| 1234567891011121314151617181920212223242526272829303132333435363738394041424344 |
- 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, 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:
- 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")
|