[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
egraphs-good · Sep 13, 2023 · cf89509 · cf89509
1 parent aa88491
commit cf89509
Showing 1 changed file with 71 additions and 16 deletions.
diff --git a/python/tests/__snapshots__/test_array_api/test_sklearn_lda.py b/python/tests/__snapshots__/test_array_api/test_sklearn_lda.py
@@ -9,31 +9,74 @@
 assume_value_one_of(_NDArray_2, _TupleValue_1)
 _NDArray_3 = reshape(_NDArray_2, TupleInt(Int(-1)))
 _NDArray_4 = astype(unique_counts(_NDArray_3)[Int(1)], DType.float64) / NDArray.scalar(Value.float(Float(150.0)))
-_NDArray_5 = zeros(TupleInt(Int(3)) + TupleInt(Int(4)), OptionalDType.some(DType.float64), OptionalDevice.some(_NDArray_1.device))
+_NDArray_5 = zeros(
+    TupleInt(Int(3)) + TupleInt(Int(4)), OptionalDType.some(DType.float64), OptionalDevice.some(_NDArray_1.device)
+)
 _MultiAxisIndexKey_1 = MultiAxisIndexKey(MultiAxisIndexKeyItem.slice(Slice()))
 _IndexKey_1 = IndexKey.multi_axis(MultiAxisIndexKey(MultiAxisIndexKeyItem.int(Int(0))) + _MultiAxisIndexKey_1)
-_NDArray_5[_IndexKey_1] = mean(_NDArray_1[ndarray_index(unique_inverse(_NDArray_3)[Int(1)] == NDArray.scalar(Value.int(Int(0))))], OptionalIntOrTuple.int(Int(0)))
+_NDArray_5[_IndexKey_1] = mean(
+    _NDArray_1[ndarray_index(unique_inverse(_NDArray_3)[Int(1)] == NDArray.scalar(Value.int(Int(0))))],
+    OptionalIntOrTuple.int(Int(0)),
+)
 _IndexKey_2 = IndexKey.multi_axis(MultiAxisIndexKey(MultiAxisIndexKeyItem.int(Int(1))) + _MultiAxisIndexKey_1)
-_NDArray_5[_IndexKey_2] = mean(_NDArray_1[ndarray_index(unique_inverse(_NDArray_3)[Int(1)] == NDArray.scalar(Value.int(Int(1))))], OptionalIntOrTuple.int(Int(0)))
+_NDArray_5[_IndexKey_2] = mean(
+    _NDArray_1[ndarray_index(unique_inverse(_NDArray_3)[Int(1)] == NDArray.scalar(Value.int(Int(1))))],
+    OptionalIntOrTuple.int(Int(0)),
+)
 _IndexKey_3 = IndexKey.multi_axis(MultiAxisIndexKey(MultiAxisIndexKeyItem.int(Int(2))) + _MultiAxisIndexKey_1)
-_NDArray_5[_IndexKey_3] = mean(_NDArray_1[ndarray_index(unique_inverse(_NDArray_3)[Int(1)] == NDArray.scalar(Value.int(Int(2))))], OptionalIntOrTuple.int(Int(0)))
+_NDArray_5[_IndexKey_3] = mean(
+    _NDArray_1[ndarray_index(unique_inverse(_NDArray_3)[Int(1)] == NDArray.scalar(Value.int(Int(2))))],
+    OptionalIntOrTuple.int(Int(0)),
+)
 _NDArray_6 = concat(
-    TupleNDArray(_NDArray_1[ndarray_index(_NDArray_3 == NDArray.vector(_TupleValue_1)[IndexKey.int(Int(0))])] - _NDArray_5[_IndexKey_1])
+    TupleNDArray(
+        _NDArray_1[ndarray_index(_NDArray_3 == NDArray.vector(_TupleValue_1)[IndexKey.int(Int(0))])]
+        - _NDArray_5[_IndexKey_1]
+    )
     + (
-        TupleNDArray(_NDArray_1[ndarray_index(_NDArray_3 == NDArray.vector(_TupleValue_1)[IndexKey.int(Int(1))])] - _NDArray_5[_IndexKey_2])
-        + TupleNDArray(_NDArray_1[ndarray_index(_NDArray_3 == NDArray.vector(_TupleValue_1)[IndexKey.int(Int(2))])] - _NDArray_5[_IndexKey_3])
+        TupleNDArray(
+            _NDArray_1[ndarray_index(_NDArray_3 == NDArray.vector(_TupleValue_1)[IndexKey.int(Int(1))])]
+            - _NDArray_5[_IndexKey_2]
+        )
+        + TupleNDArray(
+            _NDArray_1[ndarray_index(_NDArray_3 == NDArray.vector(_TupleValue_1)[IndexKey.int(Int(2))])]
+            - _NDArray_5[_IndexKey_3]
+        )
     ),
     OptionalInt.some(Int(0)),
 )
