This moves all tests from
`tests/end_to_end_tests/end_to_end_jit_clear_tensor.cc` to the test
specification in YAML format in
`tests/end_to_end_fixture/end_to_end_clear_tensor.yaml`. Parametric
tests and tests invoking lambdas in loops have been fully unrolled.
This patch adds support for scalar results to the client/server
protocol and tests. In addition to `TensorData`, a new type
`ScalarData` is added. Previous representations of scalar values using
one-dimensional `TensorData` instances have been replaced with proper
instantiations of `ScalarData`.
The generic use of `TensorData` for scalar and tensor values has been
replaced with uses of a new variant `ScalarOrTensorData`, which can
either hold an instance of `TensorData` or `ScalarData`.
This adds a new optional boolean parameter
`use_default_fhe_constraints` to the YAML description of tests that
causes the test backend to use the default FHE constraints if set to
true. This is necessary for clear text tests, since automatic
determination of FHE parameters by the `CompilerEngine` fails for
programs not using encrypted integers and causes the program to abort.
The code in `loadEndToEndDesc` attempts to load the contents of a YAML
file without ensuring that the stream from which the file is read was
set up correctly. As a result, streams in a bad state, e.g., if the
file to be opened does not exist, simply result in an empty string for
the file contents. The test driver cannot distinguish this result from
a valid YAML file that is simply empty.
This patch causes `loadEndToEndDesc` to abort execution whenever a
file input stream could not be set up correctly.
Returning tensors with elements whose width is not equal to 64 results
in garbled data. This commit extends the `TensorData` class used to
represent tensors in JIT compilation with support for signed /
unsigned elements of 8/16/32 and 64 bits, such that all clear text
tensors with up to 64 bits can be represented accurately.
For now what it works are only levelled ops with user parameters. (take a look to the tests)
Done:
- Add parameters to the fhe parameters to support CRT-based large integers
- Add command line options and tests options to allows the user to give those new parameters
- Update the dialects and pipeline to handle new fhe parameters for CRT-based large integers
- Update the client parameters and the client library to handle the CRT-based large integers
Todo:
- Plug the optimizer to compute the CRT-based large interger parameters
- Plug the pbs for the CRT-based large integer
Commit `45577fb79e7bef9d6874906971f485ca6ed111b8` introduced a
regression causing garbage to be generated for IR involving
`tensor.extract_slice` and `tensor.collapse` in some cases. This
commit adds two tests checking for the absence of the regression.
Co-authored-by: Umut Sahin <umut.sahin@zama.ai>
Rebase to llvm-project at 3f81841474fe with a pending upstream patch
for arbitrary element types in linalg named operations.
Co-authored-by: Ayoub Benaissa <ayoub.benaissa@zama.ai>
