Add .clang-format

.clang-format

@@ -0,0 +1,92 @@
+# Options are listed here:
+# https://clang.llvm.org/docs/ClangFormatStyleOptions.html
+---
+AccessModifierOffset: -3
+AlignAfterOpenBracket: BlockIndent
+AlignArrayOfStructures: Left
+AlwaysBreakTemplateDeclarations: Yes
+AlignConsecutiveAssignments: true
+AlignConsecutiveDeclarations: false
+AlignConsecutiveMacros: true
+AlignEscapedNewlines: Right
+AlignOperands: true
+AlignTrailingComments: true
+AllowAllArgumentsOnNextLine: false
+AllowAllConstructorInitializersOnNextLine: false
+AllowAllParametersOfDeclarationOnNextLine: false
+AllowShortBlocksOnASingleLine: false
+AllowShortCaseLabelsOnASingleLine: false
+AllowShortFunctionsOnASingleLine: None
+AllowShortLambdasOnASingleLine: All
+AllowShortIfStatementsOnASingleLine: Never
+AllowShortLoopsOnASingleLine: false
+AlwaysBreakAfterDefinitionReturnType: None
+AlwaysBreakAfterReturnType: None
+AlwaysBreakBeforeMultilineStrings: false
+AlwaysBreakTemplateDeclarations: MultiLine
+BinPackArguments: false
+BinPackParameters: false
+BitFieldColonSpacing: Both
+BreakBeforeBinaryOperators: None
+BreakBeforeBraces: Attach
+BreakBeforeConceptDeclarations: Always
+BreakBeforeInheritanceComma: false
+BreakInheritanceList: BeforeColon
+BreakBeforeTernaryOperators: true
+BreakConstructorInitializersBeforeComma: true
+BreakConstructorInitializers: AfterColon
+BreakStringLiterals: true
+ColumnLimit: 120
+CompactNamespaces: false
+ConstructorInitializerIndentWidth: 4
+ContinuationIndentWidth: 4
+Cpp11BracedListStyle: false
+DeriveLineEnding: false
+DerivePointerAlignment: false
+EmptyLineBeforeAccessModifier: LogicalBlock
+EmptyLineAfterAccessModifier: Never
+FixNamespaceComments: false
+IncludeBlocks: Preserve
+IncludeIsMainRegex: '(Test)?$'
+IndentCaseLabels: true
+IndentPPDirectives: AfterHash
+IndentWidth: 4
+IndentWrappedFunctionNames: true
+InsertBraces: true
+KeepEmptyLinesAtTheStartOfBlocks: true
+Language: Cpp
+MaxEmptyLinesToKeep: 1
+NamespaceIndentation: All
+PackConstructorInitializers: Never
+PenaltyBreakAssignment: 2
+PenaltyBreakBeforeFirstCallParameter: 19
+PenaltyBreakComment: 300
+PenaltyBreakFirstLessLess: 120
+PenaltyBreakString: 1000
+PenaltyExcessCharacter: 1000000
+PenaltyReturnTypeOnItsOwnLine: 1000
+PointerAlignment: Middle
+ReflowComments: true
+SortIncludes: true
+SortUsingDeclarations: true
+SpaceAfterCStyleCast: true
+SpaceAfterLogicalNot: false
+SpaceAfterTemplateKeyword: true
+SpaceBeforeAssignmentOperators: true
+SpaceBeforeCaseColon: false
+SpaceBeforeCpp11BracedList: false
+SpaceBeforeCtorInitializerColon: true
+SpaceBeforeInheritanceColon: true
+SpaceBeforeParens: ControlStatements
+SpaceBeforeRangeBasedForLoopColon: true
+SpaceInEmptyParentheses: false
+SpacesBeforeTrailingComments: 1
+SpacesInAngles: false
+SpacesInContainerLiterals: true
+SpacesInCStyleCastParentheses: false
+SpacesInParentheses: false
+SpacesInSquareBrackets: false
+Standard: c++11
+TabWidth: 4
+UseCRLF: false
+UseTab: Never

ggml.c

@@ -173,12 +173,12 @@ static inline float fp32_from_bits(uint32_t w) {
 }
 
 static inline uint32_t fp32_to_bits(float f) {
-	union {
-		float as_value;
-		uint32_t as_bits;
-	} fp32;
-	fp32.as_value = f;
-	return fp32.as_bits;
+   union {
+      float as_value;
+      uint32_t as_bits;
+   } fp32;
+   fp32.as_value = f;
+   return fp32.as_bits;
 }
 
 float ggml_fp16_to_fp32(ggml_fp16_t h) {

ggml.h

@@ -169,13 +169,13 @@
 //
 //
 
-#ifdef  __cplusplus
+#ifdef __cplusplus
 extern "C" {
 #endif
 
-#include <stdint.h>
-#include <stddef.h>
 #include <stdbool.h>
+#include <stddef.h>
+#include <stdint.h>
 
 #define GGML_MAX_DIMS     4
 #define GGML_MAX_NODES    4096
@@ -191,7 +191,7 @@ typedef uint16_t ggml_fp16_t;
 #endif
 
 // convert FP16 <-> FP32
-float       ggml_fp16_to_fp32(ggml_fp16_t x);
+float ggml_fp16_to_fp32(ggml_fp16_t x);
 ggml_fp16_t ggml_fp32_to_fp16(float x);
 
 struct ggml_object;
@@ -253,8 +253,8 @@ enum ggml_op {
 struct ggml_tensor {
     enum ggml_type type;
 
