// Copyright (c) Facebook, Inc. and its affiliates. // All rights reserved. // // Copyright 2019 Google LLC // // This source code is licensed under the BSD-style license found in the // LICENSE file in the root directory of this source tree. #include #include #include #include #include #include #include #include #include #include #include #include #include #include static enum xnn_status create_fully_connected_nc( size_t input_channels, size_t output_channels, size_t input_stride, size_t output_stride, const void* kernel, const void* bias, uint32_t flags, uint32_t log2_filter_element_size, uint32_t bias_element_size, xnn_pack_gemm_io_w_function pack_gemm_io_w, xnn_pack_gemm_goi_w_function pack_gemm_goi_w, const void* packing_params, int packed_weights_padding_byte, const void* params, size_t params_size, const struct gemm_parameters* gemm_parameters, const struct gemm_fused_ukernels* gemm_ukernels, uint32_t datatype_init_flags, enum xnn_operator_type operator_type, xnn_caches_t caches, xnn_operator_t* fully_connected_op_out) { xnn_operator_t fully_connected_op = NULL; enum xnn_status status = xnn_status_uninitialized; if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) { xnn_log_error("failed to create %s operator: XNNPACK is not initialized", xnn_operator_type_to_string(operator_type)); goto error; } status = xnn_status_unsupported_hardware; if ((xnn_params.init_flags & datatype_init_flags) != datatype_init_flags) { xnn_log_error( "failed to create %s operator: operations on data type are not supported", xnn_operator_type_to_string(operator_type)); goto error; } status = xnn_status_invalid_parameter; if (input_channels == 0) { xnn_log_error( "failed to create %s operator with %zu input channels: number of channels must be non-zero", xnn_operator_type_to_string(operator_type), input_channels); goto error; } if (output_channels == 0) { xnn_log_error( "failed to create %s operator with %zu output channels: number of channels must be non-zero", xnn_operator_type_to_string(operator_type), output_channels); goto error; } if (input_stride < input_channels) { xnn_log_error( "failed to create %s operator with input element stride of %zu: " "stride must be at least as large as the number of input channels (%zu)", xnn_operator_type_to_string(operator_type), input_stride, input_channels); goto error; } if (output_stride < output_channels) { xnn_log_error( "failed to create %s operator with output element stride of %zu: " "stride must be at least as large as the number of output channels (%zu)", xnn_operator_type_to_string(operator_type), output_stride, output_channels); goto error; } status = xnn_status_out_of_memory; fully_connected_op = xnn_allocate_zero_simd_memory(sizeof(struct xnn_operator)); if (fully_connected_op == NULL) { xnn_log_error( "failed to allocate %zu bytes for %s operator descriptor", sizeof(struct xnn_operator), xnn_operator_type_to_string(operator_type)); goto error; } if (caches != NULL) { fully_connected_op->weights_cache = caches->weights_cache; } const uint32_t nr = gemm_parameters->nr; const uint32_t kr = UINT32_C(1) << gemm_parameters->log2_kr; const uint32_t sr = UINT32_C(1) << gemm_parameters->log2_sr; const size_t n_stride = round_up(output_channels, nr); const size_t k_stride = round_up_po2(input_channels, kr * sr); const size_t packed_weights_size = n_stride * (bias_element_size + (k_stride << log2_filter_element_size)); size_t aligned_total_weights_size = round_up_po2(packed_weights_size, XNN_ALLOCATION_ALIGNMENT); void* weights_ptr = xnn_get_pointer_to_write_weights( fully_connected_op, aligned_total_weights_size, packed_weights_padding_byte); if (weights_ptr == NULL) { xnn_log_error( "failed to allocate %zu bytes for %s operator packed