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[GPU] Enabled uint8_t input for ArgMinMax ensuring TF test compliance
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Details:
This update introduces support for the uint8_t data type in the argminmax
implementation on the cldnn path, which was previously lacking.
Specifically, for the TopKV2 test case, the OpenVino IR optimization
reduced the model to an argminmax primitive that did not support uint8_t
inputs, causing failures. With the new uint8_t support for argminmax and
the addition of a kernel, the test now passes. An OpenVino unit test has
been added to verify uint8_t data type handling, with test inputs
consisting of non-negative values.

Tickets:
  - CVS-153078
  - CVS-156587

Signed-off-by: Arshad Mehmood <[email protected]>
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@arshadlab
arshadlab committed Dec 16, 2024
1 parent e8fa9f7 commit a12a82d
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Showing 7 changed files with 35 additions and 8 deletions.
2 changes: 1 addition & 1 deletion src/plugins/intel_gpu/src/graph/impls/ocl/arg_max_min.cpp
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Expand Up @@ -131,7 +131,7 @@ struct arg_max_min_impl : typed_primitive_impl_ocl<arg_max_min> {

namespace detail {
attach_arg_max_min_impl::attach_arg_max_min_impl() {
auto types = {data_types::f16, data_types::f32, data_types::i8, data_types::i32};
auto types = {data_types::f16, data_types::f32, data_types::i8, data_types::i32, data_types::u8};

auto formats = {
format::bfyx,
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1 change: 1 addition & 0 deletions src/plugins/intel_gpu/src/kernel_selector/kernels/arg_max_min/arg_max_min_kernel_axis.cpp
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Expand Up @@ -52,6 +52,7 @@ ParamsKey ArgMaxMinKernelAxis::GetSupportedKey() const {
k.EnableInputDataType(Datatype::F16);
k.EnableInputDataType(Datatype::F32);
k.EnableInputDataType(Datatype::INT8);
k.EnableInputDataType(Datatype::UINT8);
k.EnableInputDataType(Datatype::INT32);
k.EnableAllOutputDataType();
k.EnableInputLayout(DataLayout::bfyx);
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1 change: 1 addition & 0 deletions src/plugins/intel_gpu/src/kernel_selector/kernels/arg_max_min/arg_max_min_kernel_gpu_ref.cpp
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Expand Up @@ -10,6 +10,7 @@ ParamsKey ArgMaxMinKernelGPURef::GetSupportedKey() const {
k.EnableInputDataType(Datatype::F16);
k.EnableInputDataType(Datatype::F32);
k.EnableInputDataType(Datatype::INT8);
k.EnableInputDataType(Datatype::UINT8);
k.EnableAllOutputDataType();
k.EnableInputLayout(DataLayout::bfyx);
k.EnableInputLayout(DataLayout::yxfb);
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1 change: 1 addition & 0 deletions src/plugins/intel_gpu/src/kernel_selector/kernels/arg_max_min/arg_max_min_kernel_opt.cpp
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Expand Up @@ -10,6 +10,7 @@ ParamsKey ArgMaxMinKernelOpt::GetSupportedKey() const {
k.EnableInputDataType(Datatype::F16);
k.EnableInputDataType(Datatype::F32);
k.EnableInputDataType(Datatype::INT8);
k.EnableInputDataType(Datatype::UINT8);
k.EnableOutputDataType(Datatype::F32);
k.EnableInputLayout(DataLayout::bfyx);
k.EnableOutputLayout(DataLayout::bfyx);
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34 changes: 31 additions & 3 deletions src/plugins/intel_gpu/tests/unit/test_cases/arg_max_gpu_test.cpp
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Expand Up @@ -16,7 +16,6 @@
using namespace cldnn;
using namespace ::tests;


