Tinygrad-quesitons-part1

questions/1_matrix-vector-dot-product/tinygrad/solution.py

@@ -1,13 +1,11 @@
 from tinygrad.tensor import Tensor
 
-def matrix_dot_vector_tg(a, b) -> Tensor:
+def matrix_dot_vector_tg(a: Tensor, b: Tensor) -> Tensor:
     """
     Compute the product of matrix `a` and vector `b` using tinygrad.
-    Inputs can be Python lists, NumPy arrays, or tinygrad Tensors.
+    Inputs will be tinygrad Tensors.
     Returns a 1-D Tensor of length m, or Tensor(-1) if dimensions mismatch.
     """
     if len(a[0]) != len(b):
         return Tensor(-1)
-    a_t = Tensor(a)
-    b_t = Tensor(b)
-    return a_t.matmul(b_t)
+    return a @ b

questions/1_matrix-vector-dot-product/tinygrad/starter_code.py

@@ -1,16 +1,9 @@
 from tinygrad.tensor import Tensor
 
-def matrix_dot_vector_tg(a, b) -> Tensor:
+def matrix_dot_vector_tg(a:Tensor, b:Tensor) -> Tensor:
     """
     Compute the product of matrix `a` and vector `b` using tinygrad.
-    Inputs can be Python lists, NumPy arrays, or tinygrad Tensors.
+    Will be tinygrad Tensors.
     Returns a 1-D Tensor of length m, or Tensor(-1) if dimensions mismatch.
     """
-    # Dimension mismatch check
-    if len(a[0]) != len(b):
-        return Tensor(-1)
-    # Convert to Tensor
-    a_t = Tensor(a)
-    b_t = Tensor(b)
-    # Your implementation here
     pass

questions/1_matrix-vector-dot-product/tinygrad/tests.json

@@ -1,10 +1,14 @@
 [
   {
-    "test": "from tinygrad.tensor import Tensor\nres = matrix_dot_vector_tg(\n    [[1,2,3],[2,4,5],[6,8,9]],\n    [1,2,3]\n)\nprint(res.numpy().tolist())",
+    "test": "from tinygrad.tensor import Tensor\nres = matrix_dot_vector_tg(\n    Tensor([[1,2,3],[2,4,5],[6,8,9]]),\n    Tensor([1,2,3])\n)\nprint(res.numpy().tolist())",
     "expected_output": "[14.0, 25.0, 49.0]"
   },
   {
-    "test": "from tinygrad.tensor import Tensor\nres = matrix_dot_vector_tg(\n    [[1,2,3],[2,4,5]],\n    [1,2]\n)\nprint(res.numpy().tolist())",
+    "test": "from tinygrad.tensor import Tensor\nres = matrix_dot_vector_tg(\n    Tensor([[1,2,3],[2,4,5]]),\n    Tensor([1,2])\n)\nprint(res.numpy().tolist())",
     "expected_output": "-1"
+  },
+  {
+    "test": "from tinygrad.tensor import Tensor\nres = matrix_dot_vector_tg(\n    Tensor([[1, 2], [2, 4]]),\n    Tensor([1, 2])\n)\nprint(res.numpy().tolist())",
+    "expected_output": "[5, 10]"
   }
 ]

questions/2_transpose-of-a-matrix/tinygrad/solution.py

@@ -3,8 +3,7 @@
 def transpose_matrix_tg(a) -> Tensor:
     """
     Transpose a 2D matrix `a` using tinygrad.
-    Inputs can be Python lists, NumPy arrays, or tinygrad Tensors.
+    Inputs are tinygrad Tensors.
     Returns a transposed Tensor.
     """
-    a_t = Tensor(a)
-    return a_t.transpose(0,1)
+    return a.T