-    int    n_dims;
-    int    ne[GGML_MAX_DIMS]; // number of elements
+    int n_dims;
+    int ne[GGML_MAX_DIMS];    // number of elements
     size_t nb[GGML_MAX_DIMS]; // stride in bytes:
                               // nb[0] = sizeof(type)
                               // nb[1] = nb[0]   * ne[0] + padding
@@ -274,7 +274,7 @@ struct ggml_tensor {
     int n_tasks;
 
     // performance
-    int     perf_runs;
+    int perf_runs;
     int64_t perf_cycles;
     int64_t perf_time_us;
 
@@ -296,7 +296,7 @@ struct ggml_cgraph {
     struct ggml_tensor * leafs[GGML_MAX_NODES];
 
     // performance
-    int     perf_runs;
+    int perf_runs;
     int64_t perf_cycles;
     int64_t perf_time_us;
 };
@@ -307,19 +307,19 @@ struct ggml_init_params {
     void * mem_buffer; // if NULL, memory will be allocated internally
 };
 
-void    ggml_time_init(void); // call this once at the beginning of the program
+void ggml_time_init(void); // call this once at the beginning of the program
 int64_t ggml_time_ms(void);
 int64_t ggml_time_us(void);
 int64_t ggml_cycles(void);
 int64_t ggml_cycles_per_ms(void);
 
-void ggml_print_object (const struct ggml_object * obj);
+void ggml_print_object(const struct ggml_object * obj);
 void ggml_print_objects(const struct ggml_context * ctx);
 
-int    ggml_nelements(const struct ggml_tensor * tensor);
-size_t ggml_nbytes   (const struct ggml_tensor * tensor);
+int ggml_nelements(const struct ggml_tensor * tensor);
+size_t ggml_nbytes(const struct ggml_tensor * tensor);
 
-size_t ggml_type_size   (enum ggml_type type);
+size_t ggml_type_size(enum ggml_type type);
 size_t ggml_element_size(const struct ggml_tensor * tensor);
 
 struct ggml_context * ggml_init(struct ggml_init_params params);
@@ -327,290 +327,192 @@ void ggml_free(struct ggml_context * ctx);
 
 size_t ggml_used_mem(const struct ggml_context * ctx);
 
-struct ggml_tensor * ggml_new_tensor(
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    n_dims,
-        const int *ne);
-
-struct ggml_tensor * ggml_new_tensor_1d(
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    ne0);
-
-struct ggml_tensor * ggml_new_tensor_2d(
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    ne0,
-        int    ne1);
-
-struct ggml_tensor * ggml_new_tensor_3d(
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    ne0,
-        int    ne1,
-        int    ne2);
+struct ggml_tensor * ggml_new_tensor(struct ggml_context * ctx, enum ggml_type type, int n_dims, const int * ne);
+
+struct ggml_tensor * ggml_new_tensor_1d(struct ggml_context * ctx, enum ggml_type type, int ne0);
+
+struct ggml_tensor * ggml_new_tensor_2d(struct ggml_context * ctx, enum ggml_type type, int ne0, int ne1);
+
+struct ggml_tensor * ggml_new_tensor_3d(struct ggml_context * ctx, enum ggml_type type, int ne0, int ne1, int ne2);
 
 struct ggml_tensor * ggml_new_tensor_4d(
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    ne0,
-        int    ne1,
-        int    ne2,
-        int    ne3);
+    struct ggml_context * ctx,
+    enum ggml_type type,
+    int ne0,
+    int ne1,
+    int ne2,
+    int ne3
+);
 
 struct ggml_tensor * ggml_new_i32(struct ggml_context * ctx, int32_t value);
 struct ggml_tensor * ggml_new_f32(struct ggml_context * ctx, float value);
 
-struct ggml_tensor * ggml_dup_tensor (struct ggml_context * ctx, const struct ggml_tensor * src);
+struct ggml_tensor * ggml_dup_tensor(struct ggml_context * ctx, const struct ggml_tensor * src);
 struct ggml_tensor * ggml_view_tensor(struct ggml_context * ctx, const struct ggml_tensor * src);
 
 struct ggml_tensor * ggml_set_zero(struct ggml_tensor * tensor);
-struct ggml_tensor * ggml_set_i32 (struct ggml_tensor * tensor, int32_t value);
-struct ggml_tensor * ggml_set_f32 (struct ggml_tensor * tensor, float value);
+struct ggml_tensor * ggml_set_i32(struct ggml_tensor * tensor, int32_t value);
+struct ggml_tensor * ggml_set_f32(struct ggml_tensor * tensor, float value);
 
 int32_t ggml_get_i32_1d(const struct ggml_tensor * tensor, int i);
-void    ggml_set_i32_1d(const struct ggml_tensor * tensor, int i, int32_t value);
+void ggml_set_i32_1d(const struct ggml_tensor * tensor, int i, int32_t value);
 
 float ggml_get_f32_1d(const struct ggml_tensor * tensor, int i);
-void  ggml_set_f32_1d(const struct ggml_tensor * tensor, int i, float value);
+void ggml_set_f32_1d(const struct ggml_tensor * tensor, int i, float value);
 
- void * ggml_get_data    (const struct ggml_tensor * tensor);
+void * ggml_get_data(const struct ggml_tensor * tensor);
 float * ggml_get_data_f32(const struct ggml_tensor * tensor);
 
 //
 // operations on tensors with backpropagation
 //
 
-struct ggml_tensor * ggml_dup(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_dup(struct ggml_context * ctx, struct ggml_tensor * a);
 
