c0052c1533
Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/pull/2132 This diff adds the class IndexFlatCodes that becomes the parent of all "flat" encodings. IndexPQ IndexFlat IndexAdditiveQuantizer IndexScalarQuantizer IndexLSH Index2Layer The other changes are: - for IndexFlat, there is no vector<float> with the data anymore. It is replaced with a `get_xb()` function. This broke quite a few external codes, that this diff also attempts to fix. - I/O functions needed to be adapted. This is done without changing the I/O format for any index. - added a small contrib function to get the data from the IndexFlat - the functionality has been made uniform, for example remove_ids and add are now in the parent class. Eventually, we may support generic storage for flat indexes, similar to `InvertedLists`, eg to memmap the data, but this will again require a big change. Reviewed By: wickedfoo Differential Revision: D32646769 fbshipit-source-id: 04a1659173fd51b130ae45d345176b72183cae40 |
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| .. | ||
| README.md | ||
| __init__.py | ||
| client_server.py | ||
| datasets.py | ||
| evaluation.py | ||
| exhaustive_search.py | ||
| factory_tools.py | ||
| inspect_tools.py | ||
| ivf_tools.py | ||
| ondisk.py | ||
| rpc.py | ||
| torch_utils.py | ||
| vecs_io.py | ||
README.md
The contrib modules
The contrib directory contains helper modules for Faiss for various tasks.
Code structure
The contrib directory gets compiled in the module faiss.contrib. Note that although some of the modules may depend on additional modules (eg. GPU Faiss, pytorch, hdf5), they are not necessarily compiled in to avoid adding dependencies. It is the user's responsibility to provide them.
In contrib, we are progressively dropping python2 support.
List of contrib modules
rpc.py
A very simple Remote Procedure Call library, where function parameters and results are pickled, for use with client_server.py
client_server.py
The server handles requests to a Faiss index. The client calls the remote index. This is mainly to shard datasets over several machines, see Distributd index
ondisk.py
Encloses the main logic to merge indexes into an on-disk index. See On-disk storage
exhaustive_search.py
Computes the ground-truth search results for a dataset that possibly does not fit in RAM. Uses GPU if available.
Tested in tests/test_contrib.TestComputeGT
torch_utils.py
Interoperability functions for pytorch and Faiss: Importing this will allow pytorch Tensors (CPU or GPU) to be used as arguments to Faiss indexes and other functions. Torch GPU tensors can only be used with Faiss GPU indexes. If this is imported with a package that supports Faiss GPU, the necessary stream synchronization with the current pytorch stream will be automatically performed.
Numpy ndarrays can continue to be used in the Faiss python interface after importing this file. All arguments must be uniformly either numpy ndarrays or Torch tensors; no mixing is allowed.
Tested in tests/test_contrib_torch.py (CPU) and gpu/test/test_contrib_torch_gpu.py (GPU).
inspect_tools.py
Functions to inspect C++ objects wrapped by SWIG. Most often this just means reading fields and converting them to the proper python array.
ivf_tools.py
A few functions to override the coarse quantizer in IVF, providing additional flexibility for assignment.
datasets.py
(may require h5py)
Defintion of how to access data for some standard datsets.
factory_tools.py
Functions related to factory strings.
evaluation.py
A few non-trivial evaluation functions for search results