code: def report_csv(
      self,
      all_ops: List[str],
      passed: List[Optional[str]],
      experimental: List[str],
  ) -> None:
      for schema in _all_schemas:
          if schema.domain in {"", "ai.onnx"}:
              all_ops.append(schema.name)
              if (
                  schema.support_level
                  == defs.OpSchema.SupportType.EXPERIMENTAL
              ):
                  experimental.append(schema.name)
      all_ops.sort()
      nodes_path = os.path.join(
          str(os.environ.get("CSVDIR")), "nodes.csv"  # type: ignore
      )  # type: ignore
      models_path = os.path.join(
          str(os.environ.get("CSVDIR")), "models.csv"  # type: ignore
      )  # type: ignore
      existing_nodes: OrderedDict[str, Dict[str, str]] = OrderedDict()
      existing_models: OrderedDict[str, Dict[str, str]] = OrderedDict()
      frameworks: List[str] = []
      if os.path.isfile(nodes_path):
          with open(nodes_path) as nodes_file:
              reader = csv.DictReader(nodes_file)
              assert reader.fieldnames
              frameworks = list(reader.fieldnames)
              for row in reader:
                  op = row["Op"]
                  del row["Op"]
                  existing_nodes[str(op)] = row
      if os.path.isfile(models_path):
          with open(models_path) as models_file:
              reader = csv.DictReader(models_file)
              for row in reader:
                  model = row["Model"]
                  del row["Model"]
                  existing_models[str(model)] = row
      backend = os.environ.get("BACKEND")
      other_frameworks = frameworks[1:]
      with open(nodes_path, "w") as nodes_file:
          if "Op" not in frameworks:
              frameworks.append("Op")
          if backend not in frameworks:
              frameworks.append(str(backend))
          else:
              other_frameworks.remove(str(backend))
          node_writer = csv.DictWriter(
              nodes_file, fieldnames=frameworks
          )
          node_writer.writeheader()
          for node in all_ops:
              node_name = node
              if node in experimental:
                  node_name = node + " (Experimental)"
              if node_name not in existing_nodes:
                  # Also add Skipped for other nodes
                  existing_nodes[node_name] = OrderedDict()
                  for other_framework in other_frameworks:
                      existing_nodes[node_name][
                          other_framework
                      ] = "Skipped!"
              if node in passed:
                  existing_nodes[node_name][str(backend)] = "Passed!"
              else:
                  existing_nodes[node_name][str(backend)] = "Failed!"
          summaries: Dict[Any, Any] = {}
          if "Summary" in existing_nodes:
              summaries = existing_nodes["Summary"]
              del existing_nodes["Summary"]
          summaries[
              str(backend)
          ] = f"{len(passed)}/{len(all_ops)} node tests passed"
          summaries["Op"] = "Summary"
          for node in existing_nodes:
              existing_nodes[node]["Op"] = str(node)
              node_writer.writerow(existing_nodes[node])
          node_writer.writerow(summaries)
      with open(models_path, "w") as models_file:
          frameworks[0] = "Model"
          model_writer = csv.DictWriter(
              models_file, fieldnames=frameworks
          )
          model_writer.writeheader()
          # Consider both buckets
          num_models = 0
          for bucket in self.models:
              for model in self.models[bucket]:  # type: ignore
                  # Both analyze and run the model on the backend
                  num_covered = 0
                  for node in self.models[bucket][model].node_coverages:
                      if node in passed:
                          num_covered += 1
                  # TODO: Identify if there are models that are being
                  # skipped/not loaded, but that are in other frameworks
                  msg = "Passed!"
                  if bucket == "loaded":
                      if model in self.models["passed"]:
                          continue
                      msg = "Failed!"
                  num_models += 1
                  if model not in existing_models:
                      # Also add Skipped for other models
                      existing_models[model] = OrderedDict()
                      for other_framework in other_frameworks:
                          existing_models[model][
                              other_framework
                          ] = "Skipped!"
                  existing_models[model][str(backend)] = str(
                      f"{num_covered}/{len(self.models[bucket][model].node_coverages)} nodes covered: {msg}"
                  )
          summaries.clear()
          if "Summary" in existing_models:
              summaries = existing_models["Summary"]
              del existing_models["Summary"]
          if str(backend) in summaries:
              del summaries[str(backend)]
          summaries[
              str(backend)
          ] = f"{len(self.models['passed'])}/{num_models} model tests passed"
          summaries["Model"] = "Summary"
          for model in existing_models:  # type: ignore
              existing_models[model]["Model"] = model
              model_writer.writerow(existing_models[model])
          model_writer.writerow(summaries)
      with open(
          os.path.join(str(os.environ.get("CSVDIR")), "metadata.csv"),  # type: ignore
          "w",
      ) as metadata_file:  # type: ignore
          metadata_writer = csv.writer(metadata_file)
          metadata_writer.writerow(
              [
                  "Latest Update",
                  datetime.datetime.now().isoformat().replace("T", " "),
              ]
          )
  
imports: import csv
  import datetime
  import os
  from collections import OrderedDict, defaultdict
  from typing import IO, Any, Dict, List, Optional, Set
  from tabulate import tabulate
  import onnx
  from onnx import GraphProto, defs, helper
label_desc: Use image node_id 7 for calling the Coverage obj's underlying member method code with example usage: obj.report_csv(all_ops, passed, experimental) without return types