Added pytest Future Warning in relavant tests

Author: Dhruvanshu-Joshi

pytensor/configdefaults.py

@@ -6,6 +6,7 @@
 import socket
 import sys
 import textwrap
+import warnings
 
 import numpy as np
 from setuptools._distutils.spawn import find_executable
@@ -1447,6 +1448,12 @@ def add_caching_dir_configvars():
 else:
     gcc_version_str = "GCC_NOT_FOUND"
 
+if config.compute_test_value != "off":
+    warnings.warn(
+        "test_value machinery is deprecated and will stop working in the future.",
+        FutureWarning,
+    )
+
 # TODO: The caching dir resolution is a procedural mess of helper functions, local variables
 # and config definitions. And the result is also not particularly pretty..
 add_caching_dir_configvars()

pytensor/graph/basic.py

@@ -451,6 +451,12 @@ def __init__(
 
         self.tag = ValidatingScratchpad("test_value", type.filter)
 
+        # if hasattr(self.tag, "test_value"):
+        #     warnings.warn(
+        #         "test_value machinery is deprecated and will stop working in the future.",
+        #         FutureWarning,
+        #     )
+
         self.type = type
 
         self._owner = owner
@@ -479,10 +485,7 @@ def get_test_value(self):
         if not hasattr(self.tag, "test_value"):
             detailed_err_msg = get_variable_trace_string(self)
             raise TestValueError(f"{self} has no test value {detailed_err_msg}")
-        warnings.warn(
-            "test_value machinery is deprecated and will stop working in the future.",
-            FutureWarning,
-        )
+
         return self.tag.test_value
 
     def __str__(self):

pytensor/graph/fg.py

@@ -1,7 +1,6 @@
 """A container for specifying and manipulating a graph with distinct inputs and outputs."""
 
 import time
-import warnings
 from collections import OrderedDict
 from collections.abc import Iterable, Sequence
 from typing import TYPE_CHECKING, Any, Literal, Union, cast
@@ -494,10 +493,6 @@ def replace(
             return
 
         if config.compute_test_value != "off":
-            warnings.warn(
-                "test_value machinery is deprecated and will stop working in the future.",
-                FutureWarning,
-            )
             try:
                 tval = pytensor.graph.op.get_test_value(var)
                 new_tval = pytensor.graph.op.get_test_value(new_var)

pytensor/graph/op.py

@@ -70,11 +70,6 @@ def compute_test_value(node: Apply):
     """
     # Gather the test values for each input of the node
 
-    warnings.warn(
-        "compute_test_value is deprecated and will stop working in the future.",
-        FutureWarning,
-    )
-
     storage_map = {}
     compute_map = {}
     for i, ins in enumerate(node.inputs):
@@ -307,10 +302,6 @@ def __call__(
                     n.name = f"{name}_{i}"
 
         if config.compute_test_value != "off":
-            warnings.warn(
-                "test_value machinery is deprecated and will stop working in the future.",
-                FutureWarning,
-            )
             compute_test_value(node)
 
         if self.default_output is not None:
@@ -721,11 +712,6 @@ def get_test_values(*args: Variable) -> Any | list[Any]:
     if config.compute_test_value == "off":
         return []
 
-    warnings.warn(
-        "test_value machinery is deprecated and will stop working in the future.",
-        FutureWarning,
-    )
-
     rval = []
 
     for i, arg in enumerate(args):

pytensor/graph/rewriting/basic.py

@@ -983,10 +983,6 @@ def transform(self, fgraph, node, *args, **kwargs):
             if isinstance(input, pytensor.compile.SharedVariable):
                 pass
             elif hasattr(input.tag, "test_value"):
-                warnings.warn(
-                    "compute_test_value is deprecated and will stop working in the future.",
-                    FutureWarning,
-                )
                 givens[input] = pytensor.shared(
                     input.type.filter(input.tag.test_value),
                     input.name,

pytensor/graph/utils.py

@@ -1,6 +1,7 @@
 import linecache
 import sys
 import traceback
+import warnings
 from abc import ABCMeta
 from collections.abc import Sequence
 from io import StringIO
@@ -283,9 +284,19 @@ def info(self):
 
     # These two methods have been added to help Mypy
     def __getattribute__(self, name):
+        if name == "test_value":
+            warnings.warn(
+                "test_value machinery is deprecated and will stop working in the future.",
+                FutureWarning,
+            )
         return super().__getattribute__(name)
 
     def __setattr__(self, name: str, value: Any) -> None:
+        if name == "test_value":
+            warnings.warn(
+                "test_value machinery is deprecated and will stop working in the future.",
+                FutureWarning,
+            )
         self.__dict__[name] = value
 
