[torchxla2] Op Info test for fft (#8018)

pytorch · Sep 16, 2024 · 3f4b31b · 3f4b31b
1 parent 008004d
commit 3f4b31b
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Showing 2 changed files with 50 additions and 19 deletions.
diff --git a/experimental/torch_xla2/test/test_ops.py b/experimental/torch_xla2/test/test_ops.py
@@ -35,24 +35,6 @@
     "erfinv",
     "expand",
     "exponential",
-    "fft.fft2",
-    "fft.fft",
-    "fft.fftn",
-    "fft.hfft2",
-    "fft.hfft",
-    "fft.hfftn",
-    "fft.ifft2",
-    "fft.ifft",
-    "fft.ifftn",
-    "fft.ihfft2",
-    "fft.ihfft",
-    "fft.ihfftn",
-    "fft.irfft2",
-    "fft.irfft",
-    "fft.irfftn",
-    "fft.rfft2",
-    "fft.rfft",
-    "fft.rfftn",
     "floor_divide",
     "gather",
     "gcd",
@@ -366,6 +348,7 @@ def setUpClass(cls):
 
   def setUp(self):
     self.env = tensor.Environment()
+    #self.env.config.debug_accuracy_for_each_op = True 
     torch.manual_seed(0)
 
   # Replaces all values in the input torch_tensor that are less than the given threshold

diff --git a/experimental/torch_xla2/torch_xla2/ops/jaten.py b/experimental/torch_xla2/torch_xla2/ops/jaten.py
@@ -3828,7 +3828,10 @@ def _aten_unsafe_index_put(self, indices, values, accumulate=False):
   return self.index_put_(indices, values, accumulate)
 
 
-@op(torch.ops.aten.conj_physical)
+@op(torch.ops.aten.conj_physical,
+    torch.ops.aten.conj,
+    torch.ops.aten._conj_physical,
+    torch.ops.aten._conj)
 def _aten_conj_physical(self):
   return jnp.conjugate(self)
 
@@ -3894,3 +3897,48 @@ def _get_median_index(x, axis=None, keepdims=False):
 @op(torch.ops.aten.triangular_solve)
 def _aten_triangular_solve(b, a, upper=True, transpose=False, unittriangular=False):
   return (jax.lax.linalg.triangular_solve(a, b, left_side=True, lower=not upper, transpose_a=transpose, unit_diagonal=unittriangular), a)
+
+
+# func: _fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor
+@op(torch.ops.aten._fft_c2c)
+def _aten__fft_c2c(self, dim, normalization, forward):
+  if forward:
+    norm = [
+      'backward', 
+      'ortho', 
+      'forward',
+    ][normalization]
+    return jnp.fft.fftn(self, axes=dim, norm=norm)
+  else:
+    norm = [
+      'forward',
+      'ortho', 
+      'backward', 
+    ][normalization]
+    return jnp.fft.ifftn(self, axes=dim, norm=norm)
+
+
+@op(torch.ops.aten._fft_r2c)
+def _aten__fft_r2c(self, dim, normalization, onesided):
+  norm = [
+    'backward', 
+    'ortho', 
+    'forward',
+  ][normalization]
+  if onesided:
+    return jnp.fft.rfftn(self, axes=dim, norm=norm)
+  else:
+    return jnp.fft.fftn(self, axes=dim, norm=norm)
+
+@op(torch.ops.aten._fft_c2r)
+def _aten__fft_c2r(self, dim, normalization, last_dim_size):
+  norm = [
+    'forward',
+    'ortho', 
+    'backward', 
+  ][normalization]
+  if len(dim) == 1:
+    s = [last_dim_size]
+  else:
+    s = None
+  return jnp.fft.irfftn(self, norm=norm, axes=dim, s=s)