ADD: add tensor creation helpers

ucb-bar · Oct 15, 2024 · 9b25b5f · 9b25b5f
1 parent 67a6f15
commit 9b25b5f
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diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -89,6 +89,7 @@ target_link_options(target-riscv INTERFACE -T ${LINKER_SCRIPT})
 
 set(cpu_impl 
   ./src/print.c
+  ./src/cpu/creation.c
   ./src/cpu/add.c
   ./src/cpu/addmm.c
   ./src/cpu/addscalar.c

diff --git a/src/cpu/creation.c b/src/cpu/creation.c
@@ -0,0 +1,241 @@
+#include "nn.h"
+
+__attribute__((weak)) Tensor0D_F16 *nn_tensor0d_f16(float16_t data) {
+  Tensor0D_F16 *tensor = (Tensor0D_F16 *)malloc(sizeof(Tensor0D_F16));
+  tensor->data = data;
+}
+
+__attribute__((weak)) Tensor0D_F32 *nn_tensor0d_f32(float data) {
+  Tensor0D_F32 *tensor = (Tensor0D_F32 *)malloc(sizeof(Tensor0D_F32));
+  tensor->data = data;
+}
+
+__attribute__((weak)) Tensor1D_F16 *nn_tensor1d_f16(size_t shape[1], const float16_t *data) {
+  Tensor1D_F16 *tensor = (Tensor1D_F16 *)malloc(sizeof(Tensor1D_F16));
+  tensor->shape[0] = shape[0];
+
+  size_t n_bytes = shape[0] * sizeof(float16_t);
+  tensor->data = (float16_t *)malloc(n_bytes);
+  if (data != NULL) {
+    memcpy(tensor->data, data, n_bytes);
+  }
+}
+
+__attribute__((weak)) Tensor1D_F32 *nn_tensor1d_f32(size_t shape[1], const float *data) {
+  Tensor1D_F32 *tensor = (Tensor1D_F32 *)malloc(sizeof(Tensor1D_F32));
+  tensor->shape[0] = shape[0];
+
+  size_t n_bytes = shape[0] * sizeof(float);
+  tensor->data = (float *)malloc(n_bytes);
+  if (data != NULL) {
+    memcpy(tensor->data, data, n_bytes);
+  }
+}
+
+__attribute__((weak)) Tensor2D_F16 *nn_tensor2d_f16(size_t shape[2], const float16_t *data) {
+  Tensor2D_F16 *tensor = (Tensor2D_F16 *)malloc(sizeof(Tensor2D_F16));
+  tensor->shape[0] = shape[0];
+  tensor->shape[1] = shape[1];
+
+  size_t n_bytes = shape[0] * shape[1] * sizeof(float16_t);
+  tensor->data = (float16_t *)malloc(n_bytes);
+  if (data != NULL) {
+    memcpy(tensor->data, data, n_bytes);
+  }
+}
+
+__attribute__((weak)) Tensor2D_F32 *nn_tensor2d_f32(size_t shape[2], const float *data) {
+  Tensor2D_F32 *tensor = (Tensor2D_F32 *)malloc(sizeof(Tensor2D_F32));
+  tensor->shape[0] = shape[0];
+  tensor->shape[1] = shape[1];
+
+  size_t n_bytes = shape[0] * shape[1] * sizeof(float);
+  tensor->data = (float *)malloc(n_bytes);
+  if (data != NULL) {
+    memcpy(tensor->data, data, n_bytes);
+  }
+}
+
+__attribute__((weak)) Tensor0D_F16 *nn_zeros0d_f16() {
+  Tensor0D_F16 *tensor = nn_tensor0d_f16(0);
+  return tensor;
+}
+
+__attribute__((weak)) Tensor0D_F32 *nn_zeros0d_f32() {
+  Tensor0D_F32 *tensor = nn_tensor0d_f32(0);
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F16 *nn_zeros1d_f16(size_t shape[1]) {
+  Tensor1D_F16 *tensor = nn_tensor1d_f16(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 0;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F32 *nn_zeros1d_f32(size_t shape[1]) {
+  Tensor1D_F32 *tensor = nn_tensor1d_f32(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 0;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F16 *nn_zeros2d_f16(size_t shape[2]) {
+  Tensor2D_F16 *tensor = nn_tensor2d_f16(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 0;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F32 *nn_zeros2d_f32(size_t shape[2]) {
+  Tensor2D_F32 *tensor = nn_tensor2d_f32(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 0;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor0D_F16 *nn_ones0d_f16() {
+  Tensor0D_F16 *tensor = nn_tensor0d_f16(1);
+  return tensor;
+}
+
+__attribute__((weak)) Tensor0D_F32 *nn_ones0d_f32() {
+  Tensor0D_F32 *tensor = nn_tensor0d_f32(1);
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F16 *nn_ones1d_f16(size_t shape[1]) {
+  Tensor1D_F16 *tensor = nn_tensor1d_f16(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 1;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F32 *nn_ones1d_f32(size_t shape[1]) {
+  Tensor1D_F32 *tensor = nn_tensor1d_f32(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 1;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F16 *nn_ones2d_f16(size_t shape[2]) {
+  Tensor2D_F16 *tensor = nn_tensor2d_f16(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 1;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F32 *nn_ones2d_f32(size_t shape[2]) {
+  Tensor2D_F32 *tensor = nn_tensor2d_f32(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = 1;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor0D_F16 *nn_full0d_f16(float16_t data) {
+  Tensor0D_F16 *tensor = nn_tensor0d_f16(data);
+  return tensor;
+}
+
+__attribute__((weak)) Tensor0D_F32 *nn_full0d_f32(float data) {
+  Tensor0D_F32 *tensor = nn_tensor0d_f32(data);
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F16 *nn_full1d_f16(size_t shape[1], float16_t data) {
+  Tensor1D_F16 *tensor = nn_tensor1d_f16(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = data;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F32 *nn_full1d_f32(size_t shape[1], float data) {
+  Tensor1D_F32 *tensor = nn_tensor1d_f32(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = data;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F16 *nn_full2d_f16(size_t shape[2], float16_t data) {
+  Tensor2D_F16 *tensor = nn_tensor2d_f16(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = data;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F32 *nn_full2d_f32(size_t shape[2], float data) {
+  Tensor2D_F32 *tensor = nn_tensor2d_f32(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = data;
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor0D_F16 *nn_rand0d_f16() {
+  Tensor0D_F16 *tensor = nn_tensor0d_f16(as_f16(rand()));
+  return tensor;
+}
+
+__attribute__((weak)) Tensor0D_F32 *nn_rand0d_f32() {
+  Tensor0D_F32 *tensor = nn_tensor0d_f32(rand());
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F16 *nn_rand1d_f16(size_t shape[1]) {
+  Tensor1D_F16 *tensor = nn_tensor1d_f16(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = as_f16(rand());
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor1D_F32 *nn_rand1d_f32(size_t shape[1]) {
+  Tensor1D_F32 *tensor = nn_tensor1d_f32(shape, NULL);
+  size_t n = shape[0];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = rand();
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F16 *nn_rand2d_f16(size_t shape[2]) {
+  Tensor2D_F16 *tensor = nn_tensor2d_f16(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = as_f16(rand());
+  }
+  return tensor;
+}
+
+__attribute__((weak)) Tensor2D_F32 *nn_rand2d_f32(size_t shape[2]) {
+  Tensor2D_F32 *tensor = nn_tensor2d_f32(shape, NULL);
+  size_t n = shape[0] * shape[1];
+  for (size_t i = 0; i < n; i += 1) {
+    tensor->data[i] = rand();
+  }
+  return tensor;
+}