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Merged
veblush merged 1 commit into from
Jan 25, 2026
Merged

[CI] fixes #3342

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2 changes: 2 additions & 0 deletions .bazelrc
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Original file line number Diff line number Diff line change
Expand Up @@ -48,6 +48,7 @@ build:ci --show_timestamps
build:ci --terminal_columns=0
build:ci --verbose_failures
build:ci --test_output=errors
build:ci --keep_going

# Windows CI options
build:windows_ci --config=windows
Expand All @@ -59,6 +60,7 @@ build:windows_ci --show_timestamps
build:windows_ci --terminal_columns=0
build:windows_ci --verbose_failures
build:windows_ci --test_output=errors
build:windows_ci --keep_going

# When building with the address sanitizer
# E.g., bazel build --config asan
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2 changes: 1 addition & 1 deletion tensorflow/lite/micro/kernels/add_n.cc
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Expand Up @@ -86,7 +86,7 @@ TfLiteStatus CalculateOpData(TfLiteContext* context, TfLiteNode* node) {
TF_LITE_ENSURE_OK(context, context->RequestScratchBufferInArena(
context, scratch_size, &scratch_index));
node->user_data =
reinterpret_cast<decltype(node->user_data)>(scratch_index);
reinterpret_cast<void*>(static_cast<intptr_t>(scratch_index));
} else if (output->type == kTfLiteInt8) {
node->user_data =
context->AllocatePersistentBuffer(context, sizeof(OpData));
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16 changes: 8 additions & 8 deletions tensorflow/lite/micro/kernels/concatenation_test.cc
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Expand Up @@ -43,8 +43,8 @@ void TestConcatenateOneInput(int* input1_dims_data, const T* input1_data,
TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);

TfLiteConcatenationParams builtin_data = {
.axis = axis,
.activation = kTfLiteActNone // Only activation supported in this impl
axis,
kTfLiteActNone // Only activation supported in this impl
};

const TFLMRegistration registration = Register_CONCATENATION();
Expand Down Expand Up @@ -97,8 +97,8 @@ void TestConcatenateTwoInputs(
TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);

TfLiteConcatenationParams builtin_data = {
.axis = axis,
.activation = kTfLiteActNone // Only activation supported in this impl
axis,
kTfLiteActNone // Only activation supported in this impl
};

const TFLMRegistration registration = Register_CONCATENATION();
Expand Down Expand Up @@ -166,8 +166,8 @@ void TestConcatenateQuantizedTwoInputs(
TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);

TfLiteConcatenationParams builtin_data = {
.axis = axis,
.activation = kTfLiteActNone // Only activation supported in this impl
axis,
kTfLiteActNone // Only activation supported in this impl
};

const TFLMRegistration registration = Register_CONCATENATION();
Expand Down Expand Up @@ -226,8 +226,8 @@ void TestConcatenateQuantizedTwoInputsCompressed(
TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);

TfLiteConcatenationParams builtin_data = {
.axis = axis,
.activation = kTfLiteActNone // Only activation supported in this impl
axis,
kTfLiteActNone // Only activation supported in this impl
};

const TFLMRegistration registration = Register_CONCATENATION();
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4 changes: 1 addition & 3 deletions tensorflow/lite/micro/kernels/l2norm_test.cc
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Expand Up @@ -70,9 +70,7 @@ void TestL2Normalization(int* input_dims_data, const T* input_data,
int outputs_array_data[] = {1, 1};
TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);

