class_docstr: Schema for the `FeedbackDataset` metadata properties of type `float`. This kind
  of metadata property will be used for filtering the metadata of a record based on
  an float value to which `min` and `max` filters can be applied.
  
  Args:
      name: The name of the metadata property.
      title: A title of the metadata property (what's shown in the UI). Defaults to `None`,
          which means that if not provided then the `name` will be used as the `title`.
      visible_for_annotators: Whether the metadata property should be visible for
          users with the `annotator` role. Defaults to `True`.
      min: The lower bound of the float value. Must be provided, and be lower than
          the `max` value.
      max: The upper bound of the float value. Must be provided, and be greater than
          the `min` value.
  
  Examples:
      >>> from argilla.client.feedback.schemas.metadata import FloatMetadataProperty
      >>> FloatMetadataProperty(name="price", min=0.0, max=100.0)
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code: def _pydantic_field_with_validator(
      self,
  ) -> Tuple[Dict[str, tuple], Dict[str, Any]]:
      field_type, default_value = Optional[StrictFloat], None
      return {
          self.name: (field_type, default_value)
      }, _validator_definition(self)
  
imports: import math
  from abc import ABC, abstractmethod
  from typing import Any, Callable, Dict, List, Literal, Optional, Tuple, Union
  from argilla.client.feedback.schemas.enums import MetadataPropertyTypes
  from argilla.client.feedback.schemas.validators import validate_numeric_metadata_filter_bounds, validate_numeric_metadata_property_bounds
  from argilla.pydantic_v1 import BaseModel, Extra, Field, StrictFloat, StrictInt, StrictStr, ValidationError, root_validator, validator
label_desc: Use image node_id 2 for calling the FloatMetadataProperty obj's underlying member method code with example usage: obj._pydantic_field_with_validator() and returns: dict,  _validator_definition