win more lines for core library (#158)

...and sacrifice test speed

test/test_gc.py

@@ -1,32 +1,37 @@
 #!/usr/bin/env python
+import gc
 import unittest
 from tinygrad.tensor import Tensor, GPU
 
+def tensors_allocated():
+    return sum([isinstance(x, Tensor) for x in gc.get_objects()])
+    
 class TestGC(unittest.TestCase):
   gpu = False
+
   def test_gc(self):
     a = Tensor.zeros(4,4, gpu=self.gpu)
     b = Tensor.zeros(4,4, gpu=self.gpu)
     (a*b).mean().backward()
-    assert(Tensor.allocated > 0)
+    assert(tensors_allocated() > 0)
     del a,b
-    assert(Tensor.allocated == 0)
+    assert(tensors_allocated() == 0)
 
   def test_gc_complex(self):
     a = Tensor.zeros(4,4, gpu=self.gpu)
     b = Tensor.zeros(4,4, gpu=self.gpu)
-    assert(Tensor.allocated == 2)
+    assert(tensors_allocated() == 2)
     (a*b).mean().backward()
-    assert(Tensor.allocated == 4)
+    assert(tensors_allocated() == 4)
     del b
-    assert(Tensor.allocated == 2)
+    assert(tensors_allocated() == 2)
     b = Tensor.zeros(4,4, gpu=self.gpu)
-    print(Tensor.allocated)
+    print(tensors_allocated())
     (a*b).mean().backward()
-    print(Tensor.allocated)
-    assert(Tensor.allocated == 4)
+    print(tensors_allocated())
+    assert(tensors_allocated() == 4)
     del b
-    assert(Tensor.allocated == 2)
+    assert(tensors_allocated() == 2)
 
     
 

tinygrad/tensor.py

@@ -55,7 +55,6 @@ class GPUBuffer:
 class Tensor:
   did_float_warning = False
   default_gpu = False
-  allocated = 0
   ops_cpu, ops_gpu = {}, {}
 
   def __init__(self, data, gpu=None, requires_grad=True):
@@ -85,12 +84,6 @@ class Tensor:
     # internal variables used for autograd graph construction
     self._ctx = None
 
-    Tensor.allocated += 1
-
-  def __del__(self):
-    #print("cleanup", self.shape)
-    Tensor.allocated -= 1
-
   def __repr__(self):
     return f"Tensor {self.data!r} with grad {(self.grad.data if self.grad else None)!r}"