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clip : suppress unused variable warnings (#8105)

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* clip : suppress unused variable warnings

This commit suppresses unused variable warnings for the variables e in
the catch blocks.

The motivation for this change is to suppress the warnings that are
generated on Windows when using the MSVC compiler. The warnings are
not displayed when using GCC because GCC will mark all catch parameters
as used.

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>

* squash! clip : suppress unused variable warnings

Remove e (/*e*/) instead instead of using GGML_UNUSED.

---------

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
This commit is contained in:
Daniel Bevenius 2024-06-27 01:50:09 +02:00 committed by GitHub
parent c70d117c37
commit 9b31a40c6d
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1 changed files with 13 additions and 13 deletions
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26
examples/llava/clip.cpp
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@ -1121,20 +1121,20 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
} }
if (n < 32) if (n < 32)
hparams.image_grid_pinpoints[n] = 0; hparams.image_grid_pinpoints[n] = 0;
} catch (std::runtime_error & e) { } catch (std::runtime_error & /*e*/) {
hparams.image_grid_pinpoints[0]=0; hparams.image_grid_pinpoints[0]=0;
} }
try { try {
int idx = get_key_idx(ctx, KEY_MM_PATCH_MERGE_TYPE); int idx = get_key_idx(ctx, KEY_MM_PATCH_MERGE_TYPE);
strcpy(hparams.mm_patch_merge_type, gguf_get_val_str(ctx, idx)); strcpy(hparams.mm_patch_merge_type, gguf_get_val_str(ctx, idx));
} catch (std::runtime_error & e) { } catch (std::runtime_error & /*e*/) {
strcpy(hparams.mm_patch_merge_type, "flat"); strcpy(hparams.mm_patch_merge_type, "flat");
} }
try { try {
hparams.image_crop_resolution = get_u32(ctx, KEY_IMAGE_CROP_RESOLUTION); // llava-1.6 hparams.image_crop_resolution = get_u32(ctx, KEY_IMAGE_CROP_RESOLUTION); // llava-1.6
} catch(const std::exception& e) { } catch(const std::exception& /*e*/) {
hparams.image_crop_resolution = hparams.image_size; hparams.image_crop_resolution = hparams.image_size;
} }
@ -1173,7 +1173,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
try { try {
vision_model.class_embedding = get_tensor(new_clip->ctx_data, TN_CLASS_EMBD); vision_model.class_embedding = get_tensor(new_clip->ctx_data, TN_CLASS_EMBD);
new_clip->has_class_embedding = true; new_clip->has_class_embedding = true;
} catch (const std::exception& e) { } catch (const std::exception& /*e*/) {
new_clip->has_class_embedding = false; new_clip->has_class_embedding = false;
} }
@ -1181,7 +1181,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
vision_model.pre_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "weight")); vision_model.pre_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "weight"));
vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias")); vision_model.pre_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_PRE, "v", "bias"));
new_clip->has_pre_norm = true; new_clip->has_pre_norm = true;
} catch (std::exception & e) { } catch (std::exception & /*e*/) {
new_clip->has_pre_norm = false; new_clip->has_pre_norm = false;
} }
@ -1189,21 +1189,21 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
vision_model.post_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "weight")); vision_model.post_ln_w = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "weight"));
vision_model.post_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "bias")); vision_model.post_ln_b = get_tensor(new_clip->ctx_data, format(TN_LN_POST, "v", "bias"));
new_clip->has_post_norm = true; new_clip->has_post_norm = true;
} catch (std::exception & e) { } catch (std::exception & /*e*/) {
new_clip->has_post_norm = false; new_clip->has_post_norm = false;
} }
try { try {
vision_model.patch_bias = get_tensor(new_clip->ctx_data, TN_PATCH_BIAS); vision_model.patch_bias = get_tensor(new_clip->ctx_data, TN_PATCH_BIAS);
new_clip->has_patch_bias = true; new_clip->has_patch_bias = true;
} catch (std::exception & e) { } catch (std::exception & /*e*/) {
new_clip->has_patch_bias = false; new_clip->has_patch_bias = false;
} }
try { try {
vision_model.patch_embeddings = get_tensor(new_clip->ctx_data, TN_PATCH_EMBD); vision_model.patch_embeddings = get_tensor(new_clip->ctx_data, TN_PATCH_EMBD);
vision_model.position_embeddings = get_tensor(new_clip->ctx_data, format(TN_POS_EMBD, "v")); vision_model.position_embeddings = get_tensor(new_clip->ctx_data, format(TN_POS_EMBD, "v"));
} catch(const std::exception& e) { } catch(const std::exception& /*e*/) {
LOG_TEE("%s: failed to load vision model tensors\n", __func__); LOG_TEE("%s: failed to load vision model tensors\n", __func__);
} }
@ -1215,26 +1215,26 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
// Yi-type llava // Yi-type llava
vision_model.mm_1_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "weight")); vision_model.mm_1_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "weight"));
vision_model.mm_1_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "bias")); vision_model.mm_1_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 1, "bias"));
} catch (std::runtime_error & e) { } } catch (std::runtime_error & /*e*/) { }
try { try {
// missing in Yi-type llava // missing in Yi-type llava
vision_model.mm_2_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "weight")); vision_model.mm_2_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "weight"));
vision_model.mm_2_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "bias")); vision_model.mm_2_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 2, "bias"));
} catch (std::runtime_error & e) { } } catch (std::runtime_error & /*e*/) { }
try { try {
// Yi-type llava // Yi-type llava
vision_model.mm_3_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "weight")); vision_model.mm_3_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "weight"));
vision_model.mm_3_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "bias")); vision_model.mm_3_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 3, "bias"));
} catch (std::runtime_error & e) { } } catch (std::runtime_error & /*e*/) { }
try { try {
// Yi-type llava // Yi-type llava
vision_model.mm_4_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "weight")); vision_model.mm_4_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "weight"));
vision_model.mm_4_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "bias")); vision_model.mm_4_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 4, "bias"));
} catch (std::runtime_error & e) { } } catch (std::runtime_error & /*e*/) { }
try { try {
vision_model.image_newline = get_tensor(new_clip->ctx_data, TN_IMAGE_NEWLINE); vision_model.image_newline = get_tensor(new_clip->ctx_data, TN_IMAGE_NEWLINE);
// LOG_TEE("%s: image_newline tensor (llava-1.6) found\n", __func__); // LOG_TEE("%s: image_newline tensor (llava-1.6) found\n", __func__);
} catch (std::runtime_error & e) { } } catch (std::runtime_error & /*e*/) { }
} else if (new_clip->proj_type == PROJECTOR_TYPE_LDP) { } else if (new_clip->proj_type == PROJECTOR_TYPE_LDP) {
// MobileVLM projection // MobileVLM projection
vision_model.mm_model_mlp_1_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_MLP, 1, "weight")); vision_model.mm_model_mlp_1_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_MLP, 1, "weight"));