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NPUW: Added conditional checks for accuracy for spatial subgraphs #27348

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NPUW: Added conditional checks for accuracy for spatial subgraphs #27348

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2b1d2e8
Added conditional checks for accuracy for spatial subgraphs also. Add…
AsyaPronina Oct 31, 2024
bb85745
NPUW: Fix idx != real_idx assert in failover
dmatveev Oct 16, 2024
759a73a
Fixed and refactored accuracy failover and dumps for spatial execution:
AsyaPronina Nov 12, 2024
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1 change: 1 addition & 0 deletions src/plugins/intel_npu/src/al/include/intel_npu/config/npuw.hpp
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Expand Up @@ -59,6 +59,7 @@ DEFINE_OPT(NPUW_FUNCALL_ASYNC, bool, false, npuw::funcall_async, RunTime);
DEFINE_OPT(NPUW_ACC_CHECK, bool, false, npuw::accuracy::check, RunTime);
DEFINE_OPT(NPUW_ACC_THRESH, double, 0.01, npuw::accuracy::threshold, RunTime);
DEFINE_OPT(NPUW_ACC_DEVICE, std::string, "", npuw::accuracy::reference_device, RunTime);
DEFINE_OPT(NPUW_ACC_DUMP_FAILS, bool, false, npuw::accuracy::dump_failures, RunTime);
DEFINE_OPT(NPUW_DUMP_FULL, bool, false, npuw::dump::full, CompileTime);
DEFINE_OPT(NPUW_DUMP_SUBS, std::string, "", npuw::dump::subgraphs, CompileTime);
DEFINE_OPT(NPUW_DUMP_SUBS_ON_FAIL, std::string, "", npuw::dump::subgraphs_on_fail, CompileTime);
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8 changes: 8 additions & 0 deletions src/plugins/intel_npu/src/al/include/intel_npu/npuw_private_properties.hpp
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Expand Up @@ -307,6 +307,14 @@ static constexpr ov::Property<double> threshold{"NPUW_ACC_THRESH"};
* Default value: empty.
*/
static constexpr ov::Property<std::string> reference_device{"NPUW_ACC_DEVICE"};

/**
* @brief
* Type: bool.
* Enable dumps of materials for model(s), failing accuracy check.
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Please rephrase. What are the "materials"?
Also, as we operate at subgraph level, there's no "model(s)"

* Default value: false.
*/
static constexpr ov::Property<std::string> dump_failures{"NPUW_ACC_DUMP_FAILS"};
} // namespace accuracy

namespace dump {
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1 change: 1 addition & 0 deletions src/plugins/intel_npu/src/al/src/config/npuw.cpp
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Expand Up @@ -44,6 +44,7 @@ void intel_npu::registerNPUWOptions(OptionsDesc& desc) {
desc.add<NPUW_ACC_CHECK>();
desc.add<NPUW_ACC_THRESH>();
desc.add<NPUW_ACC_DEVICE>();
desc.add<NPUW_ACC_DUMP_FAILS>();
#ifdef NPU_PLUGIN_DEVELOPER_BUILD
desc.add<NPUW_DUMP_FULL>();
desc.add<NPUW_DUMP_SUBS>();
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64 changes: 44 additions & 20 deletions src/plugins/intel_npu/src/plugin/npuw/accuracy/comparator.cpp
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Expand Up @@ -13,30 +13,47 @@
ov::npuw::metrics::NRMSE::NRMSE(double threshold) : m_threshold(threshold) {}

bool ov::npuw::metrics::NRMSE::operator()(const ov::SoPtr<ov::ITensor>& actual,
const ov::SoPtr<ov::ITensor>& reference) const {
NPUW_ASSERT(actual->is_continuous());
NPUW_ASSERT(reference->is_continuous());
const ov::SoPtr<ov::ITensor>& reference,
double* result) const {
Comment on lines 15 to +17
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This bool operator() (.., double *result); thing looks weird. Just make a proper return type like Result.

For those who were only checking true/false, that type could have operator bool().

