dtypes nice and clean (#673)

* add dtype class

* dtypes

* buffers are lazy

* dtype is tracked by lazybuffer and GenericShape

* fix types in llvm

* llvm store

* dtype tests

* fix tests maybe

* fix flop counter

* fix CI

* CI fix and check format

* fix dtype and dtype check

* fix custom test

* fix test graph

test/test_dtype.py

@@ -0,0 +1,41 @@
+import unittest
+import numpy as np
+from tinygrad.helpers import getenv
+from tinygrad.lazy import Device
+from tinygrad.tensor import Tensor, dtypes
+
+# for GPU, cl_khr_fp16 isn't supported
+# for LLVM, it segfaults because it can't link to the casting function
+@unittest.skipIf(getenv("CI", "") != "" and Device.DEFAULT in ["GPU", "LLVM"], "float16 broken in some CI backends")
+class TestDtype(unittest.TestCase):
+  def test_half_to_np(self):
+    a = Tensor([1,2,3,4], dtype=dtypes.float16)
+    print(a)
+    na = a.numpy()
+    print(na, na.dtype, a.lazydata.realized)
+    assert na.dtype == np.float16
+
+  def test_half_add(self):
+    a = Tensor([1,2,3,4], dtype=dtypes.float16)
+    b = Tensor([1,2,3,4], dtype=dtypes.float16)
+    c = a+b
+    print(c.numpy())
+    assert c.dtype == dtypes.float16
+
+  def test_upcast_float(self):
+    # NOTE: there's no downcasting support
+    a = Tensor([1,2,3,4], dtype=dtypes.float16).float()
+    print(a)
+    na = a.numpy()
+    print(na, na.dtype)
+    assert na.dtype == np.float32
+
+  def test_half_add_upcast(self):
+    a = Tensor([1,2,3,4], dtype=dtypes.float16)
+    b = Tensor([1,2,3,4], dtype=dtypes.float32)
+    c = a+b
+    print(c.numpy())
+    assert c.dtype == dtypes.float32
+
+if __name__ == '__main__':
+  unittest.main()