203         channels_per_branch[b] = layer_config->out_channels;  in find_cnn_out_channels()
205         channels_per_branch[b] = layer_config->out_channels;  in find_cnn_out_channels()
215   channels_per_branch[branch] = layer_config->out_channels;  in find_cnn_out_channels()
240                               int *out_height, int *out_channels) {  in av1_find_cnn_output_size()  argument
287       out_channels[output_num] = channels_per_branch[layer_config->branch];  in av1_find_cnn_output_size()
360   for (int i = 0; i < layer_config->out_channels; ++i) {  in convolve_maxpool_padding_zero()
369               int off = k * layer_config->out_channels + i;  in convolve_maxpool_padding_zero()
402   for (int i = 0; i < layer_config->out_channels; ++i) {  in convolve_maxpool_padding_replicate()
411               int off = k * layer_config->out_channels + i;  in convolve_maxpool_padding_replicate()
444   for (int i = 0; i < layer_config->out_channels; ++i) {  in convolve_maxpool_padding_valid()
455               int off = k * layer_config->out_channels + i;  in convolve_maxpool_padding_valid()
495   for (int i = 0; i < layer_config->out_channels; ++i) {  in convolve_element_wise()
504           sum += layer_config->weights[k * layer_config->out_channels + i] *  in convolve_element_wise()
532   for (int i = start_idx; i < layer_config->out_channels; i += channel_step) {  in convolve_no_maxpool_padding_zero()
550           int off = k * layer_config->out_channels + top_cstep;  in convolve_no_maxpool_padding_zero()
584   for (int i = start_idx; i < layer_config->out_channels; i += channel_step) {  in convolve_no_maxpool_padding_replicate()
594           int off = k * layer_config->out_channels + i;  in convolve_no_maxpool_padding_replicate()
623   for (int i = start_idx; i < layer_config->out_channels; i += channel_step) {  in av1_cnn_convolve_no_maxpool_padding_valid_c()
634           int off = k * layer_config->out_channels + i;  in av1_cnn_convolve_no_maxpool_padding_valid_c()
655   const int cstep = layer_config->in_channels * layer_config->out_channels;  in av1_cnn_convolve()
789   const int cstep = layer_config->in_channels * layer_config->out_channels;  in av1_cnn_deconvolve_c()
797       for (int i = 0; i < layer_config->out_channels; ++i) {  in av1_cnn_deconvolve_c()
802               int off = k * layer_config->out_channels + i;  in av1_cnn_deconvolve_c()
832       for (int i = 0; i < layer_config->out_channels; ++i) {  in av1_cnn_deconvolve_c()
837               int off = k * layer_config->out_channels + i;  in av1_cnn_deconvolve_c()
868       for (int i = 0; i < layer_config->out_channels; ++i) {  in av1_cnn_deconvolve_c()
873               int off = k * layer_config->out_channels + i;  in av1_cnn_deconvolve_c()
947       if (!realloc_tensor(&tensor2[branch], layer_config->out_channels, o_width,  in av1_cnn_predict_c()
954                     layer_config->out_channels, o_width, o_height,  in av1_cnn_predict_c()
971     assert(tensor2[branch].channels == layer_config->out_channels);  in av1_cnn_predict_c()