-struct ggml_tensor * ggml_add(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_add(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
-struct ggml_tensor * ggml_sub(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_sub(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
-struct ggml_tensor * ggml_mul(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_mul(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
-struct ggml_tensor * ggml_div(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_div(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
-struct ggml_tensor * ggml_sqr(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_sqr(struct ggml_context * ctx, struct ggml_tensor * a);
 
-struct ggml_tensor * ggml_sqrt(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_sqrt(struct ggml_context * ctx, struct ggml_tensor * a);
 
 // return scalar
 // TODO: compute sum along rows
-struct ggml_tensor * ggml_sum(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_sum(struct ggml_context * ctx, struct ggml_tensor * a);
 
 // mean along rows
-struct ggml_tensor * ggml_mean(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_mean(struct ggml_context * ctx, struct ggml_tensor * a);
 
 // if a is the same shape as b, and a is not parameter, return a
 // otherwise, return a new tensor: repeat(a) to fit in b
-struct ggml_tensor * ggml_repeat(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_repeat(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
-struct ggml_tensor * ggml_abs(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_abs(struct ggml_context * ctx, struct ggml_tensor * a);
 
-struct ggml_tensor * ggml_sgn(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_sgn(struct ggml_context * ctx, struct ggml_tensor * a);
 
-struct ggml_tensor * ggml_neg(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_neg(struct ggml_context * ctx, struct ggml_tensor * a);
 
-struct ggml_tensor * ggml_step(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_step(struct ggml_context * ctx, struct ggml_tensor * a);
 
-struct ggml_tensor * ggml_relu(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_relu(struct ggml_context * ctx, struct ggml_tensor * a);
 
 // TODO: double-check this computation is correct
-struct ggml_tensor * ggml_gelu(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_gelu(struct ggml_context * ctx, struct ggml_tensor * a);
 
 // normalize along rows
 // TODO: eps is hardcoded to 1e-5 for now
-struct ggml_tensor * ggml_norm(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_norm(struct ggml_context * ctx, struct ggml_tensor * a);
 
 // A: m rows, n columns
 // B: p rows, n columns (i.e. we transpose it internally)
 // result is m columns, p rows
-struct ggml_tensor * ggml_mul_mat(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_mul_mat(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
 //
 // operations on tensors without backpropagation
 //
 
 // in-place, returns view(a)
-struct ggml_tensor * ggml_scale(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_scale(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
 // a -> b, return view(b)
-struct ggml_tensor * ggml_cpy(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_cpy(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
 // return view(a), b specifies the new shape
 // TODO: when we start computing gradient, make a copy instead of view
-struct ggml_tensor * ggml_reshape(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_reshape(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
 // return view(a)
 // TODO: when we start computing gradient, make a copy instead of view
-struct ggml_tensor * ggml_reshape_2d(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   ne0,
-        int                   ne1);
+struct ggml_tensor * ggml_reshape_2d(struct ggml_context * ctx, struct ggml_tensor * a, int ne0, int ne1);
 
 // return view(a)
 // TODO: when we start computing gradient, make a copy instead of view
-struct ggml_tensor * ggml_reshape_3d(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   ne0,
-        int                   ne1,
-        int                   ne2);
+struct ggml_tensor * ggml_reshape_3d(struct ggml_context * ctx, struct ggml_tensor * a, int ne0, int ne1, int ne2);
 
 // offset in bytes
-struct ggml_tensor * ggml_view_1d(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   ne0,
-        size_t                offset);
+struct ggml_tensor * ggml_view_1d(struct ggml_context * ctx, struct ggml_tensor * a, int ne0, size_t offset);
 
 struct ggml_tensor * ggml_view_2d(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   ne0,
-        int                   ne1,
-        size_t                nb1, // row stride in bytes
-        size_t                offset);
+    struct ggml_context * ctx,
+    struct ggml_tensor * a,
+    int ne0,
+    int ne1,
+    size_t nb1, // row stride in bytes
+    size_t offset
+);
 
 struct ggml_tensor * ggml_permute(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   axis0,
-        int                   axis1,
-        int                   axis2,
-        int                   axis3);
+    struct ggml_context * ctx,
+    struct ggml_tensor * a,
+    int axis0,
+    int axis1,
+    int axis2,
+    int axis3
+);
 
 // alias for ggml_permute(ctx, a, 1, 0, 2, 3)
-struct ggml_tensor * ggml_transpose(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_transpose(struct ggml_context * ctx, struct ggml_tensor * a);
 
-struct ggml_tensor * ggml_get_rows(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_get_rows(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
 // set elements above the diagonal to -INF
 // in-place, returns view(a)
-struct ggml_tensor * ggml_diag_mask_inf(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   n_past);
+struct ggml_tensor * ggml_diag_mask_inf(struct ggml_context * ctx, struct ggml_tensor * a, int n_past);
 
 // in-place, returns view(a)
-struct ggml_tensor * ggml_soft_max(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
+struct ggml_tensor * ggml_soft_max(struct ggml_context * ctx, struct ggml_tensor * a);
 
 // rotary position embedding
 // in-place, returns view(a)
 // if mode == 1, skip n_past elements
 // TODO: avoid creating a new tensor every time
-struct ggml_tensor * ggml_rope(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   n_past,
-        int                   n_dims,
-        int                   mode);
+struct ggml_tensor * ggml_rope(struct ggml_context * ctx, struct ggml_tensor * a, int n_past, int n_dims, int mode);
 
