onedayherocoming opened a new issue, #17560:
URL: https://github.com/apache/tvm/issues/17560
### Expected behavior
The
tests/python/unittest/test_arith_solve_linear_equations.py::test_solution_consistency
ut can pass
### Actual behavior
This test is intentionally non-deterministic, if it fails please report it
in github issue together with this seed 2466330562623059511
def test_solution_consistency():
seed = random.randrange(sys.maxsize)
seed = 2466330562623059511
print(
"\nThis test is intentionally non-deterministic, "
"if it fails please report it in github issue together with this
seed {}\n".format(seed)
)
random.seed(seed)
def _check(num_vars, num_formulas, coef=(-5, 5), bounds=(-20, 20)):
variables = [te.var("x" + str(i)) for i in range(num_vars)]
relations = []
for i in range(num_formulas):
s1 = sum([v * random.randint(coef[0], coef[1]) for v in
variables])
s1 += random.randint(coef[0], coef[1])
s2 = sum([v * random.randint(coef[0], coef[1]) for v in
variables])
s2 += random.randint(coef[0], coef[1])
if random.random() < 0.7:
op = tvm.tir.EQ
else:
# we also make sure it can correctly handle inequalities
op = random.choice([tvm.tir.LE, tvm.tir.LT, tvm.tir.GE,
tvm.tir.GT])
relations.append(op(s1, s2))
vranges = {v: tvm.ir.expr.Range(bounds[0], bounds[1] + 1) for v
in variables}
solution = arith.solve_linear_equations(relations, variables,
vranges)
testing.check_int_constraints_trans_consistency(solution)
# leaving some variables as parameters should also be ok
for k in [1, 2]:
if len(variables) > k:
solution = arith.solve_linear_equations(relations,
variables[:-k], vranges)
param_ranges = {v: vranges[v] for v in variables[-k:]}
testing.check_int_constraints_trans_consistency(solution, param_ranges)
for i in range(2):
_check(num_vars=1, num_formulas=1)
for i in range(2):
_check(num_vars=1, num_formulas=2)
for i in range(2):
_check(num_vars=2, num_formulas=1)
for i in range(2):
_check(num_vars=2, num_formulas=2)
for i in range(2):
> _check(num_vars=2, num_formulas=3)
../../12/tvm/tests/python/unittest/test_arith_solve_linear_equations.py:71:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _
../../12/tvm/tests/python/unittest/test_arith_solve_linear_equations.py:52:
in _check
testing.check_int_constraints_trans_consistency(solution)
../../12/tvm/python/tvm/testing/utils.py:392: in
check_int_constraints_trans_consistency
_check_forward(
../../12/tvm/python/tvm/testing/utils.py:385: in _check_forward
cond_subst = ana.simplify(cond_subst)
../../12/tvm/python/tvm/arith/analyzer.py:159: in simplify
return self._simplify(expr, steps)
../../12/tvm/python/tvm/_ffi/_ctypes/packed_func.py:239: in __call__
raise_last_ffi_error()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _
def raise_last_ffi_error():
"""Raise the previous error from FFI
This should be used instead of `raise get_last_ffi_error()`, as it
handle propagation of errors across an FFI boundary. For example,
if Python passes a callback to a C++ function, and the callback
raises an exception, the re-thrown exception should contain the
full stack trace, not just the stack frames that are above the
outermost FFI call.
"""
_LIB.TVMGetLastPythonError.restype = ctypes.c_void_p
_LIB.TVMGetLastBacktrace.restype = ctypes.c_char_p
py_err = _LIB.TVMGetLastPythonError()
if py_err is None:
c_err_msg = py_str(_LIB.TVMGetLastError())
py_err_msg, err_type = c2pyerror(c_err_msg)
if err_type is not None and err_type.startswith("tvm.error."):
err_type = err_type[10:]
py_err = ERROR_TYPE.get(err_type, TVMError)(py_err_msg)
else:
