Merge branch 'main' into limit-refined-candidates

Author: mohammedahmed18

codeflash/verification/comparator.py

@@ -23,6 +23,7 @@
 HAS_TORCH = find_spec("torch") is not None
 HAS_JAX = find_spec("jax") is not None
 HAS_XARRAY = find_spec("xarray") is not None
+HAS_TENSORFLOW = find_spec("tensorflow") is not None
 
 
 def comparator(orig: Any, new: Any, superset_obj=False) -> bool:  # noqa: ANN001, ANN401, FBT002, PLR0911
@@ -57,6 +58,7 @@ def comparator(orig: Any, new: Any, superset_obj=False) -> bool:  # noqa: ANN001
                 enum.Enum,
                 type,
                 range,
+                slice,
                 OrderedDict,
             ),
         ):
@@ -97,6 +99,45 @@ def comparator(orig: Any, new: Any, superset_obj=False) -> bool:  # noqa: ANN001
             if isinstance(orig, (xarray.Dataset, xarray.DataArray)):
                 return orig.identical(new)
 
+        # Handle TensorFlow objects early to avoid boolean context errors
+        if HAS_TENSORFLOW:
+            import tensorflow as tf  # type: ignore  # noqa: PGH003
+
+            if isinstance(orig, tf.Tensor):
+                if orig.dtype != new.dtype:
+                    return False
+                if orig.shape != new.shape:
+                    return False
+                # Use numpy conversion for proper NaN handling
+                return comparator(orig.numpy(), new.numpy(), superset_obj)
+
+            if isinstance(orig, tf.Variable):
+                if orig.dtype != new.dtype:
+                    return False
+                if orig.shape != new.shape:
+                    return False
+                return comparator(orig.numpy(), new.numpy(), superset_obj)
+
+            if isinstance(orig, tf.dtypes.DType):
+                return orig == new
+
+            if isinstance(orig, tf.TensorShape):
+                return orig == new
+
+            if isinstance(orig, tf.SparseTensor):
+                if not comparator(orig.dense_shape.numpy(), new.dense_shape.numpy(), superset_obj):
+                    return False
+                return comparator(orig.indices.numpy(), new.indices.numpy(), superset_obj) and comparator(
+                    orig.values.numpy(), new.values.numpy(), superset_obj
+                )
+
+            if isinstance(orig, tf.RaggedTensor):
+                if orig.dtype != new.dtype:
+                    return False
+                if orig.shape.rank != new.shape.rank:
+                    return False
+                return comparator(orig.to_list(), new.to_list(), superset_obj)
+
         if HAS_SQLALCHEMY:
             import sqlalchemy  # type: ignore  # noqa: PGH003
 
@@ -130,14 +171,41 @@ def comparator(orig: Any, new: Any, superset_obj=False) -> bool:  # noqa: ANN001
                     return False
             return True
 
+        # Handle dict view types (dict_keys, dict_values, dict_items)
+        # Use type name checking since these are not directly importable types
+        type_name = type(orig).__name__
+        if type_name == "dict_keys":
+            # dict_keys can be compared as sets (order doesn't matter)
+            return comparator(set(orig), set(new))
+        if type_name == "dict_values":
+            # dict_values need element-wise comparison (order matters)
+            return comparator(list(orig), list(new))
+        if type_name == "dict_items":
+            # Convert to dict for order-insensitive comparison (handles unhashable values)
+            return comparator(dict(orig), dict(new), superset_obj)
+
         if HAS_NUMPY:
             import numpy as np  # type: ignore  # noqa: PGH003
 
+            if isinstance(orig, (np.datetime64, np.timedelta64)):
+                # Handle NaT (Not a Time) - numpy's equivalent of NaN for datetime
+                if np.isnat(orig) and np.isnat(new):
+                    return True
+                if np.isnat(orig) or np.isnat(new):
+                    return False
+                return orig == new
+
             if isinstance(orig, np.ndarray):
                 if orig.dtype != new.dtype:
                     return False
                 if orig.shape != new.shape:
                     return False
+                # Handle 0-d arrays specially to avoid "iteration over a 0-d array" error
+                if orig.ndim == 0:
+                    try:
+                        return np.allclose(orig, new, equal_nan=True)
+                    except Exception:
+                        return bool(orig == new)
                 try:
                     return np.allclose(orig, new, equal_nan=True)
                 except Exception:
@@ -208,6 +276,9 @@ def comparator(orig: Any, new: Any, superset_obj=False) -> bool:  # noqa: ANN001
                     return False
                 return torch.allclose(orig, new, equal_nan=True)
 
+            if isinstance(orig, torch.dtype):
+                return orig == new
+
         if HAS_PYRSISTENT:
             import pyrsistent  # type: ignore  # noqa: PGH003