 // padding = 1
 // TODO: we don't support extra parameters for now
 //       that's why we are hard-coding the stride, padding, and dilation
 //       not great ..
-struct ggml_tensor * ggml_conv_1d_1s(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_conv_1d_1s(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
-struct ggml_tensor * ggml_conv_1d_2s(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
+struct ggml_tensor * ggml_conv_1d_2s(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
 
 struct ggml_tensor * ggml_flash_attn(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * q,
-        struct ggml_tensor  * k,
-        struct ggml_tensor  * v,
-        bool                  masked);
+    struct ggml_context * ctx,
+    struct ggml_tensor * q,
+    struct ggml_tensor * k,
+    struct ggml_tensor * v,
+    bool masked
+);
 
 struct ggml_tensor * ggml_flash_ff(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b0,
-        struct ggml_tensor  * b1,
-        struct ggml_tensor  * c0,
-        struct ggml_tensor  * c1);
+    struct ggml_context * ctx,
+    struct ggml_tensor * a,
+    struct ggml_tensor * b0,
+    struct ggml_tensor * b1,
+    struct ggml_tensor * c0,
+    struct ggml_tensor * c1
+);
 
 //
 // automatic differentiation
 //
 
-void ggml_set_param(
-        struct ggml_context * ctx,
-        struct ggml_tensor * tensor);
+void ggml_set_param(struct ggml_context * ctx, struct ggml_tensor * tensor);
 
 void ggml_build_forward_expand(struct ggml_cgraph * cgraph, struct ggml_tensor * tensor);
 
-struct ggml_cgraph ggml_build_forward (struct ggml_tensor * tensor);
+struct ggml_cgraph ggml_build_forward(struct ggml_tensor * tensor);
 struct ggml_cgraph ggml_build_backward(struct ggml_context * ctx, struct ggml_cgraph * gf, bool keep);
 
 void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph);
-void ggml_graph_reset  (struct ggml_cgraph * cgraph);
+void ggml_graph_reset(struct ggml_cgraph * cgraph);
 
 // print info and performance information for the graph
 void ggml_graph_print(const struct ggml_cgraph * cgraph);
@@ -699,8 +601,8 @@ struct ggml_opt_params {
         int n_iter;
         int max_linesearch;
 
-        float eps;      // convergence tolerance
-        float ftol;     // line search tolerance
+        float eps;  // convergence tolerance
+        float ftol; // line search tolerance
         float wolfe;
         float min_step;
         float max_step;
@@ -712,10 +614,7 @@ struct ggml_opt_params {
 struct ggml_opt_params ggml_opt_default_params(enum ggml_opt_type type);
 
 // optimize the function defined by the tensor f
-enum ggml_opt_result ggml_opt(
-        struct ggml_context * ctx,
-        struct ggml_opt_params params,
-        struct ggml_tensor * f);
+enum ggml_opt_result ggml_opt(struct ggml_context * ctx, struct ggml_opt_params params, struct ggml_tensor * f);
 
 //
 // system info
@@ -732,6 +631,6 @@ int ggml_cpu_has_fp16_va(void);
 int ggml_cpu_has_wasm_simd(void);
 int ggml_cpu_has_blas(void);
 
-#ifdef  __cplusplus
+#ifdef __cplusplus
 }
 #endif

whisper.h

@@ -1,8 +1,8 @@
 #ifndef WHISPER_H
 #define WHISPER_H
 
-#include <stdint.h>
 #include <stdbool.h>
+#include <stdint.h>
 
 #ifdef WHISPER_SHARED
 #    ifdef _WIN32
@@ -12,7 +12,7 @@
 #            define WHISPER_API __declspec(dllimport)
 #        endif
 #    else
-#        define WHISPER_API __attribute__ ((visibility ("default")))
+#        define WHISPER_API __attribute__((visibility("default")))
 #    endif
 #else
 #    define WHISPER_API
@@ -28,301 +28,295 @@
 extern "C" {
 #endif
 