 _NDArray_7 = std(_NDArray_6, OptionalIntOrTuple.int(Int(0)))
-_NDArray_7[ndarray_index(std(_NDArray_6, OptionalIntOrTuple.int(Int(0))) == NDArray.scalar(Value.int(Int(0))))] = NDArray.scalar(Value.float(Float(1.0)))
-_TupleNDArray_1 = svd(sqrt(NDArray.scalar(Value.int(NDArray.scalar(Value.float(Float(1.0))).to_int() / Int(147)))) * (_NDArray_6 / _NDArray_7), FALSE)
-_Slice_1 = Slice(OptionalInt.none, OptionalInt.some(astype(sum(_TupleNDArray_1[Int(1)] > NDArray.scalar(Value.float(Float(0.0001)))), DType.int32).to_int()))
-_NDArray_8 = (_TupleNDArray_1[Int(2)][IndexKey.multi_axis(MultiAxisIndexKey(MultiAxisIndexKeyItem.slice(_Slice_1)) + _MultiAxisIndexKey_1)] / _NDArray_7).T / _TupleNDArray_1[
-    Int(1)
-][IndexKey.slice(_Slice_1)]
+_NDArray_7[
+    ndarray_index(std(_NDArray_6, OptionalIntOrTuple.int(Int(0))) == NDArray.scalar(Value.int(Int(0))))
+] = NDArray.scalar(Value.float(Float(1.0)))
+_TupleNDArray_1 = svd(
+    sqrt(NDArray.scalar(Value.int(NDArray.scalar(Value.float(Float(1.0))).to_int() / Int(147))))
+    * (_NDArray_6 / _NDArray_7),
+    FALSE,
+)
+_Slice_1 = Slice(
+    OptionalInt.none,
+    OptionalInt.some(
+        astype(sum(_TupleNDArray_1[Int(1)] > NDArray.scalar(Value.float(Float(0.0001)))), DType.int32).to_int()
+    ),
+)
+_NDArray_8 = (
+    _TupleNDArray_1[Int(2)][
+        IndexKey.multi_axis(MultiAxisIndexKey(MultiAxisIndexKeyItem.slice(_Slice_1)) + _MultiAxisIndexKey_1)
+    ]
+    / _NDArray_7
+).T / _TupleNDArray_1[Int(1)][IndexKey.slice(_Slice_1)]
 _TupleNDArray_2 = svd(
-    (sqrt(NDArray.scalar(Value.int((Int(150) * _NDArray_4.to_int()) * (NDArray.scalar(Value.float(Float(1.0))).to_int() / Int(2))))) * (_NDArray_5 - (_NDArray_4 @ _NDArray_5)).T).T
+    (
+        sqrt(
+            NDArray.scalar(
+                Value.int(
+                    (Int(150) * _NDArray_4.to_int()) * (NDArray.scalar(Value.float(Float(1.0))).to_int() / Int(2))
+                )
+            )
+        )
+        * (_NDArray_5 - (_NDArray_4 @ _NDArray_5)).T
+    ).T
     @ _NDArray_8,
     FALSE,
 )
@@ -50,7 +93,14 @@
                             OptionalInt.none,
                             OptionalInt.some(
                                 astype(
-                                    sum(_TupleNDArray_2[Int(1)] > (NDArray.scalar(Value.float(Float(0.0001))) * _TupleNDArray_2[Int(1)][IndexKey.int(Int(0))])), DType.int32
+                                    sum(
+                                        _TupleNDArray_2[Int(1)]
+                                        > (
+                                            NDArray.scalar(Value.float(Float(0.0001)))
+                                            * _TupleNDArray_2[Int(1)][IndexKey.int(Int(0))]
+                                        )
+                                    ),
+                                    DType.int32,
                                 ).to_int()
                             ),
                         )
@@ -59,4 +109,9 @@
             )
         ]
     )
-)[IndexKey.multi_axis(_MultiAxisIndexKey_1 + MultiAxisIndexKey(MultiAxisIndexKeyItem.slice(Slice(OptionalInt.none, OptionalInt.some(Int(2))))))]
+)[
+    IndexKey.multi_axis(
+        _MultiAxisIndexKey_1
+        + MultiAxisIndexKey(MultiAxisIndexKeyItem.slice(Slice(OptionalInt.none, OptionalInt.some(Int(2)))))
+    )
+]