IQ.Pilot Release Commit @ f2a861c

artifacts/package_sources/tinygrad/test/external/external_test_example.py

@@ -0,0 +1,74 @@
+import unittest, sys
+from tinygrad import Device
+from tinygrad.tensor import Tensor
+from tinygrad.helpers import getenv, OSX
+
+def multidevice_test(fxn):
+  exclude_devices = getenv("EXCLUDE_DEVICES", "").split(",")
+  def ret(self):
+    for device in Device._devices:
+      # broken on OSX USB AMD, why?
+      if device in ["DISK", "NPY", "FAKE", "DSP", "NULL"] or (OSX and device in ["AMD"]): continue
+      if sys.stdout.isatty(): print(device)
+      if device in exclude_devices:
+        if sys.stdout.isatty(): print(f"WARNING: {device} test is excluded")
+        continue
+      with self.subTest(device=device):
+        try:
+          Device[device]
+        except Exception:
+          if sys.stdout.isatty(): print(f"WARNING: {device} test isn't running")
+          continue
+        fxn(self, device)
+  return ret
+
+class TestExample(unittest.TestCase):
+  @multidevice_test
+  def test_convert_to_cpu(self, device):
+    a = Tensor([[1,2],[3,4]], device=device)
+    assert a.numpy().shape == (2,2)
+    b = a.to("CPU")
+    assert b.numpy().shape == (2,2)
+
+  @multidevice_test
+  def test_2_plus_3(self, device):
+    a = Tensor([2], device=device)
+    b = Tensor([3], device=device)
+    result = a + b
+    print(f"{a.numpy()} + {b.numpy()} = {result.numpy()}")
+    assert result.numpy()[0] == 5.
+
+  @multidevice_test
+  def test_example_readme(self, device):
+    x = Tensor.eye(3).clone().to(device)
+    y = Tensor([[2.0,0,-2.0]], device=device)
+    z = y.matmul(x).sum()
+    z.backward()
+
+    x.grad.numpy()  # dz/dx
+    y.grad.numpy()  # dz/dy
+
+    assert x.grad.device == device
+    assert y.grad.device == device
+
+  @multidevice_test
+  def test_example_matmul(self, device):
+    try:
+      Device[device]
+    except Exception:
+      print(f"WARNING: {device} test isn't running")
+      return
+
+    x = Tensor.eye(8).clone().to(device)
+    y = Tensor.eye(8).clone().to(device)
+    z = y.matmul(x).sum()
+    z.backward()
+
+    x.grad.numpy()  # dz/dx
+    y.grad.numpy()  # dz/dy
+
+    assert x.grad.device == device
+    assert y.grad.device == device
+
+if __name__ == '__main__':
+  unittest.main()