Add CEIL operator support for CPU and SYCL backends

docs/ops.md

@@ -22,6 +22,7 @@ Legend:
 |                           ARANGE | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ |
 |                           ARGMAX | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ |
 |                          ARGSORT | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ |
+|                             CEIL | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ |
 |                            CLAMP | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ❌ |
 |                           CONCAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | 🟡 | ✅ | ❌ |
 |                             CONT | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ❌ |

docs/ops/CPU.csv

@@ -1,6 +1,8 @@
 "backend_name","op_name","op_params","test_mode","supported","error_message","backend_reg_name"
 "CPU","ABS","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"
 "CPU","ABS","type=f16,ne_a=[5,7,11,13],v=0","support","1","yes","CPU"
+"CPU","CEIL","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"
+"CPU","CEIL","type=f16,ne_a=[5,7,11,13],v=0","support","1","yes","CPU"
 "CPU","SGN","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"
 "CPU","SGN","type=f16,ne_a=[5,7,11,13],v=0","support","1","yes","CPU"
 "CPU","NEG","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"
@@ -61,6 +63,8 @@
 "CPU","GELU_ERF","type=f16,ne_a=[5,7,11,13],v=1","support","1","yes","CPU"
 "CPU","ABS","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"
 "CPU","ABS","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","CPU"
+"CPU","CEIL","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"
+"CPU","CEIL","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","CPU"
 "CPU","SGN","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"
 "CPU","SGN","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","CPU"
 "CPU","NEG","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","CPU"

docs/ops/SYCL.csv

@@ -1,6 +1,8 @@
 "backend_name","op_name","op_params","test_mode","supported","error_message","backend_reg_name"
 "SYCL0","ABS","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"
 "SYCL0","ABS","type=f16,ne_a=[5,7,11,13],v=0","support","1","yes","SYCL"
+"SYCL0","CEIL","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"
+"SYCL0","CEIL","type=f16,ne_a=[5,7,11,13],v=0","support","1","yes","SYCL"
 "SYCL0","SGN","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"
 "SYCL0","SGN","type=f16,ne_a=[5,7,11,13],v=0","support","1","yes","SYCL"
 "SYCL0","NEG","type=f16,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"
@@ -61,6 +63,8 @@
 "SYCL0","GELU_ERF","type=f16,ne_a=[5,7,11,13],v=1","support","0","no","SYCL"
 "SYCL0","ABS","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"
 "SYCL0","ABS","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","SYCL"
+"SYCL0","CEIL","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"
+"SYCL0","CEIL","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","SYCL"
 "SYCL0","SGN","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"
 "SYCL0","SGN","type=f32,ne_a=[5,7,11,13],v=0","support","1","yes","SYCL"
 "SYCL0","NEG","type=f32,ne_a=[128,2,2,2],v=0","support","1","yes","SYCL"

ggml/include/ggml.h

@@ -574,6 +574,7 @@ extern "C" {
         GGML_UNARY_OP_HARDSIGMOID,
         GGML_UNARY_OP_EXP,
         GGML_UNARY_OP_GELU_ERF,
+        GGML_UNARY_OP_CEIL,
 
         GGML_UNARY_OP_COUNT,
     };
@@ -1148,6 +1149,14 @@ extern "C" {
             struct ggml_context * ctx,
             struct ggml_tensor  * a);
 
+    GGML_API struct ggml_tensor * ggml_ceil(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * a);
+
+    GGML_API struct ggml_tensor * ggml_ceil_inplace(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * a);
+
     // gated linear unit ops
     // A: n columns, r rows,
     // result is n / 2 columns, r rows,

ggml/src/ggml-cpu/ops.cpp

@@ -9767,6 +9767,10 @@ void ggml_compute_forward_unary(
             {
                 ggml_compute_forward_exp(params, dst);
             } break;
+        case GGML_UNARY_OP_CEIL:
+            {
+                ggml_compute_forward_ceil(params, dst);
+            } break;
         default:
             {
                 GGML_ABORT("fatal error");

ggml/src/ggml-cpu/unary-ops.cpp

@@ -64,6 +64,10 @@ static inline float op_log(float x) {
     return logf(x);
 }
 
+static inline float op_ceil(float x) {
+    return ceilf(x);
+}
+
 template <float (*op)(float), typename src0_t, typename dst_t>
 static inline void vec_unary_op(int64_t n, dst_t * y, const src0_t * x) {
     constexpr auto src0_to_f32 = type_conversion_table<src0_t>::to_f32;
@@ -184,3 +188,8 @@ void ggml_compute_forward_cos(const ggml_compute_params * params, ggml_tensor *
 void ggml_compute_forward_log(const ggml_compute_params * params, ggml_tensor * dst) {
     unary_op<op_log>(params, dst);
 }
+
+void ggml_compute_forward_ceil(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_ceil>(params, dst);
+}
+

