoftype(demos, List[Dict[str, Any]])
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), f"A list of dict-s is expected in field '{self.demos_field}'. Received instance: {instance}"
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demo_instances = demos
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# pop demos from instance
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instance.pop(self.demos_field)
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demos_string = ""
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for demo_instance in demo_instances:
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demo_str = self.demo_format.format(**demo_instance)
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demos_string += demo_str
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output = self.model_input_format.format(
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instruction=instruction,
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demos=demos_string,
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source=source,
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)
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instance["source"] = output
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return instance
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