From 82c5247a20f07592ec1fd6ca1cdae6f23f1d6874 Mon Sep 17 00:00:00 2001 From: xaedes Date: Tue, 29 Aug 2023 20:59:31 +0200 Subject: [PATCH] add ggml API functions ggml_unravel_index, ggml_get_i32_nd and its analogs for set and for f32 ggml_get_i32_1d, ggml_set_i32_1d, ggml_get_f32_1d, ggml_set_f32_1d now support non-contiguous tensors. in case of non-contiguous tensor, the 1d index is unraveled into a multi index using ggml_unravel_index to be passed to '_nd' function equivalent. this fixes a bug in test-grad0 which happens due to ggml_build_backward not building purely contiguous tensors anymore --- ggml.c | 171 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ ggml.h | 9 +++ 2 files changed, 180 insertions(+) diff --git a/ggml.c b/ggml.c index c584ff2de..76f0b7b94 100644 --- a/ggml.c +++ b/ggml.c @@ -4838,7 +4838,37 @@ struct ggml_tensor * ggml_set_f32(struct ggml_tensor * tensor, float value) { return tensor; } +void ggml_unravel_index(const struct ggml_tensor * tensor, int64_t i, int64_t * i0, int64_t * i1, int64_t * i2, int64_t * i3) { + const int64_t ne3 = tensor->ne[3]; + const int64_t ne2 = tensor->ne[2]; + const int64_t ne1 = tensor->ne[1]; + const int64_t ne0 = tensor->ne[0]; + + const int64_t i3_ = (i/(ne2*ne1*ne0)); + const int64_t i2_ = (i - i3_*ne2*ne1*ne0)/(ne1*ne0); + const int64_t i1_ = (i - i3_*ne2*ne1*ne0 - i2_*ne1*ne0)/ne0; + const int64_t i0_ = (i - i3_*ne2*ne1*ne0 - i2_*ne1*ne0 - i1_*ne0); + + if (i0) { + * i0 = i0_; + } + if (i1) { + * i1 = i1_; + } + if (i2) { + * i2 = i2_; + } + if (i3) { + * i3 = i3_; + } +} + int32_t ggml_get_i32_1d(const struct ggml_tensor * tensor, int i) { + if (!ggml_is_contiguous(tensor)) { + int64_t id[4] = { 0, 0, 0, 0 }; + ggml_unravel_index(tensor, i, &id[0], &id[1], &id[2], &id[3]); + return ggml_get_i32_nd(tensor, id[0], id[1], id[2], id[3]); + } switch (tensor->type) { case GGML_TYPE_I8: { @@ -4875,6 +4905,12 @@ 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) { + if (!ggml_is_contiguous(tensor)) { + int64_t id[4] = { 0, 0, 0, 0 }; + ggml_unravel_index(tensor, i, &id[0], &id[1], &id[2], &id[3]); + ggml_set_i32_nd(tensor, id[0], id[1], id[2], id[3], value); + return; + } switch (tensor->type) { case GGML_TYPE_I8: { @@ -4908,7 +4944,74 @@ void ggml_set_i32_1d(const struct ggml_tensor * tensor, int i, int32_t value) { } } +int32_t ggml_get_i32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, int i3) { + void * data = (char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1] + i2*tensor->nb[2] + i3*tensor->nb[3]; + switch (tensor->type) { + case GGML_TYPE_I8: + { + return ((int8_t *) data)[0]; + } break; + case GGML_TYPE_I16: + { + return ((int16_t *) data)[0]; + } break; + case GGML_TYPE_I32: + { + return ((int32_t *) data)[0]; + } break; + case GGML_TYPE_F16: + { + return GGML_FP16_TO_FP32(((ggml_fp16_t *) data)[0]); + } break; + case GGML_TYPE_F32: + { + return ((float *) data)[0]; + } break; + default: + { + GGML_ASSERT(false); + } break; + } + + return 0.0f; +} + +void ggml_set_i32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, int i3, int32_t value) { + void * data = (char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1] + i2*tensor->nb[2] + i3*tensor->nb[3]; + switch (tensor->type) { + case GGML_TYPE_I8: + { + ((int8_t *)(data))[0] = value; + } break; + case GGML_TYPE_I16: + { + ((int16_t *)(data))[0] = value; + } break; + case GGML_TYPE_I32: + { + ((int32_t *)(data))[0] = value; + } break; + case GGML_TYPE_F16: + { + ((ggml_fp16_t *)(data))[0] = GGML_FP32_TO_FP16(value); + } break; + case GGML_TYPE_F32: + { + ((float *)(data))[0] = value; + } break; + default: + { + GGML_ASSERT(false); + } break; + } +} + float ggml_get_f32_1d(const struct ggml_tensor * tensor, int i) { + if (!ggml_is_contiguous(tensor)) { + int64_t id[4] = { 0, 0, 0, 0 }; + ggml_unravel_index(tensor, i, &id[0], &id[1], &id[2], &id[3]); + return ggml_get_f32_nd(tensor, id[0], id[1], id[2], id[3]); + } switch (tensor->type) { case GGML_TYPE_I8: { @@ -4945,6 +5048,12 @@ 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) { + if (!ggml_is_contiguous(tensor)) { + int64_t id[4] = { 0, 0, 0, 0 }; + ggml_unravel_index(tensor, i, &id[0], &id[1], &id[2], &id[3]); + ggml_set_f32_nd(tensor, id[0], id[1], id[2], id[3], value); + return; + } switch (tensor->type) { case GGML_TYPE_I8: { @@ -4978,6 +5087,68 @@ void ggml_set_f32_1d(const struct ggml_tensor * tensor, int i, float value) { } } +float ggml_get_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, int i3) { + void * data = (char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1] + i2*tensor->nb[2] + i3*tensor->nb[3]; + switch (tensor->type) { + case GGML_TYPE_I8: + { + return ((int8_t *) data)[0]; + } break; + case GGML_TYPE_I16: + { + return ((int16_t *) data)[0]; + } break; + case GGML_TYPE_I32: + { + return ((int32_t *) data)[0]; + } break; + case GGML_TYPE_F16: + { + return GGML_FP16_TO_FP32(((ggml_fp16_t *) data)[0]); + } break; + case GGML_TYPE_F32: + { + return ((float *) data)[0]; + } break; + default: + { + GGML_ASSERT(false); + } break; + } + + return 0.0f; +} + +void ggml_set_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, int i3, float value) { + void * data = (char *) tensor->data + i0*tensor->nb[0] + i1*tensor->nb[1] + i2*tensor->nb[2] + i3*tensor->nb[3]; + switch (tensor->type) { + case GGML_TYPE_I8: + { + ((int8_t *)(data))[0] = value; + } break; + case GGML_TYPE_I16: + { + ((int16_t *)(data))[0] = value; + } break; + case GGML_TYPE_I32: + { + ((int32_t *)(data))[0] = value; + } break; + case GGML_TYPE_F16: + { + ((ggml_fp16_t *)(data))[0] = GGML_FP32_TO_FP16(value); + } break; + case GGML_TYPE_F32: + { + ((float *)(data))[0] = value; + } break; + default: + { + GGML_ASSERT(false); + } break; + } +} + void * ggml_get_data(const struct ggml_tensor * tensor) { return tensor->data; } diff --git a/ggml.h b/ggml.h index 25f951f26..5d63dc0c3 100644 --- a/ggml.h +++ b/ggml.h @@ -671,12 +671,21 @@ extern "C" { GGML_API struct ggml_tensor * ggml_set_i32 (struct ggml_tensor * tensor, int32_t value); GGML_API struct ggml_tensor * ggml_set_f32 (struct ggml_tensor * tensor, float value); + // Converts a flat index into coordinates + GGML_API void ggml_unravel_index(const struct ggml_tensor * tensor, int64_t i, int64_t * i0, int64_t * i1, int64_t * i2, int64_t * i3); + GGML_API int32_t ggml_get_i32_1d(const struct ggml_tensor * tensor, int i); GGML_API void ggml_set_i32_1d(const struct ggml_tensor * tensor, int i, int32_t value); + GGML_API int32_t ggml_get_i32_nd(const struct ggml_tensor * tensor, int i1, int i2, int i3); + GGML_API void ggml_set_i32_nd(const struct ggml_tensor * tensor, int i1, int i2, int i3, int32_t value); + GGML_API float ggml_get_f32_1d(const struct ggml_tensor * tensor, int i); GGML_API void ggml_set_f32_1d(const struct ggml_tensor * tensor, int i, float value); + GGML_API float ggml_get_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, int i3); + GGML_API void ggml_set_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2, int i3, float value); + GGML_API void * ggml_get_data (const struct ggml_tensor * tensor); GGML_API float * ggml_get_data_f32(const struct ggml_tensor * tensor);