code: def test_log_batch_with_many_elements():
      num_metrics = MAX_METRICS_PER_BATCH * 2
      num_params = num_tags = MAX_PARAMS_TAGS_PER_BATCH * 2
      expected_metrics = {
          f"metric-key{i}": float(i) for i in range(num_metrics)
      }
      expected_params = {
          f"param-key{i}": f"param-val{i}" for i in range(num_params)
      }
      exact_expected_tags = {
          f"tag-key{i}": f"tag-val{i}" for i in range(num_tags)
      }
  
      t = get_current_time_millis()
      sorted_expected_metrics = sorted(
          expected_metrics.items(), key=lambda kv: kv[1]
      )
      metrics = [
          Metric(key=key, value=value, timestamp=t, step=i)
          for i, (key, value) in enumerate(sorted_expected_metrics)
      ]
      params = [
          Param(key=key, value=value)
          for key, value in expected_params.items()
      ]
      tags = [
          RunTag(key=key, value=value)
          for key, value in exact_expected_tags.items()
      ]
  
      with start_run() as active_run:
          run_id = active_run.info.run_id
          mlflow.tracking.MlflowClient().log_batch(
              run_id=run_id, metrics=metrics, params=params, tags=tags
          )
      client = tracking.MlflowClient()
      finished_run = client.get_run(run_id)
      # Validate metrics
      assert expected_metrics == finished_run.data.metrics
      for i in range(num_metrics):
          metric_history = client.get_metric_history(
              run_id, f"metric-key{i}"
          )
          assert {
              (m.value, m.timestamp, m.step) for m in metric_history
          } == {(float(i), t, i)}
  
      # Validate tags
      logged_tags = finished_run.data.tags
      for tag_key, tag_value in exact_expected_tags.items():
          assert logged_tags[tag_key] == tag_value
  
      # Validate params
      assert finished_run.data.params == expected_params
  
imports: import filecmp
  import json
  import os
  import pathlib
  import posixpath
  import random
  import re
  from collections import namedtuple
  from unittest import mock
  import pytest
  import yaml
  import mlflow
  from mlflow import MlflowClient, tracking
  from mlflow.entities import LifecycleStage, Metric, Param, RunStatus, RunTag, ViewType
  from mlflow.environment_variables import MLFLOW_RUN_ID
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE, RESOURCE_DOES_NOT_EXIST, ErrorCode
  from mlflow.store.tracking.file_store import FileStore
  from mlflow.tracking.fluent import start_run
  from mlflow.utils.file_utils import local_file_uri_to_path
  from mlflow.utils.mlflow_tags import MLFLOW_PARENT_RUN_ID, MLFLOW_RUN_NAME, MLFLOW_SOURCE_NAME, MLFLOW_SOURCE_TYPE, MLFLOW_USER
  from mlflow.utils.os import is_windows
  from mlflow.utils.time import get_current_time_millis
  from mlflow.utils.validation import MAX_METRICS_PER_BATCH, MAX_PARAMS_TAGS_PER_BATCH
label_desc: Use image node_id 14 for calling a global function with example usage: test_log_batch_with_many_elements() without return types