Also, I have checked the /tmp folder. the aforementioned file exists in that folder. apparently, flyte created that file as soon as the execution started and then it cannot access it anymore. surprising!

You have to upload the data and pass the s3//… key as ref

Hi @Ketan (kumare3), Please correct me if I am wrong: if there is any file access in the codebase, those files will be kept inside the tmp folder, even I am running Flyte in a cluster. My code does access some files for which I might get the aforementioned error. So, if I put those files somewhere else, I should be good, right? To test this hypothesis, I wrote the following code as a simple test where I am not accessing any file, but I am passing X and Y to a task from my workflow. So, technically it should run. But, unfortunately, I am still getting the same error saying Flyte could not convert the input of task as it could not read data from /tmp folder which is situated inside the master node. So apparently tasks parameters are also written to tmp folder. Could you suggest some way around it? Could it be the case that the blob store is not setup properly in my installation? -------------------- the experiment code: @task(container_image="istiyaksiddiquee/dummy-test-for-flyte:test01") def fitting_task( X: np.ndarray, Y: np.ndarray ) -> None: logreg = LogisticRegression(C=1e5) logreg.fit(X, Y) print("inside task") return @workflow def wf() -> None: iris = datasets.load_iris() X = iris.data[:, :2] Y = iris.target fitting_task(X=X, Y=Y) print("task returned") return ----------------- the error: Message: Failed to convert inputs of task 'workflows.example.fitting_task': Failed to get data from file:///tmp/flyte-ijh97429/raw/fb171d4d3d0ab819cf0ac3b38093a5c9/48d64e45692d894b249fa58163be483b.npy to /tmp/flytefk5c2_f3/local_flytekit/4380687bfa064af66da9d9657fdd75a4 (recursive=False). Original exception: Value error! Received: file:///tmp/flyte-ijh97429/raw/fb171d4d3d0ab819cf0ac3b38093a5c9/48d64e45692d894b249fa58163be483b.npy. File not found

update: I ran the same code in both my clusters. In the cluster where the code ran successfully, I can see the input locations are mentioned as s3://my-s3-bucket/.... and in the cluster where the code did not run successfully, the location is mentioned as file:///tmp/.... so clearly, there is some setting mismatch. but, I am running the same setup scripts for both the clusters. here are the two images depicting the setting mismatch. please help me in fixing this. thanks.

Hi @Ketan (kumare3), could you give me some input please?