Revert "Fix constant folding for Tensor([3]) (#1227)" (#1274)

This reverts commit ab645317c9.

docs/abstractions.py

@@ -120,8 +120,7 @@ from tinygrad.tensor import Tensor
 from tinygrad.ops import LazyOp, BinaryOps, LoadOps
 
 # the 2+3 from before
-# added some 0s, otherwise Tensor([2]) will be folded into a constant without using LoadOps.FROM
-result = Tensor([2, 0]) + Tensor([3, 0])
+result = Tensor([2]) + Tensor([3])
 print(type(result.lazydata), result.lazydata)  # let's look at the lazydata of result
 
 # you'll see it has a LazyOp

test/test_tensor.py

@@ -1,8 +1,9 @@
+import dataclasses
 import numpy as np
 import torch
 import unittest
-from tinygrad.tensor import Tensor
-from tinygrad.ops import LoadOps, OpType
+import itertools
+from tinygrad.tensor import Tensor, Device
 from tinygrad.helpers import dtypes
 from extra.gradcheck import numerical_jacobian, jacobian, gradcheck
 
@@ -191,26 +192,5 @@ class TestTinygrad(unittest.TestCase):
     for _, dtype in dtypes.fields().items():
       assert dtype.itemsize == Tensor.randn(3, dtype=dtype).element_size(), f"Tensor.element_size() not matching Tensor.dtype.itemsize for {dtype}"
 
-  def test_constant_fold(self):
-    def helper_assert_all_const(op: OpType):
-      if isinstance(op.op, LoadOps): assert op.op == LoadOps.CONST
-      else:
-        for buf in op.buffers: helper_assert_all_const(buf.op)
-    helper_assert_all_const(Tensor(2).lazydata.op)
-    helper_assert_all_const(Tensor(2).reshape([1, 1, 1]).lazydata.op)
-    helper_assert_all_const(Tensor([2]).lazydata.op)
-    helper_assert_all_const(Tensor([2]).reshape([1, 1, 1]).lazydata.op)
-    helper_assert_all_const((Tensor(2)+Tensor(3)).lazydata.op)
-    helper_assert_all_const((Tensor(2)+Tensor([3])).lazydata.op)
-    helper_assert_all_const((Tensor([[2]])+Tensor([3])).lazydata.op)
-    with self.assertRaises(AssertionError):
-      helper_assert_all_const((Tensor([2, 0])+Tensor([3, 0])).lazydata.op)
-
-  def test_constant_fold_shape(self):
-    self.assertEqual(Tensor(3).shape, ())
-    self.assertEqual(Tensor([3]).shape, (1,))
-    self.assertEqual(Tensor([[3]]).shape, (1, 1))
-    self.assertEqual(Tensor([[[3]]]).shape, (1, 1, 1))
-
 if __name__ == '__main__':
   unittest.main()

tinygrad/tensor.py

@@ -67,11 +67,8 @@ class Tensor:
 
     if data.__class__ is np.ndarray:
       data = cast(np.ndarray, data)
-      if data.size == 1: # constant fold
-        self.lazydata = LazyBuffer.loadop(LoadOps.CONST, tuple(), dtypes.from_np(data.dtype), device, data.flat[0]).reshape(data.shape)
-      else:
-        data = LazyBuffer.fromCPU(data)
-        self.lazydata = data if data.device == device else LazyBuffer.loadop(LoadOps.FROM, data.shape, data.dtype, device, src=data)
+      data = LazyBuffer.fromCPU(data)
+      self.lazydata = data if data.device == device else LazyBuffer.loadop(LoadOps.FROM, data.shape, data.dtype, device, src=data)
       return
 
     raise RuntimeError(f"can't create Tensor from {data}")