h5py

问题 Got a big data-set that I want to shuffle. The entire set won't fit into RAM so it would be good if I could open several files (e.g. hdf5, numpy) simultaneously, loop through my data chronologically and randomly assign each data-point to one of the piles (then afterwards shuffle each pile). I'm really inexperienced with working with data in python so I'm not sure if it's possible to write to files without holding the rest of its contents in RAM (been using np.save and savez with little

问题 While playing with HDF5 package for Python I discovered a strange behavior. I want to insert more data into table. But somehow I cannot get it work properly. As you can see from the source code, I am getting the last row of data in key 'X' using fromRow = hf["X"].shape[0] and writing the tempArray2 afterwards. Result is an empty table. import h5py tempArray1 = [[0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0

问题 I'm trying to open a HDF5 file in Python using the following code: with h5py.File('example.hdf5', 'r') as f: ls = list(f.keys()) dat = f.get('data') dt = np.array(dat) However, I get this error when executing the last line: AttributeError: 'int' object has no attribute 'encode' dat has the following class: h5py._hl.group.Group' Anyone knows where the error could come? The output from iterating inside the file is the following. How can I access inside each part of the file: checking hdf5 file

问题 We are working with large (1.2TB) uncompressed, unchunked hdf5 files with h5py in python for a machine learning application, which requires us to work through the full dataset repeatedly, loading slices of ~15MB individually in a randomized order. We are working on a linux (Ubuntu 18.04) machine with 192 GB RAM. We noticed that the program is slowly filling the cache. When total size of cache reaches size comparable with full machine RAM (free memory in top almost 0 but plenty ‘available’

问题 I am trying to read h5 file from AWS S3. I am getting the following errors using s3fs/boto3. Can you help? Thanks! import s3fs fs = s3fs.S3FileSystem(anon=False, key='key', secret='secret') with fs.open('file', mode='rb') as f: h5 = pd.read_hdf(f) TypeError: expected str, bytes or os.PathLike object, not S3File fs = s3fs.S3FileSystem(anon=False, key='key', secret='secret') with fs.open('file', mode='rb') as f: hf = h5py.File(f) TypeError: expected str, bytes or os.PathLike object, not S3File

问题 I'm trying to load hdf5 datasets into a pytorch training for loop. Regardless of num_workers in dataloader, this randomly throws "KeyError: 'Unable to open object (component not found)' " (traceback below). I'm able to start the training loop, but not able to get through 1/4 of one epoch without this error which happens for random 'datasets' (which are 2darrays each). I'm able to separately load these arrays in the console using the regular f['group/subroup'][()] so it doesn't appear like the

问题 I'm trying to use parallel h5py to create an independent group for each process and fill each group with some data.. what happens is that only one group gets created and filled with data. This is the program: from mpi4py import MPI import h5py rank = MPI.COMM_WORLD.Get_rank() f = h5py.File('parallel_test.hdf5', 'w', driver='mpio', comm=MPI.COMM_WORLD) data = range(1000) dset = f.create_dataset(str(rank), data=data) f.close() Any thoughts on what is going wrong here? Thanks alot 回答1: Ok, so as

问题 I am trying to append the hdf5 dataset to the previous hdf5 dataset following error occured h5o.link(obj.id, self.id, name, lcpl=lcpl, lapl=self._lapl) File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper File "h5py/h5o.pyx", line 202, in h5py.h5o.link RuntimeError: Unable to create link (name already exists) sal_maps = np.array([], dtype=np.float32).reshape((0,) + img_size) probs = np.array([], dtype=np

问题 I am trying to append the hdf5 dataset to the previous hdf5 dataset following error occured h5o.link(obj.id, self.id, name, lcpl=lcpl, lapl=self._lapl) File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper File "h5py/h5o.pyx", line 202, in h5py.h5o.link RuntimeError: Unable to create link (name already exists) sal_maps = np.array([], dtype=np.float32).reshape((0,) + img_size) probs = np.array([], dtype=np

来源： https://stackoverflow.com/questions/63810835/tensorflow-2-x-cannot-load-trained-model-in-h5-format-when-using-embedding-colu