code: def EmbeddingsOnCPUField(
      default: bool = False,
      description: str = None,
      parameter_metadata: ParameterMetadata = None,
  ) -> Field:
      description = description or (
          "Whether to force the placement of the embedding matrix in regular memory and have the CPU resolve them. "
          "By default embedding matrices are stored on GPU memory if a GPU is used, as it allows for faster access, "
          "but in some cases the embedding matrix may be too large. This parameter forces the placement of the "
          "embedding matrix in regular memory and the CPU is used for embedding lookup, slightly slowing down the "
          "process as a result of data transfer between CPU and GPU memory."
      )
      parameter_metadata = (
          parameter_metadata or COMMON_METADATA["embeddings_on_cpu"]
      )
      return schema_utils.Boolean(
          default=default,
          description=description,
          parameter_metadata=parameter_metadata,
      )
  
imports: from dataclasses import Field
  from typing import Optional
  from ludwig.schema import utils
  from ludwig.schema.metadata import COMMON_METADATA
  from ludwig.schema.metadata.parameter_metadata import ParameterMetadata
  from ludwig.utils.torch_utils import initializer_registry
label_desc: Use image node_id 11 for calling a global function with example usage: EmbeddingsOnCPUField(default, description, parameter_metadata) and returns: schema_utils