AttributeError: module 'tensorflow_federated.python.simulation' has no attribute 'HDF5ClientData'

Question

I have a dataset written to an h5 file, and I want to convert it totff.simulation.datasets.ClientData,That is, after pre-processing it becomes this form <tensorflow_federated.python.simulation.datasets.client_data.PreprocessClientData at 0x7f00947f6f50>. A week ago, I was able to read it with this

train_path='FederatedClients/dataTrain.h5'
train_data = tff.simulation.HDF5ClientData(train_path)

but now, I get the following error with this statement again.

----------------------------------------------------------
AttributeError           Traceback (most recent call last)
<ipython-input-6-f4c34c62ca50> in <module>
      1 train_path='FederatedClients/dataTrain.h5'
      2 #train_data=pd.read_hdf(train_path)
----> 3 train_data = tff.simulation.HDF5ClientData(train_path)
      4 test_path='FederatedClients/dataTest.h5'
      5 test_data=pd.read_hdf(test_path)

AttributeError: module 'tensorflow_federated.python.simulation' has no attribute 'HDF5ClientData'

I don't know what to do anymore, I use the most basic panda to read the H5 file and I also get the error, TAT

train_data=pd.read_hdf(train_path)

----------------------------------------------------------
ValueError               Traceback (most recent call last)
<ipython-input-7-151fe098668c> in <module>
      1 train_path='FederatedClients/dataTrain.h5'
----> 2 train_data=pd.read_hdf(train_path)
      3 train_data = tff.simulation.HDF5ClientData(train_path)
      4 test_path='FederatedClients/dataTest.h5'
      5 test_data=pd.read_hdf(test_path)

~/anaconda3/envs/tff/lib/python3.7/site-packages/pandas/io/pytables.py in read_hdf(path_or_buf, key, mode, errors, where, start, stop, columns, iterator, chunksize, **kwargs)
    437             if len(groups) == 0:
    438                 raise ValueError(
--> 439                     "Dataset(s) incompatible with Pandas data types, "
    440                     "not table, or no datasets found in HDF5 file."
    441                 )

ValueError: Dataset(s) incompatible with Pandas data types, not table, or no datasets found in HDF5 file.

I would be grateful if you could solve my problem

Zachary Garrett · Accepted Answer · 2021-08-05 16:48:39Z

1

TFF version 0.19.0 removed tff.simulation.HDF5ClientData (release notes). TFF datasets are now backed by SQLite instead of HDF5.

The HDF5 implementation could be recovered from https://github.com/tensorflow/federated/blob/v0.18.0/tensorflow_federated/python/simulation/hdf5_client_data.py. Copying that locally and replacing:

client_data.ClientData with tff.simulation.datasets.ClientData.
Remove py_typecheck and tensor_utils usage, they are not necessary.

answered Aug 5, 2021 at 16:48

Zachary Garrett

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3 Comments

zhaoyumeng Over a year ago

Thank you very much for your answer. But when I did what you said, I had other error【---------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-18-c38025bbc72a> in <module> 1 train_path='FederatedClients/dataTrain.h5' 2 #train_data=pd.read_hdf(train_path) ----> 3 train_data = HDF5ClientData(train_path) 4 test_path='FederatedClients/dataTest.h5' 5 test_data=pd.read_hdf(test_path) TypeError: Can't instantiate abstract class HDF5ClientData with abstract methods serializable_dataset_fn】

zhaoyumeng Over a year ago

I copy that locally and replace,when I use"train_path='FederatedClients/dataTrain.h5' train_data = HDF5ClientData(train_path)", the above error occurs. QAQ Thank you again for answering my confusion!!!

zhaoyumeng Over a year ago

Hello, do you know why this error occurred? Again, I would like to ask for your help, thank you very much!!

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