Uncomment tests that are passing.

I unskipped the tests in the skiplist and checked which tests were
actually passing.

experimental/torch_xla2/test/test_ops.py

@@ -15,7 +15,6 @@
     "_segment_reduce",
     "_upsample_bilinear2d_aa",
     "bincount", # NOTE: dtype for int input torch gives float. This is weird.
-    "block_diag",
     "byte",
     "cat",
     "cauchy",
@@ -29,18 +28,13 @@
     "diagflat",
     "diagonal_copy",
     "diagonal_scatter",
-    "diff",
     "digamma",
-    "erfc",
     "erfinv",
-    "expand",
     "exponential",
-    "floor_divide",
     "gather",
     "gcd",
     "geometric",
     "geqrf",
-    "grid_sampler_2d",
     "histogram", # hard op: AssertionError: Tensor-likes are not close!
     "histogramdd", # TypeError: histogram requires ndarray or scalar arguments, got <class 'list'> at position 1.
     "igammac",
@@ -68,7 +62,6 @@
     "linalg.matrix_norm",
     "linalg.matrix_power",
     "linalg.matrix_rank",
-    "linalg.multi_dot",
     "linalg.norm",
     "linalg.pinv",
     "linalg.solve",
@@ -78,15 +71,13 @@
     "linalg.svdvals",
     "linalg.tensorinv",
     "linalg.tensorsolve",
-    "linalg.vander",
     "linalg.vector_norm",
     "linspace",
     "log_normal",
     "logspace",
     "lu",
     "lu_solve",
     "lu_unpack",
-    "masked.argmin",
     "masked.median",
     "masked_scatter",
     "masked_select",
@@ -97,11 +88,9 @@
     "mvlgamma",
     "nanmedian",
     "nanquantile",
-    "native_layer_norm",
     "new_empty",
     "new_empty_strided",
     "nextafter",
-    "nn.functional.adaptive_avg_pool1d",
     "nn.functional.adaptive_avg_pool3d",
     "nn.functional.adaptive_max_pool1d",
     "nn.functional.adaptive_max_pool2d",
@@ -110,17 +99,14 @@
     "nn.functional.avg_pool1d",
     "nn.functional.avg_pool2d",
     "nn.functional.avg_pool3d",
-    "nn.functional.batch_norm",
     "nn.functional.bilinear",
-    "nn.functional.binary_cross_entropy",
     "nn.functional.conv2d",
     "nn.functional.conv3d",
     "nn.functional.conv_transpose1d",
     "nn.functional.conv_transpose2d",
     "nn.functional.conv_transpose3d",
     "nn.functional.cosine_embedding_loss",
     "nn.functional.cosine_similarity",
-    "nn.functional.cross_entropy",
     "nn.functional.ctc_loss",
     "nn.functional.dropout2d",
     "nn.functional.dropout3d",
@@ -131,9 +117,7 @@
     "nn.functional.fractional_max_pool3d",
     "nn.functional.group_norm",
     "nn.functional.hinge_embedding_loss",
-    "nn.functional.instance_norm",
     "nn.functional.interpolate",
-    "nn.functional.layer_norm",
     "nn.functional.margin_ranking_loss",
     "nn.functional.max_pool1d",
     "nn.functional.max_pool2d",
@@ -144,17 +128,12 @@
     "nn.functional.multi_head_attention_forward",
     "nn.functional.multi_margin_loss",
     "nn.functional.multilabel_margin_loss",
-    "nn.functional.multilabel_soft_margin_loss",
-    "nn.functional.nll_loss",
-    "nn.functional.normalize",
-    "nn.functional.one_hot",
     "nn.functional.pad",
     "nn.functional.pairwise_distance",
-    "nn.functional.pixel_shuffle",
-    "nn.functional.pixel_unshuffle",
     "nn.functional.poisson_nll_loss",
     "nn.functional.rrelu",
-    "nn.functional.softmin",
+    "nn.functional.triplet_margin_loss",
+    "nn.functional.triplet_margin_with_distance_loss",
     "nn.functional.unfold",
     "nn.functional.upsample_nearest",
     "nonzero",
@@ -187,54 +166,18 @@
     "sub",
     "svd",
     "svd_lowrank",
-    "take_along_dim",
     "to_sparse", # We are not supporting sparse tensors yet.
-    "triu",
-    "unbind",
     "unfold_copy",
     "unfold",
     "unique_consecutive",
     "unique",
     "unravel_index",
     "var_mean",
-    "zero_",
     "argwhere",
-    "cumulative_trapezoid",
-    "expand_as",
     "nanmean",
-    "bmm",
-    "broadcast_shapes",
-    "cartesian_prod",
-    "cdouble",
-    "ceil",
     "chalf", # Skip due to jax not support complex32 with backend: https://github.com/google/jax/issues/14180
-    "nn.functional.smooth_l1_loss",
-    "nn.functional.soft_margin_loss",
-    "nn.functional.softplus",
-    "nn.functional.softshrink",
-    "nn.functional.softsign",
-    "nn.functional.tanhshrink",
-    "nn.functional.threshold",
-    "nn.functional.triplet_margin_loss",
-    "nn.functional.triplet_margin_with_distance_loss",
     "nn.functional.upsample_bilinear",
-    "outer",
-    "permute",
-    "positive",
-    "rad2deg",
     "randint",
-    "ravel",
-    "reciprocal",
-    "remainder",
-    "repeat",
-    "true_divide",
-    "trunc",
-    "unflatten",
-    "unsafe_chunk",
-    "unsafe_split",
-    "unsqueeze",
-    "view_as_complex",
-    "view_as",
 }
 
 # These inputs are themselves views