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.h

@@ -173,9 +173,9 @@
 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
@@ -327,29 +327,13 @@ 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_tensor * ggml_new_tensor(struct ggml_context * ctx, enum ggml_type type, int n_dims, const int * ne);
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    n_dims,
-        const int *ne);
 
-struct ggml_tensor * ggml_new_tensor_1d(
+struct ggml_tensor * ggml_new_tensor_1d(struct ggml_context * ctx, enum ggml_type type, int ne0);
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    ne0);
 
-struct ggml_tensor * ggml_new_tensor_2d(
+struct ggml_tensor * ggml_new_tensor_2d(struct ggml_context * ctx, enum ggml_type type, int ne0, int ne1);
-        struct ggml_context * ctx,
-        enum   ggml_type type,
-        int    ne0,
-        int    ne1);
 
-struct ggml_tensor * ggml_new_tensor_3d(
+struct ggml_tensor * ggml_new_tensor_3d(struct ggml_context * ctx, enum ggml_type type, int ne0, int ne1, int ne2);
-        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,
@@ -357,7 +341,8 @@ struct ggml_tensor * ggml_new_tensor_4d(
     int ne0,
     int ne1,
     int ne2,
-        int    ne3);
+    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);
@@ -382,141 +367,77 @@ float * ggml_get_data_f32(const struct ggml_tensor * tensor);
 // operations on tensors with backpropagation
 //
 
-struct ggml_tensor * ggml_dup(
+struct ggml_tensor * ggml_dup(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
-struct ggml_tensor * ggml_add(
+struct ggml_tensor * ggml_add(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
 
-struct ggml_tensor * ggml_sub(
+struct ggml_tensor * ggml_sub(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
 
-struct ggml_tensor * ggml_mul(
+struct ggml_tensor * ggml_mul(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
 
-struct ggml_tensor * ggml_div(
+struct ggml_tensor * ggml_div(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
 
-struct ggml_tensor * ggml_sqr(
+struct ggml_tensor * ggml_sqr(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
-struct ggml_tensor * ggml_sqrt(
+struct ggml_tensor * ggml_sqrt(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
 // return scalar
 // TODO: compute sum along rows
-struct ggml_tensor * ggml_sum(
+struct ggml_tensor * ggml_sum(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
 // mean along rows
-struct ggml_tensor * ggml_mean(
+struct ggml_tensor * ggml_mean(struct ggml_context * ctx, struct ggml_tensor * a);
-        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_tensor * ggml_repeat(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
 
-struct ggml_tensor * ggml_abs(
+struct ggml_tensor * ggml_abs(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
-struct ggml_tensor * ggml_sgn(
+struct ggml_tensor * ggml_sgn(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
-struct ggml_tensor * ggml_neg(
+struct ggml_tensor * ggml_neg(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
-struct ggml_tensor * ggml_step(
+struct ggml_tensor * ggml_step(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
-struct ggml_tensor * ggml_relu(
+struct ggml_tensor * ggml_relu(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
 // TODO: double-check this computation is correct
-struct ggml_tensor * ggml_gelu(
+struct ggml_tensor * ggml_gelu(struct ggml_context * ctx, struct ggml_tensor * a);
-        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_tensor * ggml_norm(struct ggml_context * ctx, struct ggml_tensor * a);
-        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_tensor * ggml_mul_mat(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        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_tensor * ggml_scale(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
 
 // a -> b, return view(b)
-struct ggml_tensor * ggml_cpy(
+struct ggml_tensor * ggml_cpy(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        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_tensor * ggml_reshape(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        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_tensor * ggml_reshape_2d(struct ggml_context * ctx, struct ggml_tensor * a, int ne0, int ne1);
-        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_tensor * ggml_reshape_3d(struct ggml_context * ctx, struct ggml_tensor * a, int ne0, int ne1, int ne2);
-        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_tensor * ggml_view_1d(struct ggml_context * ctx, struct ggml_tensor * a, int ne0, size_t offset);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   ne0,
-        size_t                offset);
 
 struct ggml_tensor * ggml_view_2d(
     struct ggml_context * ctx,
@@ -524,7 +445,8 @@ struct ggml_tensor * ggml_view_2d(
     int ne0,
     int ne1,
     size_t nb1, // row stride in bytes
-        size_t                offset);
+    size_t offset
+);
 
 struct ggml_tensor * ggml_permute(
     struct ggml_context * ctx,
@@ -532,61 +454,42 @@ struct ggml_tensor * ggml_permute(
     int axis0,
     int axis1,
     int axis2,
-        int                   axis3);
+    int axis3
+);
 
