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[GPU][TESTS] Fix weightless caching tests (openvinotoolkit#27163)
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Currently the tests have weightless caching enabled, but the models
tested contain no constants eligible for weightless caching. This fixes
the situation.

To elaborate - all the models have f32 dtype constants by default. In
these particular models all of the constants which would otherwise be
eligible for weightless caching undergo some precision transformation
which invalidates this eligibilty. The PR changes the dtype of the
constants to prevent that and deletes the models which contain no
constants eligible for weightless caching even after the dtype change.
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tkrupa-intel authored Oct 24, 2024
1 parent 2a9c69d commit 17f1601
Showing 1 changed file with 3 additions and 98 deletions.
101 changes: 3 additions & 98 deletions src/plugins/intel_gpu/tests/functional/behavior/model_cache.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -97,113 +97,18 @@ void CheckWeightlessCacheAccuracy::run() {
}
}

TEST_F(CheckWeightlessCacheAccuracy, 2InputSubtract) {
model = ov::test::utils::make_2_input_subtract();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, ConcatWithParams) {
model = ov::test::utils::make_concat_with_params();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, ConvBias) {
model = ov::test::utils::make_conv_bias();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, ConvPoolRelu) {
model = ov::test::utils::make_conv_pool_relu();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, ConvPoolReluNoReshapes) {
model = ov::test::utils::make_conv_pool_relu_no_reshapes();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, ConvPoolReluNonZero) {
model = ov::test::utils::make_conv_pool_relu_non_zero();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, ConvertTranspose) {
model = ov::test::utils::make_convert_transpose();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, DetectionOutput) {
model = ov::test::utils::make_detection_output();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, KsoFunction) {
model = ov::test::utils::make_kso_function();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, MatmulBias) {
model = ov::test::utils::make_matmul_bias();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, MultiSingleConv) {
model = ov::test::utils::make_multi_single_conv();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, MultipleInputOutputDoubleConcat) {
model = ov::test::utils::make_multiple_input_output_double_concat();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, NestedBranchConvConcat) {
model = ov::test::utils::make_nested_branch_conv_concat();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, NestedSplitConvConcat) {
model = ov::test::utils::make_nested_split_conv_concat();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, ReadConcatSplitAssign) {
model = ov::test::utils::make_read_concat_split_assign();
model = ov::test::utils::make_read_concat_split_assign({1, 1, 2, 4}, ov::element::f16);
run();
}

TEST_F(CheckWeightlessCacheAccuracy, SingleConcatWithConstant) {
model = ov::test::utils::make_single_concat_with_constant();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, SingleConv) {
model = ov::test::utils::make_single_conv();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, SingleSplit) {
model = ov::test::utils::make_single_split();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, SplitConcat) {
model = ov::test::utils::make_split_concat();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, SplitConvConcat) {
model = ov::test::utils::make_split_conv_concat();
run();
}

TEST_F(CheckWeightlessCacheAccuracy, SplitMultiConvConcat) {
model = ov::test::utils::make_split_multi_conv_concat();
model = ov::test::utils::make_single_concat_with_constant({1, 1, 2, 4}, ov::element::f16);
run();
}

TEST_F(CheckWeightlessCacheAccuracy, TiWithLstmCell) {
model = ov::test::utils::make_ti_with_lstm_cell();
model = ov::test::utils::make_ti_with_lstm_cell(ov::element::f16);
run();
}

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