static inline void unpack_coeffs(SnowContext *s, SubBand *b, SubBand * parent, int orientation){
    const int w= b->width;
    const int h= b->height;
    int x,y;

    int run, runs;
    x_and_coeff *xc= b->x_coeff;
    x_and_coeff *prev_xc= NULL;
    x_and_coeff *prev2_xc= xc;
    x_and_coeff *parent_xc= parent ? parent->x_coeff : NULL;
    x_and_coeff *prev_parent_xc= parent_xc;

    runs= get_symbol2(&s->c, b->state[30], 0);
    if(runs-- > 0) run= get_symbol2(&s->c, b->state[1], 3);
    else           run= INT_MAX;

    for(y=0; y<h; y++){
        int v=0;
        int lt=0, t=0, rt=0;

        if(y && prev_xc->x == 0){
            rt= prev_xc->coeff;
        }
        for(x=0; x<w; x++){
            int p=0;
            const int l= v;

            lt= t; t= rt;

            if(y){
                if(prev_xc->x <= x)
                    prev_xc++;
                if(prev_xc->x == x + 1)
                    rt= prev_xc->coeff;
                else
                    rt=0;
            }
            if(parent_xc){
                if(x>>1 > parent_xc->x){
                    parent_xc++;
                }
                if(x>>1 == parent_xc->x){
                    p= parent_xc->coeff;
                }
            }
            if(/*ll|*/l|lt|t|rt|p){
                int context= av_log2(/*FFABS(ll) + */3*(l>>1) + (lt>>1) + (t&~1) + (rt>>1) + (p>>1));

                v=get_rac(&s->c, &b->state[0][context]);
                if(v){
                    v= 2*(get_symbol2(&s->c, b->state[context + 2], context-4) + 1);
                    v+=get_rac(&s->c, &b->state[0][16 + 1 + 3 + ff_quant3bA[l&0xFF] + 3*ff_quant3bA[t&0xFF]]);

                    xc->x=x;
                    (xc++)->coeff= v;
                }
            }else{
                if(!run){
                    if(runs-- > 0) run= get_symbol2(&s->c, b->state[1], 3);
                    else           run= INT_MAX;
                    v= 2*(get_symbol2(&s->c, b->state[0 + 2], 0-4) + 1);
                    v+=get_rac(&s->c, &b->state[0][16 + 1 + 3]);

                    xc->x=x;
                    (xc++)->coeff= v;
                }else{
                    int max_run;
                    run--;
                    v=0;
                    av_assert2(run >= 0);
                    if(y) max_run= FFMIN(run, prev_xc->x - x - 2);
                    else  max_run= FFMIN(run, w-x-1);
                    if(parent_xc)
                        max_run= FFMIN(max_run, 2*parent_xc->x - x - 1);
                    av_assert2(max_run >= 0 && max_run <= run);

                    x+= max_run;
                    run-= max_run;
                }
            }
        }
        (xc++)->x= w+1; //end marker
        prev_xc= prev2_xc;
        prev2_xc= xc;

        if(parent_xc){
            if(y&1){
                while(parent_xc->x != parent->width+1)
                    parent_xc++;
                parent_xc++;
                prev_parent_xc= parent_xc;
            }else{
                parent_xc= prev_parent_xc;
            }
        }
    }

    (xc++)->x= w+1; //end marker
}


static inline void put_symbol2(RangeCoder *c, uint8_t *state, int v, int log2){
    int i;
    int r= log2>=0 ? 1<<log2 : 1;

    av_assert2(v>=0);
    av_assert2(log2>=-4);

    while(v >= r){
        put_rac(c, state+4+log2, 1);
        v -= r;
        log2++;
        if(log2>0) r+=r;
    }
    put_rac(c, state+4+log2, 0);

    for(i=log2-1; i>=0; i--){
        put_rac(c, state+31-i, (v>>i)&1);
    }
}

avcodec/snow: split block clipping checks

Fixes out of array read
Fixes: d4476f68ca1c1c57afbc45806f581963-asan_heap-oob_2266b27_8607_cov_4044577381_snow_chroma_bug.avi
Found-by: Mateusz "j00ru" Jurczyk and Gynvael Coldwind
Signed-off-by: Michael Niedermayer <michaelni@gmx.at>


static inline int get_symbol(RangeCoder *c, uint8_t *state, int is_signed){
    if(get_rac(c, state+0))
        return 0;
    else{
        int i, e, a;
        e= 0;
        while(get_rac(c, state+1 + FFMIN(e,9))){ //1..10
            e++;
        }

        a= 1;
        for(i=e-1; i>=0; i--){
            a += a + get_rac(c, state+22 + FFMIN(i,9)); //22..31
        }

        e= -(is_signed && get_rac(c, state+11 + FFMIN(e,10))); //11..21
        return (a^e)-e;
    }
}


static av_always_inline int same_block(BlockNode *a, BlockNode *b){
    if((a->type&BLOCK_INTRA) && (b->type&BLOCK_INTRA)){
        return !((a->color[0] - b->color[0]) | (a->color[1] - b->color[1]) | (a->color[2] - b->color[2]));
    }else{
        return !((a->mx - b->mx) | (a->my - b->my) | (a->ref - b->ref) | ((a->type ^ b->type)&BLOCK_INTRA));
    }
}


static av_always_inline void predict_slice(SnowContext *s, IDWTELEM *buf, int plane_index, int add, int mb_y){
    Plane *p= &s->plane[plane_index];
    const int mb_w= s->b_width  << s->block_max_depth;
    const int mb_h= s->b_height << s->block_max_depth;
    int x, y, mb_x;
    int block_size = MB_SIZE >> s->block_max_depth;
    int block_w    = plane_index ? block_size>>s->chroma_h_shift : block_size;
    int block_h    = plane_index ? block_size>>s->chroma_v_shift : block_size;
    const uint8_t *obmc  = plane_index ? ff_obmc_tab[s->block_max_depth+s->chroma_h_shift] : ff_obmc_tab[s->block_max_depth];
    const int obmc_stride= plane_index ? (2*block_size)>>s->chroma_h_shift : 2*block_size;
    int ref_stride= s->current_picture->linesize[plane_index];
    uint8_t *dst8= s->current_picture->data[plane_index];
    int w= p->width;
    int h= p->height;
    av_assert2(s->chroma_h_shift == s->chroma_v_shift); // obmc params assume squares
    if(s->keyframe || (s->avctx->debug&512)){
        if(mb_y==mb_h)
            return;

        if(add){
            for(y=block_h*mb_y; y<FFMIN(h,block_h*(mb_y+1)); y++){
                for(x=0; x<w; x++){
                    int v= buf[x + y*w] + (128<<FRAC_BITS) + (1<<(FRAC_BITS-1));
                    v >>= FRAC_BITS;
                    if(v&(~255)) v= ~(v>>31);
                    dst8[x + y*ref_stride]= v;
                }
            }
        }else{
            for(y=block_h*mb_y; y<FFMIN(h,block_h*(mb_y+1)); y++){
                for(x=0; x<w; x++){
                    buf[x + y*w]-= 128<<FRAC_BITS;
                }
            }
        }

        return;
    }

    for(mb_x=0; mb_x<=mb_w; mb_x++){
        add_yblock(s, 0, NULL, buf, dst8, obmc,
                   block_w*mb_x - block_w/2,
                   block_h*mb_y - block_h/2,
                   block_w, block_h,
                   w, h,
                   w, ref_stride, obmc_stride,
                   mb_x - 1, mb_y - 1,
                   add, 1, plane_index);
    }
}


static inline void set_blocks(SnowContext *s, int level, int x, int y, int l, int cb, int cr, int mx, int my, int ref, int type){
    const int w= s->b_width << s->block_max_depth;
    const int rem_depth= s->block_max_depth - level;
    const int index= (x + y*w) << rem_depth;
    const int block_w= 1<<rem_depth;
    const int block_h= 1<<rem_depth; //FIXME "w!=h"
    BlockNode block;
    int i,j;

    block.color[0]= l;
    block.color[1]= cb;
    block.color[2]= cr;
    block.mx= mx;
    block.my= my;
    block.ref= ref;
    block.type= type;
    block.level= level;

    for(j=0; j<block_h; j++){
        for(i=0; i<block_w; i++){
            s->block[index + i + j*w]= block;
        }
    }
}


static inline int get_symbol2(RangeCoder *c, uint8_t *state, int log2){
    int i;
    int r= log2>=0 ? 1<<log2 : 1;
    int v=0;

    av_assert2(log2>=-4);

    while(log2<28 && get_rac(c, state+4+log2)){
        v+= r;
        log2++;
        if(log2>0) r+=r;
    }

    for(i=log2-1; i>=0; i--){
        v+= get_rac(c, state+31-i)<<i;
    }

    return v;
}


static av_always_inline void predict_plane(SnowContext *s, IDWTELEM *buf, int plane_index, int add){
    const int mb_h= s->b_height << s->block_max_depth;
    int mb_y;
    for(mb_y=0; mb_y<=mb_h; mb_y++)
        predict_slice(s, buf, plane_index, add, mb_y);
}


static inline void put_symbol(RangeCoder *c, uint8_t *state, int v, int is_signed){
    int i;

    if(v){
        const int a= FFABS(v);
        const int e= av_log2(a);
        const int el= FFMIN(e, 10);
        put_rac(c, state+0, 0);

        for(i=0; i<el; i++){
            put_rac(c, state+1+i, 1);  //1..10
        }
        for(; i<e; i++){
            put_rac(c, state+1+9, 1);  //1..10
        }
        put_rac(c, state+1+FFMIN(i,9), 0);