weights", packed_weights_size, xnn_operator_type_to_string(operator_type)); goto error; } if (flags & XNN_FLAG_TRANSPOSE_WEIGHTS) { pack_gemm_io_w( output_channels, input_channels, nr, kr, sr, kernel, bias, weights_ptr, packing_params); } else { pack_gemm_goi_w( 1, output_channels, input_channels, nr, kr, sr, kernel, bias, weights_ptr, 0 /* extra bytes */, packing_params); } if (use_weights_cache(fully_connected_op)) { fully_connected_op->packed_weights.offset = xnn_get_or_insert_weights_cache( fully_connected_op->weights_cache, weights_ptr, aligned_total_weights_size); } fully_connected_op->group_input_channels = input_channels; fully_connected_op->group_output_channels = output_channels; fully_connected_op->input_pixel_stride = input_stride; fully_connected_op->output_pixel_stride = output_stride; memcpy(&fully_connected_op->params, params, params_size); fully_connected_op->type = operator_type; fully_connected_op->flags = flags; const size_t mr = gemm_parameters->mr; fully_connected_op->ukernel.type = xnn_ukernel_type_gemm; fully_connected_op->ukernel.gemm = (struct xnn_ukernel_gemm) { .mr = mr, .nr = nr, .kr = kr, .sr = sr, }; assert(XNN_MAX_MR >= mr); fully_connected_op->ukernel.gemm.gemm_cases[0] = gemm_ukernels->gemm[0]; for (size_t i = 1; i < mr; i++) { fully_connected_op->ukernel.gemm.gemm_cases[i] = gemm_ukernels->gemm[mr-1]; } fully_connected_op->state = xnn_run_state_invalid; *fully_connected_op_out = fully_connected_op; return xnn_status_success; error: xnn_delete_operator(fully_connected_op); return status; } static enum xnn_status setup_fully_connected_nc( xnn_operator_t fully_connected_op, enum xnn_operator_type expected_operator_type, size_t batch_size, const void* input, void* output, uint32_t datatype_init_flags, uint32_t log2_input_element_size, uint32_t log2_filter_element_size, uint32_t bias_element_size, uint32_t log2_output_element_size, const void* params, size_t params_size, size_t num_threads) { if (fully_connected_op->type != expected_operator_type) { xnn_log_error("failed to setup operator: operator type mismatch (expected %s, got %s)", xnn_operator_type_to_string(expected_operator_type), xnn_operator_type_to_string(fully_connected_op->type)); return xnn_status_invalid_parameter; } fully_connected_op->state = xnn_run_state_invalid; if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) { xnn_log_error("failed to setup %s operator: XNNPACK is not initialized", xnn_operator_type_to_string(fully_connected_op->type)); return xnn_status_uninitialized; } if (batch_size == 0) { fully_connected_op->state = xnn_run_state_skip; return xnn_status_success; } if (fully_connected_op->weights_cache != NULL && !xnn_weights_cache_is_finalized(fully_connected_op->weights_cache)) { xnn_log_error("failed to setup %s operator: weights cache is not finalized", xnn_operator_type_to_string(fully_connected_op->type)); return xnn_status_invalid_state; } fully_connected_op->batch_size = 1; fully_connected_op->input_height = batch_size; fully_connected_op->input_width = 1; fully_connected_op->input = input; fully_connected_op->output_height = batch_size; fully_connected_op->output_width = 1; fully_connected_op->output = output; const size_t input_channels = fully_connected_op->group_input_channels; const size_t output_channels = fully_connected_op->group_output_channels; uint32_t mr = fully_connected_op->ukernel.gemm.mr; const uint32_t nr = fully_connected_op->ukernel.gemm.nr; struct xnn_hmp_gemm_ukernel gemm_ukernel = fully_connected_op->ukernel.gemm.gemm_cases[mr-1]; if (batch_size == 1 && fully_connected_op->ukernel.gemm.gemm_cases[0].function[XNN_UARCH_DEFAULT] != NULL) { gemm_ukernel = fully_connected_op->ukernel.gemm.gemm_cases[0]; mr = 1; } fully_connected_op->context.gemm = (struct