#include "ccv.h"

#include "ccv_internal.h"

#include "nnc/ccv_nnc.h"

#include "nnc/ccv_nnc_easy.h"

#include "nnc/ccv_nnc_internal.h"

#ifdef USE_OPENMP

#include <omp.h>

#endif

#ifdef USE_DISPATCH

#include <dispatch/dispatch.h>

#endif

// Shared methods.

#include "../_ccv_nnc_cpu_ref.h"

static int _ccv_nnc_reduce_min_forw(const ccv_nnc_cmd_t cmd, const ccv_nnc_hint_t hint, const int flags, ccv_nnc_tensor_t* const* const inputs, const int input_size, ccv_nnc_tensor_t* const* const outputs, const int output_size, ccv_nnc_stream_context_t* const stream_context)

{

  assert(input_size == 1);

  ccv_nnc_tensor_view_t* const a = (ccv_nnc_tensor_view_t*)inputs[0];

  ccv_nnc_tensor_view_t* const b = (ccv_nnc_tensor_view_t*)outputs[0];

  assert(ccv_nnc_tensor_nd(a->info.dim) <= CCV_NNC_MAX_DIM + 2);

  assert(ccv_nnc_tensor_nd(b->info.dim) <= CCV_NNC_MAX_DIM + 2);

  // Assuming this is float 32.

  int adim[CCV_NNC_MAX_DIM_ALLOC];

  int bdim[CCV_NNC_MAX_DIM_ALLOC];

  ccv_nnc_tensor_view_get_dim(a, adim);

  ccv_nnc_tensor_view_get_dim(b, bdim);

  assert(ccv_nnc_tensor_view_check_broadcast_dim(b, adim));

  int astride[CCV_NNC_MAX_DIM_ALLOC];

  int bstride[CCV_NNC_MAX_DIM_ALLOC];

  assert(CCV_NNC_MAX_DIM == 2); // Need to change this logic for CCV_NNC_MAX_DIM == other number.

  ccv_nnc_tensor_view_get_stride(a, astride);

  ccv_nnc_tensor_view_get_stride(b, bstride);

  int i[CCV_NNC_MAX_DIM + 2];

  int x;

  _ccv_nnc_tensor_set_cpu_ref_f32(b, FLT_MAX);

  float* const ap = a->data.f32;

  float* const bp = b->data.f32;

  // Non-optimal case, need to do skip if needed.

  for (i[0] = 0; i[0] < adim[0]; 
i[0]++3
)

  {

    float* const ap0 = ap + i[0] * astride[0];

    float* const bp0 = bdim[0] == 1 ? bp : 
bp + i[0] * bstride[0]0
;

    for (i[1] = 0; i[1] < adim[1]; 
i[1]++3
)

    {

      float* ap1 = ap0 + i[1] * astride[1];

      float* const bp1 = bdim[1] == 1 ? bp0 : 
bp0 + i[1] * bstride[1]0
;

      for (i[2] = 0; i[2] < adim[2]; 
i[2]++6
)

      {

        float* const bp2 = bdim[2] == 1 ? 
bp14
 : 
bp1 + i[2] * bstride[2]2
;

        if (bdim[3] == 1)

        {

          for (x = 0; x < adim[3]; 
x++6
)

            if (ap1[x] < bp2[0])

              bp2[0] = ap1[x];

        } else {

          for (x = 0; x < adim[3]; 
x++12
)

            if (ap1[x] < bp2[x])

              bp2[x] = ap1[x];

        }

        ap1 += astride[2];

      }

    }

  }

  return CCV_NNC_EXEC_SUCCESS;

}

static int _ccv_nnc_reduce_min_back(const ccv_nnc_cmd_t cmd, const ccv_nnc_hint_t hint, const int flags, ccv_nnc_tensor_t* const* const inputs, const int input_size, ccv_nnc_tensor_t* const* const outputs, const int output_size, ccv_nnc_stream_context_t* const stream_context)

{

  if (inputs[0] == 0)

