Port the logical kernel to the TfLiteEvalTensor API.
PiperOrigin-RevId: 323042504 Change-Id: I0b7814b588c9ca8b26dbc2eba28035a4226475e3
This commit is contained in:
Nick Kreeger
TensorFlower Gardener
parent
3098c7a84d
commit
23cb51dfb6
@ -265,6 +265,7 @@ tflite_micro_cc_test(
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"logical_test.cc",
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],
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deps = [
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":kernel_runner",
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"//tensorflow/lite/c:common",
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"//tensorflow/lite/micro:op_resolvers",
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"//tensorflow/lite/micro/testing:micro_test",
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@ -15,8 +15,8 @@ limitations under the License.
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/kernels/internal/reference/binary_function.h"
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#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
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#include "tensorflow/lite/kernels/kernel_util.h"
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#include "tensorflow/lite/kernels/op_macros.h"
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#include "tensorflow/lite/micro/kernels/kernel_util.h"
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namespace tflite {
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namespace ops {
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@ -31,20 +31,29 @@ constexpr int kOutputTensor = 0;
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TfLiteStatus LogicalImpl(TfLiteContext* context, TfLiteNode* node,
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bool (*func)(bool, bool)) {
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const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
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const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
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TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
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const TfLiteEvalTensor* input1 =
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tflite::micro::GetEvalInput(context, node, kInputTensor1);
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const TfLiteEvalTensor* input2 =
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tflite::micro::GetEvalInput(context, node, kInputTensor2);
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TfLiteEvalTensor* output =
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tflite::micro::GetEvalOutput(context, node, kOutputTensor);
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if (HaveSameShapes(input1, input2)) {
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if (tflite::micro::HaveSameShapes(input1, input2)) {
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reference_ops::BinaryFunction<bool, bool, bool>(
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GetTensorShape(input1), GetTensorData<bool>(input1),
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GetTensorShape(input2), GetTensorData<bool>(input2),
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GetTensorShape(output), GetTensorData<bool>(output), func);
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tflite::micro::GetTensorShape(input1),
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tflite::micro::GetTensorData<bool>(input1),
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tflite::micro::GetTensorShape(input2),
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tflite::micro::GetTensorData<bool>(input2),
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tflite::micro::GetTensorShape(output),
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tflite::micro::GetTensorData<bool>(output), func);
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} else {
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reference_ops::BroadcastBinaryFunction4DSlow<bool, bool, bool>(
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GetTensorShape(input1), GetTensorData<bool>(input1),
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GetTensorShape(input2), GetTensorData<bool>(input2),
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GetTensorShape(output), GetTensorData<bool>(output), func);
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tflite::micro::GetTensorShape(input1),
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tflite::micro::GetTensorData<bool>(input1),
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tflite::micro::GetTensorShape(input2),
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tflite::micro::GetTensorData<bool>(input2),
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tflite::micro::GetTensorShape(output),
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tflite::micro::GetTensorData<bool>(output), func);
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}
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return kTfLiteOk;
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@ -12,9 +12,11 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/lite/c/builtin_op_data.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/micro/all_ops_resolver.h"
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#include "tensorflow/lite/micro/kernels/kernel_runner.h"
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#include "tensorflow/lite/micro/testing/micro_test.h"
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#include "tensorflow/lite/micro/testing/test_utils.h"
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@ -22,9 +24,10 @@ namespace tflite {
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namespace testing {
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namespace {
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void TestLogicalOp(tflite::BuiltinOperator op, const int* input1_dims_data,
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const bool* input1_data, const int* input2_dims_data,
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const bool* input2_data, const int* output_dims_data,
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void TestLogicalOp(const TfLiteRegistration& registration,
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const int* input1_dims_data, const bool* input1_data,
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const int* input2_dims_data, const bool* input2_data,
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const int* output_dims_data,
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const bool* expected_output_data, bool* output_data) {
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TfLiteIntArray* input1_dims = IntArrayFromInts(input1_dims_data);
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TfLiteIntArray* input2_dims = IntArrayFromInts(input2_dims_data);
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@ -40,32 +43,17 @@ void TestLogicalOp(tflite::BuiltinOperator op, const int* input1_dims_data,
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CreateBoolTensor(output_data, output_dims),
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};
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TfLiteContext context;
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PopulateContext(tensors, tensors_size, micro_test::reporter, &context);
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::tflite::AllOpsResolver resolver;
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const TfLiteRegistration* registration = resolver.FindOp(op);
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TF_LITE_MICRO_EXPECT_NE(nullptr, registration);
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int inputs_array_data[] = {2, 0, 1};
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TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
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int outputs_array_data[] = {1, 2};
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TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);
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TfLiteNode node;
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node.inputs = inputs_array;
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node.outputs = outputs_array;
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node.user_data = nullptr;
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node.builtin_data = nullptr;
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node.custom_initial_data = nullptr;
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node.custom_initial_data_size = 0;
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micro::KernelRunner runner(registration, tensors, tensors_size, inputs_array,
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outputs_array,
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/*builtin_data=*/nullptr, micro_test::reporter);
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if (registration->prepare) {
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->prepare(&context, &node));
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}
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TF_LITE_MICRO_EXPECT_NE(nullptr, registration->invoke);
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->invoke(&context, &node));
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.InitAndPrepare());
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.Invoke());
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TF_LITE_MICRO_EXPECT_EQ(output_dims_count, 4);
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for (int i = 0; i < output_dims_count; ++i) {
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@ -85,8 +73,8 @@ TF_LITE_MICRO_TEST(LogicalOr) {
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const bool input2[] = {true, false, true, false};
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const bool golden[] = {true, false, true, true};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::BuiltinOperator_LOGICAL_OR, shape,
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input1, shape, input2, shape, golden,
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_OR(),
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shape, input1, shape, input2, shape, golden,
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output_data);
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}
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@ -97,7 +85,7 @@ TF_LITE_MICRO_TEST(BroadcastLogicalOr) {
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const bool input2[] = {false};
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const bool golden[] = {true, false, false, true};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::BuiltinOperator_LOGICAL_OR,
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_OR(),
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input1_shape, input1, input2_shape, input2,
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input1_shape, golden, output_data);
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}
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@ -108,8 +96,8 @@ TF_LITE_MICRO_TEST(LogicalAnd) {
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const bool input2[] = {true, false, true, false};
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const bool golden[] = {true, false, false, false};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::BuiltinOperator_LOGICAL_AND, shape,
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input1, shape, input2, shape, golden,
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_AND(),
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shape, input1, shape, input2, shape, golden,
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output_data);
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}
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@ -120,7 +108,7 @@ TF_LITE_MICRO_TEST(BroadcastLogicalAnd) {
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const bool input2[] = {true};
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const bool golden[] = {true, false, false, true};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::BuiltinOperator_LOGICAL_AND,
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_AND(),
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input1_shape, input1, input2_shape, input2,
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input1_shape, golden, output_data);
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}
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