class_docstr: This module learns positional embeddings up to a fixed maximum size.
docstr: `input_ids_shape` is expected to be [bsz x seqlen].
docstr_tok: ["`","input_ids_shape","`","is","expected","to","be","[","bsz","x","seqlen","]","."]
code: def __call__(self, positions):
      """`input_ids_shape` is expected to be [bsz x seqlen]."""
  
      return super().__call__(positions + self.offset)
  
imports: from functools import partial
  from typing import Optional, Tuple
  import flax.linen
  import jax
  import jax.numpy
  from flax.core.frozen_dict import FrozenDict, freeze, unfreeze
  from flax.linen import combine_masks, make_causal_mask
  from flax.linen.attention import dot_product_attention_weights
  from flax.traverse_util import flatten_dict, unflatten_dict
  from jax import lax
  from jax.random import PRNGKey
  from ...modeling_flax_outputs import FlaxBaseModelOutput, FlaxMaskedLMOutput
  from ...modeling_flax_utils import ACT2FN, FlaxPreTrainedModel, append_call_sample_docstring
  from ...utils import add_start_docstrings, logging
  from .configuration_opt import OPTConfig
label_desc: Use image node_id 2 for calling the FlaxOPTLearnedPositionalEmbedding obj's underlying member method code with example usage: obj.__call__(positions) and returns: super