-    //
-    // C interface
-    //
-    // The following interface is thread-safe as long as the sample whisper_context is not used by multiple threads
-    // concurrently.
-    //
-    // Basic usage:
-    //
-    //     #include "whisper.h"
-    //
-    //     ...
-    //
-    //     struct whisper_context * ctx = whisper_init("/path/to/ggml-base.en.bin");
-    //
-    //     if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
-    //         fprintf(stderr, "failed to process audio\n");
-    //         return 7;
-    //     }
-    //
-    //     const int n_segments = whisper_full_n_segments(ctx);
-    //     for (int i = 0; i < n_segments; ++i) {
-    //         const char * text = whisper_full_get_segment_text(ctx, i);
-    //         printf("%s", text);
-    //     }
-    //
-    //     whisper_free(ctx);
-    //
-    //     ...
-    //
-    // This is a demonstration of the most straightforward usage of the library.
-    // "pcmf32" contains the RAW audio data in 32-bit floating point format.
-    //
-    // The interface also allows for more fine-grained control over the computation, but it requires a deeper
-    // understanding of how the model works.
-    //
-
-    struct whisper_context;
-
-    typedef int whisper_token;
-
-    typedef struct whisper_token_data {
-        whisper_token id;  // token id
-        whisper_token tid; // forced timestamp token id
-
-        float p;           // probability of the token
-        float pt;          // probability of the timestamp token
-        float ptsum;       // sum of probabilities of all timestamp tokens
-
-        // token-level timestamp data
-        // do not use if you haven't computed token-level timestamps
-        int64_t t0;        // start time of the token
-        int64_t t1;        //   end time of the token
-
-        float vlen;        // voice length of the token
-    } whisper_token_data;
-
-    // Allocates all memory needed for the model and loads the model from the given file.
-    // Returns NULL on failure.
-    WHISPER_API struct whisper_context * whisper_init(const char * path_model);
-
-    // Frees all memory allocated by the model.
-    WHISPER_API void whisper_free(struct whisper_context * ctx);
-
-    // Convert RAW PCM audio to log mel spectrogram.
-    // The resulting spectrogram is stored inside the provided whisper context.
-    // Returns 0 on success
-    WHISPER_API int whisper_pcm_to_mel(
-            struct whisper_context * ctx,
-                       const float * samples,
-                               int   n_samples,
-                               int   n_threads);
-
-    // This can be used to set a custom log mel spectrogram inside the provided whisper context.
-    // Use this instead of whisper_pcm_to_mel() if you want to provide your own log mel spectrogram.
-    // n_mel must be 80
-    // Returns 0 on success
-    WHISPER_API int whisper_set_mel(
-            struct whisper_context * ctx,
-                       const float * data,
-                               int   n_len,
-                               int   n_mel);
-
-    // Run the Whisper encoder on the log mel spectrogram stored inside the provided whisper context.
-    // Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first.
-    // offset can be used to specify the offset of the first frame in the spectrogram.
-    // Returns 0 on success
-    WHISPER_API int whisper_encode(
-            struct whisper_context * ctx,
-                               int   offset,
-                               int   n_threads);
-
-    // Run the Whisper decoder to obtain the logits and probabilities for the next token.
-    // Make sure to call whisper_encode() first.
-    // tokens + n_tokens is the provided context for the decoder.
-    // n_past is the number of tokens to use from previous decoder calls.
-    // Returns 0 on success
-    WHISPER_API int whisper_decode(
-            struct whisper_context * ctx,
-               const whisper_token * tokens,
-                               int   n_tokens,
-                               int   n_past,
-                               int   n_threads);
-
-    // Token sampling methods.
-    // These are provided for convenience and can be used after each call to whisper_decode().
-    // You can also implement your own sampling method using the whisper_get_probs() function.
-    // whisper_sample_best() returns the token with the highest probability
-    // whisper_sample_timestamp() returns the most probable timestamp token
-    WHISPER_API whisper_token_data whisper_sample_best(struct whisper_context * ctx);
-    WHISPER_API whisper_token_data whisper_sample_timestamp(struct whisper_context * ctx, bool is_initial);
-
-    // Convert the provided text into tokens.
-    // The tokens pointer must be large enough to hold the resulting tokens.
-    // Returns the number of tokens on success, no more than n_max_tokens
-    // Returns -1 on failure
-    // TODO: not sure if correct
-    WHISPER_API int whisper_tokenize(
-            struct whisper_context * ctx,
-                        const char * text,
-                     whisper_token * tokens,
-	                           int   n_max_tokens);
-
-    // Largest language id (i.e. number of available languages - 1)
-    WHISPER_API int whisper_lang_max_id();
-
-    // Return the id of the specified language, returns -1 if not found
-    // Examples:
-    //   "de" -> 2
-    //   "german" -> 2
-    WHISPER_API int whisper_lang_id(const char * lang);
-
-    // Return the short string of the specified language id (e.g. 2 -> "de"), returns nullptr if not found
-    WHISPER_API const char * whisper_lang_str(int id);
-
-    // Use mel data at offset_ms to try and auto-detect the spoken language
-    // Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first
-    // Returns the top language id or negative on failure
-    // If not null, fills the lang_probs array with the probabilities of all languages
-    // The array must be whispe_lang_max_id() + 1 in size
-    // ref: https://github.com/openai/whisper/blob/main/whisper/decoding.py#L18-L69
-    WHISPER_API int whisper_lang_auto_detect(
-            struct whisper_context * ctx,
-                               int   offset_ms,
-                               int   n_threads,
-                             float * lang_probs);
-
