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from abc import ABC |
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from typing import Any, Dict, List, Optional |
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from .dataclass import InternalField |
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from .formats import Format, ICLFormat |
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from .instructions import Instruction |
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from .operator import Operator, SequentialOperator, StreamInstanceOperator |
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from .random_utils import get_random |
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from .templates import Template |
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class Renderer(ABC): |
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pass |
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class RenderTemplate(Renderer, StreamInstanceOperator): |
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template: Template |
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random_reference: bool = False |
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skip_rendered_instance: bool = True |
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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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if self.skip_rendered_instance: |
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if ( |
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"inputs" not in instance |
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and "outputs" not in instance |
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and "source" in instance |
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and "target" in instance |
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and "references" in instance |
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): |
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return instance |
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inputs = instance["inputs"] |
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outputs = instance["outputs"] |
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source = self.template.process_inputs(inputs) |
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targets = self.template.process_outputs(outputs) |
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if self.template.is_multi_reference: |
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assert isinstance(targets, list), f"{targets} must be a list" |
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references = targets |
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if self.random_reference: |
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target = get_random().choice(references) |
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else: |
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if len(references) == 0: |
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raise ValueError("No references found") |
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target = references[0] |
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else: |
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references = [targets] |
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target = targets |
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instance.update( |
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{ |
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"source": source, |
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"target": target, |
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"references": references, |
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} |
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) |
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return instance |
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class RenderDemonstrations(RenderTemplate): |
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demos_field: str |
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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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demos = instance.get(self.demos_field, []) |
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processed_demos = [] |
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for demo_instance in demos: |
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demo_instance = super().process(demo_instance) |
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processed_demos.append(demo_instance) |
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instance[self.demos_field] = processed_demos |
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return instance |
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class RenderInstruction(Renderer, StreamInstanceOperator): |
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instruction: Instruction |
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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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if self.instruction is not None: |
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instance["instruction"] = self.instruction() |
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else: |
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instance["instruction"] = "" |
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return instance |
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class RenderFormat(Renderer, StreamInstanceOperator): |
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format: Format |
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demos_field: str = None |
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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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demos_instances = instance.pop(self.demos_field, None) |
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if demos_instances is not None: |
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instance["source"] = self.format.format( |
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instance, demos_instances=demos_instances |
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) |
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else: |
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instance["source"] = self.format.format(instance) |
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return instance |
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class StandardRenderer(Renderer, SequentialOperator): |
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template: Template |
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instruction: Instruction = None |
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demos_field: str = None |
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format: ICLFormat = None |
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steps: List[Operator] = InternalField(default_factory=list) |
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def prepare(self): |
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self.steps = [ |
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RenderTemplate(template=self.template), |
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RenderDemonstrations(template=self.template, demos_field=self.demos_field), |
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RenderInstruction(instruction=self.instruction), |
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RenderFormat(format=self.format, demos_field=self.demos_field), |
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] |
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def get_postprocessors(self): |
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return self.template.get_postprocessors() |
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