Q&A
> 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
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
Python
1model.fit(X_train, 2 Y_train, 3 epochs=200, 4 batch_size=16, 5 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）
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。
すみません、notebookを追加したので確認お願いします。
あれ？
この質問は解決済みではありませんでしたっけ？
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。
> 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？？
回答2件
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投稿2023/09/19 08:04
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投稿2023/09/17 12:23
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