[Graph execution error:]Colab notebookでKerasを試した際にエラーがでる

Question

前提

Google Colabで発生するエラーについてです。
Google Colabでkerasのモデルをfitした際に、InvalidArgumentError: Graph execution error:が出ます。
こちらのKaggle notebookを参考に、google colab上で同じデータセット、コードで実行しました。

参考:画像分類手法を用いた時系列分類手法とKaggle Code輪読会のご紹介

RecuPlots and CNNs for time-series classification: ()

実現したいこと

ここに実現したいことを箇条書きで書いてください。

• 他のnotebookでもエラーが出ないようにしたい

発生している問題・エラーメッセージ

エラーメッセージ
Epoch 1/200
---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-20-3618e15fd333> in <module>
      3           epochs=200,
      4           batch_size=16,
----> 5           shuffle=True)

1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     53     ctx.ensure_initialized()
     54     tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
---> 55                                         inputs, attrs, num_outputs)
     56   except core._NotOkStatusException as e:
     57     if name is not None:

InvalidArgumentError: Graph execution error:

Detected at node 'gradient_tape/sequential_2/conv2d_4/Conv2D/Conv2DBackpropFilter' defined at (most recent call last):
    File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main
      "__main__", mod_spec)
    File "/usr/lib/python3.7/runpy.py", line 85, in _run_code
      exec(code, run_globals)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module>
      app.launch_new_instance()
    File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance
      app.start()
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 612, in start
      self.io_loop.start()
    File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start
      self.asyncio_loop.run_forever()
    File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever
      self._run_once()
    File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once
      handle._run()
    File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run
      self._context.run(self._callback, *self._args)
    File "/usr/local/lib/python3.7/dist-packages/tornado/ioloop.py", line 758, in _run_callback
      ret = callback()
    File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1233, in inner
      self.run()
    File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1147, in run
      yielded = self.gen.send(value)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 365, in process_one
      yield gen.maybe_future(dispatch(*args))
    File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper
      yielded = next(result)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell
      yield gen.maybe_future(handler(stream, idents, msg))
    File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper
      yielded = next(result)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 545, in execute_request
      user_expressions, allow_stdin,
    File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper
      yielded = next(result)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 306, in do_execute
      res = shell.run_cell(code, store_history=store_history, silent=silent)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 536, in run_cell
      return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2855, in run_cell
      raw_cell, store_history, silent, shell_futures)
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2881, in _run_cell
      return runner(coro)
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner
      coro.send(None)
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3058, in run_cell_async
      interactivity=interactivity, compiler=compiler, result=result)
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3249, in run_ast_nodes
      if (await self.run_code(code, result,  async_=asy)):
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3326, in run_code
      exec(code_obj, self.user_global_ns, self.user_ns)
    File "<ipython-input-20-3618e15fd333>", line 5, in <module>
      shuffle=True)
    File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1384, in fit
      tmp_logs = self.train_function(iterator)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function
      return step_function(self, iterator)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step
      outputs = model.train_step(data)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 863, in train_step
      self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
    File "/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/optimizer_v2.py", line 531, in minimize
      loss, var_list=var_list, grad_loss=grad_loss, tape=tape)
    File "/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/optimizer_v2.py", line 583, in _compute_gradients
      grads_and_vars = self._get_gradients(tape, loss, var_list, grad_loss)
    File "/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/optimizer_v2.py", line 464, in _get_gradients
      grads = tape.gradient(loss, var_list, grad_loss)
Node: 'gradient_tape/sequential_2/conv2d_4/Conv2D/Conv2DBackpropFilter'
Conv2DCustomBackpropFilterOp only supports NHWC.
	 [[{{node gradient_tape/sequential_2/conv2d_4/Conv2D/Conv2DBackpropFilter}}]] [Op:__inference_train_function_2797]

該当のソースコード

model.fit(X_train, 
          Y_train, 
          epochs=200, 
          batch_size=16,
          shuffle=True)

試したこと

該当データセットの変更、playgraund modeでの実行
正常notebook、異常notebookの両方で確認しましたが、データセットの変更、playground modeでも異常notebookのみで同様のエラーが出ました。また、セルをコピペしても同様のエラーが出ました。

補足情報（FW/ツールのバージョンなど）

Comments

[jbpb0]

> 必要であれば該当notebookを公開します

そうした方がいいでしょうね
「正常notebook」と「異常notebook」の両方を公開して、他人が実行して現象を再現させられるようにしないと、他人には状況が分かりませんので

[drango]

回答いただきありがとうございます。
質問なのですが、上記のGraph execution error:のエラー文のみでは判断が難しいのでしょうか。
補足ですが、notebookの内容はurlのkaggleのものと全く同じです。

[drango]

すみません、notebookを追加したので確認お願いします。

[jbpb0]

あれ？
この質問は解決済みではありませんでしたっけ？

[drango]

解決済みでしたが、回答者が答えを消してしまったようです。

[jbpb0]

> 回答者が答えを消してしまった

回答がベストアンサーになっても、削除することができるのですか
知らなかった

その回答内容を質問者さんが回答に書いて、自己解決にしたらいかがでしょうか
たしか、gpuを使うかどうかで、エラーになったりならなかったりするのでしたっけ？？