TfLiteL2NormParams builtin_data = {
.activation = kTfLiteActNone,
};
TfLiteL2NormParams builtin_data = {kTfLiteActNone};

const TFLMRegistration registration = tflite::Register_L2_NORMALIZATION();
micro::KernelRunner runner(registration, tensors, tensors_size, inputs_array,
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4 changes: 1 addition & 3 deletions tensorflow/lite/micro/kernels/mul_test.cc
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Expand Up @@ -45,9 +45,7 @@ template <typename T>
void ValidateMulGoldens(TfLiteTensor* tensors, int tensors_size,
TfLiteFusedActivation activation, const T* golden,
int output_len, float tolerance, T* output) {
TfLiteMulParams builtin_data = {
.activation = activation,
};
TfLiteMulParams builtin_data = {activation};

int inputs_array_data[] = {2, 0, 1};
TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
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12 changes: 6 additions & 6 deletions tensorflow/lite/micro/kernels/pack_test.cc
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Expand Up @@ -63,8 +63,8 @@ void TestPackTwoInputsFloat(int* input1_dims_data, const float* input1_data,
CreateTensor(output_data, output_dims)};

TfLitePackParams builtin_data = {
.values_count = 2,
.axis = axis,
2,
axis,
};
int inputs_array_data[] = {2, 0, 1};
TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
Expand Down Expand Up @@ -97,8 +97,8 @@ void TestPackThreeInputsFloat(int* input1_dims_data, const float* input1_data,
CreateTensor(output_data, output_dims)};

TfLitePackParams builtin_data = {
.values_count = 3,
.axis = axis,
3,
axis,
};
int inputs_array_data[] = {3, 0, 1, 2};
TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
Expand Down Expand Up @@ -128,8 +128,8 @@ void TestPackTwoInputs(int* input1_dims_data, const T* input1_data,
CreateTensor(output_data, output_dims)};

TfLitePackParams builtin_data = {
.values_count = 2,
.axis = axis,
2,
axis,
};
int inputs_array_data[] = {2, 0, 1};
TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
Expand Down
12 changes: 6 additions & 6 deletions tensorflow/lite/micro/kernels/unpack_test.cc
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Expand Up @@ -60,8 +60,8 @@ void TestUnpackThreeOutputsFloat(
}

TfLiteUnpackParams builtin_data = {
.num = 3,
.axis = axis,
3,
axis,
};

int inputs_array_data[] = {1, 0};
Expand Down Expand Up @@ -110,8 +110,8 @@ void TestUnpackOneOutputFloat(int* input_dims_data, const float* input_data,
}

TfLiteUnpackParams builtin_data = {
.num = 1,
.axis = axis,
1,
axis,
};

int inputs_array_data[] = {1, 0};
Expand Down Expand Up @@ -172,8 +172,8 @@ void TestUnpackThreeOutputs(int* input_dims_data, const T* input_data, int axis,
}

TfLiteUnpackParams builtin_data = {
.num = 3,
.axis = axis,
3,
axis,
};

int inputs_array_data[] = {1, 0};
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13 changes: 6 additions & 7 deletions tensorflow/lite/micro/micro_resource_variable_test.cc
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Expand Up @@ -116,20 +116,19 @@ TF_LITE_MICRO_TEST(VerifyAssignAndReadResourceBuffer) {
23, 24, 25, 26, 27, 28, 29, 30, 31, 32};
int dims[] = {1, 32};
TfLiteEvalTensor assign_tensor = {
.data = {golden},
.dims = tflite::testing::IntArrayFromInts(dims),

.type = kTfLiteFloat32,
{reinterpret_cast<float*>(golden)},
tflite::testing::IntArrayFromInts(dims),
kTfLiteFloat32,
};
resource_variables->Assign(
id, tflite::EvalTensorBytes(&assign_tensor),
tflite::micro::GetTensorData<void>(&assign_tensor));

int32_t buffer[32];
TfLiteEvalTensor read_tensor = {
.data = {buffer},
.dims = tflite::testing::IntArrayFromInts(dims),
.type = kTfLiteInt32,
{reinterpret_cast<float*>(buffer)},
tflite::testing::IntArrayFromInts(dims),
kTfLiteInt32,
};
resource_variables->Read(id, &read_tensor);
for (int i = 0; i < 32; i++) {
Expand Down
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