| /* Copyright 2023 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| |
| #if defined(HIFIMINI) |
| #include "tensorflow/lite/micro/kernels/fully_connected.h" |
| |
| #include "tensorflow/lite/c/builtin_op_data.h" |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/kernels/internal/common.h" |
| #include "tensorflow/lite/kernels/internal/quantization_util.h" |
| #include "tensorflow/lite/kernels/internal/reference/fully_connected.h" |
| #include "tensorflow/lite/kernels/internal/reference/integer_ops/fully_connected.h" |
| #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" |
| #include "tensorflow/lite/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/kernels/xtensa/hifimini/fixedpoint_utils.h" |
| #include "tensorflow/lite/micro/kernels/xtensa/xtensa.h" |
| |
| namespace tflite { |
| |
| void FullyConnectedEvalHifimini( |
| const FullyConnectedParams& params, const RuntimeShape& input_shape, |
| const int8_t* input_data, const RuntimeShape& filter_shape, |
| const int8_t* filter_data, const RuntimeShape& bias_shape, |
| const int32_t* bias_data, const RuntimeShape& output_shape, |
| int8_t* output_data) { |
| const int32_t input_offset = params.input_offset; |
| const int32_t filter_offset = params.weights_offset; |
| const int32_t output_offset = params.output_offset; |
| const int32_t output_multiplier = params.output_multiplier; |
| const int output_shift = params.output_shift; |
| const int32_t output_activation_min = params.quantized_activation_min; |
| const int32_t output_activation_max = params.quantized_activation_max; |
| |
| const int filter_dim_count = filter_shape.DimensionsCount(); |
| const int batches = output_shape.Dims(0); |
| const int output_depth = output_shape.Dims(1); |
| const int accum_depth = filter_shape.Dims(filter_dim_count - 1); |
| const int accum_depth_iters = accum_depth / 2; |
| |
| ae_p24x2s offsets_input_24x2 = AE_MOVPA24(input_offset); |
| ae_p24x2s offsets_filter_24x2 = AE_MOVPA24(filter_offset); |
| ae_q56s output_offset_56 = AE_CVTQ48A32S(output_offset); |
| ae_q56s output_activation_max_56 = AE_CVTQ48A32S(output_activation_max); |
| ae_q56s output_activation_min_56 = AE_CVTQ48A32S(output_activation_min); |
| |
| for (int b = 0; b < batches; ++b) { |
| for (int out_c = 0; out_c < output_depth; ++out_c) { |
| // Load intrinsics advance pointer before loading so backoff data pointers |
| // by two before loading: |
| const int8_t* input_ptr = (input_data + b * accum_depth) - 2; |
| const int8_t* filter_ptr = (filter_data + out_c * accum_depth) - 2; |
| |
| // Main accumulator register entry for loop: |
| ae_q56s sum_56 = AE_ZEROQ56(); |
| |
| for (int d = 0; d < accum_depth_iters; d++) { |
| // Load the signed 8bit values into the PR register: |
| ae_p24x2s input_24x2; |
| ae_p24x2s filter_24x2; |
| AE_LP8X2F_IU(input_24x2, input_ptr, 2); |
| AE_LP8X2F_IU(filter_24x2, filter_ptr, 2); |
| |
| // Right shift the signed 8bit values to expand to signed 24bit values: |
| input_24x2 = AE_P24X2S_SRAI(input_24x2, 16); |
| filter_24x2 = AE_P24X2S_SRAI(filter_24x2, 16); |
| |
| // Add offsets to data values (24 bit aligned): |
| input_24x2 = AE_P24S_ADDS_P24X2S(offsets_input_24x2, input_24x2); |
| filter_24x2 = AE_P24S_ADDS_P24X2S(offsets_filter_24x2, filter_24x2); |
| |
| // 24x2 signed integer dual MAC w/ addition into 56bit accumulator (48 |
| // bit aligned): |
| AE_MULAAP24S_HH_LL(sum_56, input_24x2, filter_24x2); |
| } |
| |
| // Left shift to get back into 32bit space (right padded to 48bit): |
| sum_56 = AE_Q56S_SLAI(sum_56, 16); |
| |
| // Add bias data if needed: |
| if (bias_data) { |
| ae_q56s bias_56 = AE_CVTQ48A32S(bias_data[out_c]); |
| sum_56 = AE_ADDQ56(sum_56, bias_56); |
| } |
| |
| // Shift left into 24bit space and place back on PR register: |
| sum_56 = AE_Q56S_SLAI(sum_56, 8); |
| ae_p24x2s sum_24x2 = AE_TRUNCP24Q48(sum_56); |
| |
| // MultiplyByQuantizedMultiplier returns a 48bit aligned value |
| sum_56 = MultiplyByQuantizedMultiplier(sum_24x2, output_multiplier, |
| output_shift); |
| |
| // Add output_offset and cap min/max values: |
| sum_56 = AE_ADDQ56(sum_56, output_offset_56); |
| sum_56 = AE_MINQ56S(sum_56, output_activation_max_56); |
| sum_56 = AE_MAXQ56S(sum_56, output_activation_min_56); |
| |
| output_data[out_c + output_depth * b] = |
| static_cast<int8_t>(AE_TRUNCA32Q48(sum_56)); |
| } |
| } |
| } |
| |
| } // namespace tflite |
| #endif // defined(HIFIMINI) |