        for(i=e-1; i>=el; i--){
            put_rac(c, state+22+9, (a>>i)&1); //22..31
        }
        for(; i>=0; i--){
            put_rac(c, state+22+i, (a>>i)&1); //22..31
        }

        if(is_signed)
            put_rac(c, state+11 + el, v < 0); //11..21
    }else{
        put_rac(c, state+0, 1);
    }
}


static inline void snow_set_blocks(SnowContext *s, int level, int x, int y, int l, int cb, int cr, int mx, int my, int ref, int type){
    const int w= s->b_width << s->block_max_depth;
    const int rem_depth= s->block_max_depth - level;
    const int index= (x + y*w) << rem_depth;
    const int block_w= 1<<rem_depth;
    BlockNode block;
    int i,j;

    block.color[0]= l;
    block.color[1]= cb;
    block.color[2]= cr;
    block.mx= mx;
    block.my= my;
    block.ref= ref;
    block.type= type;
    block.level= level;

    for(j=0; j<block_w; j++){
        for(i=0; i<block_w; i++){
            s->block[index + i + j*w]= block;
        }
    }
}


static av_always_inline void add_yblock(SnowContext *s, int sliced, slice_buffer *sb, IDWTELEM *dst, uint8_t *dst8, const uint8_t *obmc, int src_x, int src_y, int b_w, int b_h, int w, int h, int dst_stride, int src_stride, int obmc_stride, int b_x, int b_y, int add, int offset_dst, int plane_index){
    const int b_width = s->b_width  << s->block_max_depth;
    const int b_height= s->b_height << s->block_max_depth;
    const int b_stride= b_width;
    BlockNode *lt= &s->block[b_x + b_y*b_stride];
    BlockNode *rt= lt+1;
    BlockNode *lb= lt+b_stride;
    BlockNode *rb= lb+1;
    uint8_t *block[4];
    int tmp_step= src_stride >= 7*MB_SIZE ? MB_SIZE : MB_SIZE*src_stride;
    uint8_t *tmp = s->scratchbuf;
    uint8_t *ptmp;
    int x,y;

    if(b_x<0){
        lt= rt;
        lb= rb;
    }else if(b_x + 1 >= b_width){
        rt= lt;
        rb= lb;
    }
    if(b_y<0){
        lt= lb;
        rt= rb;
    }else if(b_y + 1 >= b_height){
        lb= lt;
        rb= rt;
    }

    if(src_x<0){ //FIXME merge with prev & always round internal width up to *16
        obmc -= src_x;
        b_w += src_x;
        if(!sliced && !offset_dst)
            dst -= src_x;
        src_x=0;
    }
    if(src_x + b_w > w){
        b_w = w - src_x;
    }
    if(src_y<0){
        obmc -= src_y*obmc_stride;
        b_h += src_y;
        if(!sliced && !offset_dst)
            dst -= src_y*dst_stride;
        src_y=0;
    }
    if(src_y + b_h> h){
        b_h = h - src_y;
    }

    if(b_w<=0 || b_h<=0) return;

    av_assert2(src_stride > 2*MB_SIZE + 5);

    if(!sliced && offset_dst)
        dst += src_x + src_y*dst_stride;
    dst8+= src_x + src_y*src_stride;
//    src += src_x + src_y*src_stride;

    ptmp= tmp + 3*tmp_step;
    block[0]= ptmp;
    ptmp+=tmp_step;
    ff_snow_pred_block(s, block[0], tmp, src_stride, src_x, src_y, b_w, b_h, lt, plane_index, w, h);

    if(same_block(lt, rt)){
        block[1]= block[0];
    }else{
        block[1]= ptmp;
        ptmp+=tmp_step;
        ff_snow_pred_block(s, block[1], tmp, src_stride, src_x, src_y, b_w, b_h, rt, plane_index, w, h);
    }

    if(same_block(lt, lb)){
        block[2]= block[0];
    }else if(same_block(rt, lb)){
        block[2]= block[1];
    }else{
        block[2]= ptmp;
        ptmp+=tmp_step;
        ff_snow_pred_block(s, block[2], tmp, src_stride, src_x, src_y, b_w, b_h, lb, plane_index, w, h);
    }

    if(same_block(lt, rb) ){
        block[3]= block[0];
    }else if(same_block(rt, rb)){
        block[3]= block[1];
    }else if(same_block(lb, rb)){
        block[3]= block[2];
    }else{
        block[3]= ptmp;
        ff_snow_pred_block(s, block[3], tmp, src_stride, src_x, src_y, b_w, b_h, rb, plane_index, w, h);
    }
    if(sliced){
        s->dwt.inner_add_yblock(obmc, obmc_stride, block, b_w, b_h, src_x,src_y, src_stride, sb, add, dst8);
    }else{
        for(y=0; y<b_h; y++){
            //FIXME ugly misuse of obmc_stride
            const uint8_t *obmc1= obmc + y*obmc_stride;
            const uint8_t *obmc2= obmc1+ (obmc_stride>>1);
            const uint8_t *obmc3= obmc1+ obmc_stride*(obmc_stride>>1);
            const uint8_t *obmc4= obmc3+ (obmc_stride>>1);
            for(x=0; x<b_w; x++){
                int v=   obmc1[x] * block[3][x + y*src_stride]
                        +obmc2[x] * block[2][x + y*src_stride]
                        +obmc3[x] * block[1][x + y*src_stride]
                        +obmc4[x] * block[0][x + y*src_stride];

                v <<= 8 - LOG2_OBMC_MAX;
                if(FRAC_BITS != 8){
                    v >>= 8 - FRAC_BITS;
                }
                if(add){
                    v += dst[x + y*dst_stride];
                    v = (v + (1<<(FRAC_BITS-1))) >> FRAC_BITS;
                    if(v&(~255)) v= ~(v>>31);
                    dst8[x + y*src_stride] = v;
                }else{
                    dst[x + y*dst_stride] -= v;
                }
            }
        }
    }
}


static av_always_inline void snow_horizontal_compose_lift_lead_out(int i, IDWTELEM * dst, IDWTELEM * src, IDWTELEM * ref, int width, int w, int lift_high, int mul, int add, int shift){
    for(; i<w; i++){
        dst[i] = src[i] - ((mul * (ref[i] + ref[i + 1]) + add) >> shift);
    }

    if((width^lift_high)&1){
        dst[w] = src[w] - ((mul * 2 * ref[w] + add) >> shift);
    }
}


static inline void pred_mv(SnowContext *s, int *mx, int *my, int ref,
                           const BlockNode *left, const BlockNode *top, const BlockNode *tr){
    if(s->ref_frames == 1){
        *mx = mid_pred(left->mx, top->mx, tr->mx);
        *my = mid_pred(left->my, top->my, tr->my);
    }else{
        const int *scale = ff_scale_mv_ref[ref];
        *mx = mid_pred((left->mx * scale[left->ref] + 128) >>8,
                       (top ->mx * scale[top ->ref] + 128) >>8,
                       (tr  ->mx * scale[tr  ->ref] + 128) >>8);
        *my = mid_pred((left->my * scale[left->ref] + 128) >>8,
                       (top ->my * scale[top ->ref] + 128) >>8,
                       (tr  ->my * scale[tr  ->ref] + 128) >>8);
    }
}


static av_always_inline void snow_interleave_line_footer(int * i, IDWTELEM * low, IDWTELEM * high){
    for (; (*i)>=0; (*i)-=2){
        low[(*i)+1] = high[(*i)>>1];
        low[*i] = low[(*i)>>1];
    }
}


static av_always_inline void snow_interleave_line_header(int * i, int width, IDWTELEM * low, IDWTELEM * high){
    (*i) = (width) - 2;

    if (width & 1){
        low[(*i)+1] = low[((*i)+1)>>1];
        (*i)--;
    }
}


static av_always_inline void snow_horizontal_compose_liftS_lead_out(int i, IDWTELEM * dst, IDWTELEM * src, IDWTELEM * ref, int width, int w){
        for(; i<w; i++){
            dst[i] = src[i] + ((ref[i] + ref[(i+1)]+W_BO + 4 * src[i]) >> W_BS);
        }

        if(width&1){
            dst[w] = src[w] + ((2 * ref[w] + W_BO + 4 * src[w]) >> W_BS);
        }
}


  void Compute(OpKernelContext *ctx) override {
    const Tensor *indices_t, *values_t, *shape_t, *reduction_axes_t;
    OP_REQUIRES_OK(ctx, ctx->input("input_indices", &indices_t));
    OP_REQUIRES_OK(ctx, ctx->input("input_values", &values_t));
    OP_REQUIRES_OK(ctx, ctx->input("input_shape", &shape_t));
    OP_REQUIRES_OK(ctx, ctx->input("reduction_axes", &reduction_axes_t));

    OP_REQUIRES_OK(ctx, ValidateInputs(shape_t, reduction_axes_t));

    SparseTensor sp;
    OP_REQUIRES_OK(ctx, SparseTensor::Create(tensor::DeepCopy(*indices_t),
                                         tensor::DeepCopy(*values_t),
                    TensorShape(shape_t->vec<int64>()), &sp));
    ReduceDetails reduction = SparseTensorReduceHelper(
        sp, reduction_axes_t->flat<int32>(), keep_dims_);

    sp.Reorder<T>(reduction.reorder_dims);
    // Count nnzs in the output SparseTensor.
    int64_t nnz = 0;
    auto iter = sp.group(reduction.group_by_dims);
    for (auto it = iter.begin(); it != iter.end(); ++it) {
      nnz++;
    }

    Tensor *out_indices_t;
    OP_REQUIRES_OK(ctx,
                   ctx->allocate_output(
                       0, TensorShape({nnz, reduction.reduced_shape.dims()}),
                       &out_indices_t));
    typename TTypes<int64>::Matrix out_indices_mat =
        out_indices_t->matrix<int64>();
    // For keep_dims. We don't explicitly set dim fields for reduced dims below.
    out_indices_mat.setZero();

