sdpython · sdpython · Nov 13, 2023 · Nov 13, 2023 · Nov 13, 2023
diff --git a/_unittests/ut_light_api/test_light_api.py b/_unittests/ut_light_api/test_light_api.py
@@ -138,7 +138,7 @@ def list_ops_missing(self, n_inputs):
                     methods.append("")
                 new_missing.append(m)
             text = "\n".join(methods)
-            if len(new_missing) > 0:
+            if new_missing:
                 raise AssertionError(
                     f"n_inputs={n_inputs}: missing method for operators "
                     f"{new_missing}\n{text}"

diff --git a/_unittests/ut_validation/test_f8.py b/_unittests/ut_validation/test_f8.py
@@ -344,7 +344,7 @@ def test_search_float32_into_fe5m2(self):
                             add = value
                         else:
                             add = v - value
-                            if len(w) > 0:
+                            if w:
                                 raise AssertionError(
                                     f"A warning was thrown for v={v}, "
                                     f"value={value}, w={w[0]}."

diff --git a/_unittests/ut_xrun_doc/test_documentation_examples.py b/_unittests/ut_xrun_doc/test_documentation_examples.py
@@ -26,7 +26,7 @@ def import_source(module_file_path, module_name):
 class TestDocumentationExamples(ExtTestCase):
     def run_test(self, fold: str, name: str, verbose=0) -> int:
         ppath = os.environ.get("PYTHONPATH", "")
-        if len(ppath) == 0:
+        if not ppath:
             os.environ["PYTHONPATH"] = ROOT
         elif ROOT not in ppath:
             sep = ";" if is_windows() else ":"
@@ -42,7 +42,7 @@ def run_test(self, fold: str, name: str, verbose=0) -> int:
             res = p.communicate()
             out, err = res
             st = err.decode("ascii", errors="ignore")
-            if len(st) > 0 and "Traceback" in st:
+            if st and "Traceback" in st:
                 if '"dot" not found in path.' in st:
                     # dot not installed, this part
                     # is tested in onnx framework

diff --git a/onnx_array_api/ext_test_case.py b/onnx_array_api/ext_test_case.py
@@ -226,9 +226,7 @@ def assertRaise(self, fct: Callable, exc_type: Exception):
         raise AssertionError("No exception was raised.")
 
     def assertEmpty(self, value: Any):
-        if value is None:
-            return
-        if len(value) == 0:
+        if not value:
             return
         raise AssertionError(f"value is not empty: {value!r}.")
 
@@ -240,7 +238,7 @@ def assertNotEmpty(self, value: Any):
         if value is None:
             raise AssertionError(f"value is empty: {value!r}.")
         if isinstance(value, (list, dict, tuple, set)):
-            if len(value) == 0:
+            if value:
                 raise AssertionError(f"value is empty: {value!r}.")
 
     def assertStartsWith(self, prefix: str, full: str):

diff --git a/onnx_array_api/light_api/emitter.py b/onnx_array_api/light_api/emitter.py
@@ -85,7 +85,7 @@ def render_attribute_value(self, value: Any) -> Tuple[List[str], str]:
         if isinstance(v, str):
             return [], f"{v!r}"
         if isinstance(v, np.ndarray):
-            if len(v.shape) == 0:
+            if not v.shape:
                 return [], str(v)
             if len(v.shape) == 1:
                 if value[0].type in (

diff --git a/onnx_array_api/light_api/translate.py b/onnx_array_api/light_api/translate.py
@@ -51,7 +51,7 @@ def export(self, as_str, single_line: bool = False) -> Union[str, List[str]]:
         else:
             raise ValueError(f"Unexpected type {type(self.proto_)} for proto.")
 
