class_docstr: Draw activations of a specific layer for a given input
docstr: Generate a graph between inputs and targeted layers.
  
  Args:
      model (tf.keras.Model): tf.keras model to inspect
      layers_name (List[str]): List of layer names to inspect
  
  Returns:
      tf.keras.Model: Subgraph to the targeted layers
code: def generate_activations_graph(model, layers_name):
      """
      Generate a graph between inputs and targeted layers.
  
      Args:
          model (tf.keras.Model): tf.keras model to inspect
          layers_name (List[str]): List of layer names to inspect
  
      Returns:
          tf.keras.Model: Subgraph to the targeted layers
      """
      outputs = [
          layer.output
          for layer in model.layers
          if layer.name in layers_name
      ]
      activations_model = tf.keras.models.Model(
          model.inputs, outputs=outputs
      )
      activations_model.compile(
          optimizer="sgd", loss="categorical_crossentropy"
      )
  
      return activations_model
  
file_path: tf-explain/tf_explain/core/activations.py
imports: import numpy
  import tensorflow
  from tf_explain.utils.display import filter_display
  from tf_explain.utils.saver import save_grayscale
label_desc: Use image node_id 3 for calling the ExtractActivations obj's underlying member method code with example usage: obj.generate_activations_graph(model, layers_name) and returns: activations_model