Fix RUF015

Author: Armavica

pytensor/link/c/cmodule.py

@@ -1038,7 +1038,7 @@ def unpickle_failure():
                     _logger.info(f"deleting ModuleCache entry {entry}")
                     key_data.delete_keys_from(self.entry_from_key)
                     del self.module_hash_to_key_data[module_hash]
-                    if key_data.keys and list(key_data.keys)[0][0]:
+                    if key_data.keys and next(iter(key_data.keys))[0]:
                         # this is a versioned entry, so should have been on
                         # disk. Something weird happened to cause this, so we
                         # are responding by printing a warning, removing

pytensor/tensor/utils.py

@@ -151,7 +151,7 @@ def broadcast_static_dim_lengths(
     dim_lengths_set = set(dim_lengths)
     # All dim_lengths are the same
     if len(dim_lengths_set) == 1:
-        return tuple(dim_lengths_set)[0]
+        return next(iter(dim_lengths_set))
 
     # Only valid indeterminate case
     if dim_lengths_set == {None, 1}:
@@ -161,7 +161,7 @@ def broadcast_static_dim_lengths(
     dim_lengths_set.discard(None)
     if len(dim_lengths_set) > 1:
         raise ValueError
-    return tuple(dim_lengths_set)[0]
+    return next(iter(dim_lengths_set))
 
 
 # Copied verbatim from numpy.lib.function_base

tests/link/test_vm.py

@@ -275,7 +275,7 @@ def test_allow_gc_cvm():
     f = function([v], v + 1, mode=mode)
 
     f([1])
-    n = list(f.maker.fgraph.apply_nodes)[0].outputs[0]
+    n = next(iter(f.maker.fgraph.apply_nodes)).outputs[0]
     assert f.vm.storage_map[n][0] is None
     assert f.vm.allow_gc is True
 

tests/scan/test_basic.py

@@ -1630,7 +1630,7 @@ def reset_rng_grad_fn(*args):
 
         # Also validate that the mappings outer_inp_from_outer_out and
         # outer_inp_from_inner_inp produce the correct results
-        scan_node = list(updates.values())[0].owner
+        scan_node = next(iter(updates.values())).owner
 
         var_mappings = scan_node.op.get_oinp_iinp_iout_oout_mappings()
         result = var_mappings["outer_inp_from_outer_out"]
@@ -1922,7 +1922,7 @@ def inner_fn():
         _, updates = scan(
             inner_fn, n_steps=10, truncate_gradient=-1, go_backwards=False
         )
-        cost = list(updates.values())[0]
+        cost = next(iter(updates.values()))
         g_sh = grad(cost, shared_var)
         fgrad = function([], g_sh)
         assert fgrad() == 1

tests/scan/test_rewriting.py

@@ -270,7 +270,7 @@ def lambda_fn(h, W1, W2):
 
         f = function([h0, W1, W2], o, mode=self.mode)
 
-        scan_node = [x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan)][0]
+        scan_node = next(x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan))
         assert (
             len(
                 [
@@ -444,9 +444,9 @@ def test_dot_not_output(self):
         # Ensure that the optimization was performed correctly in f_opt
         # The inner function of scan should have only one output and it should
         # not be the result of a Dot
-        scan_node = [
+        scan_node = next(
             node for node in f_opt.maker.fgraph.toposort() if isinstance(node.op, Scan)
-        ][0]
+        )
         assert len(scan_node.op.inner_outputs) == 1
         assert not isinstance(scan_node.op.inner_outputs[0], Dot)
 
@@ -488,9 +488,9 @@ def inner_fct(vect, mat):
         # Ensure that the optimization was performed correctly in f_opt
         # The inner function of scan should have only one output and it should
         # not be the result of a Dot
-        scan_node = [
+        scan_node = next(
             node for node in f_opt.maker.fgraph.toposort() if isinstance(node.op, Scan)
-        ][0]
+        )
         # NOTE: WHEN INFER_SHAPE IS RE-ENABLED, BELOW THE SCAN MUST
         # HAVE ONLY 1 OUTPUT.
         assert len(scan_node.op.inner_outputs) == 2
@@ -536,9 +536,9 @@ def inner_fct(seq1, previous_output1, nonseq1):
         # Ensure that the optimization was performed correctly in f_opt
         # The inner function of scan should have only one output and it should
         # not be the result of a Dot
-        scan_node = [
+        scan_node = next(
             node for node in f_opt.maker.fgraph.toposort() if isinstance(node.op, Scan)
-        ][0]
+        )
         assert len(scan_node.op.inner_outputs) == 2
         assert not isinstance(scan_node.op.inner_outputs[0], Dot)
 