-        if len(sparse_initializers) != 0:
+        if sparse_initializers:
             raise NotImplementedError("Sparse initializer not supported yet.")
 
         rows.extend(

diff --git a/onnx_array_api/npx/npx_graph_builder.py b/onnx_array_api/npx/npx_graph_builder.py
@@ -919,7 +919,7 @@ def to_onnx(
                     [(var, i, None) for i in range(var.n_var_outputs)]
                 )
 
-        if len(possible_types) > 0:
+        if possible_types:
             # converts possibles types into a dictionary
             map_types = {}
             for var, i, dt in possible_types:

diff --git a/onnx_array_api/npx/npx_helper.py b/onnx_array_api/npx/npx_helper.py
@@ -47,7 +47,7 @@ def _process_attributes(attributes):
     nodes = []
     modified = False
     for node in graph.node:
-        if len(set(node.input) & set_rep) == 0:
+        if not (set(node.input) & set_rep):
             modified = True
             new_inputs = [replacements.get(i, i) for i in node.input]
             atts = _process_attributes(node.attribute) or node.attribute
@@ -66,7 +66,7 @@ def _process_attributes(attributes):
     if not modified:
         return None
 
-    if len(set(i.name for i in graph.input) & set_rep) == 0:
+    if not (set(i.name for i in graph.input) & set_rep):
         return make_graph(nodes, graph.name, graph.input, graph.output)
 
     new_inputs = []

diff --git a/onnx_array_api/npx/npx_jit_eager.py b/onnx_array_api/npx/npx_jit_eager.py
@@ -253,7 +253,7 @@ def to_jit(self, *values, **kwargs):
         """
         self.info("+", "to_jit", args=values, kwargs=kwargs)
         annotations = self.f.__annotations__
-        if len(annotations) > 0:
+        if annotations:
             input_to_kwargs = {}
             kwargs_to_input = {}
             names = list(annotations.keys())
@@ -352,10 +352,10 @@ def to_jit(self, *values, **kwargs):
             if iname in constraints
         ]
         names = [i.name for i in inputs]
-        if len(new_kwargs) > 0:
+        if new_kwargs:
             # An attribute is not named in the numpy API
             # but is the ONNX definition.
-            if len(kwargs) == 0:
+            if not kwargs:
                 kwargs = new_kwargs
             else:
                 kwargs = kwargs.copy()
@@ -375,13 +375,13 @@ def to_jit(self, *values, **kwargs):
             target_opsets=self.target_opsets,
             ir_version=self.ir_version,
         )
-        if len(values) > 0 and len(values[0].shape) == 0:
+        if values and not values[0].shape:
             inps = onx.graph.input[0]
             shape = []
             for d in inps.type.tensor_type.shape.dim:
                 v = d.dim_value if d.dim_value > 0 else d.dim_param
                 shape.append(v)
-            if len(shape) != 0:
+            if shape:
                 raise RuntimeError(
                     f"Shape mismatch, values[0]={values[0]} "
                     f"and inputs={onx.graph.input}."
@@ -441,7 +441,7 @@ def move_input_to_kwargs(
                 f"self.input_to_kwargs_ is not initialized for function {self.f} "
                 f"from module {self.f.__module__!r}."
             )
-        if len(self.input_to_kwargs_) == 0:
+        if not self.input_to_kwargs_:
             return values, kwargs
         new_values = []
         new_kwargs = kwargs.copy()

diff --git a/onnx_array_api/npx/npx_numpy_tensors.py b/onnx_array_api/npx/npx_numpy_tensors.py
@@ -220,7 +220,7 @@ def __bool__(self):
             )
         if self.shape == (0,):
             return False
-        if len(self.shape) != 0:
+        if self.shape:
             warnings.warn(
                 f"Conversion to bool only works for scalar, not for {self!r}, "
                 f"bool(...)={bool(self._tensor)}."
@@ -233,7 +233,7 @@ def __bool__(self):
 
     def __int__(self):
         "Implicit conversion to int."
-        if len(self.shape) != 0:
+        if self.shape:
             raise ValueError(
                 f"Conversion to bool only works for scalar, not for {self!r}."
             )
@@ -255,7 +255,7 @@ def __int__(self):
 
     def __float__(self):
         "Implicit conversion to float."
-        if len(self.shape) != 0:
+        if self.shape:
             raise ValueError(
                 f"Conversion to bool only works for scalar, not for {self!r}."
             )

diff --git a/onnx_array_api/npx/npx_var.py b/onnx_array_api/npx/npx_var.py
@@ -174,7 +174,7 @@ def to_onnx(
                     f"Mismatch number of outputs, expecting {len(outputs)}, "
                     f"got ({len(onx.output)})."
                 )
-            if len(g.functions_) > 0:
+            if g.functions_:
                 return [g.functions_, onx]
             return onx
 
