code: def test_vector_embedder():
      params = InputEmbedderParameters(scheme=EmbedderScheme.Medium)
      emb = VectorEmbedder(params=params)
      emb.initialize()
      input_data = mx.nd.random.uniform(
          low=0, high=255, shape=(10, 100)
      )
      output = emb(input_data)
      assert len(output.shape) == 2  # since last block was flatten
      assert output.shape[0] == 10  # since batch_size is 10
      assert output.shape[1] == 256
  
file_path: coach/rl_coach/tests/architectures/mxnet_components/embedders/test_vector_embedder.py
imports: import mxnet
  import os
  import pytest
  import sys
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.architectures.mxnet_components.embedders.vector_embedder import VectorEmbedder
  from rl_coach.base_parameters import EmbedderScheme
label_desc: Use image node_id 1 for calling a global function with example usage: test_vector_embedder() without return types