Turn on meta converter for complex (#98869)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/98869
Approved by: https://github.com/ngimel
diff --git a/test/test_proxy_tensor.py b/test/test_proxy_tensor.py
index 49d0af7..928e84c 100644
--- a/test/test_proxy_tensor.py
+++ b/test/test_proxy_tensor.py
@@ -1330,6 +1330,22 @@
xfail('nanquantile'),
xfail('narrow'),
+ # many complex operators incorrect striding, metadata
+ skip('fft.fft', ''),
+ skip('fft.hfft2', ''),
+ skip('fft.hfft', ''),
+ skip('fft.hfftn', ''),
+ skip('fft.ifft', ''),
+ skip('fft.ihfft2', ''),
+ skip('fft.ihfft', ''),
+ skip('fft.ihfftn', ''),
+ skip('fft.irfft2', ''),
+ skip('fft.irfft', ''),
+ skip('fft.irfftn', ''),
+ skip('fft.rfft2', ''),
+ skip('fft.rfft', ''),
+ skip('fft.rfftn', ''),
+
# Seems like it's creating a sparse tensor that isn't captured by tensor.is_sparse
xfail('sparse.sampled_addmm'),
xfail('sparse.mm', 'reduce'),
@@ -1350,6 +1366,23 @@
xfail('repeat_interleave'),
# ASAN failures due to divide by 0
skip('nn.functional.nll_loss'),
+
+ xfail('linalg.cond', ''),
+ xfail("linalg.matrix_norm"),
+ xfail("linalg.norm"),
+ xfail("linalg.matrix_norm"),
+ xfail("linalg.matrix_rank"),
+ xfail("linalg.norm"),
+ xfail("linalg.norm", "subgradients_at_zero"),
+ xfail("linalg.svd"),
+ xfail("linalg.svdvals"),
+
+ xfail("norm", "nuc"),
+ xfail("pca_lowrank"),
+ xfail("stft"),
+ xfail("svd"),
+ xfail("svd_lowrank"),
+ xfail("linalg.matrix_norm"),
}
symbolic_tensor_failures = {