@@ -1020,7 +1020,7 @@ def __getitem__(self, index: Any) -> "Var":
 
         if not isinstance(index, tuple):
             index = (index,)
-        elif len(index) == 0:
+        elif not index:
             # The array contains a scalar and it needs to be returned.
             return var(self, op="Identity")
 
@@ -1091,7 +1091,7 @@ def __getitem__(self, index: Any) -> "Var":
         starts = np.array(starts, dtype=np.int64)
         axes = np.array(axes, dtype=np.int64)
 
-        if len(needs_shape) > 0:
+        if needs_shape:
             shape = self.shape
             conc = []
             for e in ends:
@@ -1116,7 +1116,7 @@ def __getitem__(self, index: Any) -> "Var":
             sliced_args.append(steps)
         sliced_args_cst = [v if isinstance(v, Var) else cst(v) for v in sliced_args]
         sliced = var(self.self_var, *sliced_args_cst, op="Slice")
-        if len(axis_squeeze) > 0:
+        if axis_squeeze:
             return var(
                 sliced,
                 cst(np.array(axis_squeeze, dtype=np.int64)),

diff --git a/onnx_array_api/plotting/_helper.py b/onnx_array_api/plotting/_helper.py
@@ -120,10 +120,7 @@ def get_tensor_shape(obj):
     for d in obj.tensor_type.shape.dim:
         v = d.dim_value if d.dim_value > 0 else d.dim_param
         shape.append(v)
-    if len(shape) == 0:
-        shape = None
-    else:
-        shape = list(None if s == 0 else s for s in shape)
+    shape = None if not shape else list(None if s == 0 else s for s in shape)
     return shape
 
 

diff --git a/onnx_array_api/plotting/dot_plot.py b/onnx_array_api/plotting/dot_plot.py
@@ -242,7 +242,7 @@ def dot_label(text):
     for node in nodes:
         exp.append("")
         for out in node.output:
-            if len(out) > 0 and out not in inter_vars:
+            if out and out not in inter_vars:
                 inter_vars[out] = out
                 sh = shapes.get(out, "")
                 if sh:
@@ -318,7 +318,7 @@ def dot_label(text):
                         f"{dot_name(subprefix)}{dot_name(inp2.name)};"
                     )
                 for out1, out2 in zip(body.output, node.output):
-                    if len(out2) == 0:
+                    if not out2:
                         # Empty output, it cannot be used.
                         continue
                     exp.append(
@@ -346,7 +346,7 @@ def dot_label(text):
                 f"{dot_name(prefix)}{dot_name(node.name)};"
             )
         for out in node.output:
-            if len(out) == 0:
+            if not out:
                 # Empty output, it cannot be used.
                 continue
             exp.append(

diff --git a/onnx_array_api/plotting/text_plot.py b/onnx_array_api/plotting/text_plot.py
@@ -75,7 +75,7 @@ def append_target(self, tid, weight):
         def process_node(self):
             "node to string"
             if self.nodes_modes == "LEAF":
-                if len(self.targets) == 0:
+                if not self.targets:
                     text = f"{self.true_false}f"
                 elif len(self.targets) == 1:
                     t = self.targets[0]
@@ -264,7 +264,7 @@ def _append_succ_pred_s(
                     unknown.add(i)
             for i in n.output:
                 known[i] = n
-        if len(unknown) > 0:
+        if unknown:
             # These inputs are coming from the graph below.
             for name in unknown:
                 successors[name].append(parent_node_name)
@@ -402,7 +402,7 @@ def _find_sequence(node_name, known, done):
                     % (k, ",".join(sequences[k]), list(sequences))
                 )
 
