class_docstr: Language model embeddings.
  
  Arguments:
      hidden_size: hidden size
      vocab_size: vocabulary size
      max_sequence_length: maximum size of sequence. This
                           is used for positional embedding
      embedding_dropout_prob: dropout probability for embeddings
      init_method: weight initialization method
      num_tokentypes: size of the token-type embeddings. 0 value
                      will ignore this embedding
      position_embedding_type: position embedding type determines whether we instantiate a learnable position embedding table.
docstr: Zero out all parameters in embedding.
docstr_tok: ["Zero","out","all","parameters","in","embedding","."]
code: def zero_parameters(self):
      """Zero out all parameters in embedding."""
      self.word_embeddings.weight.data.fill_(0)
      self.word_embeddings.weight.shared = True
      if self.position_embedding_type == "learned_absolute":
          self.position_embeddings.weight.data.fill_(0)
          self.position_embeddings.weight.shared = True
      if self.num_tokentypes > 0:
          self.tokentype_embeddings.weight.data.fill_(0)
          self.tokentype_embeddings.weight.shared = True
  
imports: from ast import Mod
  import torch
  from nemo.collections.nlp.modules.common.megatron.adapters.parallel_adapters import AdapterName, PromptEncoderAdapterConfig
  from nemo.collections.nlp.modules.common.megatron.layer_type import LayerType
  from nemo.collections.nlp.modules.common.megatron.module import MegatronModule
  from nemo.collections.nlp.modules.common.megatron.position_embedding import ALiBiRelativePositionEmbedding, KERPLERelativePositionEmbedding, RotaryEmbedding, SandwichRelativePositionEmbedding
  from nemo.collections.nlp.modules.common.megatron.transformer import ParallelTransformer
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults, get_linear_layer, init_method_normal, scaled_init_method_normal
  from nemo.collections.nlp.parts import utils_funcs
  from nemo.core import adapter_mixins
label_desc: Use image node_id 2 for calling the Embedding obj's underlying member method code with example usage: obj.zero_parameters() without return types