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author | Przemyslaw Szczepaniak <pszczepaniak@google.com> | 2020-03-04 10:41:24 +0000 |
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committer | Przemyslaw Szczepaniak <pszczepaniak@google.com> | 2020-03-04 10:55:30 +0000 |
commit | bdbd44fc712ecaa6b55029096a99f6c710424c95 (patch) | |
tree | 5ffa4559418fc97c5d38fadfbb2be9ecc37643c0 | |
parent | f2091affab02743fb4ecbe6d5bdb426b93bbd283 (diff) | |
download | ml-bdbd44fc712ecaa6b55029096a99f6c710424c95.tar.gz |
Set output shape in RANK operation prepare
This fixes segfaults for graphs where RANK output
is a graph internal variable.
Test: GeneratedTest.rank_internal_result
Fix: 150728111
Change-Id: I321d7d4df918d4ecba15af788696f2fbf7545110
-rw-r--r-- | nn/common/operations/Rank.cpp | 3 | ||||
-rw-r--r-- | nn/runtime/test/generated/spec_V1_3/rank.example.cpp | 71 | ||||
-rw-r--r-- | nn/runtime/test/specs/V1_3/rank.mod.py | 27 |
3 files changed, 100 insertions, 1 deletions
diff --git a/nn/common/operations/Rank.cpp b/nn/common/operations/Rank.cpp index 0dc78e877..5f744375d 100644 --- a/nn/common/operations/Rank.cpp +++ b/nn/common/operations/Rank.cpp @@ -51,7 +51,8 @@ bool validate(const IOperationValidationContext* context) { } bool prepare(IOperationExecutionContext* context) { - return true; + Shape output = context->getOutputShape(kOutputScalar); + return context->setOutputShape(kOutputScalar, output); } bool execute(IOperationExecutionContext* context) { diff --git a/nn/runtime/test/generated/spec_V1_3/rank.example.cpp b/nn/runtime/test/generated/spec_V1_3/rank.example.cpp index 69db68b93..6e0fa86b1 100644 --- a/nn/runtime/test/generated/spec_V1_3/rank.example.cpp +++ b/nn/runtime/test/generated/spec_V1_3/rank.example.cpp @@ -1122,3 +1122,74 @@ const auto dummy_test_model_1d_quant8_signed_all_inputs_as_internal_2 = TestMode } // namespace generated_tests::rank +namespace generated_tests::rank { + +const TestModel& get_test_model_internal_output() { + static TestModel model = { + .expectFailure = false, + .expectedMultinomialDistributionTolerance = 0, + .isRelaxed = false, + .main = { + .inputIndexes = {0, 2}, + .operands = {{ + .channelQuant = {}, + .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}), + .dimensions = {2, 3}, + .isIgnored = false, + .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, + .numberOfConsumers = 1, + .scale = 0.0f, + .type = TestOperandType::TENSOR_FLOAT32, + .zeroPoint = 0 + }, { + .channelQuant = {}, + .data = TestBuffer::createFromVector<int32_t>({}), + .dimensions = {}, + .isIgnored = false, + .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, + .numberOfConsumers = 1, + .scale = 0.0f, + .type = TestOperandType::INT32, + .zeroPoint = 0 + }, { + .channelQuant = {}, + .data = TestBuffer::createFromVector<int32_t>({2, 3, 4}), + .dimensions = {3}, + .isIgnored = false, + .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, + .numberOfConsumers = 1, + .scale = 0.0f, + .type = TestOperandType::TENSOR_INT32, + .zeroPoint = 0 + }, { + .channelQuant = {}, + .data = TestBuffer::createFromVector<int32_t>({2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2}), + .dimensions = {2, 3, 4}, + .isIgnored = false, + .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, + .numberOfConsumers = 0, + .scale = 0.0f, + .type = TestOperandType::TENSOR_INT32, + .zeroPoint = 0 + }}, + .operations = {{ + .inputs = {0}, + .outputs = {1}, + .type = TestOperationType::RANK + }, { + .inputs = {2, 1}, + .outputs = {3}, + .type = TestOperationType::FILL + }}, + .outputIndexes = {3} + }, + .minSupportedVersion = TestHalVersion::V1_3, + .referenced = {} + }; + return model; +} + +const auto dummy_test_model_internal_output = TestModelManager::get().add("rank_internal_output", get_test_model_internal_output()); + +} // namespace generated_tests::rank + diff --git a/nn/runtime/test/specs/V1_3/rank.mod.py b/nn/runtime/test/specs/V1_3/rank.mod.py index e6db5324d..884af35be 100644 --- a/nn/runtime/test/specs/V1_3/rank.mod.py +++ b/nn/runtime/test/specs/V1_3/rank.mod.py @@ -41,3 +41,30 @@ test( input0_data=[1, 2, 3, 4, 5, 6], output0_data=[2], ) + +# b/150728111 regression test. +# Rank is a first operation that produces a scalar output. +# This test verifies that RANK works with a scalar output +# that's internal graph variable (not input or output of a graph). +def test_internal_output(name, rank_input, fill_dims, fill_output, rank_input_data, + fill_dims_data, fill_output_data): + internal_result = Internal("rank_internal_result", "INT32", "{}") + model = Model() + model = model.Operation("RANK", rank_input).To(internal_result) + model = model.Operation("FILL", fill_dims, internal_result).To(fill_output) + + example = Example({ + rank_input: rank_input_data, + fill_dims: fill_dims_data, + fill_output: fill_output_data, + }, model=model, name=name) + +test_internal_output( + name="internal_output", + rank_input=Input("input0", "TENSOR_FLOAT32", "{2, 3}"), + fill_dims=Input("input0", "TENSOR_INT32", "{3}"), + fill_output=Output("output", "TENSOR_INT32", "{2, 3, 4}"), + rank_input_data=[1, 2, 3, 4, 5, 6], + fill_dims_data=[2, 3, 4], + fill_output_data=[2] * (2 * 3 * 4), +) |