class_docstr: Transformer image encoder.
class_docstr_tok: ["Transformer","image","encoder","."]
code: def __call__(
      self,
      image: jnp.ndarray,
      *,
      train: bool = False,
      debug: bool = False,
  ) -> jnp.ndarray:
      return Transformer(
          num_heads=self.num_heads,
          head_dim=self.head_dim,
          mlp_dim=self.mlp_dim,
          num_layers=self.num_layers,
          dropout_rate=self.dropout_rate,
          activations=self.activations,
          dtype=self.dtype,
          return_all_tokens=self.return_all_tokens,
      )(image, train=train, debug=debug)
  
imports: from collections.abc import Callable
  from collections.abc import Sequence
  from typing import Optional
  from typing import Union
  import flax.linen
  import jax.numpy
  from scenic.projects.lang4video.model.base_encoders import ImageEncoder
  from scenic.projects.lang4video.model.base_encoders import TextEncoder
  from flaxformer.architectures.t5 import t5_1_1
  from flaxformer.components import layer_norm
  from flaxformer.components.attention import dense_attention
label_desc: Use image node_id 1 for calling the TransformerImageEncoder obj's underlying member method code with example usage: obj.__call__(image) and returns: Transformer