    Tensor *out_values_t;
    OP_REQUIRES_OK(ctx,
                   ctx->allocate_output(1, TensorShape({nnz}), &out_values_t));
    auto out_flat = out_values_t->flat<T>();

    Tensor tmp_reduced_val;
    OP_REQUIRES_OK(ctx, ctx->allocate_temp(DataTypeToEnum<T>::value,
                                           TensorShape({}), &tmp_reduced_val));
    auto reduced_val = tmp_reduced_val.scalar<T>();
    int64_t i = 0;
    for (const auto &g : sp.group(reduction.group_by_dims)) {
      Op::template Run<T>(ctx, reduced_val, g.template values<T>());
      std::vector<int64> group = g.group();
      for (int64_t j = 0; j < group.size(); j++) {
        if (keep_dims_) {
          out_indices_mat(i, reduction.group_by_dims[j]) = group[j];
        } else {
          out_indices_mat(i, j) = group[j];
        }
      }
      out_flat(i) = reduced_val();
      i++;
      VLOG(2) << "coords: " << absl::StrJoin(g.group(), ",")
              << "; group " << Op::Name() << ": "
              << reduced_val();
    }

    Tensor *out_shape_t;
    OP_REQUIRES_OK(ctx, ctx->allocate_output(
                            2, TensorShape({reduction.reduced_shape.dims()}),
                            &out_shape_t));
    auto out_shape_flat = out_shape_t->flat<int64>();
    auto out_dim_sizes = reduction.reduced_shape.dim_sizes();
    if (!out_dim_sizes.empty()) {
      std::copy(out_dim_sizes.begin(), out_dim_sizes.end(), &out_shape_flat(0));
    }
  }

Prevent heap OOB in sparse reduction ops.

PiperOrigin-RevId: 387934524
Change-Id: I894aa30f1e454f09b471d565b4a325da49322c1a


Status ValidateInputs(const Tensor *shape_t, const Tensor *reduction_axes_t) {
  // indices and values are validated in SparseTensor ctor.
  if (!TensorShapeUtils::IsVector(shape_t->shape())) {
    return errors::InvalidArgument(
        "Expected input_shape to be a vector; got shape: ",
        shape_t->shape().DebugString());
  }
  if (!TensorShapeUtils::IsScalar(reduction_axes_t->shape()) &&
      !TensorShapeUtils::IsVector(reduction_axes_t->shape())) {
    return errors::InvalidArgument(
        "Expected reduction_axes to be a scalar or a vector; got shape: ",
        reduction_axes_t->shape().DebugString());
  }

  const auto reduction_axes_flat = reduction_axes_t->flat<int32>();
  for (int64_t i = 0; i < reduction_axes_flat.size(); i++) {
    int32_t axis = reduction_axes_flat(i);
    if (axis < -shape_t->NumElements() || axis >= shape_t->NumElements()) {
      return errors::InvalidArgument("Invalid reduction dimension ", axis,
                                     ", for input with ",
                                     shape_t->NumElements(), " dimensions.");
    }
  }

  return Status::OK();
}


  static void Run(OpKernelContext *ctx, typename TTypes<T>::Scalar &s, const typename TTypes<T>::UnalignedVec &v) {
      s.device(ctx->eigen_cpu_device()) = v.maximum();
  }


  void Compute(OpKernelContext *ctx) override {
    const Tensor *indices_t, *values_t, *shape_t, *reduction_axes_t;
    OP_REQUIRES_OK(ctx, ctx->input("input_indices", &indices_t));
    OP_REQUIRES_OK(ctx, ctx->input("input_values", &values_t));
    OP_REQUIRES_OK(ctx, ctx->input("input_shape", &shape_t));
    OP_REQUIRES_OK(ctx, ctx->input("reduction_axes", &reduction_axes_t));

    OP_REQUIRES_OK(ctx, ValidateInputs(shape_t, reduction_axes_t));

    // TODO(zongheng): we will call Reorder() below, which will modify
    // in-place the underlying indices and values buffers.  To avoid
    // surprises of this kernel being stateful, we work around the above by
    // making deep copies here.  Remove this if/when we change Reorder()'s
    // semantics.
    const auto shape_vec = shape_t->vec<int64>();
    SparseTensor sp;
    OP_REQUIRES_OK(ctx, SparseTensor::Create(
        tensor::DeepCopy(*indices_t), tensor::DeepCopy(*values_t),
                    TensorShape(shape_vec), &sp));
    ReduceDetails reduction = SparseTensorReduceHelper(
        sp, reduction_axes_t->flat<int32>(), keep_dims_);

    Tensor *out_values;
    OP_REQUIRES_OK(
        ctx, ctx->allocate_output(0, reduction.reduced_shape, &out_values));
    auto out_flat = out_values->flat<T>();
    out_flat.setZero();

    Tensor tmp_reduced_val;
    OP_REQUIRES_OK(ctx, ctx->allocate_temp(DataTypeToEnum<T>::value,
                                           TensorShape({}), &tmp_reduced_val));
    auto reduced_val = tmp_reduced_val.scalar<T>();

    // Compute strides, and use it to convert coords to flat index.  The
    // coordinates returned by .group() have the same ndims as group_by_dims.
    gtl::InlinedVector<int64, 8> output_strides(reduction.group_by_dims.size());
    if (!output_strides.empty()) {  // Do this iff we don't reduce all.
      output_strides.back() = 1;
      for (int d = output_strides.size() - 2; d >= 0; --d) {
        output_strides[d] =
            output_strides[d + 1] * shape_vec(reduction.group_by_dims[d + 1]);
      }
    }

    auto CoordinatesToFlatIndex = [](ArraySlice<int64> coords,
                                     ArraySlice<int64> strides) -> int64 {
      if (strides.empty()) {  // Reduce all.
        return 0;
      }
      CHECK_EQ(coords.size(), strides.size());
      int64_t idx = 0;
      for (int i = 0; i < coords.size(); ++i) {
        idx += coords[i] * strides[i];
      }
      return idx;
    };

    // Each group maps one-on-one onto a value in the reduced tensor.
    // g.group() provides the coordinates of a particular reduced value.
    sp.Reorder<T>(reduction.reorder_dims);
    for (const auto &g : sp.group(reduction.group_by_dims)) {
      Op::template Run<T>(ctx, reduced_val, g.template values<T>());
      OP_REQUIRES(ctx,
                  output_strides.empty() ||
                  (g.group().size() == output_strides.size()),
                  errors::Internal(
                      "Expected group size and output_strides size to match",
                      ", but got ", g.group().size(), " and ",
                      output_strides.size()));
      const int64_t idx = CoordinatesToFlatIndex(g.group(), output_strides);
      OP_REQUIRES(ctx,
                  idx >= 0 && idx < out_flat.size(),
                  errors::Internal(
                      "Obtained a write index of ", idx,
                      " which is outside of bounds of [0, ",
                      out_flat.size(), ")"));
      out_flat(idx) = reduced_val();
      VLOG(2) << "coords: " << absl::StrJoin(g.group(), ",")
              << "; idx: " << idx << "; group " << Op::Name() << ": "
              << reduced_val();
    }
  }


  static StringPiece Name() {
      return "sum";
  }


ReduceDetails SparseTensorReduceHelper(const SparseTensor &sp,
                                       gtl::ArraySlice<int32> axes_slice,
                                       bool keep_dims) {
  ReduceDetails reduction;

  std::vector<int32> reduction_axes(axes_slice.begin(), axes_slice.end());
  int ndims = sp.dims();
  for (int64_t i = 0; i < reduction_axes.size(); ++i) {
    reduction_axes[i] = (reduction_axes[i] + ndims) % ndims;
  }
  std::sort(reduction_axes.begin(), reduction_axes.end());

  // (0) Calculate the grouping dimensions:
  // group_by_dims == {0, .., NDIMS-1} \ reduction_axes.
  std::vector<int64> perm(ndims);
  std::iota(perm.begin(), perm.end(), 0);

  // Requires perm and reduction_axes_ be sorted; group_by_dims will be
  // sorted as well.
  std::set_difference(
      perm.begin(), perm.end(), reduction_axes.begin(), reduction_axes.end(),
      std::inserter(reduction.group_by_dims, reduction.group_by_dims.begin()));

  // Now append the rest of the axes (the complement of group_by_dims_);
  // result is used by Reorder().
  reduction.reorder_dims = reduction.group_by_dims;
  std::set_difference(perm.begin(), perm.end(), reduction.group_by_dims.begin(),
                      reduction.group_by_dims.end(),
                      std::back_inserter(reduction.reorder_dims));