ggml/src/ggml-cpu/unary-ops.h

@@ -22,6 +22,7 @@ void ggml_compute_forward_sqrt(const struct ggml_compute_params * params, struct
 void ggml_compute_forward_sin(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 void ggml_compute_forward_cos(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 void ggml_compute_forward_log(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_ceil(const struct ggml_compute_params * params, struct ggml_tensor * dst);
 
 #ifdef __cplusplus
 }

ggml/src/ggml-sycl/element_wise.cpp

@@ -156,6 +156,11 @@ static void unary_op_sgn_kernel(const T * x, T * dst, const int k, const sycl::n
         dst[i] = op_sgn(x[i]);
     }
 }
+template<typename T>
+static __dpct_inline__ T op_ceil(T x) {
+    return sycl::ceil(x);
+}
+
 
 template<typename T>
 static void unary_op_abs_kernel(const T * x, T * dst, const int k, const sycl::nd_item<1> &item_ct1) {
@@ -304,6 +309,13 @@ static void unary_op_clamp_kernel(const T * x, T * dst, const int k, const sycl:
     }
 }
 
+template<typename T>
+static void unary_op_ceil_kernel(const T * x, T * dst, const int k, const sycl::nd_item<1> &item_ct1) {
+    SYCL_GLOBAL_ID_LOOP(k, item_ct1) {
+        dst[i] = op_ceil(x[i]);
+    }
+}
+
 template<typename  T>
 static void upscale(const T  *x, T *dst, const int nb00, const int nb01,
                         const int nb02, const int nb03, const int ne10, const int ne11,
@@ -944,6 +956,19 @@ static inline void ggml_sycl_op_clamp(ggml_backend_sycl_context & ctx, ggml_tens
         }, min_val, max_val);
 }
 
+static inline void ggml_sycl_op_ceil(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
+    ggml_sycl_detail::dispatch_ggml_sycl_op_unary(ctx, dst,
+        [](const auto* src, auto* dst_ptr, int k_elements, queue_ptr stream) {
+            const int num_blocks = ceil_div(k_elements, 256);
+            stream->parallel_for(
+                sycl::nd_range<1>(sycl::range<1>(num_blocks) * sycl::range<1>(256),
+                                  sycl::range<1>(256)),
+                [=](sycl::nd_item<1> item_ct1) {
+                    unary_op_ceil_kernel(src, dst_ptr, k_elements, item_ct1);
+                });
+        });
+}
+
 static inline void ggml_sycl_op_acc(ggml_backend_sycl_context & ctx, ggml_tensor *dst) {
     GGML_ASSERT(dst->src[0]->type == GGML_TYPE_F32);
     GGML_ASSERT(dst->src[1]->type == GGML_TYPE_F32);
@@ -1168,3 +1193,7 @@ void ggml_sycl_geglu_quick(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
     scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/1);
     ggml_sycl_op_geglu_quick(ctx, dst);
 }
+void ggml_sycl_ceil(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
+    scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/1);
+    ggml_sycl_op_ceil(ctx, dst);
+}

ggml/src/ggml-sycl/element_wise.hpp

@@ -75,6 +75,8 @@ void ggml_sycl_sgn(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
 
 void ggml_sycl_abs(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
 
+void ggml_sycl_ceil(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
+
 void ggml_sycl_elu(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
 
 void ggml_sycl_geglu(ggml_backend_sycl_context & ctx, ggml_tensor * dst);

ggml/src/ggml-sycl/ggml-sycl.cpp

@@ -3636,6 +3636,9 @@ static bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct gg
                 case GGML_UNARY_OP_ELU:
                     ggml_sycl_elu(ctx, dst);
                     break;
+                case GGML_UNARY_OP_CEIL:
+                    ggml_sycl_ceil(ctx, dst);
+                    break;
                 default:
                     return false;
             }
@@ -4190,6 +4193,7 @@ static bool ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, const g
                 case GGML_UNARY_OP_SGN:
                 case GGML_UNARY_OP_ABS:
                 case GGML_UNARY_OP_ELU:
+                case GGML_UNARY_OP_CEIL:
 #if defined (GGML_SYCL_F16)
                     return ggml_is_contiguous(op->src[0]) && (op->type == op->src[0]->type);
 #else

ggml/src/ggml.c

@@ -1143,9 +1143,10 @@ static const char * GGML_UNARY_OP_NAME[GGML_UNARY_OP_COUNT] = {
     "HARDSIGMOID",
     "EXP",
     "GELU_ERF",
+    "CEIL"
 };
 
