code: def test_data_logger_val_inferred_proc_no_class(wandb_init):
      run = wandb_init()
      vd = ValidationDataLogger(
          inputs=np.array([[i, i, i] for i in range(10)]),
          targets={
              "simple": np.random.randint(5, size=(10)),
              "wrapped": np.random.randint(5, size=(10, 1)),
              "logits": np.random.randint(5, size=(10, 5))
              + 2,  # +2 avoids only having 0s and 1s
              "nodes": np.random.randint(5, size=(10, 10)),
              "2dimages": np.random.randint(255, size=(10, 5, 5)),
              "3dimages": np.random.randint(255, size=(10, 5, 5, 3)),
              "video": np.random.randint(255, size=(10, 5, 5, 3, 10)),
          },
          indexes=None,
          validation_row_processor=None,
          prediction_row_processor=None,
          class_labels=None,
          infer_missing_processors=True,
      )
  
      cols = [
          "input",
          "simple",
          "wrapped",
          "logits",
          "nodes",
          "2dimages",
          "3dimages",
          "video",
          "input:node",
          "input:argmax",
          "input:argmin",
          "wrapped:val",
          "logits:node",
          "logits:argmax",
          "logits:argmin",
          "nodes:node",
          "nodes:argmax",
          "nodes:argmin",
      ]
  
      if CAN_INFER_IMAGE_AND_VIDEO:
          cols.append("2dimages:image")
          cols.append("3dimages:image")
          cols.append("video:video")
  
      tcols = vd.validation_indexes[0]._table.columns
  
      row = vd.validation_indexes[0]._table.data[0]
      assert set(tcols) == set(cols)
      assert np.all(row[tcols.index("input")] == [0, 0, 0])
      assert isinstance(row[tcols.index("simple")].tolist(), int)
      assert len(row[tcols.index("wrapped")]) == 1
      assert len(row[tcols.index("logits")]) == 5
      assert len(row[tcols.index("nodes")]) == 10
      assert row[tcols.index("2dimages")].shape == (5, 5)
      assert row[tcols.index("3dimages")].shape == (5, 5, 3)
      assert row[tcols.index("video")].shape == (5, 5, 3, 10)
      # assert isinstance(row[tcols.index("input:node")], dict)
      assert isinstance(row[tcols.index("input:node")], list)
      assert isinstance(row[tcols.index("input:argmax")].tolist(), int)
      assert isinstance(row[tcols.index("input:argmin")].tolist(), int)
      assert isinstance(row[tcols.index("wrapped:val")].tolist(), int)
      # assert isinstance(row[tcols.index("logits:node")], dict)
      assert isinstance(row[tcols.index("logits:node")], list)
      assert isinstance(row[tcols.index("logits:argmax")].tolist(), int)
      assert isinstance(row[tcols.index("logits:argmin")].tolist(), int)
      # assert isinstance(row[tcols.index("nodes:node")], dict)
      assert isinstance(row[tcols.index("nodes:node")], list)
      assert isinstance(row[tcols.index("nodes:argmax")].tolist(), int)
      assert isinstance(row[tcols.index("nodes:argmin")].tolist(), int)
  
      if CAN_INFER_IMAGE_AND_VIDEO:
          assert isinstance(
              row[tcols.index("2dimages:image")], wandb.data_types.Image
          )
          assert isinstance(
              row[tcols.index("3dimages:image")], wandb.data_types.Image
          )
          assert isinstance(
              row[tcols.index("video:video")], wandb.data_types.Video
          )
      run.finish()
  
file_path: wandb/tests/pytest_tests/system_tests/test_core/test_validation_data_logger.py
imports: import numpy
  import pytest
  import wandb
  import wandb.data_types
  from wandb.sdk.integration_utils.data_logging import CAN_INFER_IMAGE_AND_VIDEO, ValidationDataLogger
label_desc: Use image node_id 7 for calling a global function with example usage: test_data_logger_val_inferred_proc_no_class(wandb_init) without return types