-        if len(sequences) == 0:
+        if not sequences:
             raise RuntimeError(  # pragma: no cover
                 "Unexpected empty sequence (len(possibles)=%d, "
                 "len(done)=%d, len(nodes)=%d). This is usually due to "
@@ -417,7 +417,7 @@ def _find_sequence(node_name, known, done):
                 # if the sequence of successors is longer
                 best = k
             elif len(v) == len(sequences[best]):
-                if len(new_nodes) > 0:
+                if new_nodes:
                     # then choose the next successor sharing input with
                     # previous output
                     so = set(new_nodes[-1].output)
@@ -808,7 +808,7 @@ def str_node(indent, node):
                     val = ".%d" % att.type
                 atts.append(f"{att.name}={val}")
         inputs = list(node.input)
-        if len(atts) > 0:
+        if atts:
             inputs.extend(atts)
         if node.domain in ("", "ai.onnx.ml"):
             domain = ""
@@ -917,7 +917,7 @@ def str_node(indent, node):
             indent = previous_indent
         else:
             inds = [indents.get(i, 0) for i in node.input if i not in init_names]
-            if len(inds) == 0:
+            if not inds:
                 indent = 0
             else:
                 mi = min(inds)
@@ -929,7 +929,7 @@ def str_node(indent, node):
                         )
                     add_break = True
             if not add_break and previous_out is not None:
-                if len(set(node.input) & previous_out) == 0:
+                if not (set(node.input) & previous_out):
                     if verbose:
                         print(f"[onnx_simple_text_plot] break3 {node.op_type}")
                     add_break = True

diff --git a/onnx_array_api/profiling.py b/onnx_array_api/profiling.py
@@ -71,7 +71,7 @@ def get_root(self):
         def _get_root(node, stor=None):
             if stor is not None:
                 stor.append(node)
-            if len(node.called_by) == 0:
+            if not node.called_by:
                 return node
             if len(node.called_by) == 1:
                 return _get_root(node.called_by[0], stor=stor)
@@ -383,7 +383,7 @@ def walk(node, roots_keys, indent=0):
                         continue
                     child[key] = walk(n, roots_key, indent + 1)
 
-            if len(child) > 0:
+            if child:
                 mx = max(_[0] for _ in child)
                 dg = int(math.log(mx) / math.log(10) + 1.5)
                 form = f"%-{dg}d-%s"

diff --git a/onnx_array_api/reference/ops/op_constant_of_shape.py b/onnx_array_api/reference/ops/op_constant_of_shape.py
@@ -7,7 +7,7 @@ class ConstantOfShape(OpRun):
     def _process(value):
         cst = value[0] if isinstance(value, np.ndarray) and value.size > 0 else value
         if isinstance(value, np.ndarray):
-            if len(value.shape) == 0:
+            if not value.shape:
                 cst = value
             elif value.size > 0:
                 cst = value.ravel()[0]

diff --git a/onnx_array_api/validation/tools.py b/onnx_array_api/validation/tools.py
@@ -49,7 +49,7 @@ def randomize_proto(
             doc_string=onx.doc_string,
             opset_imports=list(onx.opset_import),
         )
-        if len(onx.metadata_props) > 0:
+        if onx.metadata_props:
             values = {p.key: p.value for p in onx.metadata_props}
             set_model_props(onnx_model, values)
         return onnx_model

diff --git a/setup.py b/setup.py
@@ -18,7 +18,7 @@
         requirements = f.read().strip(" \n\r\t").split("\n")
 except FileNotFoundError:
     requirements = []
-if len(requirements) == 0 or requirements == [""]:
+if not requirements or requirements == [""]:
     requirements = ["numpy", "scipy", "onnx"]
 
 try:
@@ -34,7 +34,7 @@
         for _ in [_.strip("\r\n ") for _ in f.readlines()]
         if _.startswith("__version__")
     ]
-    if len(line) > 0:
+    if line:
         version_str = line[0].split("=")[1].strip('" ')