🚀 The feature, motivation and pitch Request: A feature in torch.testing.assert_close() that allows users to state: "It's OK if the assertion fails on less than x% of the input (or y entries in absolute terms)" e.g. assert_close(a, b, ato...
testing.assert_close(expected[i][j], new_out[i][j]) batch = torch.export.Dim("batch") seq_length = torch.export.Dim("seq_length") dynamic_shapes = ({0: batch}, {0: batch, 1: seq_length}, None) # We try to export with (tensor, tensor, int) # ep = torch.export.export(...
离散傅里叶变换是可分离的,因此这里的fft2()相当于两个一维的fft()调用: >>>two_ffts = torch.fft.fft(torch.fft.fft(x, dim=0), dim=1)>>>torch.testing.assert_close(fft2, two_ffts, check_stride=False)
y = torch.testing.randn_like( x if (x.is_floating_point() or x.is_complex()) else x.double(), memory_format=torch.legacy_contiguous_format) if gen_non_contig_grad_outputs: y = torch.testing.make_non_contiguous(y) return y.requires_grad_() ...
@pytest.mark.task0_2@given(small_floats,small_floats)deftest_sigmoid(a:float,b:float)->None:assertsigmoid(a)>=0.0andsigmoid(a)<=1.0assert_close(1-sigmoid(a),sigmoid(-a))assertsigmoid(0)==0.5# ?严格单增asserta==bor(a<bandsigmoid(a)<=sigmoid(b))or(a>bandsigmoid(a)>=sigmoid(b))...
We recently added torch.testing.assert_close, which allows us to compare all kind of numerics with expressive error messages if they don't match. This PR adopts it by going for the low hanging fruits: value comparisons of torch.Tensor's or np.ndarray's. We could also go for scalar or ...
testing.assert_close(ret_eager[0], ret_compiled[0]) Error logs # AssertionError: Tensor-likes are not close! # # Mismatched elements: 7200 / 7200 (100.0%) # Greatest absolute difference: 4132.387735664385 at index (7, 0, 14, 5) (up to 1e-07 allowed) # Greatest relative difference: ...
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torch.testing.assert_close(sdpa_out,flex_out)mha_out,_=self.mha(x,x,x,need_weights=False,attn_mask=Noneifself.attn_maskisNoneelse~self.attn_mask)torch.testing.assert_close(sdpa_out,mha_out)returnmha_outdefmain():args=parser.parse_args()forargs.test_flex_attention,args.mask,args.compile...
testing.assert_close(ret_eager[1], ret_compiled[1]) # assert torch.allclose(ret_eager[1], ret_compiled[1]), '\n'.join(map(str, ["", ret_eager[1], ret_compiled[1]])) # torch.testing.assert_close(ret_eager[2], ret_compiled[2]) # assert torch.allclose(ret_eager[2], ret_...