  {

    ccv_nnc_tensor_view_t* const h = (ccv_nnc_tensor_view_t*)outputs[0];

    ccv_nnc_tensor_view_t* const a = (ccv_nnc_tensor_view_t*)inputs[1];

    ccv_nnc_tensor_view_t* const b = (ccv_nnc_tensor_view_t*)inputs[2];

    assert(ccv_nnc_tensor_nd(h->info.dim) <= CCV_NNC_MAX_DIM + 2);

    assert(ccv_nnc_tensor_nd(a->info.dim) <= CCV_NNC_MAX_DIM + 2);

    assert(ccv_nnc_tensor_nd(b->info.dim) <= CCV_NNC_MAX_DIM + 2);

    // Assuming this is float 32.

    int hdim[CCV_NNC_MAX_DIM_ALLOC];

    int bdim[CCV_NNC_MAX_DIM_ALLOC];

    ccv_nnc_tensor_view_get_dim(h, hdim);

    ccv_nnc_tensor_view_get_dim(b, bdim);

    assert(ccv_nnc_tensor_view_check_broadcast_dim(b, hdim));

    assert(ccv_nnc_tensor_view_check_dim(a, hdim));

    int hstride[CCV_NNC_MAX_DIM_ALLOC];

    int astride[CCV_NNC_MAX_DIM_ALLOC];

    int bstride[CCV_NNC_MAX_DIM_ALLOC];

    assert(CCV_NNC_MAX_DIM == 2); // Need to change this logic for CCV_NNC_MAX_DIM == other number.

    ccv_nnc_tensor_view_get_stride(h, hstride);

    ccv_nnc_tensor_view_get_stride(a, astride);

    ccv_nnc_tensor_view_get_stride(b, bstride);

    int i[CCV_NNC_MAX_DIM + 2];

    int x;

    float* const hp = h->data.f32;

    float* const ap = a->data.f32;

    float* const bp = b->data.f32;

    ccv_nnc_tensor_zero(h);

    // Non-optimal case, need to do skip if needed.

    for (i[0] = 0; i[0] < hdim[0]; i[0]++)

    {

      float* const ap0 = ap + i[0] * astride[0];

      float* const hp0 = hp + i[0] * hstride[0];

      float* const bp0 = bdim[0] == 1 ? bp : bp + i[0] * bstride[0];

      for (i[1] = 0; i[1] < hdim[1]; i[1]++)

      {

        float* ap1 = ap0 + i[1] * astride[1];

        float* hp1 = hp0 + i[1] * hstride[1];

        float* const bp1 = bdim[1] == 1 ? bp0 : bp0 + i[1] * bstride[1];

        for (i[2] = 0; i[2] < hdim[2]; i[2]++)

        {

          float* const bp2 = bdim[2] == 1 ? bp1 : bp1 + i[2] * bstride[2];

          if (bdim[3] == 1)

          {

            for (x = 0; x < hdim[3]; x++)

              if (ap1[x] == bp2[0])

                hp1[x] = 1;

          } else {

            for (x = 0; x < hdim[3]; x++)

              if (ap1[x] == bp2[x])

                hp1[x] = 1;

          }

          hp1 += hstride[2];

          ap1 += astride[2];

        }

      }

    }

    return CCV_NNC_EXEC_SUCCESS;

  }

  ccv_nnc_tensor_view_t* const h = (ccv_nnc_tensor_view_t*)outputs[0];

  ccv_nnc_tensor_view_t* const g = (ccv_nnc_tensor_view_t*)inputs[0];

  ccv_nnc_tensor_view_t* const a = (ccv_nnc_tensor_view_t*)inputs[1];

  ccv_nnc_tensor_view_t* const b = (ccv_nnc_tensor_view_t*)inputs[2];

  assert(ccv_nnc_tensor_nd(h->info.dim) <= CCV_NNC_MAX_DIM + 2);

  assert(ccv_nnc_tensor_nd(g->info.dim) <= CCV_NNC_MAX_DIM + 2);

  assert(ccv_nnc_tensor_nd(a->info.dim) <= CCV_NNC_MAX_DIM + 2);

  assert(ccv_nnc_tensor_nd(b->info.dim) <= CCV_NNC_MAX_DIM + 2);

  // Assuming this is float 32.

