import sys import os sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..")) import infinicore import torch from framework import ( BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner, is_broadcast, ) # Test cases format: (in_shape, in_strides_or_None, dim_or_None, keepdim_or_None, dtype_or_None) # sum computes the sum along dim(s) or overall _TEST_CASES_DATA = [ ((8, 8), None, None, None, None), ((8, 8), (16, 1), 1, False, None), ((2, 3, 4), None, 0, True, None), ((1, 8), None, (0,), False, None), # tuple 导致 infini_list kwargs dim,[0] ((16, 64), (128, 1), None, None, None), ((4, 5, 6), (60, 12, 2), 2, True, None), ] _TOLERANCE_MAP = { infinicore.float16: {"atol": 1e-3, "rtol": 1e-2}, infinicore.float32: {"atol": 1e-5, "rtol": 1e-4}, } _TENSOR_DTYPES = [infinicore.float16, infinicore.float32] def parse_test_cases(): test_cases = [] for data in _TEST_CASES_DATA: shape, strides, dim, keepdim, dtype_param = data # out_supports_inplace = not is_broadcast(out_strides) for dtype in _TENSOR_DTYPES: tol = _TOLERANCE_MAP.get(dtype, {"atol": 1e-5, "rtol": 1e-3}) in_spec = TensorSpec.from_tensor(shape, strides, dtype) kwargs = {} if dim is not None: kwargs["dim"] = dim if keepdim is not None: kwargs["keepdim"] = keepdim if dtype_param is not None: kwargs["dtype"] = dtype_param test_cases.append( TestCase( inputs=[in_spec], kwargs=kwargs, output_spec=None, comparison_target=None, tolerance=tol, description="Sum - OUT_OF_PLACE", ) ) return test_cases class OpTest(BaseOperatorTest): """Sum operator test with simplified implementation""" def __init__(self): super().__init__("Sum") def get_test_cases(self): return parse_test_cases() def torch_operator(self, *args, **kwargs): return torch.sum(*args, **kwargs) def infinicore_operator(self, *args, **kwargs): """InfiniCore implementation (operator not yet available).""" return infinicore.sum( *args, **kwargs ) # todo 找到具体对应的 python/infinicore/ops/sum.py def main(): """Main entry point""" runner = GenericTestRunner(OpTest) runner.run_and_exit() if __name__ == "__main__": main()