  // (1) Calculate the shape after reduction.
  auto sp_shape = sp.shape();
  std::vector<int64> out_dim_sizes;
  if (keep_dims) {
    out_dim_sizes.reserve(ndims);
    auto beg = reduction.group_by_dims.begin();
    auto end = reduction.group_by_dims.end();
    for (int d = 0; d < ndims; ++d) {
      if (std::find(beg, end, d) == end) {
        out_dim_sizes.push_back(1);  // A reduced axis.
      } else {
        out_dim_sizes.push_back(sp_shape[d]);
      }
    }
  } else {
    out_dim_sizes = sp.PickDims(reduction.group_by_dims);
  }

  reduction.reduced_shape = TensorShape(out_dim_sizes);
  return reduction;
}


  static StringPiece Name() {
      return "max";
  }


  explicit SparseReduceOp(OpKernelConstruction *ctx) : OpKernel(ctx) {
    OP_REQUIRES_OK(ctx, ctx->GetAttr("keep_dims", &keep_dims_));
  }


  explicit SparseReduceSparseOp(OpKernelConstruction *ctx) : OpKernel(ctx) {
    OP_REQUIRES_OK(ctx, ctx->GetAttr("keep_dims", &keep_dims_));
  }


  static void Run(OpKernelContext *ctx, typename TTypes<T>::Scalar &s, const typename TTypes<T>::UnalignedVec &v) {
      s.device(ctx->eigen_cpu_device()) = v.sum();
  }


  void Compute(OpKernelContext* context) override {
    // Here's the basic idea:
    // Batch and depth dimension are independent from row and col dimension. And
    // because FractionalAvgPool currently only support pooling along row and
    // col, we can basically think of this 4D tensor backpropagation as
    // operation of a series of 2D planes.
    //
    // For each element of a 'slice' (2D plane) of output_backprop, we need to
    // figure out its contributors when doing FractionalAvgPool operation. This
    // can be done based on row_pooling_sequence, col_pooling_seq and
    // overlapping.
    // Once we figure out the original contributors, we just need to evenly
    // divide the value of this element among these contributors.
    //
    // Internally, we divide the out_backprop tensor and store it in a temporary
    // tensor of double type. And cast it to the corresponding type.
    typedef Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>
        ConstEigenMatrixMap;
    typedef Eigen::Map<Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>>
        EigenDoubleMatrixMap;

    // Grab the inputs.
    const Tensor& orig_input_tensor_shape = context->input(0);
    OP_REQUIRES(context,
                orig_input_tensor_shape.dims() == 1 &&
                    orig_input_tensor_shape.NumElements() == 4,
                errors::InvalidArgument("original input tensor shape must be"
                                        "1-dimensional and 4 elements"));
    const Tensor& out_backprop = context->input(1);
    const Tensor& row_seq_tensor = context->input(2);
    const Tensor& col_seq_tensor = context->input(3);

    const int64_t out_batch = out_backprop.dim_size(0);
    const int64_t out_rows = out_backprop.dim_size(1);
    const int64_t out_cols = out_backprop.dim_size(2);
    const int64_t out_depth = out_backprop.dim_size(3);

    OP_REQUIRES(context, row_seq_tensor.NumElements() > out_rows,
                errors::InvalidArgument("Given out_backprop shape ",
                                        out_backprop.shape().DebugString(),
                                        ", row_seq_tensor must have at least ",
                                        out_rows + 1, " elements, but got ",
                                        row_seq_tensor.NumElements()));
    OP_REQUIRES(context, col_seq_tensor.NumElements() > out_cols,
                errors::InvalidArgument("Given out_backprop shape ",
                                        out_backprop.shape().DebugString(),
                                        ", col_seq_tensor must have at least ",
                                        out_cols + 1, " elements, but got ",
                                        col_seq_tensor.NumElements()));

    auto row_seq_tensor_flat = row_seq_tensor.flat<int64>();
    auto col_seq_tensor_flat = col_seq_tensor.flat<int64>();
    auto orig_input_tensor_shape_flat = orig_input_tensor_shape.flat<int64>();

    const int64_t in_batch = orig_input_tensor_shape_flat(0);
    const int64_t in_rows = orig_input_tensor_shape_flat(1);
    const int64_t in_cols = orig_input_tensor_shape_flat(2);
    const int64_t in_depth = orig_input_tensor_shape_flat(3);
    OP_REQUIRES(
        context, in_batch != 0,
        errors::InvalidArgument("Batch dimension of input must not be 0"));
    OP_REQUIRES(
        context, in_rows != 0,
        errors::InvalidArgument("Rows dimension of input must not be 0"));
    OP_REQUIRES(
        context, in_cols != 0,
        errors::InvalidArgument("Columns dimension of input must not be 0"));
    OP_REQUIRES(
        context, in_depth != 0,
        errors::InvalidArgument("Depth dimension of input must not be 0"));

    constexpr int tensor_in_and_out_dims = 4;
    // Transform orig_input_tensor_shape into TensorShape
    TensorShape in_shape;
    for (auto i = 0; i < tensor_in_and_out_dims; ++i) {
      in_shape.AddDim(orig_input_tensor_shape_flat(i));
    }

    // Create intermediate in_backprop.
    Tensor in_backprop_tensor_temp;
    OP_REQUIRES_OK(context, context->forward_input_or_allocate_temp(
                                {0}, DataTypeToEnum<double>::v(), in_shape,
                                &in_backprop_tensor_temp));
    in_backprop_tensor_temp.flat<double>().setZero();
    // Transform 4D tensor to 2D matrix.
    EigenDoubleMatrixMap in_backprop_tensor_temp_mat(
        in_backprop_tensor_temp.flat<double>().data(), in_depth,
        in_cols * in_rows * in_batch);
    ConstEigenMatrixMap out_backprop_mat(out_backprop.flat<T>().data(),
                                         out_depth,
                                         out_cols * out_rows * out_batch);
    // Loop through each element of out_backprop and evenly distribute the
    // element to the corresponding pooling cell.
    const int64_t in_max_row_index = in_rows - 1;
    const int64_t in_max_col_index = in_cols - 1;
    for (int64_t b = 0; b < out_batch; ++b) {
      for (int64_t r = 0; r < out_rows; ++r) {
        const int64_t in_row_start = row_seq_tensor_flat(r);
        int64_t in_row_end = overlapping_ ? row_seq_tensor_flat(r + 1)
                                          : row_seq_tensor_flat(r + 1) - 1;
        in_row_end = std::min(in_row_end, in_max_row_index);
        for (int64_t c = 0; c < out_cols; ++c) {
          const int64_t in_col_start = col_seq_tensor_flat(c);
          int64_t in_col_end = overlapping_ ? col_seq_tensor_flat(c + 1)
                                            : col_seq_tensor_flat(c + 1) - 1;
          in_col_end = std::min(in_col_end, in_max_col_index);

          const int64_t num_elements_in_pooling_cell =
              (in_row_end - in_row_start + 1) * (in_col_end - in_col_start + 1);
          const int64_t out_index = (b * out_rows + r) * out_cols + c;
          // Now we can evenly distribute out_backprop(b, h, w, *) to
          // in_backprop(b, hs:he, ws:we, *).
          for (int64_t in_r = in_row_start; in_r <= in_row_end; ++in_r) {
            for (int64_t in_c = in_col_start; in_c <= in_col_end; ++in_c) {
              const int64_t in_index = (b * in_rows + in_r) * in_cols + in_c;
              // Walk through each channel (depth).
              for (int64_t d = 0; d < out_depth; ++d) {
                const double out_backprop_element = static_cast<double>(
                    out_backprop_mat.coeffRef(d, out_index));
                double& in_backprop_ref =
                    in_backprop_tensor_temp_mat.coeffRef(d, in_index);
                in_backprop_ref +=
                    out_backprop_element / num_elements_in_pooling_cell;
              }
            }
          }
        }
      }
    }

    // Depending on the type, cast double to type T.
    Tensor* in_backprop_tensor = nullptr;
    OP_REQUIRES_OK(context, context->forward_input_or_allocate_output(
                                {0}, 0, in_shape, &in_backprop_tensor));
    auto in_backprop_tensor_flat = in_backprop_tensor->flat<T>();
    auto in_backprop_tensor_temp_flat = in_backprop_tensor_temp.flat<double>();
    for (int64_t i = 0; i < in_backprop_tensor_flat.size(); ++i) {
      in_backprop_tensor_flat(i) =
          static_cast<T>(in_backprop_tensor_temp_flat(i));
    }
  }

Validate dimensions of input tensor in `FractionalAvgPoolGrad`

PiperOrigin-RevId: 388286227
Change-Id: Ieb7566155e92acc8993a2212c76deacadc0edc8a


  void Compute(OpKernelContext* context) override {
    typedef Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>
        ConstEigenMatrixMap;
    typedef Eigen::Map<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>
        EigenMatrixMap;

    constexpr int tensor_in_and_out_dims = 4;

    const Tensor& tensor_in = context->input(0);
    OP_REQUIRES(context, tensor_in.dims() == tensor_in_and_out_dims,
                errors::InvalidArgument("tensor_in must be 4-dimensional"));

    std::vector<int> input_size(tensor_in_and_out_dims);
    std::vector<int> output_size(tensor_in_and_out_dims);
    for (int i = 0; i < tensor_in_and_out_dims; ++i) {
      input_size[i] = tensor_in.dim_size(i);
      OP_REQUIRES(
          context, pooling_ratio_[i] <= input_size[i],
          errors::InvalidArgument(
              "Pooling ratio cannot be bigger than input tensor dim size."));
    }
    // Output size.
    for (int i = 0; i < tensor_in_and_out_dims; ++i) {
      output_size[i] =
          static_cast<int>(std::floor(input_size[i] / pooling_ratio_[i]));
      DCHECK_GT(output_size[i], 0);
    }

    // Generate pooling sequence.
    std::vector<int64> row_cum_seq;
    std::vector<int64> col_cum_seq;
    GuardedPhiloxRandom generator;
    generator.Init(seed_, seed2_);
    row_cum_seq = GeneratePoolingSequence(input_size[1], output_size[1],
                                          &generator, pseudo_random_);
    col_cum_seq = GeneratePoolingSequence(input_size[2], output_size[2],
                                          &generator, pseudo_random_);

    // Prepare output.
    Tensor* output_tensor = nullptr;
    OP_REQUIRES_OK(context, context->allocate_output(
                                0,
                                TensorShape({output_size[0], output_size[1],
                                             output_size[2], output_size[3]}),
                                &output_tensor));
    Tensor* output_row_seq_tensor = nullptr;
    OP_REQUIRES_OK(context,
                   context->allocate_output(
                       1, TensorShape({static_cast<int64>(row_cum_seq.size())}),
                       &output_row_seq_tensor));
    Tensor* output_col_seq_tensor = nullptr;
    OP_REQUIRES_OK(context,
                   context->allocate_output(
                       2, TensorShape({static_cast<int64>(col_cum_seq.size())}),
                       &output_col_seq_tensor));

