diff options
Diffstat (limited to 'runtime/libs/tflite/port/1.13.1/src/nnapi_delegate.cpp')
| -rw-r--r-- | runtime/libs/tflite/port/1.13.1/src/nnapi_delegate.cpp | 196 |
1 files changed, 96 insertions, 100 deletions
diff --git a/runtime/libs/tflite/port/1.13.1/src/nnapi_delegate.cpp b/runtime/libs/tflite/port/1.13.1/src/nnapi_delegate.cpp index 99272f0e5..2924c44e9 100644 --- a/runtime/libs/tflite/port/1.13.1/src/nnapi_delegate.cpp +++ b/runtime/libs/tflite/port/1.13.1/src/nnapi_delegate.cpp @@ -35,6 +35,8 @@ limitations under the License. #include <sys/system_properties.h> #endif +#include <memory> + namespace nnfw { namespace tflite { @@ -159,6 +161,9 @@ TfLiteStatus addTensorOperands(::tflite::Subgraph* subgraph, uint32_t* no_of_operands_added, std::vector<int64_t>* nnapi_ids) { uint32_t next_id = 0; + // Allocate temporary buffer to save casted boolean tensor + std::unordered_map<size_t, std::unique_ptr<uint8_t[]>> const_boolean_tensors; + for (size_t i = 0; i < subgraph->tensors_size(); i++) { // Skip temporaries and RNN back-edges. if ((*nnapi_ids)[i] == kOperandNotNeeded) continue; @@ -196,9 +201,7 @@ TfLiteStatus addTensorOperands(::tflite::Subgraph* subgraph, case kTfLiteBool: // Workaround to pass bool type under NNAPI // Use bool type using ANEURALNETWORKS_TENSOR_QUANT8_ASYMM with scale = 1.0f and zero_point = 0 - nn_type = ANEURALNETWORKS_TENSOR_QUANT8_ASYMM; - scale = 1.0f; - zeroPoint = 0; + nn_type = ANEURALNETWORKS_TENSOR_BOOL8; break; default: logError("Unsupported tensor type %d", tensor->type); @@ -243,7 +246,19 @@ TfLiteStatus addTensorOperands(::tflite::Subgraph* subgraph, // TODO(aselle): Based on Michael's suggestion, limiting this to read // only memory if (tensor->allocation_type == kTfLiteMmapRo) { - if (const NNAPIAllocation* alloc = dynamic_cast<const NNAPIAllocation*>( + if (tensor->type == kTfLiteBool) + { + // ANEURALNETWORKS_TENSOR_BOOL8 tensor element size is 8 bits + size_t elements = tensor->bytes / sizeof(bool); + const_boolean_tensors[i] = std::make_unique<uint8_t[]>(elements); + for (size_t idx = 0; idx < elements; idx++) + { + const_boolean_tensors[i].get()[idx] = (tensor->data.b[idx] ? 0x00 : 0xff); + } + RETURN_ERROR_IF_NN_FAILED(ANeuralNetworksModel_setOperandValue( + nn_model, next_id, const_boolean_tensors[i].get(), tensor->bytes)); + } + else if (const NNAPIAllocation* alloc = dynamic_cast<const NNAPIAllocation*>( static_cast<const ::tflite::Allocation*>(tensor->allocation))) { RETURN_ERROR_IF_NN_FAILED( ANeuralNetworksModel_setOperandValueFromMemory( @@ -703,19 +718,32 @@ TfLiteStatus AddOpsAndParams( nnapi_version = 12; // require NNAPI 1.2 nn_op_type = ANEURALNETWORKS_TOPK_V2; break; + case tflite::BuiltinOperator_GREATER: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_GREATER; + break; + case tflite::BuiltinOperator_GREATER_EQUAL: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_GREATER_EQUAL; + break; + case tflite::BuiltinOperator_LESS: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_LESS; + break; + case tflite::BuiltinOperator_LESS_EQUAL: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_LESS_EQUAL; + break; case tflite::BuiltinOperator_GATHER: nnapi_version = 12; // require NNAPI 1.2 nn_op_type = ANEURALNETWORKS_GATHER; add_gather_params(node.builtin_data); break; case tflite::BuiltinOperator_SPLIT: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_SPLIT; add_split_params(node.builtin_data); - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_SPLIT_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + break; case tflite::BuiltinOperator_NEG: nnapi_version = 12; // require NNAPI 1.2 nn_op_type = ANEURALNETWORKS_NEG; @@ -733,21 +761,14 @@ TfLiteStatus AddOpsAndParams( reinterpret_cast<uint32_t*>(node.outputs->data))); continue; case