NPUW_ASSERT(actual->get_shape() == reference->get_shape());
// Check for alignment:
NPUW_ASSERT(actual->get_byte_size() == reference->get_byte_size());
// FIXME: Check for strides

ov::Tensor in_actual(actual->get_element_type(), actual->get_shape());
ov::Tensor in_reference(reference->get_element_type(), reference->get_shape());

if (!actual->is_continuous()) {
ov::make_tensor(actual).copy_to(in_actual);
} else {
in_actual = ov::make_tensor(actual);
}
if (!reference->is_continuous()) {
ov::make_tensor(reference).copy_to(in_reference);
} else {
in_reference = ov::make_tensor(reference);
}

// TODO: it might be more correct to make to_f32 function
// to work with strided tensors
NPUW_ASSERT(in_actual.is_continuous());
NPUW_ASSERT(in_reference.is_continuous());

ov::Tensor actual_f32;
ov::Tensor reference_f32;

if (ov::element::Type_t::f32 == actual->get_element_type()) {
actual_f32 = ov::make_tensor(actual);
if (ov::element::f32 == in_actual.get_element_type()) {
actual_f32 = in_actual;
} else {
ov::Tensor dst(ov::element::Type_t::f32, actual->get_shape());
ov::npuw::util::to_f32(ov::make_tensor(actual), dst);
ov::Tensor dst(ov::element::Type_t::f32, in_actual.get_shape());
ov::npuw::util::to_f32(in_actual, dst);
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since you anyways convert to f32, it could be easier to teach this to_f32 function work with strided tensors - at least for inputs.
May be worth a todo and a follow-up ticket.

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Added TODO, will create a ticket!

actual_f32 = std::move(dst);
}

if (ov::element::Type_t::f32 == reference->get_element_type()) {
reference_f32 = ov::make_tensor(reference);
if (ov::element::f32 == in_reference.get_element_type()) {
reference_f32 = in_reference;
} else {
ov::Tensor dst(ov::element::Type_t::f32, reference->get_shape());
ov::npuw::util::to_f32(ov::make_tensor(reference), dst);
ov::Tensor dst(ov::element::Type_t::f32, in_reference.get_shape());
ov::npuw::util::to_f32(in_reference, dst);
reference_f32 = dst;
}

Expand All @@ -51,13 +68,21 @@ bool ov::npuw::metrics::NRMSE::operator()(const ov::SoPtr<ov::ITensor>& actual,
}

if (squared_error <= std::numeric_limits<double>::epsilon()) {
LOG_INFO("NRMSE loss: 0.0, threshold: " << m_threshold << ".");
LOG_INFO("PASS");
if (result != nullptr) {
*result = 0.0;
}
return true;
}

double rmse = sqrt(squared_error / size);
NPUW_ASSERT(rmse >= 0.0);

if (rmse < 0.0) {
// Calculated RMSE metric is < 0.0, what is unexpected. So, return that tensors are unequal.
if (result != nullptr) {
*result = rmse;
}
return false;
}

auto actual_min_max = std::minmax_element(actual_data, actual_data + size);
auto reference_min_max = std::minmax_element(reference_data, reference_data + size);
Expand All @@ -66,9 +91,8 @@ bool ov::npuw::metrics::NRMSE::operator()(const ov::SoPtr<ov::ITensor>& actual,
std::max(0.f, *actual_min_max.second) - std::min(0.f, *actual_min_max.first)});

double nrmse = rmse / den;
LOG_INFO("NRMSE loss: " << nrmse << ", threshold: " << m_threshold << ".");

bool success = nrmse <= m_threshold;
LOG_INFO((success ? "PASS" : "FAIL"));
return success;
if (result != nullptr) {
*result = nrmse;
}
return nrmse <= m_threshold;
}
5 changes: 3 additions & 2 deletions src/plugins/intel_npu/src/plugin/npuw/accuracy/comparator.hpp
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Expand Up @@ -15,8 +15,9 @@ namespace metrics {
class NRMSE {
public:
explicit NRMSE(double threshold);
bool operator()(const ov::SoPtr<ov::ITensor>& backup_tensor, const ov::SoPtr<ov::ITensor>& original_tensor) const;

bool operator()(const ov::SoPtr<ov::ITensor>& backup_tensor,
const ov::SoPtr<ov::ITensor>& original_tensor,
double* result = nullptr) const;
private:
double m_threshold{};
};
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