Fix pow create another vector

csrc/cpu.cpp

@@ -25,9 +25,9 @@ void elementwise_mul_tensor_cpu(Tensor* tensor1, Tensor* tensor2, float* result_
     }
 }
 
-void pow_tensor_cpu(Tensor* tensor, float power) {
+void pow_tensor_cpu(Tensor* tensor, float power, float* result_data) {
     
     for (int i = 0; i < tensor->size; i++) {
-        tensor->data[i] = powf(tensor->data[i], power);
+        result_data[i] = powf(tensor->data[i], power);
     }
 }

csrc/cpu.h

@@ -2,4 +2,4 @@ void add_tensor_cpu(Tensor* tensor1, Tensor* tensor2, float* result_data);
 void sub_tensor_cpu(Tensor* tensor1, Tensor* tensor2, float* result_data);
 void elementwise_mul_tensor_cpu(Tensor* tensor1, Tensor* tensor2, float* result_data);
 
-void pow_tensor_cpu(Tensor* tensor, float power);
+void pow_tensor_cpu(Tensor* tensor, float power, float* result_data);

csrc/cuda.cu

@@ -97,17 +97,17 @@ __host__ void elementwise_mul_tensor_cuda(Tensor* tensor1, Tensor* tensor2, floa
     cudaDeviceSynchronize();
 }
 
-__global__ void pow_tensor_cuda_kernel(float* data, float power, int size) {
+__global__ void pow_tensor_cuda_kernel(float* data, float power, float* result_data, int size) {
     int i = blockIdx.x * blockDim.x + threadIdx.x;
     if (i < size) {
-        data[i] = powf(data[i], power);
+        result_data[i] = powf(data[i], power);
     }
 }
 
-__host__ void pow_tensor_cuda(Tensor* tensor, float power) {
+__host__ void pow_tensor_cuda(Tensor* tensor, float power, float* result_data) {
     
     int number_of_blocks = (tensor->size + THREADS_PER_BLOCK - 1) / THREADS_PER_BLOCK;
-    pow_tensor_cuda_kernel<<<number_of_blocks, THREADS_PER_BLOCK>>>(tensor->data, power, tensor->size);
+    pow_tensor_cuda_kernel<<<number_of_blocks, THREADS_PER_BLOCK>>>(tensor->data, power, result_data, tensor->size);
 
     cudaError_t error = cudaGetLastError();
     if (error != cudaSuccess) {

csrc/cuda.h

@@ -13,7 +13,7 @@
     __global__ void elementwise_mul_tensor_cuda_kernel(float* data1, float* data2, float* result_data, int size);
     __host__ void elementwise_mul_tensor_cuda(Tensor* tensor1, Tensor* tensor2, float* result_data);
 
-    __global__ void pow_tensor_cuda_kernel(float* data, float power, int size);
-    __host__ void pow_tensor_cuda(Tensor* tensor, float power);
+    __global__ void pow_tensor_cuda_kernel(float* data, float power, float* result_data, int size);
+    __host__ void pow_tensor_cuda(Tensor* tensor, float power, float* result_data);
 
 #endif /* CUDA_KERNEL_H_ */

csrc/tensor.cpp

@@ -304,12 +304,40 @@ extern "C" {
         return create_tensor(result_data, shape, ndim, device);
     }
 
-    void pow_tensor(Tensor* tensor, float power) {
+    Tensor* pow_tensor(Tensor* tensor, float power) {
+        char* device = (char*)malloc(strlen(tensor->device) + 1);
+        if (device != NULL) {
+            strcpy(device, tensor->device);
+        } else {
+            fprintf(stderr, "Memory allocation failed\n");
+            exit(-1);
+        }
+        int ndim = tensor->ndim;
+        int* shape = (int*)malloc(ndim * sizeof(int));
+        if (shape == NULL) {
+            fprintf(stderr, "Memory allocation failed\n");
+            exit(1);
+        }
+
+        for (int i = 0; i < ndim; i++) {
+            shape[i] = tensor->shape[i];
+        }
+
         if (strcmp(tensor->device, "cuda") == 0) {
-            pow_tensor_cuda(tensor, power);
+
+            float* result_data;
+            cudaMalloc((void **)&result_data, tensor->size * sizeof(float));
+            pow_tensor_cuda(tensor, power, result_data);
+            return create_tensor(result_data, shape, ndim, device);
         } 
         else {
-            pow_tensor_cpu(tensor, power);
+            float* result_data = (float*)malloc(tensor->size * sizeof(float));
+            if (result_data == NULL) {
+                fprintf(stderr, "Memory allocation failed\n");
+                exit(1);
+            }
+            pow_tensor_cpu(tensor, power, result_data);
+            return create_tensor(result_data, shape, ndim, device);
         }
     }
 

csrc/tensor.h

@@ -20,7 +20,7 @@ extern "C" {
     Tensor* elementwise_mul_tensor(Tensor* tensor1, Tensor* tensor2);
     void reshape_tensor(Tensor* tensor, int* new_shape, int new_ndim);
     Tensor* matmul_tensor(Tensor* tensor1, Tensor* tensor2);
-    void pow_tensor(Tensor* tensor, float power);
+    Tensor* pow_tensor(Tensor* tensor, float power);
     void to_device(Tensor* tensor, char* device);
 }
 

norch/tensor.py

@@ -204,8 +204,14 @@ class Tensor:
         power = ctypes.c_float(power)
 
         Tensor._C.pow_tensor.argtypes = [ctypes.POINTER(CTensor), ctypes.c_float]
-        Tensor._C.pow_tensor.restype = None
+        Tensor._C.pow_tensor.restype = ctypes.POINTER(CTensor)
 
-        Tensor._C.pow_tensor(self.tensor, power)
+        result_tensor_ptr = Tensor._C.pow_tensor(self.tensor, power)
 
-        return self
+        result_data = Tensor()
+        result_data.tensor = result_tensor_ptr
+        result_data.shape = self.shape.copy()
+        result_data.ndim = self.ndim
+        result_data.device = self.device
+
+        return result_data

test.py

@@ -28,7 +28,9 @@ if __name__ == "__main__":
     #c = Tensor([[1, 2, 3], [1, 2, 3], [1, 2, 3]])#.to("cuda")
 
     #d = b-c
-    print(a ** 2)
+
+    b = a ** 2
+    print(b)
     #print(a ** 2)
     
     """#print(a)