Class: Transformers::Vit::ViTEncoder

Inherits:
Torch::NN::Module
  • Object
show all
Defined in:
lib/transformers/models/vit/modeling_vit.rb

Instance Method Summary collapse

Constructor Details

#initialize(config) ⇒ ViTEncoder 



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# File 'lib/transformers/models/vit/modeling_vit.rb', line 288

def initialize(config)
  super()
  @config = config
  @layer = Torch::NN::ModuleList.new(config.num_hidden_layers.times.map { ViTLayer.new(config) })
  @gradient_checkpointing = false
end

Instance Method Details

#forward(hidden_states, head_mask: nil, output_attentions: false, output_hidden_states: false, return_dict: true) ⇒ Object 



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# File 'lib/transformers/models/vit/modeling_vit.rb', line 295

def forward(
  hidden_states,
  head_mask: nil,
  output_attentions: false,
  output_hidden_states: false,
  return_dict: true
)
  all_hidden_states = output_hidden_states ? [] : nil
  all_self_attentions = output_attentions ? [] : nil

  @layer.each_with_index do |layer_module, i|
    if output_hidden_states
      all_hidden_states = all_hidden_states + [hidden_states]
    end

    layer_head_mask = !head_mask.nil? ? head_mask[i] : nil

    if @gradient_checkpointing && @training
      raise Todo
    else
      layer_outputs = layer_module.(hidden_states, head_mask: layer_head_mask, output_attentions: output_attentions)
    end

    hidden_states = layer_outputs[0]

    if output_attentions
      all_self_attentions = all_self_attentions + [layer_outputs[1]]
    end
  end

  if output_hidden_states
    all_hidden_states = all_hidden_states + [hidden_states]
  end

  if !return_dict
    raise Todo
  end
  BaseModelOutput.new(
    last_hidden_state: hidden_states,
    hidden_states: all_hidden_states,
    attentions: all_self_attentions
  )
end