Searched refs:num_groups (Results 1 – 12 of 12) sorted by relevance
/hardware/qcom/sm8150p/gps/utils/ |
D | loc_cfg.h | 96 unsigned char num_groups; member
|
D | loc_cfg.cpp | 806 child_proc[j].num_groups = 0; in loc_read_process_conf() 811 child_proc[j].group_list[child_proc[j].num_groups] = grp->gr_gid; in loc_read_process_conf() 812 child_proc[j].num_groups++; in loc_read_process_conf()
|
/hardware/qcom/sm7150/gps/utils/ |
D | loc_cfg.h | 96 unsigned char num_groups; member
|
D | loc_cfg.cpp | 823 child_proc[j].num_groups = 0; in loc_read_process_conf() 828 child_proc[j].group_list[child_proc[j].num_groups] = grp->gr_gid; in loc_read_process_conf() 829 child_proc[j].num_groups++; in loc_read_process_conf()
|
/hardware/qcom/sm7250/gps/utils/ |
D | loc_cfg.h | 100 unsigned char num_groups; member
|
D | loc_cfg.cpp | 843 child_proc[j].num_groups = 0; in loc_read_process_conf() 848 child_proc[j].group_list[child_proc[j].num_groups] = grp->gr_gid; in loc_read_process_conf() 849 child_proc[j].num_groups++; in loc_read_process_conf()
|
/hardware/qcom/sm8150/gps/utils/ |
D | loc_cfg.h | 100 unsigned char num_groups; member
|
D | loc_cfg.cpp | 843 child_proc[j].num_groups = 0; in loc_read_process_conf() 848 child_proc[j].group_list[child_proc[j].num_groups] = grp->gr_gid; in loc_read_process_conf() 849 child_proc[j].num_groups++; in loc_read_process_conf()
|
/hardware/google/gfxstream/host/apigen-codec-common/X11/ |
D | XKBlib.h | 130 int num_groups; /* total groups on keyboard */ member
|
/hardware/google/gfxstream/host/apigen-codec-common/X11/extensions/ |
D | XKBstr.h | 263 unsigned char num_groups; member
|
/hardware/interfaces/neuralnetworks/1.2/ |
D | types.hal | 2774 * Given an input tensor and a integer value of num_groups, CHANNEL_SHUFFLE 2775 * divide the channel dimension into num_groups groups, and reorganize the 2780 * output_channel[k * num_groups + g] = input_channel[g * group_size + k] 2782 * where group_size = num_channels / num_groups 2784 * The number of channels must be divisible by num_groups. 3131 * Specifically, the input channels are divided into num_groups groups, each with 3132 * depth depth_group, i.e. depth_in = num_groups * depth_group. The convolutional 3133 * filters are also divided into num_groups groups, i.e. depth_out is divisible 3134 * by num_groups. GROUPED_CONV applies each group of filters to the corresponding 3149 * where channel_multiplier = depth_out / num_groups [all …]
|
/hardware/interfaces/neuralnetworks/1.3/ |
D | types.hal | 2947 * Given an input tensor and a integer value of num_groups, CHANNEL_SHUFFLE 2948 * divide the channel dimension into num_groups groups, and reorganize the 2953 * output_channel[k * num_groups + g] = input_channel[g * group_size + k] 2955 * where group_size = num_channels / num_groups 2957 * The number of channels must be divisible by num_groups. 3317 * Specifically, the input channels are divided into num_groups groups, each with 3318 * depth depth_group, i.e. depth_in = num_groups * depth_group. The convolutional 3319 * filters are also divided into num_groups groups, i.e. depth_out is divisible 3320 * by num_groups. GROUPED_CONV applies each group of filters to the corresponding 3335 * where channel_multiplier = depth_out / num_groups [all …]
|