    ConstEigenMatrixMap in_mat(tensor_in.flat<T>().data(), input_size[3],
                               input_size[2] * input_size[1] * input_size[0]);

    EigenMatrixMap out_mat(output_tensor->flat<T>().data(), output_size[3],
                           output_size[2] * output_size[1] * output_size[0]);
    // out_count corresponds to number of elements in each pooling cell.
    Eigen::Matrix<T, Eigen::Dynamic, 1> out_count(out_mat.cols());

    // Initializes the output tensor and out_count with 0.
    out_mat.setZero();
    out_count.setZero();

    auto output_row_seq_flat = output_row_seq_tensor->flat<int64>();
    auto output_col_seq_flat = output_col_seq_tensor->flat<int64>();

    // Set output tensors.
    for (int i = 0; i < row_cum_seq.size(); ++i) {
      output_row_seq_flat(i) = row_cum_seq[i];
    }

    for (int i = 0; i < col_cum_seq.size(); ++i) {
      output_col_seq_flat(i) = col_cum_seq[i];
    }

    // For both input and output,
    // 0: batch
    // 1: row / row
    // 2: col / col
    // 3: depth / channel
    const int64_t row_max = input_size[1] - 1;
    const int64_t col_max = input_size[2] - 1;
    for (int64_t b = 0; b < input_size[0]; ++b) {
      // row sequence.
      for (int64_t hs = 0; hs < row_cum_seq.size() - 1; ++hs) {
        // row start and end.
        const int64_t row_start = row_cum_seq[hs];
        int64_t row_end =
            overlapping_ ? row_cum_seq[hs + 1] : row_cum_seq[hs + 1] - 1;
        row_end = std::min(row_end, row_max);

        // col sequence.
        for (int64_t ws = 0; ws < col_cum_seq.size() - 1; ++ws) {
          const int64_t out_offset =
              (b * output_size[1] + hs) * output_size[2] + ws;
          // col start and end.
          const int64_t col_start = col_cum_seq[ws];
          int64_t col_end =
              overlapping_ ? col_cum_seq[ws + 1] : col_cum_seq[ws + 1] - 1;
          col_end = std::min(col_end, col_max);
          for (int64_t h = row_start; h <= row_end; ++h) {
            for (int64_t w = col_start; w <= col_end; ++w) {
              const int64_t in_offset =
                  (b * input_size[1] + h) * input_size[2] + w;
              out_mat.col(out_offset) += in_mat.col(in_offset);
              out_count(out_offset)++;
            }
          }
        }
      }
    }
    DCHECK_GT(out_count.minCoeff(), 0);
    out_mat.array().rowwise() /= out_count.transpose().array();
  }


static CustomStreamInfo *TIFFAcquireCustomStreamForWriting(
  PhotoshopProfile *profile,ExceptionInfo *exception)
{
  CustomStreamInfo
    *custom_stream;

  custom_stream=AcquireCustomStreamInfo(exception);
  if (custom_stream == (CustomStreamInfo *) NULL)
    return(custom_stream);
  SetCustomStreamData(custom_stream,(void *) profile);
  SetCustomStreamWriter(custom_stream,TIFFWriteCustomStream);
  SetCustomStreamSeeker(custom_stream,TIFFSeekCustomStream);
  SetCustomStreamTeller(custom_stream,TIFFTellCustomStream);
  return(custom_stream);
}


static void TIFFReadPhotoshopLayers(const ImageInfo *image_info,Image *image,
  ExceptionInfo *exception)
{
  const char
    *option;

  const StringInfo
    *profile;

  CustomStreamInfo
    *custom_stream;

  Image
    *layers;

  ImageInfo
    *clone_info;

  PhotoshopProfile
    photoshop_profile;

  PSDInfo
    info;

  ssize_t
    i;

  if (GetImageListLength(image) != 1)
    return;
  if ((image_info->number_scenes == 1) && (image_info->scene == 0))
    return;
  option=GetImageOption(image_info,"tiff:ignore-layers");
  if (option != (const char * ) NULL)
    return;
  profile=GetImageProfile(image,"tiff:37724");
  if (profile == (const StringInfo *) NULL)
    return;
  for (i=0; i < (ssize_t) profile->length-8; i++)
  {
    if (LocaleNCompare((const char *) (profile->datum+i),
        image->endian == MSBEndian ? "8BIM" : "MIB8",4) != 0)
      continue;
    i+=4;
    if ((LocaleNCompare((const char *) (profile->datum+i),
         image->endian == MSBEndian ? "Layr" : "ryaL",4) == 0) ||
        (LocaleNCompare((const char *) (profile->datum+i),
         image->endian == MSBEndian ? "LMsk" : "ksML",4) == 0) ||
        (LocaleNCompare((const char *) (profile->datum+i),
         image->endian == MSBEndian ? "Lr16" : "61rL",4) == 0) ||
        (LocaleNCompare((const char *) (profile->datum+i),
         image->endian == MSBEndian ? "Lr32" : "23rL",4) == 0))
      break;
  }
  i+=4;
  if (i >= (ssize_t) (profile->length-8))
    return;
  photoshop_profile.data=(StringInfo *) profile;
  photoshop_profile.length=profile->length;
  custom_stream=TIFFAcquireCustomStreamForReading(&photoshop_profile,exception);
  if (custom_stream == (CustomStreamInfo *) NULL)
    return;
  layers=CloneImage(image,0,0,MagickTrue,exception);
  if (layers == (Image *) NULL)
    {
      custom_stream=DestroyCustomStreamInfo(custom_stream);
      return;
    }
  (void) DeleteImageProfile(layers,"tiff:37724");
  AttachCustomStream(layers->blob,custom_stream);
  SeekBlob(layers,(MagickOffsetType) i,SEEK_SET);
  InitPSDInfo(layers,&info);
  clone_info=CloneImageInfo(image_info);
  clone_info->number_scenes=0;
  (void) ReadPSDLayers(layers,clone_info,&info,exception);
  clone_info=DestroyImageInfo(clone_info);
  DeleteImageFromList(&layers);
  if (layers != (Image *) NULL)
    {
      SetImageArtifact(image,"tiff:has-layers","true");
      AppendImageToList(&image,layers);
      while (layers != (Image *) NULL)
      {
        SetImageArtifact(layers,"tiff:has-layers","true");
        DetachBlob(layers->blob);
        layers=GetNextImageInList(layers);
      }
    }
  custom_stream=DestroyCustomStreamInfo(custom_stream);
}


static inline size_t WriteLSBLong(FILE *file,const unsigned int value)
{
  unsigned char
    buffer[4];

  buffer[0]=(unsigned char) value;
  buffer[1]=(unsigned char) (value >> 8);
  buffer[2]=(unsigned char) (value >> 16);
  buffer[3]=(unsigned char) (value >> 24);
  return(fwrite(buffer,1,4,file));
}


static ssize_t TIFFWriteCustomStream(unsigned char *data,const size_t count,
  void *user_data)
{
  PhotoshopProfile
    *profile;

  if (count == 0)
    return(0);
  profile=(PhotoshopProfile *) user_data;
  if ((profile->offset+(MagickOffsetType) count) >=
        (MagickOffsetType) profile->extent)
    {
      profile->extent+=count+profile->quantum;
      profile->quantum<<=1;
      SetStringInfoLength(profile->data,profile->extent);
    }
  (void) memcpy(profile->data->datum+profile->offset,data,count);
  profile->offset+=count;
  return(count);
}


static void TIFFSetProfiles(TIFF *tiff,Image *image)
{
  const char
    *name;

  const StringInfo
    *profile;

  if (image->profiles == (void *) NULL)
    return;
  ResetImageProfileIterator(image);
  for (name=GetNextImageProfile(image); name != (const char *) NULL; )
  {
    profile=GetImageProfile(image,name);
    if (GetStringInfoLength(profile) == 0)
      {
        name=GetNextImageProfile(image);
        continue;
      }
#if defined(TIFFTAG_XMLPACKET)
    if (LocaleCompare(name,"xmp") == 0)
      (void) TIFFSetField(tiff,TIFFTAG_XMLPACKET,(uint32) GetStringInfoLength(
        profile),GetStringInfoDatum(profile));
#endif
#if defined(TIFFTAG_ICCPROFILE)
    if (LocaleCompare(name,"icc") == 0)
      (void) TIFFSetField(tiff,TIFFTAG_ICCPROFILE,(uint32) GetStringInfoLength(
        profile),GetStringInfoDatum(profile));
#endif
    if (LocaleCompare(name,"iptc") == 0)
      {
        const TIFFField
          *field;

        size_t
          length;