 
@@ -300,6 +311,11 @@ def __init__(self, attr, attr_filter):
 
     def __setattr__(self, attr, obj):
         if getattr(self, "attr", None) == attr:
+            if attr == "test_value":
+                warnings.warn(
+                    "test_value machinery is deprecated and will stop working in the future.",
+                    FutureWarning,
+                )
             obj = self.attr_filter(obj)
 
         return object.__setattr__(self, attr, obj)

pytensor/misc/pkl_utils.py

@@ -9,7 +9,6 @@
 import pickle
 import sys
 import tempfile
-import warnings
 import zipfile
 from collections import defaultdict
 from contextlib import closing
@@ -62,10 +61,6 @@ class StripPickler(Pickler):
     def __init__(self, file, protocol=0, extra_tag_to_remove=None):
         # Can't use super as Pickler isn't a new style class
         super().__init__(file, protocol)
-        warnings.warn(
-            "compute_test_value is deprecated and will stop working in the future.",
-            FutureWarning,
-        )
         self.tag_to_remove = ["trace", "test_value"]
         if extra_tag_to_remove:
             self.tag_to_remove.extend(extra_tag_to_remove)

pytensor/scalar/basic.py

@@ -12,7 +12,6 @@
 
 import builtins
 import math
-import warnings
 from collections.abc import Callable, Mapping
 from copy import copy
 from itertools import chain
@@ -4415,10 +4414,6 @@ def apply(self, fgraph):
             if i.dtype == "float16":
                 mapping[i] = get_scalar_type("float32")()
                 if hasattr(i.tag, "test_value"):
-                    warnings.warn(
-                        "test_value machinery is deprecated and will stop working in the future.",
-                        FutureWarning,
-                    )
                     mapping[i].tag.test_value = i.tag.test_value
             else:
                 mapping[i] = i

pytensor/scan/basic.py

@@ -598,10 +598,6 @@ def wrap_into_list(x):
 
                 # Try to transfer test_value to the new variable
                 if config.compute_test_value != "off":
-                    warnings.warn(
-                        "test_value machinery is deprecated and will stop working in the future.",
-                        FutureWarning,
-                    )
                     try:
                         nw_slice.tag.test_value = get_test_value(_seq_val_slice)
                     except TestValueError:
@@ -729,10 +725,6 @@ def wrap_into_list(x):
 
             # Try to transfer test_value to the new variable
             if config.compute_test_value != "off":
-                warnings.warn(
-                    "test_value machinery is deprecated and will stop working in the future.",
-                    FutureWarning,
-                )
                 try:
                     arg.tag.test_value = get_test_value(actual_arg)
                 except TestValueError:
@@ -788,10 +780,6 @@ def wrap_into_list(x):
 
                 # Try to transfer test_value to the new variable
                 if config.compute_test_value != "off":
-                    warnings.warn(
-                        "test_value machinery is deprecated and will stop working in the future.",
-                        FutureWarning,
-                    )
                     try:
                         nw_slice.tag.test_value = get_test_value(_init_out_var_slice)
                     except TestValueError:

pytensor/scan/op.py

@@ -46,7 +46,6 @@
 import dataclasses
 import logging
 import time
-import warnings
 from collections import OrderedDict
 from collections.abc import Callable, Iterable
 from copy import copy
@@ -2651,10 +2650,6 @@ def compute_all_gradients(known_grads):
             # fct add and we want to keep it for all Scan op.  This is
             # used in T_Scan.test_grad_multiple_outs_taps to test
             # that.
-            warnings.warn(
-                "test_value machinery is deprecated and will stop working in the future.",
-                FutureWarning,
-            )
             if info.as_while:
                 n = n_steps.tag.test_value
             else:

pytensor/scan/rewriting.py

@@ -2,7 +2,6 @@
 
 import copy
 import dataclasses
-import warnings
 from itertools import chain
 from sys import maxsize
 from typing import cast
@@ -306,10 +305,6 @@ def add_to_replace(y):
             pushed_out_node = nd.op.make_node(*new_inputs)
 
             if config.compute_test_value != "off":
-                warnings.warn(
-                    "test_value machinery is deprecated and will stop working in the future.",
-                    FutureWarning,
-                )
                 compute_test_value(pushed_out_node)
 
             # Step 2. Create variables to replace the old outputs of the node
@@ -516,10 +511,6 @@ def add_to_replace(y):
             nw_outer_node = nd.op.make_node(*outside_ins)
 
             if config.compute_test_value != "off":
-                warnings.warn(
-                    "test_value machinery is deprecated and will stop working in the future.",
-                    FutureWarning,
-                )
                 compute_test_value(nw_outer_node)
 