# TVMGetLastPythonError returns a PyObject*, with NULL when
# there is no such value. If we annotated the restype as
# ctypes.py_object, we would need to return Py_None from the
# C++ implementation. This would require introducing a
# dependency on libpython that we want to avoid when not in a
# Python environment. Therefore, casting the resulting void*
# pointer to PyObject* using ctypes.
py_err = ctypes.cast(ctypes.c_void_p(py_err),
ctypes.py_object).value
tb = py_err.__traceback__
# The py_err.__traceback__ only goes from the location thrown
# up to the next FFI handoff. To have the stacktrace also
# include the C++ side, we need to adjust the __traceback__
# before re-throwing.
backtrace = _LIB.TVMGetLastBacktrace()
if backtrace:
frames = re.split(r"\n\W+\d+:\W+", py_str(backtrace))
frames = frames[1:] # Skip "Stack trace: "
for frame in frames:
if " at " in frame:
func_name, frame = frame.split(" at ", 1)
filename, lineno = frame.rsplit(":", 1)
func_name = func_name.strip()
filename = filename.strip()
lineno = int(lineno.strip())
tb = _append_traceback_frame(tb, func_name, filename,
lineno)
# Remove stack frames that provide little benefit to
# debugging. These are only removed from the stack frames
# contained within the exception we are re-raising, and not to
# the stack frames that it will continue to collect.
# Therefore, there may still be a single instance of these
# frames in the outermost Python-to-FFI call.
filter_funcs = [
lambda code: "tvm/_ffi/_ctypes/packed_func.py" in
code.co_filename,
lambda code: "tvm/_ffi/base.py" in code.co_filename,
]
tb = _filter_traceback_frames(tb, filter_funcs)
py_err = py_err.with_traceback(tb)
# The exception PyObject may contain a large amount of state,
# including all stack frames that may be inspected in a later
# PDB post-mortem. Therefore, we must make sure to remove the
# underlying PyObject* from the C++ side after we retrieve it.
_LIB.TVMDropLastPythonError()
> raise py_err
E TypeError: Traceback (most recent call last):
E 36:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::arith::{lambda(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*) const::{lambda(std::__cxx11::basic_string<char,
std::char_traits<char>, std::allocator<char>
>)#1}::operator()(std::__cxx11::basic_string<char, std::char_traits<char>,
std::allocator<char> >) const::{lambda(tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*)#4}> >::Call(tvm::runtime::PackedFuncObj const*,
tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
E 35: tvm::arith::Analyzer::Simplify(tvm::PrimExpr const&, int)
E 34: tvm::arith::CanonicalSimplifier::operator()(tvm::PrimExpr
const&)
E 33: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
E 32: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 31:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 30:
tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::AndNode const*)
E 29: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
E 28: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 27:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 26:
tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::AndNode const*)
E 25:
tvm::arith::RewriteSimplifier::Impl::RecursiveRewrite(tvm::PrimExpr const&)
E 24: tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 23: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 22:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 21:
tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::AndNode const*)
E 20: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
E 19: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 18:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 17:
tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::AndNode const*)
E 16: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
E 15: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 14:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 13:
tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::AndNode const*)
E 12: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
E 11: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 10:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 9:
tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::AndNode const*)
E 8: non-virtual thunk to
tvm::arith::CanonicalSimplifier::Impl::VisitExpr(tvm::PrimExpr const&)
E 7: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 6:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 5:
tvm::arith::CanonicalSimplifier::Impl::VisitExpr_(tvm::tir::LTNode const*)
E 4: tvm::arith::RewriteSimplifier::Impl::VisitExpr(tvm::PrimExpr
const&)
E 3:
_ZZN3tvm3tir11ExprFunctorIFNS_8PrimExprERKS2_EE10InitVTableEvENUlRKNS_7runtime
E 2:
tvm::arith::CanonicalSimplifier::Impl::VisitExpr_(tvm::tir::LTNode const*)
E 1:
tvm::arith::RewriteSimplifier::Impl::VisitExpr_(tvm::tir::LTNode const*)
E 0: tvm::tir::LT::LT(tvm::PrimExpr, tvm::PrimExpr, tvm::Span)
E File "/home/max.qin/time_wheel_24/12/tvm/src/tir/ir/expr.cc", line
320
E TypeError: Check failed: (a.dtype() == b.dtype()) is false:
mismatched types. int64 vs. int32
../../12/tvm/python/tvm/_ffi/base.py:482: TypeError
### Environment
Ubuntu 2004, the tvm version is private version
### Steps to reproduce
First , set seed to 2466330562623059511, then run
tests/python/unittest/test_arith_solve_linear_equations.py::test_solution_consistency
ut
### Triage
None
* needs-triage
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