-    WHISPER_API int whisper_n_len          (struct whisper_context * ctx); // mel length
-    WHISPER_API int whisper_n_vocab        (struct whisper_context * ctx);
-    WHISPER_API int whisper_n_text_ctx     (struct whisper_context * ctx);
-    WHISPER_API int whisper_n_audio_ctx    (struct whisper_context * ctx);
-    WHISPER_API int whisper_is_multilingual(struct whisper_context * ctx);
-
-    // The probabilities for the next token
-    WHISPER_API float * whisper_get_probs(struct whisper_context * ctx);
-
-    // Token Id -> String. Uses the vocabulary in the provided context
-    WHISPER_API const char * whisper_token_to_str(struct whisper_context * ctx, whisper_token token);
-
-    // Special tokens
-    WHISPER_API whisper_token whisper_token_eot (struct whisper_context * ctx);
-    WHISPER_API whisper_token whisper_token_sot (struct whisper_context * ctx);
-    WHISPER_API whisper_token whisper_token_prev(struct whisper_context * ctx);
-    WHISPER_API whisper_token whisper_token_solm(struct whisper_context * ctx);
-    WHISPER_API whisper_token whisper_token_not (struct whisper_context * ctx);
-    WHISPER_API whisper_token whisper_token_beg (struct whisper_context * ctx);
-    WHISPER_API whisper_token whisper_token_lang(struct whisper_context * ctx, int lang_id);
-
-    // Task tokens
-    WHISPER_API whisper_token whisper_token_translate (void);
-    WHISPER_API whisper_token whisper_token_transcribe(void);
-
-    // Performance information
-    WHISPER_API void whisper_print_timings(struct whisper_context * ctx);
-    WHISPER_API void whisper_reset_timings(struct whisper_context * ctx);
-
-    // Print system information
-    WHISPER_API const char * whisper_print_system_info(void);
-
-    ////////////////////////////////////////////////////////////////////////////
-
-    // Available sampling strategies
-    enum whisper_sampling_strategy {
-        WHISPER_SAMPLING_GREEDY,      // Always select the most probable token
-        WHISPER_SAMPLING_BEAM_SEARCH, // TODO: not implemented yet!
-    };
-
-    // Text segment callback
-    // Called on every newly generated text segment
-    // Use the whisper_full_...() functions to obtain the text segments
-    typedef void (*whisper_new_segment_callback)(struct whisper_context * ctx, int n_new, void * user_data);
-
-    // Encoder begin callback
-    // If not NULL, called before the encoder starts
-    // If it returns false, the computation is aborted
-    typedef bool (*whisper_encoder_begin_callback)(struct whisper_context * ctx, void * user_data);
-
-    // Parameters for the whisper_full() function
-    // If you chnage the order or add new parameters, make sure to update the default values in whisper.cpp:
-    // whisper_full_default_params()
-    struct whisper_full_params {
-        enum whisper_sampling_strategy strategy;
-
-        int n_threads;
-        int n_max_text_ctx;
-        int offset_ms;          // start offset in ms
-        int duration_ms;        // audio duration to process in ms
-
-        bool translate;
-        bool no_context;
-        bool single_segment;    // force single segment output (useful for streaming)
-        bool print_special;
-        bool print_progress;
-        bool print_realtime;
-        bool print_timestamps;
-
-        // [EXPERIMENTAL] token-level timestamps
-        bool  token_timestamps; // enable token-level timestamps
-        float thold_pt;         // timestamp token probability threshold (~0.01)
-        float thold_ptsum;      // timestamp token sum probability threshold (~0.01)
-        int   max_len;          // max segment length in characters
-        int   max_tokens;       // max tokens per segment (0 = no limit)
-
-        // [EXPERIMENTAL] speed-up techniques
-        bool speed_up;          // speed-up the audio by 2x using Phase Vocoder
-        int  audio_ctx;         // overwrite the audio context size (0 = use default)
-
-        // tokens to provide the whisper model as initial prompt
-        // these are prepended to any existing text context from a previous call
-        const whisper_token * prompt_tokens;
-        int prompt_n_tokens;
-
-        // for auto-detection, set to nullptr, "" or "auto"
-        const char * language;
-
-        struct {
-            int n_past;
-        } greedy;
-
-        struct {
-            int n_past;
-            int beam_width;
-            int n_best;
-        } beam_search;
-
-        whisper_new_segment_callback new_segment_callback;
-        void * new_segment_callback_user_data;
-
-        whisper_encoder_begin_callback encoder_begin_callback;
-        void * encoder_begin_callback_user_data;
-    };
-
-    WHISPER_API struct whisper_full_params whisper_full_default_params(enum whisper_sampling_strategy strategy);
-
-    // Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
-    // Uses the specified decoding strategy to obtain the text.
-    WHISPER_API int whisper_full(
-                struct whisper_context * ctx,
-            struct whisper_full_params   params,
-                           const float * samples,
-                                   int   n_samples);
-
-    // Split the input audio in chunks and process each chunk separately using whisper_full()
-    // It seems this approach can offer some speedup in some cases.
-    // However, the transcription accuracy can be worse at the beginning and end of each chunk.
-    WHISPER_API int whisper_full_parallel(
-                struct whisper_context * ctx,
-            struct whisper_full_params   params,
-                           const float * samples,
-                                   int   n_samples,
-                                   int   n_processors);
-
-    // Number of generated text segments.
-    // A segment can be a few words, a sentence, or even a paragraph.
-    WHISPER_API int whisper_full_n_segments(struct whisper_context * ctx);
-
-    // Get the start and end time of the specified segment.
-    WHISPER_API int64_t whisper_full_get_segment_t0(struct whisper_context * ctx, int i_segment);
-    WHISPER_API int64_t whisper_full_get_segment_t1(struct whisper_context * ctx, int i_segment);
-
-    // Get the text of the specified segment.
-    WHISPER_API const char * whisper_full_get_segment_text(struct whisper_context * ctx, int i_segment);
-
-    // Get number of tokens in the specified segment.
