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- Adds arm_convolve_wrapper function for 4bit weights - Adds arm_convolve_1x1 normal and fast variant for 4bit weights - Adds arm_nn_mat_mult_kernel_s4_s16 for multiply 4bit weights with 16bit input - Adds mat_mult_nt_t_s4 function for dsp and scalar - Adds scalar and dsp implementation for arm_convolve with 4bit weights - Adds Unit tests for 4bit weight convolutions Change-Id: Idea55432fdab2db05a033889d7c39dd0ea69f8ad Signed-off-by: Ryan O'Shea <[email protected]>
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * SPDX-FileCopyrightText: Copyright 2022-2023 Arm Limited and/or its affiliates <[email protected]> | ||
| * | ||
| * SPDX-License-Identifier: Apache-2.0 | ||
| * | ||
| * 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 | ||
| * | ||
| * 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. | ||
| */ | ||
|
|
||
| /* ---------------------------------------------------------------------- | ||
| * Project: CMSIS NN Library | ||
| * Title: arm_convolve_1x1_s4.c | ||
| * Description: Generic s4 version of 1x1 convolution | ||
| * | ||
| * $Date: 01 November 2023 | ||
| * $Revision: V.1.0.0 | ||
| * | ||
| * Target : Arm(R) M-Profile Architecture | ||
| * | ||
| * -------------------------------------------------------------------- */ | ||
|
|
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| #include "arm_nnfunctions.h" | ||
| #include "arm_nnsupportfunctions.h" | ||
|
|
||
| /** | ||
| * @ingroup Public | ||
| */ | ||
|
|
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| /** | ||
| * @addtogroup NNConv | ||
| * @{ | ||
| */ | ||
|
|
||
| /* | ||
| * A more generic version of s4 1x1 convolution intended for non-unity strides. This is slower | ||
| * than the _fast() version if used for unity stride values. | ||
| * | ||
| * Refer header file for details. | ||
| * | ||
| */ | ||
| arm_cmsis_nn_status arm_convolve_1x1_s4(const cmsis_nn_context *ctx, | ||
| const cmsis_nn_conv_params *conv_params, | ||
| const cmsis_nn_per_channel_quant_params *quant_params, | ||
| const cmsis_nn_dims *input_dims, | ||
| const int8_t *input_data, | ||
| const cmsis_nn_dims *filter_dims, | ||
| const int8_t *filter_data, | ||
| const cmsis_nn_dims *bias_dims, | ||
| const int32_t *bias_data, | ||
| const cmsis_nn_dims *output_dims, | ||
| int8_t *output_data) | ||
| { | ||
| (void)ctx; | ||
| (void)filter_dims; | ||
| (void)bias_dims; | ||
| if (conv_params->padding.w != 0 || conv_params->padding.h != 0) | ||
| { | ||
| return ARM_CMSIS_NN_ARG_ERROR; | ||
| } | ||
|
|
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| const int32_t lhs_rows = output_dims->w; | ||
| const int32_t rhs_rows = output_dims->c; | ||
| const int32_t rhs_cols = input_dims->c; | ||
| const int32_t stride_w = conv_params->stride.w; | ||
| const int32_t input_inc = input_dims->w * conv_params->stride.h * rhs_cols; | ||
| const int32_t output_inc = output_dims->w * rhs_rows; | ||
| const int32_t output_h = output_dims->h; | ||
| const int32_t batch = input_dims->n; | ||
| const int8_t *input_data_ref = input_data; | ||
|
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| for (int i_batch = 0; i_batch < batch; i_batch++) | ||
| { | ||
| input_data = input_data_ref + (i_batch * rhs_cols * input_dims->w * input_dims->h); | ||
| for (int i_output_h = 0; i_output_h < output_h; i_output_h++) | ||
| { | ||
| // Process one input row | ||
| arm_cmsis_nn_status result = arm_nn_mat_mult_nt_t_s4(input_data, | ||
| filter_data, | ||
| bias_data, | ||
| output_data, | ||
| quant_params->multiplier, | ||
| quant_params->shift, | ||
| lhs_rows, | ||
| rhs_rows, | ||
| rhs_cols, | ||
| conv_params->input_offset, | ||
| conv_params->output_offset, | ||
| conv_params->activation.min, | ||
| conv_params->activation.max, | ||
| rhs_cols * stride_w); | ||
| if (result != ARM_CMSIS_NN_SUCCESS) | ||
| { | ||
| return result; | ||
| } | ||
| input_data += input_inc; | ||
| output_data += output_inc; | ||
| } | ||
| } | ||
|
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| /* Return to application */ | ||
| return ARM_CMSIS_NN_SUCCESS; | ||
| } | ||
|
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| /** | ||
| * @} end of NNConv group | ||
| */ |
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