questions/2_transpose-of-a-matrix/tinygrad/starter_code.py

@@ -1,12 +1,9 @@
 from tinygrad.tensor import Tensor
 
-def transpose_matrix_tg(a) -> Tensor:
+def transpose_matrix_tg(a:Tensor) -> Tensor:
     """
     Transpose a 2D matrix `a` using tinygrad.
-    Inputs can be Python lists, NumPy arrays, or tinygrad Tensors.
+    Inputs are tinygrad Tensors.
     Returns a transposed Tensor.
     """
-    # Convert to Tensor
-    a_t = Tensor(a)
-    # Your implementation here
     pass

questions/2_transpose-of-a-matrix/tinygrad/tests.json

@@ -1,10 +1,10 @@
 [
   {
-    "test": "from tinygrad.tensor import Tensor\nres = transpose_matrix_tg([[1,2,3],[4,5,6]])\nprint(res.numpy().tolist())",
+    "test": "from tinygrad.tensor import Tensor\nres = transpose_matrix_tg(Tensor([[1,2,3],[4,5,6]]))\nprint(res.numpy().tolist())",
     "expected_output": "[[1, 4], [2, 5], [3, 6]]"
   },
   {
-    "test": "from tinygrad.tensor import Tensor\nres = transpose_matrix_tg([[1,2],[3,4]])\nprint(res.numpy().tolist())",
+    "test": "from tinygrad.tensor import Tensor\nres = transpose_matrix_tg(Tensor([[1,2],[3,4]]))\nprint(res.numpy().tolist())",
     "expected_output": "[[1, 3], [2, 4]]"
   }
 ]

questions/3_reshape-matrix/tinygrad/solution.py

@@ -3,11 +3,10 @@
 def reshape_matrix_tg(a, new_shape) -> Tensor:
     """
     Reshape a 2D matrix `a` to shape `new_shape` using tinygrad.
-    Inputs can be Python lists, NumPy arrays, or tinygrad Tensors.
+    Inputs are tinygrad Tensors.
     Returns a Tensor of shape `new_shape`, or an empty Tensor on mismatch.
     """
     # Dimension check
     if len(a) * len(a[0]) != new_shape[0] * new_shape[1]:
         return Tensor([])
-    a_t = Tensor(a)
-    return a_t.reshape(new_shape)
+    return a.reshape(new_shape)

questions/3_reshape-matrix/tinygrad/starter_code.py

@@ -1,15 +1,9 @@
 from tinygrad.tensor import Tensor
 
-def reshape_matrix_tg(a, new_shape) -> Tensor:
+def reshape_matrix_tg(a:Tensor, new_shape:tuple) -> Tensor:
     """
     Reshape a 2D matrix `a` to shape `new_shape` using tinygrad.
-    Inputs can be Python lists, NumPy arrays, or tinygrad Tensors.
+    Inputs are tinygrad Tensors.
     Returns a Tensor of shape `new_shape`, or an empty Tensor on mismatch.
     """
-    # Dimension check
-    if len(a) * len(a[0]) != new_shape[0] * new_shape[1]:
-        return Tensor([])
-    # Convert to Tensor and reshape
-    a_t = Tensor(a)
-    # Your implementation here
     pass

questions/3_reshape-matrix/tinygrad/tests.json

@@ -1,10 +1,10 @@
 [
   {
-    "test": "from tinygrad.tensor import Tensor\nres = reshape_matrix_tg(\n    [[1,2,3],[4,5,6]],\n    (3, 2)\n)\nprint(res.numpy().tolist())",
+    "test": "from tinygrad.tensor import Tensor\nres = reshape_matrix_tg(\n    Tensor([[1,2,3],[4,5,6]]),\n    (3, 2)\n)\nprint(res.numpy().tolist())",
     "expected_output": "[[1, 2], [3, 4], [5, 6]]"
   },
   {
-    "test": "from tinygrad.tensor import Tensor\nres = reshape_matrix_tg(\n    [[1,2],[3,4]],\n    (3, 2)\n)\nprint(res.numpy().tolist())",
+    "test": "from tinygrad.tensor import Tensor\nres = reshape_matrix_tg(\n    Tensor([[1,2],[3,4]]),\n    (3, 2)\n)\nprint(res.numpy().tolist())",
     "expected_output": "[]"
   }
 ]