the call does return an `std::function` and was being referenced using
an `llvm::function_ref`, which apparently with some optim on Mac was
referncing bad memory location
Quick fix due to ordering of includes, had to add #include
<mlir/Transforms/DialectConversion.h> to include/concretelang/Conversion/Utils/GenericOpTypeConversionPattern.h
Upon invocation of a function with memref arguments, the strides for
all dimensions are currently set to 0. This causes dynamic offsets to
be calculated incorrectly in the function body.
This patch replaces the placeholder values with the actual strides for
each dimension and adds a test with parametric slice extraction from a
tensor that triggers dynamic indexing.
[----------] Global test environment tear-down
[==========] 7 tests from 1 test suite ran. (1513 ms total)
[ PASSED ] 7 tests.
YOU HAVE 2 DISABLED TESTS
[----------] Global test environment tear-down
[==========] 6 tests from 1 test suite ran. (1513 ms total)
[ PASSED ] 6 tests.
YOU HAVE 3 DISABLED TESTS
Compared to previous commit, a fatal test is disabled
[----------] Global test environment tear-down
[==========] 6 tests from 1 test suite ran. (1327 ms total)
[ PASSED ] 5 tests.
[ FAILED ] 1 test, listed below:
[ FAILED ] Lambda_check_param.scalar_tensor_to_tensor_good_number_param
1 FAILED TEST
YOU HAVE 3 DISABLED TESTS
Resolves#288
example
before:
Failed to lower to LLVM dialect
after:
Failed to lower to LLVM dialect
test.mlir:3:10: error: unexpected error: 'linalg.copy' op expected indexing_map #1 to have 2 dim(s) to match the number of loops
%0 = tensor.extract_slice %arg0[0, 0] [3, 1] [1, 1] : tensor<3x2x!HLFHE.eint<3>> to tensor<3x!HLFHE.eint<3>>
^
Try to find the runtime library automatically (should only work on
proper installation of the package), and fail silently by not passing
any RT lib. The RT lib can also be specified manually. The RT lib will
be used as a shared library by the JIT compiler.
Add a new method `JITLambda::Arguments::getResultWidth` returning the
width of a scalar result or the element type of a tensor result at a
given position.
Currently, `JITLambda::Arguments` assumes result tensors are always
composed of `uint64_t` elements. This change adds support for
arbitrary scalar element types.
All results in code compiled by zamacompiler are passed as return
values, which means that all tensors passed as function arguments are
constant inputs that are never written.
This patch changes the arguments used as data pointers for input
tensors in `JITLambda::Arguments::setArg()` from `void*` to `const
void*` to emphasize their use as inputs and to allow for constant
arrays to be passed as function inputs.