-    WHISPER_API int whisper_full_n_tokens(struct whisper_context * ctx, int i_segment);
-
-    // Get the token text of the specified token in the specified segment.
-    WHISPER_API const char * whisper_full_get_token_text(struct whisper_context * ctx, int i_segment, int i_token);
-    WHISPER_API whisper_token whisper_full_get_token_id (struct whisper_context * ctx, int i_segment, int i_token);
-
-    // Get token data for the specified token in the specified segment.
-    // This contains probabilities, timestamps, etc.
-    WHISPER_API whisper_token_data whisper_full_get_token_data(struct whisper_context * ctx, int i_segment, int i_token);
-
-    // Get the probability of the specified token in the specified segment.
-    WHISPER_API float whisper_full_get_token_p(struct whisper_context * ctx, int i_segment, int i_token);
+//
+// C interface
+//
+// The following interface is thread-safe as long as the sample whisper_context is not used by multiple threads
+// concurrently.
+//
+// Basic usage:
+//
+//     #include "whisper.h"
+//
+//     ...
+//
+//     struct whisper_context * ctx = whisper_init("/path/to/ggml-base.en.bin");
+//
+//     if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
+//         fprintf(stderr, "failed to process audio\n");
+//         return 7;
+//     }
+//
+//     const int n_segments = whisper_full_n_segments(ctx);
+//     for (int i = 0; i < n_segments; ++i) {
+//         const char * text = whisper_full_get_segment_text(ctx, i);
+//         printf("%s", text);
+//     }
+//
+//     whisper_free(ctx);
+//
+//     ...
+//
+// This is a demonstration of the most straightforward usage of the library.
+// "pcmf32" contains the RAW audio data in 32-bit floating point format.
+//
+// The interface also allows for more fine-grained control over the computation, but it requires a deeper
+// understanding of how the model works.
+//
+
+struct whisper_context;
+
+typedef int whisper_token;
+
+typedef struct whisper_token_data {
+    whisper_token id;  // token id
+    whisper_token tid; // forced timestamp token id
+
+    float p;     // probability of the token
+    float pt;    // probability of the timestamp token
+    float ptsum; // sum of probabilities of all timestamp tokens
+
+    // token-level timestamp data
+    // do not use if you haven't computed token-level timestamps
+    int64_t t0; // start time of the token
+    int64_t t1; //   end time of the token
+
+    float vlen; // voice length of the token
+} whisper_token_data;
+
+// Allocates all memory needed for the model and loads the model from the given file.
+// Returns NULL on failure.
+WHISPER_API struct whisper_context * whisper_init(const char * path_model);
+
+// Frees all memory allocated by the model.
+WHISPER_API void whisper_free(struct whisper_context * ctx);
+
+// Convert RAW PCM audio to log mel spectrogram.
+// The resulting spectrogram is stored inside the provided whisper context.
+// Returns 0 on success
+WHISPER_API int whisper_pcm_to_mel(struct whisper_context * ctx, const float * samples, int n_samples, int n_threads);
+
+// This can be used to set a custom log mel spectrogram inside the provided whisper context.
+// Use this instead of whisper_pcm_to_mel() if you want to provide your own log mel spectrogram.
+// n_mel must be 80
+// Returns 0 on success
+WHISPER_API int whisper_set_mel(struct whisper_context * ctx, const float * data, int n_len, int n_mel);
+
+// Run the Whisper encoder on the log mel spectrogram stored inside the provided whisper context.
+// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first.
+// offset can be used to specify the offset of the first frame in the spectrogram.
+// Returns 0 on success
+WHISPER_API int whisper_encode(struct whisper_context * ctx, int offset, int n_threads);
+
+// Run the Whisper decoder to obtain the logits and probabilities for the next token.
+// Make sure to call whisper_encode() first.
+// tokens + n_tokens is the provided context for the decoder.
+// n_past is the number of tokens to use from previous decoder calls.
+// Returns 0 on success
+WHISPER_API int whisper_decode(
+    struct whisper_context * ctx,
+    const whisper_token * tokens,
+    int n_tokens,
+    int n_past,
+    int n_threads
+);
+
+// Token sampling methods.
+// These are provided for convenience and can be used after each call to whisper_decode().
+// You can also implement your own sampling method using the whisper_get_probs() function.
+// whisper_sample_best() returns the token with the highest probability
+// whisper_sample_timestamp() returns the most probable timestamp token
+WHISPER_API whisper_token_data whisper_sample_best(struct whisper_context * ctx);
+WHISPER_API whisper_token_data whisper_sample_timestamp(struct whisper_context * ctx, bool is_initial);
+
+// Convert the provided text into tokens.
+// The tokens pointer must be large enough to hold the resulting tokens.
+// Returns the number of tokens on success, no more than n_max_tokens
+// Returns -1 on failure
+// TODO: not sure if correct
+WHISPER_API int whisper_tokenize(
+    struct whisper_context * ctx,
+    const char * text,
+    whisper_token * tokens,
+    int n_max_tokens
+);
+
+// Largest language id (i.e. number of available languages - 1)
+WHISPER_API int whisper_lang_max_id();
+
+// Return the id of the specified language, returns -1 if not found
+// Examples:
+//   "de" -> 2
+//   "german" -> 2
+WHISPER_API int whisper_lang_id(const char * lang);
+
+// Return the short string of the specified language id (e.g. 2 -> "de"), returns nullptr if not found
+WHISPER_API const char * whisper_lang_str(int id);
+
+// Use mel data at offset_ms to try and auto-detect the spoken language
+// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first
+// Returns the top language id or negative on failure
+// If not null, fills the lang_probs array with the probabilities of all languages
+// The array must be whispe_lang_max_id() + 1 in size
+// ref: https://github.com/openai/whisper/blob/main/whisper/decoding.py#L18-L69
+WHISPER_API int whisper_lang_auto_detect(
+    struct whisper_context * ctx,
+    int offset_ms,
+    int n_threads,
+    float * lang_probs
+);
+
+WHISPER_API int whisper_n_len(struct whisper_context * ctx); // mel length
+WHISPER_API int whisper_n_vocab(struct whisper_context * ctx);
+WHISPER_API int whisper_n_text_ctx(struct whisper_context * ctx);
