minor editorconfig-check fixes
This commit is contained in:
Saba Fallah
parent
1c88647ec6
commit
d981f19e9d
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@ -457,7 +457,7 @@ static std::string to_ne_string(const ggml_tensor * t) {
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static void print_tensor_info(ggml_tensor * t) {
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const struct ggml_tensor * src0 = t->src[0];
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const struct ggml_tensor * src1 = t->src[1];
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char src1_str[128] = {0};
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if (src1) {
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snprintf(src1_str, sizeof(src1_str), "%s{%s}", src1->name, to_ne_string(src1).c_str());
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@ -643,7 +643,7 @@ static void save_tensor_to_file(const struct ggml_tensor * tensor, const uint8_t
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append_str(" [");
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for (int64_t i0 = 0; i0 < ne[0]; i0++) {
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size_t i = i3 * nb[3] + i2 * nb[2] + i1 * nb[1] + i0 * nb[0];
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float v;
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float v;
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if (type == GGML_TYPE_F16) {
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v = ggml_fp16_to_fp32(*(ggml_fp16_t *) &data[i]);
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} else if (type == GGML_TYPE_F32) {
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@ -659,13 +659,15 @@ static void save_tensor_to_file(const struct ggml_tensor * tensor, const uint8_t
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}
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int len = snprintf(num_buf, sizeof(num_buf), "%8.4f", v);
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append(num_buf, len);
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if (i0 < ne[0] - 1) append_str(", ");
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if (i0 < ne[0] - 1) {
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append_str(", ");
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}
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}
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append_str("],\n");
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}
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append_str(" ],\n");
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}
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append_str(" ]"); // End of batch
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append_str(" ]"); // End of batch
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if (i3 < ne[3] - 1) {
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append_str(",\n"); // Comma between batches
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} else {
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@ -662,19 +662,19 @@ struct clip_graph {
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ggml_cgraph * build_deepseek_ocr() {
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//patch embedding
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ggml_tensor * inp_raw = build_inp_raw();
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ggml_tensor * sam_out = build_sam(inp_raw);
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ggml_tensor * inp_raw = build_inp_raw();
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ggml_tensor * sam_out = build_sam(inp_raw);
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ggml_tensor * clip_out = build_dsocr_clip(sam_out);
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int clip_n_patches = sam_out->ne[0] * sam_out->ne[1];
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sam_out = ggml_cont(ctx0, ggml_permute(ctx0, sam_out, 1, 2, 0, 3));
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sam_out = ggml_reshape_2d(ctx0, sam_out, sam_out->ne[0], clip_n_patches);
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sam_out = ggml_cont(ctx0, ggml_permute(ctx0, sam_out, 1, 2, 0, 3));
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sam_out = ggml_reshape_2d(ctx0, sam_out, sam_out->ne[0], clip_n_patches);
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clip_out = ggml_view_2d(ctx0, clip_out, n_embd, clip_n_patches, clip_out->nb[1], clip_out->nb[1]);
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ggml_tensor * cur;
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cur = ggml_concat(ctx0, clip_out, sam_out, 0);
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cur = ggml_reshape_2d(ctx0, cur, 2*n_embd,clip_n_patches);
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cur = ggml_reshape_2d(ctx0, cur, 2 * n_embd, clip_n_patches);
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cur = ggml_cont(ctx0, cur);
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cur = ggml_mul_mat(ctx0, model.fc_w, cur);
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cur = ggml_add(ctx0, cur, model.fc_b);
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@ -687,10 +687,10 @@ struct clip_graph {
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ggml_tensor * vs;
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imgnl = ggml_repeat_4d(ctx0, model.image_newline, n_dim, 1, h, 1);
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vs = ggml_reshape_2d(ctx0, model.view_seperator, n_dim, 1); // (n_dim, 1)
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cur = ggml_reshape_3d(ctx0, cur, n_dim, w, h);
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cur = ggml_reshape_2d(ctx0, ggml_concat(ctx0, cur, imgnl, 1), n_dim, (w+1)*h);
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cur = ggml_concat(ctx0, cur, vs, 1); // (n_dim, h*(w+1) + 1)
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vs = ggml_reshape_2d(ctx0, model.view_seperator, n_dim, 1); // (n_dim, 1)
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cur = ggml_reshape_3d(ctx0, cur, n_dim, w, h);
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cur = ggml_reshape_2d(ctx0, ggml_concat(ctx0, cur, imgnl, 1), n_dim, (w + 1) * h);
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cur = ggml_concat(ctx0, cur, vs, 1); // (n_dim, h*(w+1) + 1)
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cb(cur, "dsocr_output", -1);
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@ -2156,7 +2156,7 @@ private:
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ggml_tensor * Qcur;
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ggml_tensor * Kcur;
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ggml_tensor * Vcur;
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if (layer.qkv_w) {
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ggml_tensor * QKV;
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@ -2181,12 +2181,12 @@ private:
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if (layer.q_b) {
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Qcur = ggml_add(ctx0, Qcur, layer.q_b);
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}
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Kcur = ggml_mul_mat(ctx0, layer.k_w, cur);
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if (layer.k_b) {
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Kcur = ggml_add(ctx0, Kcur, layer.k_b);
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}
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Vcur = ggml_mul_mat(ctx0, layer.v_w, cur);
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if (layer.v_b) {
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Vcur = ggml_add(ctx0, Vcur, layer.v_b);
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@ -2591,7 +2591,7 @@ private:
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} else {
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ggml_tensor * v = ggml_permute(ctx0, v_cur, 1, 2, 0, 3);
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v = ggml_cont(ctx0, v);
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ggml_tensor * kq = ggml_mul_mat(ctx0, k, q);
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// F32 may not needed for vision encoders?