tflite::BuiltinOperator_PRELU: - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_PRELU_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), - static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_PRELU; + break; case tflite::BuiltinOperator_ARG_MAX: check_arg_max_input(node.builtin_data); - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_ARGMAX_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_ARGMAX; + break; case tflite::BuiltinOperator_PACK: add_pack_ex_params(node.builtin_data); CHECK_NN(ANeuralNetworksModel_addOperationEx( @@ -773,66 +794,40 @@ TfLiteStatus AddOpsAndParams( nn_op_type = ANEURALNETWORKS_RSQRT; break; case tflite::BuiltinOperator_EQUAL: - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_EQUAL_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_EQUAL; + break; case tflite::BuiltinOperator_NOT_EQUAL: - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_NOT_EQUAL_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_NOT_EQUAL; + break; case tflite::BuiltinOperator_SUM: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_REDUCE_SUM; add_reducer_params(node.builtin_data); - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_REDUCE_SUM_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), - static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + break; case tflite::BuiltinOperator_REDUCE_MAX: - add_reducer_v12_params(node.builtin_data); + add_reducer_params(node.builtin_data); nnapi_version = 12; // require NNAPI 1.2 nn_op_type = ANEURALNETWORKS_REDUCE_MAX; break; case tflite::BuiltinOperator_REDUCE_MIN: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_REDUCE_MIN; add_reducer_params(node.builtin_data); - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_REDUCE_MIN_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), - static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + break; case tflite::BuiltinOperator_LOGICAL_AND: - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_LOGICAL_AND_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), - static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_LOGICAL_AND; + break; case tflite::BuiltinOperator_LOGICAL_OR: - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_LOGICAL_OR_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), - static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_LOGICAL_OR; + break; case tflite::BuiltinOperator_LOGICAL_NOT: - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_LOGICAL_NOT_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), - static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_LOGICAL_NOT; + break; case tflite::BuiltinOperator_SQUARED_DIFFERENCE: CHECK_NN(ANeuralNetworksModel_addOperationEx( nn_model, ANEURALNETWORKS_SQUARED_DIFFERENCE_EX, @@ -851,6 +846,26 @@ TfLiteStatus AddOpsAndParams( nnapi_version = 12; // require NNAPI 1.2 nn_op_type = ANEURALNETWORKS_ABS; break; + case tflite::BuiltinOperator_ONE_HOT: + add_one_hot_tensor_inputs_as_scalar(); + add_one_hot_params(node.builtin_data); + CHECK_NN(ANeuralNetworksModel_addOperationEx( + nn_model, ANEURALNETWORKS_ONE_HOT_EX, + static_cast<uint32_t>(augmented_inputs.size()), + augmented_inputs.data(), static_cast<uint32_t>(node.outputs->size), + reinterpret_cast<uint32_t*>(node.outputs->data))); + continue; // _EX operator should use `continue` to skip addOperanation. + case tflite::BuiltinOperator_SIN: + nnapi_version = 12; // require NNAPI 1.2 + nn_op_type = ANEURALNETWORKS_SIN; + break; + case tflite::BuiltinOperator_SHAPE: + CHECK_NN(ANeuralNetworksModel_addOperationEx( + nn_model, ANEURALNETWORKS_SHAPE_EX, + static_cast<uint32_t>(augmented_inputs.size()), + augmented_inputs.data(), static_cast<uint32_t>(node.outputs->size), + reinterpret_cast<uint32_t*>(node.outputs->data))); + continue; // _EX