             # Step 2. Create variables for replacements
@@ -554,10 +545,6 @@ def add_to_replace(y):
             replace_with_out.append(new_outer)
 
             if hasattr(new_outer.tag, "test_value"):
-                warnings.warn(
-                    "test_value machinery is deprecated and will stop working in the future.",
-                    FutureWarning,
-                )
                 new_sh = new_outer.tag.test_value.shape
                 ref_sh = (outside_ins.tag.test_value.shape[0],)
                 ref_sh += nd.outputs[0].tag.test_value.shape
@@ -995,10 +982,6 @@ def attempt_scan_inplace(
                 new_lsi = inp.owner.op.make_node(*inp.owner.inputs)
 
                 if config.compute_test_value != "off":
-                    warnings.warn(
-                        "test_value machinery is deprecated and will stop working in the future.",
-                        FutureWarning,
-                    )
                     compute_test_value(new_lsi)
 
                 new_lsi_out = new_lsi.outputs

pytensor/scan/utils.py

@@ -3,7 +3,6 @@
 import copy
 import dataclasses
 import logging
-import warnings
 from collections import OrderedDict, namedtuple
 from collections.abc import Callable, Sequence
 from itertools import chain
@@ -75,10 +74,6 @@ def safe_new(
         nw_x.name = nw_name
         if config.compute_test_value != "off":
             # Copy test value, cast it if necessary
-            warnings.warn(
-                "test_value machinery is deprecated and will stop working in the future.",
-                FutureWarning,
-            )
             try:
                 x_test_value = get_test_value(x)
             except TestValueError:
@@ -109,10 +104,6 @@ def safe_new(
     # between test values, due to inplace operations for instance. This may
     # not be the most efficient memory-wise, though.
     if config.compute_test_value != "off":
-        warnings.warn(
-            "test_value machinery is deprecated and will stop working in the future.",
-            FutureWarning,
-        )
         try:
             nw_x.tag.test_value = copy.deepcopy(get_test_value(x))
         except TestValueError:

pytensor/tensor/blas.py

@@ -78,7 +78,6 @@
 import logging
 import os
 import time
-import warnings
 
 import numpy as np
 
@@ -1968,10 +1967,6 @@ def R_op(self, inputs, eval_points):
         test_values_enabled = config.compute_test_value != "off"
 
         if test_values_enabled:
-            warnings.warn(
-                "test_value machinery is deprecated and will stop working in the future.",
-                FutureWarning,
-            )
             try:
                 iv0 = pytensor.graph.op.get_test_value(inputs[0])
             except TestValueError:

pytensor/tensor/random/rewriting/basic.py

@@ -1,4 +1,3 @@
-import warnings
 from itertools import chain
 
 from pytensor.compile import optdb
@@ -109,10 +108,6 @@ def local_rv_size_lift(fgraph, node):
     new_node = node.op.make_node(rng, None, *dist_params)
 
     if config.compute_test_value != "off":
-        warnings.warn(
-            "test_value machinery is deprecated and will stop working in the future.",
-            FutureWarning,
-        )
         compute_test_value(new_node)
 
     return new_node.outputs
@@ -192,10 +187,6 @@ def local_dimshuffle_rv_lift(fgraph, node):
     new_node = rv_op.make_node(rng, new_size, *new_dist_params)
 
     if config.compute_test_value != "off":
-        warnings.warn(
-            "test_value machinery is deprecated and will stop working in the future.",
-            FutureWarning,
-        )
         compute_test_value(new_node)
 
     out = new_node.outputs[1]

tests/compile/test_builders.py

@@ -523,11 +523,12 @@ def test_infer_shape(self):
 
     @config.change_flags(compute_test_value="raise")
     def test_compute_test_value(self):
-        x = scalar("x")
-        x.tag.test_value = np.array(1.0, dtype=config.floatX)
-        op = OpFromGraph([x], [x**3])
-        y = scalar("y")
-        y.tag.test_value = np.array(1.0, dtype=config.floatX)
+        with pytest.warns(FutureWarning):
+            x = scalar("x")
+            x.tag.test_value = np.array(1.0, dtype=config.floatX)
+            op = OpFromGraph([x], [x**3])
+            y = scalar("y")
+            y.tag.test_value = np.array(1.0, dtype=config.floatX)
         f = op(y)
         grad_f = grad(f, y)
         assert grad_f.tag.test_value is not None