only warn once

tinygrad/tensor.py

@@ -6,15 +6,18 @@ import numpy as np
 # **** start with two base classes ****
 
 class Tensor:
+  did_float_warning = False
+
   def __init__(self, data):
     if isinstance(data, list):
       data = np.array(data, dtype=np.float32)
     elif not isinstance(data, np.ndarray):
       raise TypeError("Error constructing tensor with %r" % data)
 
-    if data.dtype != np.float32:
+    if data.dtype != np.float32 and not Tensor.did_float_warning:
       # warning? float64 is actually needed for numerical jacobian
       print("warning, %r isn't float32" % (data.shape,))
+      Tensor.did_float_warning = True
 
     self.data = data
     self.grad = None