Deprecation of Triton-C and Replacement by decorated Python functions (#86)

This PR implements a major overhaul of the frontend for Triton, and replaces Triton-C by a pure Python API in which kernels are defined as @triton.jit decorated functions. The documentation and tutorials have also been updated to accommodate these changes.

See documentations for more information on the new API

python/triton/testing.py

@@ -47,13 +47,37 @@ def mask_tensor(x, mask, block, value=0):
 
 
 def allclose(x, y, tol=1e-2):
-    assert x.dtype == y.dtype
+    if x.dtype != y.dtype:
+        raise RuntimeError(f'{x.dtype} did not match with {x.dtype}')
+    if x.shape != y.shape:
+        raise RuntimeError(f'{x.shape} did not match with {y.shape}')
+    if x.dtype == torch.bool:
+        return torch.sum(x ^ y) == 0
+    if x.dtype in [torch.int8, torch.int16, torch.int32, torch.int64]:
+        tol = 0
     diff = abs(x - y)
     x_max = torch.max(x)
     y_max = torch.max(y)
     tol = 1e-2
     err = torch.max(diff) / torch.max(x_max, y_max)
-    return err < tol
+    return err <= tol
+
+
+def assert_allclose(x, y, tol=1e-2):
+    assert x.dtype == y.dtype
+    assert allclose(x, y, tol)
+
+
+def random(shape, dtype, device):
+    if isinstance(shape, int):
+        shape = (shape, )
+    if dtype == torch.bool:
+        return torch.randint(0, 2, shape, dtype=dtype, device=device)
+    if dtype in [torch.int8, torch.int16, torch.int32, torch.int64]:
+        return torch.randint(1, 32, shape, dtype=dtype, device=device)
+    if dtype in [torch.float16, torch.float32, torch.float64]:
+        return torch.randn(shape, dtype=dtype, device=device)
+    raise RuntimeError(f'Unknown dtype {dtype}')
 
 
 def do_bench(fn, warmup=25, rep=100, grad_to_none=None, percentiles=[0.2, 0.8]):