@@ -1639,7 +1639,7 @@ def lambda_fn(h, W1, W2):
     )
 
     f = function([h0, W1, W2], o, mode=get_default_mode().including("scan"))
-    scan_node = [x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan)][0]
+    scan_node = next(x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan))
     assert (
         len(
             [
@@ -1673,7 +1673,7 @@ def lambda_fn(W1, h, W2):
     )
 
     f = function([h0, W1, W2], o, mode=get_default_mode().including("scan"))
-    scan_node = [x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan)][0]
+    scan_node = next(x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan))
 
     assert (
         len(
@@ -1709,7 +1709,7 @@ def lambda_fn(W1, h, W2):
 
     # TODO FIXME: This result depends on unrelated rewrites in the "fast" mode.
     f = function([_h0, _W1, _W2], o, mode="FAST_RUN")
-    scan_node = [x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan)][0]
+    scan_node = next(x for x in f.maker.fgraph.toposort() if isinstance(x.op, Scan))
 
     assert len(scan_node.op.inner_inputs) == 1
 

tests/tensor/rewriting/test_math.py

@@ -3274,7 +3274,7 @@ def test_local_reduce_broadcast_some_0(self):
             order = f.maker.fgraph.toposort()
             assert 1 == sum(isinstance(node.op, CAReduce) for node in order)
 
-            node = [node for node in order if isinstance(node.op, CAReduce)][0]
+            node = next(node for node in order if isinstance(node.op, CAReduce))
 
             op = node.op
             assert isinstance(op, CAReduce)

tests/tensor/test_merge.py

@@ -75,7 +75,7 @@ def test_merge_with_weird_eq():
     MergeOptimizer().rewrite(g)
 
     assert len(g.apply_nodes) == 1
-    node = list(g.apply_nodes)[0]
+    node = next(iter(g.apply_nodes))
     assert len(node.inputs) == 2
     assert node.inputs[0] is node.inputs[1]
 
@@ -87,6 +87,6 @@ def test_merge_with_weird_eq():
     MergeOptimizer().rewrite(g)
 
     assert len(g.apply_nodes) == 1
-    node = list(g.apply_nodes)[0]
+    node = next(iter(g.apply_nodes))
     assert len(node.inputs) == 2
     assert node.inputs[0] is node.inputs[1]

tests/tensor/test_shape.py

@@ -465,7 +465,7 @@ def test_bad_shape(self):
             f(xval)
 
         assert isinstance(
-            [n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
+            next(n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape))
             .inputs[0]
             .type,
             self.input_type,
@@ -475,7 +475,7 @@ def test_bad_shape(self):
         xval = np.random.random((2, 3)).astype(config.floatX)
         f = pytensor.function([x], specify_shape(x, 2, 3), mode=self.mode)
         assert isinstance(
-            [n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
+            next(n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape))
             .inputs[0]
             .type,
             self.input_type,

tests/test_ifelse.py

@@ -194,7 +194,7 @@ def test_multiple_out(self):
         f = function([c, x1, x2, y1, y2], z, mode=self.mode)
         self.assertFunctionContains1(f, self.get_ifelse(2))
 
-        ifnode = [x for x in f.maker.fgraph.toposort() if isinstance(x.op, IfElse)][0]
+        ifnode = next(x for x in f.maker.fgraph.toposort() if isinstance(x.op, IfElse))
         assert len(ifnode.outputs) == 2
 
         rng = np.random.default_rng(utt.fetch_seed())
@@ -369,7 +369,7 @@ def test_remove_useless_inputs1(self):
         z = ifelse(c, (x, x), (y, y))
         f = function([c, x, y], z)
 
-        ifnode = [n for n in f.maker.fgraph.toposort() if isinstance(n.op, IfElse)][0]
+        ifnode = next(n for n in f.maker.fgraph.toposort() if isinstance(n.op, IfElse))
         assert len(ifnode.inputs) == 3
 
     @pytest.mark.skip(reason="Optimization temporarily disabled")
@@ -382,7 +382,7 @@ def test_remove_useless_inputs2(self):
         z = ifelse(c, (x1, x1, x1, x2, x2), (y1, y1, y2, y2, y2))
         f = function([c, x1, x2, y1, y2], z)
 
-        ifnode = [x for x in f.maker.fgraph.toposort() if isinstance(x.op, IfElse)][0]
+        ifnode = next(x for x in f.maker.fgraph.toposort() if isinstance(x.op, IfElse))
         assert len(ifnode.outputs) == 3
 
     @pytest.mark.skip(reason="Optimization temporarily disabled")