        StringInfo
          *iptc_profile;

        iptc_profile=CloneStringInfo(profile);
        length=GetStringInfoLength(profile)+4-(GetStringInfoLength(profile) &
          0x03);
        SetStringInfoLength(iptc_profile,length);
        field=TIFFFieldWithTag(tiff,TIFFTAG_RICHTIFFIPTC);
        if (TIFFFieldDataType(field) == TIFF_LONG)
          {
            if (TIFFIsByteSwapped(tiff))
              TIFFSwabArrayOfLong((uint32 *) GetStringInfoDatum(iptc_profile),
                (unsigned long) (length/4));
            (void) TIFFSetField(tiff,TIFFTAG_RICHTIFFIPTC,(uint32)
              GetStringInfoLength(iptc_profile)/4,GetStringInfoDatum(
                iptc_profile));
          }
        else
          (void) TIFFSetField(tiff,TIFFTAG_RICHTIFFIPTC,(uint32)
            GetStringInfoLength(iptc_profile),GetStringInfoDatum(
              iptc_profile));
        iptc_profile=DestroyStringInfo(iptc_profile);
      }
#if defined(TIFFTAG_PHOTOSHOP)
    if (LocaleCompare(name,"8bim") == 0)
      (void) TIFFSetField(tiff,TIFFTAG_PHOTOSHOP,(uint32)
        GetStringInfoLength(profile),GetStringInfoDatum(profile));
#endif
    if (LocaleCompare(name,"tiff:37724") == 0)
      (void) TIFFSetField(tiff,37724,(uint32) GetStringInfoLength(profile),
        GetStringInfoDatum(profile));
    if (LocaleCompare(name,"tiff:34118") == 0)
      (void) TIFFSetField(tiff,34118,(uint32) GetStringInfoLength(profile),
        GetStringInfoDatum(profile));
    name=GetNextImageProfile(image);
  }
}


ModuleExport void UnregisterTIFFImage(void)
{
  (void) UnregisterMagickInfo("TIFF64");
  (void) UnregisterMagickInfo("TIFF");
  (void) UnregisterMagickInfo("TIF");
  (void) UnregisterMagickInfo("PTIF");
#if defined(MAGICKCORE_TIFF_DELEGATE)
  if (tiff_semaphore == (SemaphoreInfo *) NULL)
    ActivateSemaphoreInfo(&tiff_semaphore);
  LockSemaphoreInfo(tiff_semaphore);
  if (instantiate_key != MagickFalse)
    {
#if defined(MAGICKCORE_HAVE_TIFFMERGEFIELDINFO) && defined(MAGICKCORE_HAVE_TIFFSETTAGEXTENDER)
      if (tag_extender == (TIFFExtendProc) NULL)
        (void) TIFFSetTagExtender(tag_extender);
#endif
      if (DeleteMagickThreadKey(tiff_exception) == MagickFalse)
        ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
      (void) TIFFSetWarningHandler(warning_handler);
      (void) TIFFSetErrorHandler(error_handler);
      instantiate_key=MagickFalse;
    }
  UnlockSemaphoreInfo(tiff_semaphore);
  RelinquishSemaphoreInfo(&tiff_semaphore);
#endif
}


static void TIFFSetImageProperties(TIFF *tiff,Image *image,
  const char *tag,ExceptionInfo *exception)
{
  char
    buffer[MagickPathExtent],
    filename[MagickPathExtent];

  FILE
    *file;

  int
    unique_file;

  /*
    Set EXIF or GPS image properties.
  */
  unique_file=AcquireUniqueFileResource(filename);
  file=(FILE *) NULL;
  if (unique_file != -1)
    file=fdopen(unique_file,"rb+");
  if ((unique_file == -1) || (file == (FILE *) NULL))
    {
      (void) RelinquishUniqueFileResource(filename);
      (void) ThrowMagickException(exception,GetMagickModule(),WandError,
        "UnableToCreateTemporaryFile","`%s'",filename);
      return;
    }
  TIFFPrintDirectory(tiff,file,0);
  (void) fseek(file,0,SEEK_SET);
  while (fgets(buffer,(int) sizeof(buffer),file) != NULL)
  {
    char
      *p,
      property[MagickPathExtent],
      value[MagickPathExtent];

    (void) StripMagickString(buffer);
    p=strchr(buffer,':');
    if (p == (char *) NULL)
      continue;
    *p='\0';
    (void) sprintf(property,"%s%.1024s",tag,buffer);
    (void) sprintf(value,"%s",p+1);
    (void) StripMagickString(value);
    (void) SetImageProperty(image,property,value,exception);
  }
  (void) fclose(file);
  (void) RelinquishUniqueFileResource(filename);
}


static MagickOffsetType TIFFTellCustomStream(void *user_data)
{
  PhotoshopProfile
    *profile;

  profile=(PhotoshopProfile *) user_data;
  return(profile->offset);
}


static CustomStreamInfo *TIFFAcquireCustomStreamForReading(
  PhotoshopProfile *profile,ExceptionInfo *exception)
{
  CustomStreamInfo
    *custom_stream;

  custom_stream=AcquireCustomStreamInfo(exception);
  if (custom_stream == (CustomStreamInfo *) NULL)
    return(custom_stream);
  SetCustomStreamData(custom_stream,(void *) profile);
  SetCustomStreamReader(custom_stream,TIFFReadCustomStream);
  SetCustomStreamSeeker(custom_stream,TIFFSeekCustomStream);
  SetCustomStreamTeller(custom_stream,TIFFTellCustomStream);
  return(custom_stream);
}


static void TIFFGetEXIFProperties(TIFF *tiff,Image *image,
  const ImageInfo* image_info,ExceptionInfo *exception)
{
#if defined(MAGICKCORE_HAVE_TIFFREADEXIFDIRECTORY)
  const char
    *option;

  tdir_t
    directory;

#if defined(TIFF_VERSION_BIG)
  uint64
#else
  uint32
#endif
    offset;

  /*
    Read EXIF properties.
  */
  option=GetImageOption(image_info,"tiff:exif-properties");
  if (IsStringFalse(option) != MagickFalse)
    return;
  offset=0;
  if (TIFFGetField(tiff,TIFFTAG_EXIFIFD,&offset) != 1)
    return;
  directory=TIFFCurrentDirectory(tiff);
  if (TIFFReadEXIFDirectory(tiff,offset) == 1)
    TIFFSetImageProperties(tiff,image,"exif:",exception);
  TIFFSetDirectory(tiff,directory);
#else
  magick_unreferenced(tiff);
  magick_unreferenced(image);
  magick_unreferenced(image_info);
  magick_unreferenced(exception);
#endif
}


static MagickBooleanType WriteGROUP4Image(const ImageInfo *image_info,
  Image *image,ExceptionInfo *exception)
{
  char
    filename[MagickPathExtent];

  FILE
    *file;

  Image
    *huffman_image;

  ImageInfo
    *write_info;

  int
    unique_file;

  MagickBooleanType
    status;

  ssize_t
    i;

  ssize_t
    count;

  TIFF
    *tiff;

  toff_t
    *byte_count,
    strip_size;

  unsigned char
    *buffer;

  /*
    Write image as CCITT Group4 TIFF image to a temporary file.
  */
  assert(image_info != (const ImageInfo *) NULL);
  assert(image_info->signature == MagickCoreSignature);
  assert(image != (Image *) NULL);
  assert(image->signature == MagickCoreSignature);
  if (image->debug != MagickFalse)
    (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
  assert(exception != (ExceptionInfo *) NULL);
  assert(exception->signature == MagickCoreSignature);
  status=OpenBlob(image_info,image,WriteBinaryBlobMode,exception);
  if (status == MagickFalse)
    return(status);
  huffman_image=CloneImage(image,0,0,MagickTrue,exception);
  if (huffman_image == (Image *) NULL)
    {
      (void) CloseBlob(image);
      return(MagickFalse);
    }
  huffman_image->endian=MSBEndian;
  file=(FILE *) NULL;
  unique_file=AcquireUniqueFileResource(filename);
  if (unique_file != -1)
    file=fdopen(unique_file,"wb");
  if ((unique_file == -1) || (file == (FILE *) NULL))
    {
      ThrowFileException(exception,FileOpenError,"UnableToCreateTemporaryFile",
        filename);
      return(MagickFalse);
    }
  (void) FormatLocaleString(huffman_image->filename,MagickPathExtent,"tiff:%s",
    filename);
  if (IsImageMonochrome(image) == MagickFalse)
    (void) SetImageType(huffman_image,BilevelType,exception);
  write_info=CloneImageInfo((ImageInfo *) NULL);
  SetImageInfoFile(write_info,file);
  if (IsImageMonochrome(image) == MagickFalse)
    (void) SetImageType(image,BilevelType,exception);
  (void) SetImageDepth(image,1,exception);
  write_info->compression=Group4Compression;
  write_info->type=BilevelType;
  status=WriteTIFFImage(write_info,huffman_image,exception);
  (void) fflush(file);
  write_info=DestroyImageInfo(write_info);
  if (status == MagickFalse)
    {
      huffman_image=DestroyImage(huffman_image);
      (void) fclose(file);
      (void) RelinquishUniqueFileResource(filename);
      return(MagickFalse);
    }
  tiff=TIFFOpen(filename,"rb");
  if (tiff == (TIFF *) NULL)
    {
      huffman_image=DestroyImage(huffman_image);
      (void) fclose(file);
      (void) RelinquishUniqueFileResource(filename);
      ThrowFileException(exception,FileOpenError,"UnableToOpenFile",
        image_info->filename);
      return(MagickFalse);
    }
  /*
    Allocate raw strip buffer.
  */
  if (TIFFGetField(tiff,TIFFTAG_STRIPBYTECOUNTS,&byte_count) != 1)
    {
      TIFFClose(tiff);
      huffman_image=DestroyImage(huffman_image);
      (void) fclose(file);
      (void) RelinquishUniqueFileResource(filename);
      return(MagickFalse);
    }
  strip_size=byte_count[0];
  for (i=1; i < (ssize_t) TIFFNumberOfStrips(tiff); i++)
    if (byte_count[i] > strip_size)
      strip_size=byte_count[i];
  buffer=(unsigned char *) AcquireQuantumMemory((size_t) strip_size,
    sizeof(*buffer));
  if (buffer == (unsigned char *) NULL)
    {
      TIFFClose(tiff);
      huffman_image=DestroyImage(huffman_image);
      (void) fclose(file);
      (void) RelinquishUniqueFileResource(filename);
      ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
        image_info->filename);
    }
  /*
    Compress runlength encoded to 2D Huffman pixels.
  */
  for (i=0; i < (ssize_t) TIFFNumberOfStrips(tiff); i++)
  {
    count=(ssize_t) TIFFReadRawStrip(tiff,(uint32) i,buffer,strip_size);
    if (WriteBlob(image,(size_t) count,buffer) != count)
      status=MagickFalse;
  }
  buffer=(unsigned char *) RelinquishMagickMemory(buffer);
  TIFFClose(tiff);
  huffman_image=DestroyImage(huffman_image);
  (void) fclose(file);
  (void) RelinquishUniqueFileResource(filename);
  (void) CloseBlob(image);
  return(status);
}