operator should use `continue` to skip addOperanation. case tflite::BuiltinOperator_CONCAT_EMBEDDINGS: case tflite::BuiltinOperator_LSH_PROJECTION: case tflite::BuiltinOperator_BIDIRECTIONAL_SEQUENCE_RNN: @@ -881,14 +896,14 @@ TfLiteStatus AddOpsAndParams( //case tflite::BuiltinOperator_MINIMUM: //case tflite::BuiltinOperator_ARG_MAX: case tflite::BuiltinOperator_ARG_MIN: - case tflite::BuiltinOperator_GREATER: - case tflite::BuiltinOperator_GREATER_EQUAL: - case tflite::BuiltinOperator_LESS: - case tflite::BuiltinOperator_LESS_EQUAL: + //case tflite::BuiltinOperator_GREATER: + //case tflite::BuiltinOperator_GREATER_EQUAL: + //case tflite::BuiltinOperator_LESS: + //case tflite::BuiltinOperator_LESS_EQUAL: //case tflite::BuiltinOperator_NEG: case tflite::BuiltinOperator_SELECT: // case tflite::BuiltinOperator_SLICE: - case tflite::BuiltinOperator_SIN: + //case tflite::BuiltinOperator_SIN: case tflite::BuiltinOperator_LOG: //case tflite::BuiltinOperator_TRANSPOSE_CONV: case tflite::BuiltinOperator_TILE: @@ -902,12 +917,12 @@ TfLiteStatus AddOpsAndParams( case tflite::BuiltinOperator_REDUCE_PROD: //case tflite::BuiltinOperator_SQRT: //case tflite::BuiltinOperator_RSQRT: - case tflite::BuiltinOperator_SHAPE: + //case tflite::BuiltinOperator_SHAPE: case tflite::BuiltinOperator_POW: case tflite::BuiltinOperator_FAKE_QUANT: //case tflite::BuiltinOperator_PACK: //case tflite::BuiltinOperator_LOGICAL_OR: - case tflite::BuiltinOperator_ONE_HOT: + //case tflite::BuiltinOperator_ONE_HOT: //case tflite::BuiltinOperator_LOGICAL_AND: //case tflite::BuiltinOperator_LOGICAL_NOT: //case tflite::BuiltinOperator_UNPACK: @@ -928,13 +943,7 @@ TfLiteStatus AddOpsAndParams( break; case tflite::BuiltinOperator_CUSTOM: { std::string custom_name(registration.custom_name); - if (custom_name.compare("TensorFlowMax") == 0) { - add_reducer_v12_params(node.builtin_data); - nnapi_version = 12; // require NNAPI 1.2 - nn_op_type = ANEURALNETWORKS_REDUCE_MAX; - break; - } - else if (custom_name.compare("SquaredDifference") == 0) { + if (custom_name.compare("SquaredDifference") == 0) { CHECK_NN(ANeuralNetworksModel_addOperationEx( nn_model, ANEURALNETWORKS_SQUARED_DIFFERENCE_EX, static_cast<uint32_t>(augmented_inputs.size()), @@ -943,21 +952,6 @@ TfLiteStatus AddOpsAndParams( reinterpret_cast<uint32_t*>(node.outputs->data))); continue; } - else if (custom_name.compare("TensorFlowSum") == 0) { - add_reducer_params(node.builtin_data); - CHECK_NN(ANeuralNetworksModel_addOperationEx( - nn_model, ANEURALNETWORKS_REDUCE_SUM_EX, - static_cast<uint32_t>(augmented_inputs.size()), - augmented_inputs.data(), - static_cast<uint32_t>(node.outputs->size), - reinterpret_cast<uint32_t*>(node.outputs->data))); - continue; - } - else if (custom_name.compare("Abs") == 0) { - nnapi_version = 12; // require NNAPI 1.2 - nn_op_type = ANEURALNETWORKS_ABS; - break; - } logError("Custom operations are not supported when using NNAPI."); return kTfLiteError; break; @@ -1110,6 +1104,7 @@ TfLiteStatus NNAPIDelegate::Invoke(::tflite::Subgraph* subgraph) { // TODO(aselle): This should be called setInputValue maybe to be cons. TfLiteTensor* tensor = subgraph->tensor(input); // Workaround to pass bool type under NNAPI + // ANEURALNETWORKS_TENSOR_BOOL8 tensor element size is 8 bits if (tensor->type == kTfLiteBool) { CHECK_NN(ANeuralNetworksExecution_setInput( @@ -1128,6 +1123,7 @@ TfLiteStatus NNAPIDelegate::Invoke(::tflite::Subgraph* subgraph) { TfLiteTensor* tensor = subgraph->tensor(output); // Workaround to pass bool type under NNAPI + // ANEURALNETWORKS_TENSOR_BOOL8 tensor element size is 8 bits if (tensor->type == kTfLiteBool) { CHECK_NN(ANeuralNetworksExecution_setOutput( |