template <format::type layoutFormat, typename DataType>
struct arg_max_input_types {
static const auto format = layoutFormat;
Expand Down Expand Up @@ -56,10 +55,21 @@ using format_types = testing::Types<arg_max_input_types<format::bfyx, float>,
arg_max_input_types<format::bfyx, ov::float16>,
arg_max_input_types<format::bs_fs_yx_bsv32_fsv16, ov::float16>,
arg_max_input_types<format::bfyx, int8_t>,
arg_max_input_types<format::bs_fs_yx_bsv32_fsv16, int8_t>>;
arg_max_input_types<format::bs_fs_yx_bsv32_fsv16, int8_t>,
arg_max_input_types<format::bs_fs_yx_bsv32_fsv32, int8_t>,
arg_max_input_types<format::bfyx, uint8_t>,
arg_max_input_types<format::bs_fs_yx_bsv32_fsv16, uint8_t>,
arg_max_input_types<format::bs_fs_yx_bsv32_fsv32, uint8_t>>;

TYPED_TEST_SUITE(argmax_gpu_test, format_types);

// Helper trait to check for uint8_t input_type
template<typename T>
struct is_uint8_input : std::false_type {};

template<format::type Fmt>
struct is_uint8_input<arg_max_input_types<Fmt, uint8_t>> : std::true_type {};

TYPED_TEST(argmax_gpu_test, base) {
// Input : 2x4x2x2
static const int32_t x_size = 2, y_size = 2, feature_num = 4, batch_num = 2;
Expand All @@ -82,7 +92,25 @@ TYPED_TEST(argmax_gpu_test, base) {
/*b1f1*/ 4.f, 0.5f, 8.f, 8.2f,
/*b1f2*/ 0.2f, 0.2f, -10.f, 5.2f,
/*b1f3*/ 4.f, 0.5f, 8.f, 8.2f};
set_values(input, this->getTypedVector(input_vec));

// Positive values for u8 input type test
std::vector<float> input_vec_u8 = {// y0x0 y0x1 y1x0 y1x1
/*b0f0*/ 0.1f, 0.1f, 0.9f, 1.5f,
/*b0f1*/ 0.2f, 0.2f, 0.1f, 5.2f,
/*b0f2*/ 0.2f, 0.2f, 0.1f, 5.2f,
/*b0f3*/ 0.2f, 0.2f, 0.1f, 4.2f,

/*b1f0*/ 3.f, 0.5f, 7.f, 10.f,
/*b1f1*/ 4.f, 0.5f, 8.f, 8.2f,
/*b1f2*/ 0.2f, 0.2f, 0.1f, 5.2f,
/*b1f3*/ 4.f, 0.5f, 8.f, 8.2f};

// If format is of type u8 then use non negative values as input.
if (is_uint8_input<TypeParam>::value) {
set_values(input, this->getTypedVector(input_vec_u8));
} else {
set_values(input, this->getTypedVector(input_vec));
}

network network(engine, topology, get_test_default_config(engine));

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2 changes: 0 additions & 2 deletions tests/layer_tests/tensorflow_tests/test_tf_ArgMinMax.py
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Expand Up @@ -69,8 +69,6 @@ def test_argmin_max_net(self, input_shape, dimension, input_type, output_type, o
ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
if platform.machine() in ['aarch64', 'arm64', 'ARM64']:
pytest.skip('153077: Segmentation fault on ARM')
if ie_device == 'GPU' and input_type == np.uint8:
pytest.skip('153078: No layout format available for topk')
if ie_device == 'GPU' and input_type == np.float32 and input_shape == [10, 15, 20]:
pytest.skip('153079: Accuracy error on GPU')
self._test(*self.create_argmin_max_net(input_shape=input_shape, dimension=dimension,
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2 changes: 0 additions & 2 deletions tests/layer_tests/tensorflow_tests/test_tf_TopKV2.py
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Expand Up @@ -55,8 +55,6 @@ def create_topk_v2_net(self, input_shape, input_type, k, k_type, sorted, index_t
def test_topk_v2(self, input_shape, input_type, k, k_type, sorted, index_type,
ie_device, precision, ir_version,
temp_dir, use_legacy_frontend):
if ie_device == 'GPU' and input_type == np.uint8:
pytest.skip('156587: Check correct_layout_selected failed for input uint8 on GPU')
if platform.machine() in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64'] and \
input_type in [np.int32, np.uint8, np.int16, np.int8, np.int64,
np.uint16, np.uint32, np.uint64]:
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