gemm_context) { .k_scaled = input_channels << log2_input_element_size, .w_stride = bias_element_size + (round_up_po2(input_channels, fully_connected_op->ukernel.gemm.kr * fully_connected_op->ukernel.gemm.sr) << log2_input_element_size), .a = input, .a_stride = fully_connected_op->input_pixel_stride << log2_input_element_size, .packed_w = packed_weights(fully_connected_op), .c = output, .cm_stride = fully_connected_op->output_pixel_stride << log2_output_element_size, .cn_stride = nr << log2_output_element_size, .log2_csize = log2_output_element_size, .ukernel = gemm_ukernel, }; memcpy(&fully_connected_op->context.gemm.params, params, params_size); fully_connected_op->context.gemm.fused_params = &fully_connected_op->context.gemm.params; #if XNN_TEST_MODE const size_t nc = nr; #else size_t nc = output_channels; if (num_threads > 1) { const size_t num_other_tiles = divide_round_up(batch_size, mr); const size_t target_tiles_per_thread = 5; const size_t max_nc = divide_round_up(output_channels * num_other_tiles, num_threads * target_tiles_per_thread); if (max_nc < nc) { nc = min(nc, divide_round_up(nc, max_nc * nr) * nr); } } #endif #if XNN_MAX_UARCH_TYPES > 1 if (xnn_is_hmp_gemm_ukernel(gemm_ukernel)) { fully_connected_op->compute.type = xnn_parallelization_type_2d_tile_2d_with_uarch; fully_connected_op->compute.task_2d_tile_2d_with_id = (pthreadpool_task_2d_tile_2d_with_id_t) xnn_compute_hmp_gemm; } else { fully_connected_op->compute.type = xnn_parallelization_type_2d_tile_2d; fully_connected_op->compute.task_2d_tile_2d = (pthreadpool_task_2d_tile_2d_t) xnn_compute_gemm; } #else fully_connected_op->compute.type = xnn_parallelization_type_2d_tile_2d; fully_connected_op->compute.task_2d_tile_2d = (pthreadpool_task_2d_tile_2d_t) xnn_compute_gemm; #endif fully_connected_op->compute.range[0] = batch_size; fully_connected_op->compute.range[1] = output_channels; fully_connected_op->compute.tile[0] = mr; fully_connected_op->compute.tile[1] = nc; fully_connected_op->state = xnn_run_state_ready; return xnn_status_success; } enum xnn_status xnn_create_fully_connected_nc_f16( size_t input_channels, size_t output_channels, size_t input_stride, size_t output_stride, const void* kernel, const void* bias, float output_min, float output_max, uint32_t flags, xnn_caches_t caches, xnn_operator_t* fully_connected_op_out) { if (isnan(output_min)) { xnn_log_error( "failed to create %s operator with NaN output lower bound: lower bound must be non-NaN", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f16)); return xnn_status_invalid_parameter; } if (isnan(output_max)) { xnn_log_error( "failed to create %s operator with NaN output upper bound: upper bound must be non-NaN", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f16)); return xnn_status_invalid_parameter; } const uint16_t fp16_output_min = fp16_ieee_from_fp32_value(output_min); const uint16_t fp16_output_max = fp16_ieee_from_fp32_value(output_max); const float rounded_output_min = fp16_ieee_to_fp32_value(fp16_output_min); const float rounded_output_max = fp16_ieee_to_fp32_value(fp16_output_max); if (rounded_output_min >= rounded_output_max) { xnn_log_error( "failed to create %s operator with [%.7g, %.7g] output range: lower bound must be below upper bound", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f16), rounded_output_min, rounded_output_max); return xnn_status_invalid_parameter; } union xnn_f16_minmax_params params; if XNN_LIKELY(xnn_params.f16.gemm.init.f16 != NULL) { xnn_params.f16.gemm.init.f16(¶ms, fp16_output_min, fp16_output_max); } xnn_pack_gemm_io_w_function pack_gemm_io_w = (xnn_pack_gemm_io_w_function) xnn_pack_f16_gemm_io_w; xnn_pack_gemm_goi_w_function pack_gemm_goi_w = (xnn_pack_gemm_goi_w_function) xnn_pack_f16_gemm_goi_w; if (flags & XNN_FLAG_FP32_STATIC_WEIGHTS) { pack_gemm_io_w = (xnn_pack_gemm_io_w_function) xnn_pack_f32_to_f16_gemm_io_w; pack_gemm_goi_w = (xnn_pack_gemm_goi_w_function) xnn_pack_f32_to_f16_gemm_goi_w; } return create_fully_connected_nc( input_channels, output_channels, input_stride, output_stride, kernel, bias, flags, 1 /* log2(sizeof(filter element)) = log2(sizeof(uint16_t)) */, sizeof(uint16_t) /* sizeof(bias element) */, pack_gemm_io_w, pack_gemm_goi_w, NULL /* packing params */, 0 /* packed weights padding byte */, ¶ms, sizeof(params), &xnn_params.f16.gemm, &xnn_params.f16.gemm.minmax, XNN_INIT_FLAG_F16, xnn_operator_type_fully_connected_nc_f16, caches, fully_connected_op_out); } enum xnn_status xnn_create_fully_connected_nc_f32( size_t input_channels, size_t output_channels, size_t input_stride, size_t output_stride, const float* kernel, const float* bias, float output_min, float output_max, uint32_t flags, xnn_caches_t caches, xnn_operator_t* fully_connected_op_out) { if (isnan(output_min)) { xnn_log_error( "failed to create %s operator with NaN output lower bound: lower bound must be non-NaN", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f32)); return xnn_status_invalid_parameter; } if (isnan(output_max)) { xnn_log_error( "failed to create %s operator with NaN output upper bound: upper bound must be non-NaN", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f32)); return xnn_status_invalid_parameter; } if (output_min >= output_max) { xnn_log_error( "failed to create %s operator with [%.7g, %.7g] output range: lower bound must be below upper bound", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_f32), output_min, output_max); return xnn_status_invalid_parameter; } const struct gemm_fused_ukernels* gemm_ukernels = &xnn_params.f32.gemm.minmax; const bool linear_activation = (output_max == INFINITY) && (output_min == -output_max); if (linear_activation && xnn_params.f32.gemm.linear.gemm[xnn_params.f32.gemm.mr-1].function[XNN_UARCH_DEFAULT] != NULL) { gemm_ukernels = &xnn_params.f32.gemm.linear; } union xnn_f32_minmax_params params; if XNN_LIKELY(xnn_params.f32.gemm.init.f32 != NULL) { xnn_params.f32.gemm.init.f32(¶ms, output_min, output_max); } return create_fully_connected_nc( input_channels, output_channels, input_stride, output_stride, kernel, bias, flags, 2 /* log2(sizeof(filter element)) = log2(sizeof(float)) */, sizeof(float) /* sizeof(bias element) */, (xnn_pack_gemm_io_w_function) xnn_pack_f32_gemm_io_w, (xnn_pack_gemm_goi_w_function) xnn_pack_f32_gemm_goi_w, NULL /* packing params */, 0 /* packed weights padding byte */, ¶ms, sizeof(params), &xnn_params.f32.gemm, gemm_ukernels, XNN_INIT_FLAG_F32, xnn_operator_type_fully_connected_nc_f32, caches, fully_connected_op_out); } enum xnn_status xnn_create_fully_connected_nc_qs8( size_t input_channels, size_t output_channels, size_t input_stride, size_t output_stride, int8_t input_zero_point, float input_scale, float kernel_scale, const int8_t* kernel, const int32_t* bias, int8_t output_zero_point, float output_scale, int8_t output_min, int8_t output_max, uint32_t flags, xnn_caches_t caches, xnn_operator_t* fully_connected_op_out) { if (input_scale <= 0.0f || !isnormal(input_scale)) { xnn_log_error( "failed to create %s operator with %.7g input scale: scale must be finite, normalized, and positive", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qs8), input_scale); return xnn_status_invalid_parameter; } if (kernel_scale <= 0.0f || !isnormal(kernel_scale)) { xnn_log_error( "failed to create %s operator with %.7g kernel scale: scale must be finite, normalized, and positive", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qs8), kernel_scale); return xnn_status_invalid_parameter; } if (output_scale <= 