static void TIFFSetProperties(TIFF *tiff,const MagickBooleanType adjoin,
  Image *image,ExceptionInfo *exception)
{
  const char
    *value;

  value=GetImageArtifact(image,"tiff:document");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_DOCUMENTNAME,value);
  value=GetImageArtifact(image,"tiff:hostcomputer");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_HOSTCOMPUTER,value);
  value=GetImageArtifact(image,"tiff:artist");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_ARTIST,value);
  value=GetImageArtifact(image,"tiff:timestamp");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_DATETIME,value);
  value=GetImageArtifact(image,"tiff:make");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_MAKE,value);
  value=GetImageArtifact(image,"tiff:model");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_MODEL,value);
  value=GetImageArtifact(image,"tiff:software");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_SOFTWARE,value);
  value=GetImageArtifact(image,"tiff:copyright");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_COPYRIGHT,value);
  value=GetImageArtifact(image,"kodak-33423");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,33423,value);
  value=GetImageArtifact(image,"kodak-36867");
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,36867,value);
  value=GetImageProperty(image,"label",exception);
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_PAGENAME,value);
  value=GetImageProperty(image,"comment",exception);
  if (value != (const char *) NULL)
    (void) TIFFSetField(tiff,TIFFTAG_IMAGEDESCRIPTION,value);
  value=GetImageArtifact(image,"tiff:subfiletype");
  if (value != (const char *) NULL)
    {
      if (LocaleCompare(value,"REDUCEDIMAGE") == 0)
        (void) TIFFSetField(tiff,TIFFTAG_SUBFILETYPE,FILETYPE_REDUCEDIMAGE);
      else
        if (LocaleCompare(value,"PAGE") == 0)
          (void) TIFFSetField(tiff,TIFFTAG_SUBFILETYPE,FILETYPE_PAGE);
        else
          if (LocaleCompare(value,"MASK") == 0)
            (void) TIFFSetField(tiff,TIFFTAG_SUBFILETYPE,FILETYPE_MASK);
    }
  else
    {
      uint16
        page,
        pages;

      page=(uint16) image->scene;
      pages=(uint16) GetImageListLength(image);
      if ((adjoin != MagickFalse) && (pages > 1))
        (void) TIFFSetField(tiff,TIFFTAG_SUBFILETYPE,FILETYPE_PAGE);
      (void) TIFFSetField(tiff,TIFFTAG_PAGENUMBER,page,pages);
    }
}


static tmsize_t TIFFWritePixels(TIFF *tiff,TIFFInfo *tiff_info,ssize_t row,
  tsample_t sample,Image *image)
{
  ssize_t
    i;

  tmsize_t
    status;

  size_t
    number_tiles,
    tile_width;

  ssize_t
    bytes_per_pixel,
    j,
    k,
    l;

  unsigned char
    *p,
    *q;

  if (TIFFIsTiled(tiff) == 0)
    return(TIFFWriteScanline(tiff,tiff_info->scanline,(uint32) row,sample));
  /*
    Fill scanlines to tile height.
  */
  i=(ssize_t) (row % tiff_info->tile_geometry.height)*TIFFScanlineSize(tiff);
  (void) memcpy(tiff_info->scanlines+i,(char *) tiff_info->scanline,
    (size_t) TIFFScanlineSize(tiff));
  if (((size_t) (row % tiff_info->tile_geometry.height) !=
      (tiff_info->tile_geometry.height-1)) &&
      (row != (ssize_t) (image->rows-1)))
    return(0);
  /*
    Write tile to TIFF image.
  */
  status=0;
  bytes_per_pixel=TIFFTileSize(tiff)/(ssize_t) (
    tiff_info->tile_geometry.height*tiff_info->tile_geometry.width);
  number_tiles=(image->columns+tiff_info->tile_geometry.width)/
    tiff_info->tile_geometry.width;
  for (i=0; i < (ssize_t) number_tiles; i++)
  {
    tile_width=(i == (ssize_t) (number_tiles-1)) ? image->columns-(i*
      tiff_info->tile_geometry.width) : tiff_info->tile_geometry.width;
    for (j=0; j < (ssize_t) ((row % tiff_info->tile_geometry.height)+1); j++)
      for (k=0; k < (ssize_t) tile_width; k++)
      {
        if (bytes_per_pixel == 0)
          {
            p=tiff_info->scanlines+(j*TIFFScanlineSize(tiff)+(i*
              tiff_info->tile_geometry.width+k)/8);
            q=tiff_info->pixels+(j*TIFFTileRowSize(tiff)+k/8);
            *q++=(*p++);
            continue;
          }
        p=tiff_info->scanlines+(j*TIFFScanlineSize(tiff)+(i*
          tiff_info->tile_geometry.width+k)*bytes_per_pixel);
        q=tiff_info->pixels+(j*TIFFTileRowSize(tiff)+k*bytes_per_pixel);
        for (l=0; l < bytes_per_pixel; l++)
          *q++=(*p++);
      }
    if ((i*tiff_info->tile_geometry.width) != image->columns)
      status=TIFFWriteTile(tiff,tiff_info->pixels,(uint32) (i*
        tiff_info->tile_geometry.width),(uint32) ((row/
        tiff_info->tile_geometry.height)*tiff_info->tile_geometry.height),0,
        sample);
    if (status < 0)
      break;
  }
  return(status);
}


static MagickOffsetType TIFFSeekCustomStream(const MagickOffsetType offset,
  const int whence,void *user_data)
{
  PhotoshopProfile
    *profile;

  profile=(PhotoshopProfile *) user_data;
  switch (whence)
  {
    case SEEK_SET:
    default:
    {
      if (offset < 0)
        return(-1);
      profile->offset=offset;
      break;
    }
    case SEEK_CUR:
    {
      if (((offset > 0) && (profile->offset > (MAGICK_SSIZE_MAX-offset))) ||
          ((offset < 0) && (profile->offset < (MAGICK_SSIZE_MIN-offset))))
        {
          errno=EOVERFLOW;
          return(-1);
        }
      if ((profile->offset+offset) < 0)
        return(-1);
      profile->offset+=offset;
      break;
    }
    case SEEK_END:
    {
      if (((MagickOffsetType) profile->length+offset) < 0)
        return(-1);
      profile->offset=profile->length+offset;
      break;
    }
  }

  return(profile->offset);
}


static ssize_t TIFFReadCustomStream(unsigned char *data,const size_t count,
  void *user_data)
{
  PhotoshopProfile
    *profile;

  size_t
    total;

  MagickOffsetType
    remaining;

  if (count == 0)
    return(0);
  profile=(PhotoshopProfile *) user_data;
  remaining=(MagickOffsetType) profile->length-profile->offset;
  if (remaining <= 0)
    return(-1);
  total=MagickMin(count, (size_t) remaining);
  (void) memcpy(data,profile->data->datum+profile->offset,total);
  profile->offset+=total;
  return(total);
}


static MagickBooleanType DecodeLabImage(Image *image,ExceptionInfo *exception)
{
  CacheView
    *image_view;

  MagickBooleanType
    status;

  ssize_t
    y;

  status=MagickTrue;
  image_view=AcquireAuthenticCacheView(image,exception);
  for (y=0; y < (ssize_t) image->rows; y++)
  {
    Quantum
      *magick_restrict q;

    ssize_t
      x;

    q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,exception);
    if (q == (Quantum *) NULL)
      {
        status=MagickFalse;
        break;
      }
    for (x=0; x < (ssize_t) image->columns; x++)
    {
      double
        a,
        b;

      a=QuantumScale*GetPixela(image,q)+0.5;
      if (a > 1.0)
        a-=1.0;
      b=QuantumScale*GetPixelb(image,q)+0.5;
      if (b > 1.0)
        b-=1.0;
      SetPixela(image,QuantumRange*a,q);
      SetPixelb(image,QuantumRange*b,q);
      q+=GetPixelChannels(image);
    }
    if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
      {
        status=MagickFalse;
        break;
      }
  }
  image_view=DestroyCacheView(image_view);
  return(status);
}


static MagickBooleanType TIFFGetProfiles(TIFF *tiff,Image *image,
  ExceptionInfo *exception)
{
  MagickBooleanType
    status;

  uint32
    length = 0;

  unsigned char
    *profile = (unsigned char *) NULL;

  status=MagickTrue;
#if defined(TIFFTAG_ICCPROFILE)
  if ((TIFFGetField(tiff,TIFFTAG_ICCPROFILE,&length,&profile) == 1) &&
      (profile != (unsigned char *) NULL))
    status=ReadProfile(image,"icc",profile,(ssize_t) length,exception);
#endif
#if defined(TIFFTAG_PHOTOSHOP)
  if ((TIFFGetField(tiff,TIFFTAG_PHOTOSHOP,&length,&profile) == 1) &&
      (profile != (unsigned char *) NULL))
    status=ReadProfile(image,"8bim",profile,(ssize_t) length,exception);
#endif
#if defined(TIFFTAG_RICHTIFFIPTC) && (TIFFLIB_VERSION >= 20191103)
  if ((TIFFGetField(tiff,TIFFTAG_RICHTIFFIPTC,&length,&profile) == 1) &&
      (profile != (unsigned char *) NULL))
    {
      const TIFFField
        *field;