  int hdim[CCV_NNC_MAX_DIM_ALLOC];

  int gdim[CCV_NNC_MAX_DIM_ALLOC];

  ccv_nnc_tensor_view_get_dim(h, hdim);

  ccv_nnc_tensor_view_get_dim(g, gdim);

  assert(ccv_nnc_tensor_view_check_broadcast_dim(g, hdim));

  assert(ccv_nnc_tensor_view_check_dim(a, hdim));

  assert(ccv_nnc_tensor_view_check_dim(b, gdim));

  int hstride[CCV_NNC_MAX_DIM_ALLOC];

  int gstride[CCV_NNC_MAX_DIM_ALLOC];

  int astride[CCV_NNC_MAX_DIM_ALLOC];

  int bstride[CCV_NNC_MAX_DIM_ALLOC];

  assert(CCV_NNC_MAX_DIM == 2); // Need to change this logic for CCV_NNC_MAX_DIM == other number.

  ccv_nnc_tensor_view_get_stride(h, hstride);

  ccv_nnc_tensor_view_get_stride(g, gstride);

  ccv_nnc_tensor_view_get_stride(a, astride);

  ccv_nnc_tensor_view_get_stride(b, bstride);

  int i[CCV_NNC_MAX_DIM + 2];

  int x;

  float* const hp = h->data.f32;

  float* const gp = g->data.f32;

  float* const ap = a->data.f32;

  float* const bp = b->data.f32;

  ccv_nnc_tensor_zero(h);

  // Non-optimal case, need to do skip if needed.

  for (i[0] = 0; i[0] < hdim[0]; i[0]++)

  {

    float* const ap0 = ap + i[0] * astride[0];

    float* const hp0 = hp + i[0] * hstride[0];

    float* const gp0 = gdim[0] == 1 ? gp : gp + i[0] * gstride[0];

    float* const bp0 = gdim[0] == 1 ? bp : bp + i[0] * bstride[0];

    for (i[1] = 0; i[1] < hdim[1]; i[1]++)

    {

      float* ap1 = ap0 + i[1] * astride[1];

      float* hp1 = hp0 + i[1] * hstride[1];

      float* const gp1 = gdim[1] == 1 ? gp0 : gp0 + i[1] * gstride[1];

      float* const bp1 = gdim[1] == 1 ? bp0 : bp0 + i[1] * bstride[1];

      for (i[2] = 0; i[2] < hdim[2]; i[2]++)

      {

        float* const gp2 = gdim[2] == 1 ? gp1 : gp1 + i[2] * gstride[2];

        float* const bp2 = gdim[2] == 1 ? bp1 : bp1 + i[2] * bstride[2];

        if (gdim[3] == 1)

        {

          for (x = 0; x < hdim[3]; x++)

            if (ap1[x] == bp2[0])

              hp1[x] = gp2[0];

        } else {

          for (x = 0; x < hdim[3]; x++)

            if (ap1[x] == bp2[x])

              hp1[x] = gp2[x];

        }

        hp1 += hstride[2];

        ap1 += astride[2];

      }

    }

  }

  return CCV_NNC_EXEC_SUCCESS;

}

REGISTER_COMMAND_BACKEND(CCV_NNC_REDUCE_MIN_FORWARD, CCV_NNC_BACKEND_CPU_REF)(ccv_nnc_cmd_backend_registry_t* const registry)

{

  registry->tensor_formats = CCV_TENSOR_FORMAT_NHWC | CCV_TENSOR_FORMAT_NCHW | CCV_TENSOR_FORMAT_CHWN;

  registry->tensor_datatypes = CCV_32F;

  registry->tensor_memory = CCV_TENSOR_CPU_MEMORY;

  registry->algorithms = 1;

  registry->exec = _ccv_nnc_reduce_min_forw;

}

REGISTER_COMMAND_BACKEND(CCV_NNC_REDUCE_MIN_BACKWARD, CCV_NNC_BACKEND_CPU_REF)(ccv_nnc_cmd_backend_registry_t* const registry)

{

  registry->tensor_formats = CCV_TENSOR_FORMAT_NHWC | CCV_TENSOR_FORMAT_NCHW | CCV_TENSOR_FORMAT_CHWN;

  registry->tensor_datatypes = CCV_32F;

  registry->tensor_memory = CCV_TENSOR_CPU_MEMORY;

  registry->algorithms = 1;

  registry->exec = _ccv_nnc_reduce_min_back;

}