0.0f || !isnormal(output_scale)) { xnn_log_error( "failed to create %s operator with %.7g output scale: scale must be finite, normalized, and positive", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qs8), output_scale); return xnn_status_invalid_parameter; } if (output_min >= output_max) { xnn_log_error( "failed to create %s operator with [%" PRId8 ", %" PRId8 "] output range: range min must be below range max", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qs8), output_min, output_max); return xnn_status_invalid_parameter; } const float requantization_scale = input_scale * kernel_scale / output_scale; if (requantization_scale >= 256.0f) { xnn_log_error( "failed to create %s operator with %.7g input scale, %.7g kernel scale, and %.7g output scale: " "requantization scale %.7g is greater or equal to 256.0", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qs8), input_scale, kernel_scale, output_scale, requantization_scale); return xnn_status_unsupported_parameter; } union xnn_qs8_conv_minmax_params params; if XNN_LIKELY(xnn_params.qs8.gemm.init.qs8 != NULL) { xnn_params.qs8.gemm.init.qs8(¶ms, requantization_scale, output_zero_point, output_min, output_max); } const struct xnn_qs8_packing_params packing_params = { .input_zero_point = input_zero_point, }; return create_fully_connected_nc( input_channels, output_channels, input_stride, output_stride, kernel, bias, flags, 0 /* log2(sizeof(filter element)) = log2(sizeof(int8_t)) */, sizeof(int32_t) /* sizeof(bias element) */, (xnn_pack_gemm_io_w_function) xnn_pack_qs8_gemm_io_w, (xnn_pack_gemm_goi_w_function) xnn_pack_qs8_gemm_goi_w, &packing_params, 0 /* packed weights padding byte */, ¶ms, sizeof(params), &xnn_params.qs8.gemm, &xnn_params.qs8.gemm.minmax, XNN_INIT_FLAG_QS8, xnn_operator_type_fully_connected_nc_qs8, caches, fully_connected_op_out); } enum xnn_status xnn_create_fully_connected_nc_qu8( size_t input_channels, size_t output_channels, size_t input_stride, size_t output_stride, uint8_t input_zero_point, float input_scale, uint8_t kernel_zero_point, float kernel_scale, const uint8_t* kernel, const int32_t* bias, uint8_t output_zero_point, float output_scale, uint8_t output_min, uint8_t output_max, uint32_t flags, xnn_caches_t caches, xnn_operator_t* fully_connected_op_out) { if (input_scale <= 0.0f || !isnormal(input_scale)) { xnn_log_error( "failed to create %s operator with %.7g input scale: scale must be finite, normalized, and positive", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qu8), input_scale); return xnn_status_invalid_parameter; } if (kernel_scale <= 0.0f || !isnormal(kernel_scale)) { xnn_log_error( "failed to create %s operator with %.7g kernel scale: scale must be finite, normalized, and positive", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qu8), kernel_scale); return xnn_status_invalid_parameter; } if (output_scale <= 0.0f || !isnormal(output_scale)) { xnn_log_error( "failed to create %s operator with %.7g output scale: scale must be finite, normalized, and positive", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qu8), output_scale); return xnn_status_invalid_parameter; } if (output_min >= output_max) { xnn_log_error( "failed to create %s operator with [%" PRIu8 ", %" PRIu8 "] output range: range min must be below range max", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qu8), output_min, output_max); return xnn_status_invalid_parameter; } const float requantization_scale = input_scale * kernel_scale / output_scale; if (requantization_scale >= 256.0f) { xnn_log_error( "failed to create %s operator with %.7g input scale, %.7g kernel scale, and %.7g output scale: " "requantization scale %.7g is greater or equal to 