Try skipping create accurate span bc too expensive

Author: saulshanabrook

python/tests/__snapshots__/test_array_api/TestLDA.test_trace.py

@@ -1,11 +1,38 @@
 _NDArray_1 = NDArray.var("X")
 assume_dtype(_NDArray_1, DType.float64)
-assume_shape(_NDArray_1, TupleInt.from_vec(Vec[Int](Int(150), Int(4))))
+_TupleInt_1 = TupleInt.from_vec(Vec[Int](Int(150), Int(4)))
+assume_shape(_NDArray_1, _TupleInt_1)
+assume_isfinite(_NDArray_1)
+assume_dtype(_NDArray_1, DType.float64)
+assume_shape(_NDArray_1, _TupleInt_1)
+assume_isfinite(_NDArray_1)
+assume_dtype(_NDArray_1, DType.float64)
+assume_shape(_NDArray_1, _TupleInt_1)
+assume_isfinite(_NDArray_1)
+assume_dtype(_NDArray_1, DType.float64)
+assume_shape(_NDArray_1, _TupleInt_1)
+assume_isfinite(_NDArray_1)
+assume_dtype(_NDArray_1, DType.float64)
+assume_shape(_NDArray_1, _TupleInt_1)
 assume_isfinite(_NDArray_1)
 _NDArray_2 = NDArray.var("y")
 assume_dtype(_NDArray_2, DType.int64)
-assume_shape(_NDArray_2, TupleInt.from_vec(Vec[Int](Int(150))))
-assume_value_one_of(_NDArray_2, TupleValue.from_vec(Vec[Value](Value.int(Int(0)), Value.int(Int(1)), Value.int(Int(2)))))
+_TupleInt_2 = TupleInt.from_vec(Vec[Int](Int(150)))
+assume_shape(_NDArray_2, _TupleInt_2)
+_TupleValue_1 = TupleValue.from_vec(Vec[Value](Value.int(Int(0)), Value.int(Int(1)), Value.int(Int(2))))
+assume_value_one_of(_NDArray_2, _TupleValue_1)
+assume_dtype(_NDArray_2, DType.int64)
+assume_shape(_NDArray_2, _TupleInt_2)
+assume_value_one_of(_NDArray_2, _TupleValue_1)
+assume_dtype(_NDArray_2, DType.int64)
+assume_shape(_NDArray_2, _TupleInt_2)
+assume_value_one_of(_NDArray_2, _TupleValue_1)
+assume_dtype(_NDArray_2, DType.int64)
+assume_shape(_NDArray_2, _TupleInt_2)
+assume_value_one_of(_NDArray_2, _TupleValue_1)
+assume_dtype(_NDArray_2, DType.int64)
+assume_shape(_NDArray_2, _TupleInt_2)
+assume_value_one_of(_NDArray_2, _TupleValue_1)
 _NDArray_3 = asarray(reshape(asarray(_NDArray_2), TupleInt.from_vec(Vec[Int](Int(-1)))))
 _NDArray_4 = astype(unique_counts(_NDArray_3)[Int(1)], asarray(_NDArray_1).dtype) / NDArray.scalar(Value.float(Float(150.0)))
 _NDArray_5 = zeros(