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- 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 = getenv("N", 4096)
- M = getenv("M", N)
- K = getenv("K", N)
- CNT = getenv("CNT", 10)
- ATOL = getenv("ATOL", 1e-4)
- RTOL = getenv("RTOL", 3e-2)
- if __name__ == "__main__":
- a, b = Tensor.rand(M, K, dtype=dtype_in).realize(), Tensor.rand(K, N, dtype=dtype_in).realize()
- for i in range(CNT):
- if i > 0 and getenv("RAND", 0) != 0:
- a, b = Tensor.rand(M, K, dtype=dtype_in).realize(), Tensor.rand(K, N, dtype=dtype_in).realize()
- c = a.matmul(b, acc_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:
- 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)
- raise e
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