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// ggml_mul_mat_set_prec(kq, GGML_PREC_F32);
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@ -2727,11 +2727,11 @@ private:
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const int d_heads = n_embd / n_heads;
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ggml_tensor * inpL;
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inpL = ggml_conv_2d_sk_p0(ctx0, model.patch_embed_proj_w, inp_raw);
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inpL = ggml_add(ctx0, inpL, ggml_reshape_3d(ctx0, model.patch_embed_proj_b, 1, 1, n_embd));
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inpL = ggml_cont(ctx0, ggml_permute(ctx0, inpL, 1, 2, 0, 3));
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ggml_tensor * cur;
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const auto tgt_size = inpL->ne[1];
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const auto str_size = model.pos_embed->ne[1];
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@ -2776,7 +2776,7 @@ private:
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// self-attention
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{
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const int B = cur->ne[3];
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cur = ggml_mul_mat(ctx0, layer.qkv_w, cur);
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cur = ggml_add(ctx0, cur, layer.qkv_b);
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cur = ggml_cont(ctx0, cur); // Ensure tensor is contiguous before reshape
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@ -2853,7 +2853,7 @@ private:
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cur = ggml_cont(ctx0, ggml_permute(ctx0, cur, 1, 2, 0, 3));
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cur = build_norm(cur, model.neck_1_w, model.neck_1_b, NORM_TYPE_NORMAL, hparams.eps, -1);
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cur = ggml_cont(ctx0, ggml_permute(ctx0, cur, 2, 0, 1, 3));
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cur = ggml_conv_2d(ctx0, model.neck_2_w, cur, 1, 1, 1, 1, 1, 1);
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cur = ggml_cont(ctx0, ggml_permute(ctx0, cur, 1, 2, 0, 3));
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cur = build_norm(cur, model.neck_3_w, model.neck_3_b, NORM_TYPE_NORMAL, hparams.eps, -1);
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@ -2883,7 +2883,7 @@ private:
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if (tgt_size != src_size) {
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ggml_tensor * old_pos_embd;
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ggml_tensor * cls_tok;
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old_pos_embd = ggml_view_2d(
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ctx0, new_pos_embd,
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new_pos_embd->ne[0], src_size * src_size,
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@ -2912,7 +2912,7 @@ private:
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ggml_tensor * positions = ggml_cast(ctx0, ggml_arange(ctx0, 0, n_pos, 1), GGML_TYPE_I32);
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ggml_tensor * learned_pos_embd = ggml_get_rows(ctx0, new_pos_embd, positions);
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ggml_tensor * cur = build_vit(inp, n_pos, NORM_TYPE_NORMAL, ffn_op_type::FFN_GELU_QUICK,
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ggml_tensor * cur = build_vit(inp, n_pos, NORM_TYPE_NORMAL, ffn_op_type::FFN_GELU_QUICK,
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learned_pos_embd, nullptr); // shape [1024, 16, 16]
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ggml_build_forward_expand(gf, cur);
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@ -5193,11 +5193,11 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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const int orig_h = original_size.height;
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const int orig_area = orig_h * orig_w;
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std::array<uint8_t, 3u> color;
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for (int i = 0; i < 3; i++) {
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color[i] = (int)(255 * params.image_mean[i]);
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}
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int mode_i = 0;
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int min_diff = orig_area;
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@ -5212,7 +5212,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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if (mode_i < 2) {
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/* Native Resolution (Tiny/Small) */
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const int image_size = native_resolutions[mode_i];
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// Just resize the image to image_size × image_size
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clip_image_u8_ptr resized_img(clip_image_u8_init());
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img_tool::resize(*img, *resized_img,
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@ -5229,7 +5229,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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else if (mode_i < 4) {
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/* Native Resolution (Base/Large) */
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const int image_size = native_resolutions[mode_i];
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// Resize maintaining aspect ratio, then pad to square
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float scale = std::min(
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static_cast<float>(image_size) / orig_w,
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@ -5286,7 +5286,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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else {
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GGML_ABORT("DeepSeek-OCR hasn't supported Gundam/Gundam-Master yet");
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/* Dynamic Resolution (Gundam/Gundam-Master) */
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// configurable, or read from params
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const int min_num = 2;
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const int max_num = 9;
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@ -5295,10 +5295,10 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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// original image size
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const int orig_w = original_size.width;
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const int orig_h = original_size.height;
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// create overview image (thumbnail)
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clip_image_u8_ptr overview_img(clip_image_u8_init());
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img_tool::resize(*img, *overview_img, { image_size, image_size },
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img_tool::resize(*img, *overview_img, { image_size, image_size },
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img_tool::RESIZE_ALGO_BICUBIC_PILLOW, true, color);
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clip_image_f32_ptr overview_f32(clip_image_f32_init());
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normalize_image_u8_to_f32(*overview_img, *overview_f32, params.image_mean, params.image_std);
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@ -5306,7 +5306,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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// build candidate grids (cols, rows)
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auto target_ratios = ds_build_target_ratios(min_num, max_num);
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// pick the grid that best matches the original aspect ratio
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const float aspect_ratio = static_cast<float>(orig_w) / static_cast<float>(orig_h);
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auto best = ds_find_closest_ratio(aspect_ratio, target_ratios, orig_w, orig_h, image_size);
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@ -5315,7 +5315,7 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, str
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// resize to refined size (no padding, direct resize)
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clip_image_u8_ptr refined_img(clip_image_u8_init());
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img_tool::resize(*img, *refined_img, { image_size * grid_cols, image_size * grid_rows },
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img_tool::resize(*img, *refined_img, { image_size * grid_cols, image_size * grid_rows },
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img_tool::RESIZE_ALGO_BICUBIC_PILLOW, false);
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// crop slices from the refined image
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