## Coverage Report

#### Created: 2026-04-14 19:22

next uncovered line (L), next uncovered region (R), next uncovered branch (B)

    /home/liu/actions-runner/_work/ccv/ccv/lib/nnc/cmd/loss/ccv_nnc_smooth_l1.c

    Line
    Count
    Source
    1
    #include "ccv.h"
    2
    #include "nnc/ccv_nnc.h"
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    #include "nnc/ccv_nnc_easy.h"
    4
    #include "nnc/ccv_nnc_internal.h"
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    6
    static int _ccv_nnc_smooth_l1_forw_bitmask(const ccv_nnc_cmd_param_t cmd, const int input_size, const int output_size, const uint64_t* const input_bitmasks, const int input_bitmask_size, const uint64_t* const output_bitmasks, const int output_bitmask_size)
    7
    0
    {
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      // input: activation, label
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      // output: loss
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    0
      if ((input_bitmasks[0] & 3u) == 3u && output_bitmasks[0] == 1u)
    11
    0
        return 1;
    12
    0
      return 0;
    13
    0
    }
    14
    15
    static int _ccv_nnc_smooth_l1_back_bitmask(const ccv_nnc_cmd_param_t cmd, const int input_size, const int output_size, const uint64_t* const input_bitmasks, const int input_bitmask_size, const uint64_t* const output_bitmasks, const int output_bitmask_size)
    16
    8
    {
    17
      // input: [gradient of loss], activation, label, loss
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      // output: w.r.t activation, [label]
    19
    8
      if ((input_bitmasks[0] & 14u) == 14u && (output_bitmasks[0] & 1u) == 1u2)
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    2
        return 1;
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    6
      return 0;
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    8
    }
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    24
    static void _ccv_nnc_smooth_l1_tensor_auto_forw(const ccv_nnc_cmd_param_t cmd, const ccv_nnc_tensor_param_t* const inputs, const int input_size, const ccv_nnc_hint_t hint, ccv_nnc_tensor_param_t* const outputs, const int output_size)
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    2
    {
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    2
      assert(input_size == 2);
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    2
      assert(output_size >= 1);
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    2
      outputs[0] = inputs[0];
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      // The output should have the same dimentionality of the label data.
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    2
      memcpy(outputs[0].dim, inputs[1].dim, sizeof(outputs[0].dim));
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    2
      const int nd = ccv_nnc_tensor_nd(outputs[0].dim);
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      // Set channel to 1 if it is not..
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    2
      if (nd > 1 && ccv_nnc_tensor_get_c(outputs[0]) > 1)
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    2
        ccv_nnc_tensor_set_c(&outputs[0], nd, 1);
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    2
    }
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    37
    static void _ccv_nnc_smooth_l1_tensor_auto_back(const ccv_nnc_cmd_param_t cmd, const ccv_nnc_tensor_param_t* const inputs, const int input_size, const ccv_nnc_hint_t hint, ccv_nnc_tensor_param_t* const outputs, const int output_size)
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    1
    {
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    1
      assert(input_size >= 3);
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    1
      assert(output_size >= 1);
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    1
      outputs[0] = inputs[1];
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    1
      if (output_size > 1)
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    1
        outputs[1] = inputs[2];
    44
    1
    }
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    46
    REGISTER_COMMAND(CCV_NNC_SMOOTH_L1_FORWARD)(ccv_nnc_cmd_registry_t* const registry)
    47
      FIND_BACKEND(ccv_nnc_smooth_l1_cpu_ref.c, gpu/ccv_nnc_smooth_l1_gpu_ref.cu)
    48
    1
    {
    49
    1
      registry->bitmask = _ccv_nnc_smooth_l1_forw_bitmask;
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    1
      registry->tensor_auto = _ccv_nnc_smooth_l1_tensor_auto_forw;
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    1
    }
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    53
    REGISTER_COMMAND(CCV_NNC_SMOOTH_L1_BACKWARD)(ccv_nnc_cmd_registry_t* const registry)
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      FIND_BACKEND(ccv_nnc_smooth_l1_cpu_ref.c, gpu/ccv_nnc_smooth_l1_gpu_ref.cu)
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    1
    {
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    1
      registry->flags = CCV_NNC_CMD_ATTR_NULL_IS_ONES;
    57
    1
      registry->bitmask = _ccv_nnc_smooth_l1_back_bitmask;
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    1
      registry->tensor_auto = _ccv_nnc_smooth_l1_tensor_auto_back;
    59
    1
    }
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    61
    //@REGISTER_EASY_COMMAND_MACRO(CCV_NNC_SMOOTH_L1_FORWARD)
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    #define CMD_SMOOTH_L1_FORWARD(_b) ccv_nnc_cmd(CCV_NNC_SMOOTH_L1_FORWARD, 0, ((ccv_nnc_cmd_param_t){.size={.dim={1,1,1}},.smooth_l1={.beta=_b}}), 0)
    63
    //@REGISTER_EASY_COMMAND_MACRO(CCV_NNC_SMOOTH_L1_BACKWARD)
    64
    #define CMD_SMOOTH_L1_BACKWARD(_b) ccv_nnc_cmd(CCV_NNC_SMOOTH_L1_BACKWARD, 0, ((ccv_nnc_cmd_param_t){.size={.dim={1,1,1}},.smooth_l1={.beta=_b}}), 0)