 // alias for ggml_permute(ctx, a, 1, 0, 2, 3)
-struct ggml_tensor * ggml_transpose(
+struct ggml_tensor * ggml_transpose(struct ggml_context * ctx, struct ggml_tensor * a);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a);
 
-struct ggml_tensor * ggml_get_rows(
+struct ggml_tensor * ggml_get_rows(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        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_tensor * ggml_diag_mask_inf(struct ggml_context * ctx, struct ggml_tensor * a, int n_past);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        int                   n_past);
 
 // in-place, returns view(a)
-struct ggml_tensor * ggml_soft_max(
+struct ggml_tensor * ggml_soft_max(struct ggml_context * ctx, struct ggml_tensor * a);
-        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_tensor * ggml_rope(struct ggml_context * ctx, struct ggml_tensor * a, int n_past, int n_dims, int mode);
-        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_tensor * ggml_conv_1d_1s(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b);
 
-struct ggml_tensor * ggml_conv_1d_2s(
+struct ggml_tensor * ggml_conv_1d_2s(struct ggml_context * ctx, struct ggml_tensor * a, struct ggml_tensor * b);
-        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);
+    bool masked
+);
 
 struct ggml_tensor * ggml_flash_ff(
     struct ggml_context * ctx,
@@ -594,15 +497,14 @@ struct ggml_tensor * ggml_flash_ff(
     struct ggml_tensor * b0,
     struct ggml_tensor * b1,
     struct ggml_tensor * c0,
-        struct ggml_tensor  * c1);
+    struct ggml_tensor * c1
+);
 
 //
 // automatic differentiation
 //
 
-void ggml_set_param(
+void ggml_set_param(struct ggml_context * ctx, struct ggml_tensor * tensor);
-        struct ggml_context * ctx,
-        struct ggml_tensor * tensor);
 
 void ggml_build_forward_expand(struct ggml_cgraph * cgraph, struct ggml_tensor * tensor);
 
@@ -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(
+enum ggml_opt_result ggml_opt(struct ggml_context * ctx, struct ggml_opt_params params, struct ggml_tensor * f);
-        struct ggml_context * ctx,
-        struct ggml_opt_params params,
-        struct ggml_tensor * f);
 
 //
 // system info

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
@@ -94,30 +94,19 @@ extern "C" {
 // 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(
+WHISPER_API int whisper_pcm_to_mel(struct whisper_context * ctx, const float * samples, int n_samples, int n_threads);
-            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(
+WHISPER_API int whisper_set_mel(struct whisper_context * ctx, const float * data, int n_len, int n_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(
+WHISPER_API int whisper_encode(struct whisper_context * ctx, int offset, int n_threads);
-            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.
@@ -129,7 +118,8 @@ extern "C" {
     const whisper_token * tokens,
     int n_tokens,
     int n_past,
-                               int   n_threads);
+    int n_threads
+);
 
 // Token sampling methods.
 // These are provided for convenience and can be used after each call to whisper_decode().
@@ -148,7 +138,8 @@ extern "C" {
     struct whisper_context * ctx,
     const char * text,
     whisper_token * tokens,
-	                           int   n_max_tokens);
+    int n_max_tokens
+);
 
 // Largest language id (i.e. number of available languages - 1)
 WHISPER_API int whisper_lang_max_id();
@@ -172,7 +163,8 @@ extern "C" {
     struct whisper_context * ctx,
     int offset_ms,
     int n_threads,
-                             float * lang_probs);
+    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);
@@ -287,7 +279,8 @@ extern "C" {
     struct whisper_context * ctx,
     struct whisper_full_params params,
     const float * samples,
-                                   int   n_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.
@@ -297,7 +290,8 @@ extern "C" {
     struct whisper_full_params params,
     const float * samples,
     int n_samples,
-                                   int   n_processors);
+    int n_processors
+);
 
 // Number of generated text segments.
 // A segment can be a few words, a sentence, or even a paragraph.