IQ.Pilot Release Commit @ b6534c0

artifacts/package_sources/tinygrad/extra/gemm/fuzz_matmul.py

@@ -0,0 +1,44 @@
+import numpy as np
+from tinygrad.helpers import getenv
+from tinygrad import dtypes, Tensor
+dtype_in = dtypes.half if getenv("HALF") else dtypes.bfloat16 if getenv("BFLOAT16") else dtypes.float
+acc_dtype = dtypes.half if getenv("ACC_HALF") else dtypes.bfloat16 if getenv("ACC_BFLOAT16") else None
+N_START = getenv("N_START", 1)
+M_START = getenv("M_START", 1)
+K_START = getenv("K_START", 1)
+N_STOP = getenv("N_STOP", 32)
+M_STOP = getenv("M_STOP", N_STOP)
+K_STOP = getenv("K_STOP", N_STOP)
+N_STEP = getenv("N_STEP", 1)
+M_STEP = getenv("M_STEP", 1)
+K_STEP = getenv("K_STEP", 1)
+ATOL = getenv("ATOL", 1e-4)
+RTOL = getenv("RTOL", 3e-2)
+
+if __name__ == "__main__":
+  failed = []
+  for M in range(M_START, M_STOP+1, M_STEP):
+    for N in range(N_START, N_STOP+1, N_STEP):
+      for K in range(K_START, K_STOP+1, K_STEP):
+        print(f"testing {M=} {N=} {K=}")
+        a, b = Tensor.rand(M, K, dtype=dtype_in).realize(), Tensor.rand(K, N, dtype=dtype_in).realize()
+        c = a.matmul(b, dtype=acc_dtype).realize()
+        comp = a.numpy().astype(np.float32) @ b.numpy().astype(np.float32)
+        nc = c.numpy()
+        try:
+          np.testing.assert_allclose(nc, comp, atol=ATOL, rtol=RTOL)
+        except AssertionError as e:
+          failed.append((M,N,K,))
+          if getenv("DEBUG_VALUES") > 0:
+            indices = np.where(~np.isclose(nc, comp, rtol=RTOL, atol=ATOL))
+            non_matching_elements_nc = nc[indices]
+            non_matching_elements_comp = comp[indices]
+            print(indices)
+            print("result      :", non_matching_elements_nc)
+            print("ground truth:", non_matching_elements_comp)
+          print(e)
+          pass
+  print(f"failed sizes: {failed}")
+  print(f"num failures: {len(failed)}")
+  if len(failed) > 0:
+    raise RuntimeError(f"failed on {len(failed)} kernels")