256.0", xnn_operator_type_to_string(xnn_operator_type_fully_connected_nc_qu8), input_scale, kernel_scale, output_scale, requantization_scale); return xnn_status_unsupported_parameter; } union xnn_qu8_conv_minmax_params params; if XNN_LIKELY(xnn_params.qu8.gemm.init.qu8 != NULL) { xnn_params.qu8.gemm.init.qu8(¶ms, kernel_zero_point, requantization_scale, output_zero_point, output_min, output_max); } const struct xnn_qu8_packing_params packing_params = { .input_zero_point = input_zero_point, .kernel_zero_point = kernel_zero_point, }; return create_fully_connected_nc( input_channels, output_channels, input_stride, output_stride, kernel, bias, flags, 0 /* log2(sizeof(filter element)) = log2(sizeof(uint8_t)) */, sizeof(int32_t) /* sizeof(bias element) */, (xnn_pack_gemm_io_w_function) xnn_pack_qu8_gemm_io_w, (xnn_pack_gemm_goi_w_function) xnn_pack_qu8_gemm_goi_w, &packing_params, kernel_zero_point /* packed weights padding byte */, ¶ms, sizeof(params), &xnn_params.qu8.gemm, &xnn_params.qu8.gemm.minmax, XNN_INIT_FLAG_QU8, xnn_operator_type_fully_connected_nc_qu8, caches, fully_connected_op_out); } enum xnn_status xnn_setup_fully_connected_nc_f16( xnn_operator_t fully_connected_op, size_t batch_size, const void* input, void* output, pthreadpool_t threadpool) { return setup_fully_connected_nc( fully_connected_op, xnn_operator_type_fully_connected_nc_f16, batch_size, input, output, XNN_INIT_FLAG_F32, 1 /* log2(sizeof(input element)) = log2(sizeof(uint16_t)) */, 1 /* log2(sizeof(filter element)) = log2(sizeof(uint16_t)) */, sizeof(uint16_t) /* sizeof(bias element) */, 1 /* log2(sizeof(output element)) = log2(sizeof(uint16_t)) */, &fully_connected_op->params.f16_minmax, sizeof(fully_connected_op->params.f16_minmax), pthreadpool_get_threads_count(threadpool)); } enum xnn_status xnn_setup_fully_connected_nc_f32( xnn_operator_t fully_connected_op, size_t batch_size, const float* input, float* output, pthreadpool_t threadpool) { return setup_fully_connected_nc( fully_connected_op, xnn_operator_type_fully_connected_nc_f32, batch_size, input, output, XNN_INIT_FLAG_F32, 2 /* log2(sizeof(input element)) = log2(sizeof(float)) */, 2 /* log2(sizeof(filter element)) = log2(sizeof(float)) */, sizeof(float) /* sizeof(bias element) */, 2 /* log2(sizeof(output element)) = log2(sizeof(float)) */, &fully_connected_op->params.f32_minmax, sizeof(fully_connected_op->params.f32_minmax), pthreadpool_get_threads_count(threadpool)); } enum xnn_status xnn_setup_fully_connected_nc_qs8( xnn_operator_t fully_connected_op, size_t batch_size, const int8_t* input, int8_t* output, pthreadpool_t threadpool) { return setup_fully_connected_nc( fully_connected_op, xnn_operator_type_fully_connected_nc_qs8, batch_size, input, output, XNN_INIT_FLAG_QS8, 0 /* log2(sizeof(input element)) = log2(sizeof(int8_t)) */, 0 /* log2(sizeof(filter element)) = log2(sizeof(int8_t)) */, sizeof(int32_t) /* sizeof(bias element) */, 0 /* log2(sizeof(output element)) = log2(sizeof(int8_t)) */, &fully_connected_op->params.qs8_conv_minmax, sizeof(fully_connected_op->params.qs8_conv_minmax), pthreadpool_get_threads_count(threadpool)); } enum xnn_status xnn_setup_fully_connected_nc_qu8( xnn_operator_t fully_connected_op, size_t batch_size, const uint8_t* input, uint8_t* output, pthreadpool_t threadpool) { return setup_fully_connected_nc( fully_connected_op, xnn_operator_type_fully_connected_nc_qu8, batch_size, input, output, XNN_INIT_FLAG_QU8, 0 /* log2(sizeof(input element)) = log2(sizeof(uint8_t)) */, 0 /* log2(sizeof(filter element)) = log2(sizeof(uint8_t)) */, sizeof(int32_t) /* sizeof(bias element) */, 0 /* log2(sizeof(output element)) = log2(sizeof(uint8_t)) */, &fully_connected_op->params.qu8_conv_minmax, sizeof(fully_connected_op->params.qu8_conv_minmax), pthreadpool_get_threads_count(threadpool)); }