Latest attempt to add image (#462)

* add image

* load + store + boring stuff:

* image tests pass

* thneed print GFLOPS

* op conv test

* more debugging

* hack for multiview image

* shapetracker creates less views

* disable image tests

* working better

* ugh, lkey not key

* print in DEBUG, and allow views

* works

* simple padding conv2d

* use index for image

* that was bad code

* debug print

* fix types

* less lines

* save lines

test/external_test_image.py

@@ -0,0 +1,56 @@
+#!/usr/bin/env python
+import os
+import unittest
+import numpy as np
+if 'IMAGE' not in os.environ:
+  os.environ['IMAGE'] = '2'
+os.environ['GPU'] = '1'
+os.environ['OPT'] = '2'
+from tinygrad.tensor import Tensor
+from tinygrad.llops.ops_gpu import CLImage
+from tinygrad.nn import Conv2d
+Tensor.no_grad = True
+
+class TestImage(unittest.TestCase):
+  def test_create_image(self):
+    t = Tensor.ones(128, 128, 1)
+    t = t.reshape(128, 32, 4) + 3
+    t.realize()
+    assert isinstance(t.lazydata.realized._buf, CLImage)
+    np.testing.assert_array_equal(t.numpy(), np.ones((128,32,4))*4)
+
+  def test_sum_image(self):
+    t1 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 3
+    t1.realize()
+    assert isinstance(t1.lazydata.realized._buf, CLImage)
+    t1 = t1.sum()
+    t1.realize()
+    assert t1.numpy()[0] == 16*4*4*4, f"got {t1.numpy()}"
+  
+  def test_add_image(self):
+    t1 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 3
+    t2 = Tensor.ones(16, 16, 1).reshape(16, 4, 4) + 4
+    t1.realize()
+    t2.realize()
+    t3 = t1 + t2
+    t3.realize()
+    assert isinstance(t3.lazydata.realized._buf, CLImage)
+    np.testing.assert_array_equal(t3.numpy(), np.ones((16,4,4))*9)
+
+  def test_padded_conv(self):
+    bs, in_chans, out_chans = 1,12,32
+    tiny_conv = Conv2d(in_chans, out_chans, 3, bias=None, padding=1)
+    tiny_dat = Tensor.ones(bs, 12, 64, 128)
+    tiny_conv(tiny_dat).realize()
+  
+  def test_op_conv(self):
+    bs, in_chans, out_chans = 1,12,32
+    tiny_conv = Conv2d(in_chans, out_chans, 3, bias=None, padding=0)
+    tiny_dconv = Conv2d(out_chans, out_chans, 1, bias=None, padding=0)
+    tiny_dat = Tensor.ones(bs, 12, 64, 128)
+    p2 = tiny_conv(tiny_dat).relu()
+    p2 = tiny_dconv(p2)
+    p2.realize()
+
+if __name__ == '__main__':
+  unittest.main()