      field=TIFFFieldWithTag(tiff,TIFFTAG_RICHTIFFIPTC);
      if (TIFFFieldDataType(field) == TIFF_LONG)
        {
          if (TIFFIsByteSwapped(tiff) != 0)
            TIFFSwabArrayOfLong((uint32 *) profile,(size_t) length);
          status=ReadProfile(image,"iptc",profile,4L*length,exception);
        }
      else
        status=ReadProfile(image,"iptc",profile,length,exception);
    }
#endif
#if defined(TIFFTAG_XMLPACKET)
  if ((TIFFGetField(tiff,TIFFTAG_XMLPACKET,&length,&profile) == 1) &&
      (profile != (unsigned char *) NULL))
    {
      StringInfo
        *dng;

      status=ReadProfile(image,"xmp",profile,(ssize_t) length,exception);
      dng=BlobToStringInfo(profile,length);
      if (dng != (StringInfo *) NULL)
        {
          const char
            *target = "dc:format=\"image/dng\"";

          if (strstr((char *) GetStringInfoDatum(dng),target) != (char *) NULL)
            (void) CopyMagickString(image->magick,"DNG",MagickPathExtent);
          dng=DestroyStringInfo(dng);
        }
    }
#endif
  if ((TIFFGetField(tiff,34118,&length,&profile) == 1) &&
      (profile != (unsigned char *) NULL))
    status=ReadProfile(image,"tiff:34118",profile,(ssize_t) length,
      exception);
  if ((TIFFGetField(tiff,37724,&length,&profile) == 1) &&
      (profile != (unsigned char *) NULL))
    status=ReadProfile(image,"tiff:37724",profile,(ssize_t) length,exception);
  return(status);
}


static Image *ReadGROUP4Image(const ImageInfo *image_info,
  ExceptionInfo *exception)
{
  char
    filename[MagickPathExtent];

  FILE
    *file;

  Image
    *image;

  ImageInfo
    *read_info;

  int
    c,
    unique_file;

  MagickBooleanType
    status;

  size_t
    length;

  ssize_t
    offset,
    strip_offset;

  /*
    Open image file.
  */
  assert(image_info != (const ImageInfo *) NULL);
  assert(image_info->signature == MagickCoreSignature);
  if (image_info->debug != MagickFalse)
    (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
      image_info->filename);
  assert(exception != (ExceptionInfo *) NULL);
  assert(exception->signature == MagickCoreSignature);
  image=AcquireImage(image_info,exception);
  status=OpenBlob(image_info,image,ReadBinaryBlobMode,exception);
  if (status == MagickFalse)
    {
      image=DestroyImageList(image);
      return((Image *) NULL);
    }
  /*
    Write raw CCITT Group 4 wrapped as a TIFF image file.
  */
  file=(FILE *) NULL;
  unique_file=AcquireUniqueFileResource(filename);
  if (unique_file != -1)
    file=fdopen(unique_file,"wb");
  if ((unique_file == -1) || (file == (FILE *) NULL))
    ThrowImageException(FileOpenError,"UnableToCreateTemporaryFile");
  length=fwrite("\111\111\052\000\010\000\000\000\016\000",1,10,file);
  if (length != 10)
    ThrowReaderException(CorruptImageError,"UnexpectedEndOfFile");
  length=fwrite("\376\000\003\000\001\000\000\000\000\000\000\000",1,12,file);
  length=fwrite("\000\001\004\000\001\000\000\000",1,8,file);
  length=WriteLSBLong(file,(unsigned int) image->columns);
  length=fwrite("\001\001\004\000\001\000\000\000",1,8,file);
  length=WriteLSBLong(file,(unsigned int) image->rows);
  length=fwrite("\002\001\003\000\001\000\000\000\001\000\000\000",1,12,file);
  length=fwrite("\003\001\003\000\001\000\000\000\004\000\000\000",1,12,file);
  length=fwrite("\006\001\003\000\001\000\000\000\000\000\000\000",1,12,file);
  length=fwrite("\021\001\003\000\001\000\000\000",1,8,file);
  strip_offset=10+(12*14)+4+8;
  length=WriteLSBLong(file,(unsigned int) strip_offset);
  length=fwrite("\022\001\003\000\001\000\000\000",1,8,file);
  length=WriteLSBLong(file,(unsigned int) image_info->orientation);
  length=fwrite("\025\001\003\000\001\000\000\000\001\000\000\000",1,12,file);
  length=fwrite("\026\001\004\000\001\000\000\000",1,8,file);
  length=WriteLSBLong(file,(unsigned int) image->rows);
  length=fwrite("\027\001\004\000\001\000\000\000\000\000\000\000",1,12,file);
  offset=(ssize_t) ftell(file)-4;
  length=fwrite("\032\001\005\000\001\000\000\000",1,8,file);
  length=WriteLSBLong(file,(unsigned int) (strip_offset-8));
  length=fwrite("\033\001\005\000\001\000\000\000",1,8,file);
  length=WriteLSBLong(file,(unsigned int) (strip_offset-8));
  length=fwrite("\050\001\003\000\001\000\000\000\002\000\000\000",1,12,file);
  length=fwrite("\000\000\000\000",1,4,file);
  length=WriteLSBLong(file,(unsigned int) image->resolution.x);
  length=WriteLSBLong(file,1);
  status=MagickTrue;
  for (length=0; (c=ReadBlobByte(image)) != EOF; length++)
    if (fputc(c,file) != c)
      status=MagickFalse;
  offset=(ssize_t) fseek(file,(ssize_t) offset,SEEK_SET);
  length=WriteLSBLong(file,(unsigned int) length);
  if (ferror(file) != 0)
    {
      (void) fclose(file);
      ThrowImageException(FileOpenError,"UnableToCreateTemporaryFile");
    }
  (void) fclose(file);
  (void) CloseBlob(image);
  image=DestroyImage(image);
  /*
    Read TIFF image.
  */
  read_info=CloneImageInfo((ImageInfo *) NULL);
  (void) FormatLocaleString(read_info->filename,MagickPathExtent,"%s",filename);
  image=ReadTIFFImage(read_info,exception);
  read_info=DestroyImageInfo(read_info);
  if (image != (Image *) NULL)
    {
      (void) CopyMagickString(image->filename,image_info->filename,
        MagickPathExtent);
      (void) CopyMagickString(image->magick_filename,image_info->filename,
        MagickPathExtent);
      (void) CopyMagickString(image->magick,"GROUP4",MagickPathExtent);
    }
  (void) RelinquishUniqueFileResource(filename);
  if (status == MagickFalse)
    image=DestroyImage(image);
  return(image);
}


static MagickBooleanType TIFFWritePhotoshopLayers(Image* image,
  const ImageInfo *image_info,EndianType endian,ExceptionInfo *exception)
{
  BlobInfo
    *blob;

  CustomStreamInfo
    *custom_stream;

  Image
    *base_image,
    *next;

  ImageInfo
    *clone_info;

  MagickBooleanType
    status;

  PhotoshopProfile
    profile;

  PSDInfo
    info;

  StringInfo
    *layers;

  base_image=CloneImage(image,0,0,MagickFalse,exception);
  if (base_image == (Image *) NULL)
    return(MagickTrue);
  clone_info=CloneImageInfo(image_info);
  if (clone_info == (ImageInfo *) NULL)
    ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
      image->filename);
  profile.offset=0;
  profile.quantum=MagickMinBlobExtent;
  layers=AcquireStringInfo(profile.quantum);
  if (layers == (StringInfo *) NULL)
    {
      base_image=DestroyImage(base_image);
      clone_info=DestroyImageInfo(clone_info);
      ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
        image->filename);
    }
  profile.data=layers;
  profile.extent=layers->length;
  custom_stream=TIFFAcquireCustomStreamForWriting(&profile,exception);
  if (custom_stream == (CustomStreamInfo *) NULL)
    {
      base_image=DestroyImage(base_image);
      clone_info=DestroyImageInfo(clone_info);
      layers=DestroyStringInfo(layers);
      ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
        image->filename);
    }
  blob=CloneBlobInfo((BlobInfo *) NULL);
  if (blob == (BlobInfo *) NULL)
    {
      base_image=DestroyImage(base_image);
      clone_info=DestroyImageInfo(clone_info);
      layers=DestroyStringInfo(layers);
      custom_stream=DestroyCustomStreamInfo(custom_stream);
      ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
        image->filename);
    }
  DestroyBlob(base_image);
  base_image->blob=blob;
  next=base_image;
  while (next != (Image *) NULL)
    next=SyncNextImageInList(next);
  AttachCustomStream(base_image->blob,custom_stream);
  InitPSDInfo(image,&info);
  base_image->endian=endian;
  WriteBlobString(base_image,"Adobe Photoshop Document Data Block");
  WriteBlobByte(base_image,0);
  WriteBlobString(base_image,base_image->endian == LSBEndian ? "MIB8ryaL" :
    "8BIMLayr");
  status=WritePSDLayers(base_image,clone_info,&info,exception);
  if (status != MagickFalse)
    {
      SetStringInfoLength(layers,(size_t) profile.offset);
      status=SetImageProfile(image,"tiff:37724",layers,exception);
    }
  next=base_image;
  while (next != (Image *) NULL)
  {
    CloseBlob(next);
    next=next->next;
  }
  layers=DestroyStringInfo(layers);
  clone_info=DestroyImageInfo(clone_info);
  custom_stream=DestroyCustomStreamInfo(custom_stream);
  return(status);
}