+WHISPER_API int whisper_n_audio_ctx(struct whisper_context * ctx);
+WHISPER_API int whisper_is_multilingual(struct whisper_context * ctx);
+
+// The probabilities for the next token
+WHISPER_API float * whisper_get_probs(struct whisper_context * ctx);
+
+// Token Id -> String. Uses the vocabulary in the provided context
+WHISPER_API const char * whisper_token_to_str(struct whisper_context * ctx, whisper_token token);
+
+// Special tokens
+WHISPER_API whisper_token whisper_token_eot(struct whisper_context * ctx);
+WHISPER_API whisper_token whisper_token_sot(struct whisper_context * ctx);
+WHISPER_API whisper_token whisper_token_prev(struct whisper_context * ctx);
+WHISPER_API whisper_token whisper_token_solm(struct whisper_context * ctx);
+WHISPER_API whisper_token whisper_token_not(struct whisper_context * ctx);
+WHISPER_API whisper_token whisper_token_beg(struct whisper_context * ctx);
+WHISPER_API whisper_token whisper_token_lang(struct whisper_context * ctx, int lang_id);
+
+// Task tokens
+WHISPER_API whisper_token whisper_token_translate(void);
+WHISPER_API whisper_token whisper_token_transcribe(void);
+
+// Performance information
+WHISPER_API void whisper_print_timings(struct whisper_context * ctx);
+WHISPER_API void whisper_reset_timings(struct whisper_context * ctx);
+
+// Print system information
+WHISPER_API const char * whisper_print_system_info(void);
+
+////////////////////////////////////////////////////////////////////////////
+
+// Available sampling strategies
+enum whisper_sampling_strategy {
+    WHISPER_SAMPLING_GREEDY,      // Always select the most probable token
+    WHISPER_SAMPLING_BEAM_SEARCH, // TODO: not implemented yet!
+};
+
+// Text segment callback
+// Called on every newly generated text segment
+// Use the whisper_full_...() functions to obtain the text segments
+typedef void (*whisper_new_segment_callback)(struct whisper_context * ctx, int n_new, void * user_data);
+
+// Encoder begin callback
+// If not NULL, called before the encoder starts
+// If it returns false, the computation is aborted
+typedef bool (*whisper_encoder_begin_callback)(struct whisper_context * ctx, void * user_data);
+
+// Parameters for the whisper_full() function
+// If you chnage the order or add new parameters, make sure to update the default values in whisper.cpp:
+// whisper_full_default_params()
+struct whisper_full_params {
+    enum whisper_sampling_strategy strategy;
+
+    int n_threads;
+    int n_max_text_ctx;
+    int offset_ms;   // start offset in ms
+    int duration_ms; // audio duration to process in ms
+
+    bool translate;
+    bool no_context;
+    bool single_segment; // force single segment output (useful for streaming)
+    bool print_special;
+    bool print_progress;
+    bool print_realtime;
+    bool print_timestamps;
+
+    // [EXPERIMENTAL] token-level timestamps
+    bool token_timestamps; // enable token-level timestamps
+    float thold_pt;        // timestamp token probability threshold (~0.01)
+    float thold_ptsum;     // timestamp token sum probability threshold (~0.01)
+    int max_len;           // max segment length in characters
+    int max_tokens;        // max tokens per segment (0 = no limit)
+
+    // [EXPERIMENTAL] speed-up techniques
+    bool speed_up; // speed-up the audio by 2x using Phase Vocoder
+    int audio_ctx; // overwrite the audio context size (0 = use default)
+
+    // tokens to provide the whisper model as initial prompt
+    // these are prepended to any existing text context from a previous call
+    const whisper_token * prompt_tokens;
+    int prompt_n_tokens;
+
+    // for auto-detection, set to nullptr, "" or "auto"
+    const char * language;
+
+    struct {
+        int n_past;
+    } greedy;
+
+    struct {
+        int n_past;
+        int beam_width;
+        int n_best;
+    } beam_search;
+
+    whisper_new_segment_callback new_segment_callback;
+    void * new_segment_callback_user_data;
+
+    whisper_encoder_begin_callback encoder_begin_callback;
+    void * encoder_begin_callback_user_data;
+};
+
+WHISPER_API struct whisper_full_params whisper_full_default_params(enum whisper_sampling_strategy strategy);
+
+// Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
+// Uses the specified decoding strategy to obtain the text.
+WHISPER_API int whisper_full(
+    struct whisper_context * ctx,
+    struct whisper_full_params params,
+    const float * samples,
+    int n_samples
+);
+
+// Split the input audio in chunks and process each chunk separately using whisper_full()
+// It seems this approach can offer some speedup in some cases.
+// However, the transcription accuracy can be worse at the beginning and end of each chunk.
+WHISPER_API int whisper_full_parallel(
+    struct whisper_context * ctx,
+    struct whisper_full_params params,
+    const float * samples,
+    int n_samples,
+    int n_processors
+);
+
+// Number of generated text segments.
+// A segment can be a few words, a sentence, or even a paragraph.
+WHISPER_API int whisper_full_n_segments(struct whisper_context * ctx);
+
+// Get the start and end time of the specified segment.
+WHISPER_API int64_t whisper_full_get_segment_t0(struct whisper_context * ctx, int i_segment);
+WHISPER_API int64_t whisper_full_get_segment_t1(struct whisper_context * ctx, int i_segment);
+
+// Get the text of the specified segment.
+WHISPER_API const char * whisper_full_get_segment_text(struct whisper_context * ctx, int i_segment);
+
+// Get number of tokens in the specified segment.
+WHISPER_API int whisper_full_n_tokens(struct whisper_context * ctx, int i_segment);
+
+// Get the token text of the specified token in the specified segment.
+WHISPER_API const char * whisper_full_get_token_text(struct whisper_context * ctx, int i_segment, int i_token);
+WHISPER_API whisper_token whisper_full_get_token_id(struct whisper_context * ctx, int i_segment, int i_token);
+
+// Get token data for the specified token in the specified segment.
+// This contains probabilities, timestamps, etc.
+WHISPER_API whisper_token_data whisper_full_get_token_data(struct whisper_context * ctx, int i_segment, int i_token);
+
+// Get the probability of the specified token in the specified segment.
+WHISPER_API float whisper_full_get_token_p(struct whisper_context * ctx, int i_segment, int i_token);
 
 #ifdef __cplusplus
 }