diff --git a/test/test_gc.py b/test/test_gc.py
index f857e0d107..49773dd98a 100644
--- a/test/test_gc.py
+++ b/test/test_gc.py
@@ -1,6 +1,7 @@
 #!/usr/bin/env python
 import gc
 import unittest
+import numpy as np
 from tinygrad.tensor import Tensor
 
 def tensors_allocated():
@@ -17,14 +18,14 @@ class TestGC(unittest.TestCase):
     assert(tensors_allocated() == 0)
 
   def test_gc_complex(self):
-    a = Tensor.zeros(4, 4, requires_grad=True)
-    b = Tensor.zeros(4, 4, requires_grad=True)
+    a = Tensor(np.zeros((4, 4), dtype=np.float32), requires_grad=True)
+    b = Tensor(np.zeros((4, 4), dtype=np.float32), requires_grad=True)
     assert(tensors_allocated() == 2)
     (a*b).mean().backward()
     assert(tensors_allocated() == 4)
     del b
     assert(tensors_allocated() == 2)
-    b = Tensor.zeros(4, 4, requires_grad=True)
+    b = Tensor(np.zeros((4, 4), dtype=np.float32), requires_grad=True)
     print(tensors_allocated())
     (a*b).mean().backward()
     print(tensors_allocated())
diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index f40d9a3fac..40afd6febe 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -126,7 +126,7 @@ class Tensor:
   def empty(cls, *shape, **kwargs): return cls.zeros(*shape, **kwargs)
 
   @classmethod
-  def eye(cls, dim, **kwargs): return cls(np.eye(dim, dtype=np.float32), **kwargs)
+  def eye(cls, dim, **kwargs): return cls([1], **kwargs).slice(((0,dim+1),)).reshape(1, dim+1).expand(dim, dim+1).reshape(dim*(dim+1)).slice(((0,dim*dim),)).reshape(dim, dim)
 
   # TODO: requires cumsum to remove numpy
   @classmethod
@@ -222,7 +222,7 @@ class Tensor:
         new_shape.append(1 if s is None else slcfix(s.stop, sz, sz) - slcfix(s.start, sz, 0))
     new_shape += [self.shape[i] for i in range(len(new_slice), len(self.shape))]
     new_slice += [(0,self.shape[i]) for i in range(len(new_slice), len(self.shape))]
-    return self.slice(arg = new_slice).reshape(new_shape if len(new_shape) else (1,))
+    return self.slice(new_slice).reshape(new_shape if len(new_shape) else (1,))
 
   def cat(self, *args, dim=0):
     dim = (dim + len(self.shape)) if dim < 0 else dim
@@ -233,21 +233,21 @@ class Tensor:
     slc = [[(0, s) for s in self.shape] for _ in catargs]
     for s,k in zip(slc, shape_cumsum):
       s[dim] = (-k, shape_cumsum[-1]-k)
-    return functools.reduce(Tensor.__add__, [arg.slice(arg=s) for arg,s in zip(catargs, slc)])
+    return functools.reduce(Tensor.__add__, [arg.slice(s) for arg,s in zip(catargs, slc)])
 
   # TODO: make this nicer with syntactic sugar in slice
   def chunk(self, num, dim):
     slice_params = [[(0, s) for s in self.shape] for _ in range(num)]
     for i,k in enumerate(range(0, self.shape[dim], self.shape[dim]//num)):
       slice_params[i][dim] = (k, min(self.shape[dim], k+self.shape[dim]//num))
-    return [self.slice(arg=p) for p in slice_params]
+    return [self.slice(p) for p in slice_params]
 
   def unsqueeze(self, dim):
     if dim < 0: dim = len(self.shape) + dim + 1
     return self.reshape(self.shape[:dim] + (1,) + self.shape[dim:])
 
   # (padding_left, padding_right, padding_top, padding_bottom)
-  def pad2d(self, padding:Tuple[int, ...]): return self.slice(arg = [(0,self.shape[0]), (0,self.shape[1]), (-padding[2],self.shape[2]+padding[3]), (-padding[0],self.shape[3]+padding[1])])
+  def pad2d(self, padding:Tuple[int, ...]): return self.slice(((0,self.shape[0]), (0,self.shape[1]), (-padding[2],self.shape[2]+padding[3]), (-padding[0],self.shape[3]+padding[1])))
   # TODO: this is totally not transpose
   def transpose(self, order=(1,0)): return self.permute(order=order)
   def flatten(self, start_dim=0): return self.reshape(shape=tuple(list(self.shape[0:start_dim]) + [-1]))