Medium 1 - tensor and math operations

csrc/tensor.cpp

@@ -45,14 +45,14 @@ extern "C" {
         }
         printf("]\n");
 
-        printf("Data:\n[");
+        /*printf("Data:\n[");
         for (int i = 0; i < stride; i++) {
             printf("%.2f", tensor->data[i]);
             if (i < stride - 1) {
                 printf(", ");
             }
         }
-        printf("]\n\n\n");
+        printf("]\n\n\n");*/
         
         return tensor;
     }
@@ -81,24 +81,24 @@ extern "C" {
         }
 
         printf("Size: %d\n", tensor1->size);
-        printf("Data: [");
+        /*printf("Data: [");
         for (int i = 0; i < tensor1->size; i++) {
             printf("%.2f", tensor1->data[i]);
             if (i < tensor1->size - 1) {
                 printf(", ");
             }
         }
-        printf("]\n");
+        printf("]\n");*/
 
         printf("Size: %d\n", tensor2->size);
-        printf("Data: [");
+        /*printf("Data: [");
         for (int i = 0; i < tensor2->size; i++) {
             printf("%.2f", tensor2->data[i]);
             if (i < tensor2->size - 1) {
                 printf(", ");
             }
         }
-        printf("]\n");
+        printf("]\n");*/
 
         printf("Shapes : [");
         for (int i = 0; i < tensor1->ndim; i++) {

csrc/tensor.h

@@ -17,6 +17,7 @@ extern "C" {
     Tensor* sub_tensor(Tensor* tensor1, Tensor* tensor2);
     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);
 }
 
 #endif /* TENSOR_H */

norch/tensor.py

@@ -177,21 +177,64 @@ class Tensor:
 
         return result_data
 
+
+def matrix_sum(matrix1, matrix2):
+    # Check if the matrices can be multiplied
+    if len(matrix1[0]) != len(matrix2):
+        raise ValueError("Matrices cannot be multiplied. Inner dimensions must match.")
+
+    # Initialize the result matrix with zeros
+    result = [[0 for _ in range(len(matrix2[0]))] for _ in range(len(matrix1))]
+
+    # Perform matrix multiplication
+    for i in range(len(matrix1)):
+        for j in range(len(matrix2[0])):
+            result[i][j] += matrix1[i][i] + matrix2[i][j]
+
+    return result
+
+
 if __name__ == "__main__":
     from tensor import Tensor
     import time
+    import random
+    import numpy as np
 
-    ini = time.time()
-    a = Tensor([[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]],[[13, 14, 15], [16, 17, 18], [19, 20, 21], [22, 23, 24]]])
-    print(a)
-    b = a.reshape([4, 3, 2])
+    
+    #a = Tensor([[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]],[[13, 14, 15], [16, 17, 18], [19, 20, 21], [22, 23, 24]]])
+    #print(a)
+    N = 1000
+    a = Tensor([[random.uniform(0, 1) for _ in range(N)] for _ in range(N)])
+    b = Tensor([[random.uniform(0, 1) for _ in range(N)] for _ in range(N)])
     #b = Tensor([[1, 2, 3], [1, 2, 3], [1, 2, 3]])
     #a = Tensor([[[[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]], [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]], [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]], [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]]]])
     #b = Tensor([[[[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]], [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]], [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]], [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]]]])
-    #c = a @ b
+    ini = time.time()
+    c = a + b
 
-    print("\n###########", b)
+    print("\n#####2######")
     
     fim = time.time()
 
-    print(fim-ini)
+    print(fim-ini)
+
+    print("\n\n")
+
+    
+    a = [[random.uniform(0, 1) for _ in range(N)] for _ in range(N)]
+    b = [[random.uniform(0, 1) for _ in range(N)] for _ in range(N)]
+    ini = time.time()
+    result_matrix = matrix_sum(a, b)
+    fim = time.time()
+    print(fim-ini)
+
+
+    print("\n\n")
+
+    ini = time.time()
+    a = np.random.rand(N, N)
+    b = np.random.rand(N, N)
+    result_matrix = a + b
+    fim = time.time()
+    print(fim-ini)
+