-static_assert(GGML_UNARY_OP_COUNT == 15, "GGML_UNARY_OP_COUNT != 15");
+static_assert(GGML_UNARY_OP_COUNT == 16, "GGML_UNARY_OP_COUNT != 16");
 
 
 static const char * GGML_GLU_OP_NAME[GGML_GLU_OP_COUNT] = {
@@ -5743,6 +5744,21 @@ struct ggml_tensor * ggml_cross_entropy_loss_back(
     return result;
 }
 
+// ggml_ceil
+
+struct ggml_tensor * ggml_ceil(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * a) {
+    return ggml_unary(ctx, a, GGML_UNARY_OP_CEIL);
+}
+
+struct ggml_tensor * ggml_ceil_inplace(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * a) {
+    return ggml_unary_inplace(ctx, a, GGML_UNARY_OP_CEIL);
+}
+
+
 // opt_step_adamw
 
 struct ggml_tensor * ggml_opt_step_adamw(

tests/test-backend-ops.cpp

@@ -3524,6 +3524,45 @@ struct test_log : public test_case {
     }
 };
 
+// GGML_OP_CEIL
+struct test_ceil : public test_case {
+    const ggml_type type;
+    const std::array<int64_t, 4> ne;
+
+    std::string vars() override {
+        return VARS_TO_STR2(type, ne);
+    }
+
+    test_ceil(ggml_type type = GGML_TYPE_F32,
+               std::array<int64_t, 4> ne = {10, 5, 4, 3})
+        : type(type), ne(ne) {}
+
+    ggml_tensor * build_graph(ggml_context * ctx) override {
+        ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne.data());
+        ggml_set_param(a);
+        ggml_set_name(a, "a");
+
+        ggml_tensor * out = ggml_ceil(ctx, a);
+        ggml_set_name(out, "out");
+
+        return out;
+    }
+
+    void initialize_tensors(ggml_context * ctx) override {
+        for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
+            init_tensor_uniform(t, -10.0f, 10.0f);
+        }
+    }
+
+    float grad_eps() override {
+        return 1.0f;
+    }
+
+    bool grad_precise() override {
+        return true;
+    }
+};
+
 // GGML_OP_SIN
 struct test_sin : public test_case {
     const ggml_type type;
@@ -6328,6 +6367,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
         test_cases.emplace_back(new test_sqr(type));
         test_cases.emplace_back(new test_sqrt(type));
         test_cases.emplace_back(new test_log(type));
+        test_cases.emplace_back(new test_ceil(type));
         test_cases.emplace_back(new test_sin(type));
         test_cases.emplace_back(new test_cos(type));
         test_cases.emplace_back(new test_clamp(type));

vendor/miniaudio/miniaudio.h

@@ -28227,7 +28227,7 @@ static ma_result ma_device_start__alsa(ma_device* pDevice)
     }
 
     if (pDevice->type == ma_device_type_playback || pDevice->type == ma_device_type_duplex) {
-        /*        
+        /*
         When data is written to the device we wait for the device to get ready to receive data with poll(). In my testing
         I have observed that poll() can sometimes block forever unless the device is started explicitly with snd_pcm_start()
         or some data is written with snd_pcm_writei().
@@ -34520,7 +34520,7 @@ static ma_result ma_device_init_internal__coreaudio(ma_context* pContext, ma_dev
             #endif
         }
 
-        
+
         status = ((ma_AudioUnitSetProperty_proc)pContext->coreaudio.AudioUnitSetProperty)(pData->audioUnit, kAudioUnitProperty_StreamFormat, formatScope, formatElement, &bestFormat, sizeof(bestFormat));
         if (status != noErr) {
             ((ma_AudioComponentInstanceDispose_proc)pContext->coreaudio.AudioComponentInstanceDispose)(pData->audioUnit);
@@ -38526,7 +38526,7 @@ static ma_result ma_device_reinit__aaudio(ma_device* pDevice, ma_device_type dev
                 ma_device_stop(pDevice);    /* Do a full device stop so we set internal state correctly. */
             }
         }
-        
+
         result = MA_SUCCESS;
     }
 done: