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
                    methods.append("")
                new_missing.append(m)
            text = "\n".join(methods)
            iflen(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
 add=value
 else:
 add=v-value
 iflen(w)>0:
 ifw:
 raiseAssertionError(
 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
 classTestDocumentationExamples(ExtTestCase):
 defrun_test(self,fold:str,name:str,verbose=0)->int:
 ppath=os.environ.get("PYTHONPATH","")
 iflen(ppath)==0:
 ifnotppath:
 os.environ["PYTHONPATH"]=ROOT
 elifROOTnotinppath:
 sep=";"ifis_windows()else":"
 res=p.communicate()
 out,err=res
 st=err.decode("ascii",errors="ignore")
 iflen(st)>0and"Traceback"inst:
 ifstand"Traceback"inst:
 if'"dot" not found in path.'inst:
 # 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
 raiseAssertionError("No exception was raised.")

 defassertEmpty(self,value:Any):
 ifvalueisNone:
 return
 iflen(value)==0:
 ifnotvalue:
 return
 raiseAssertionError(f"value is not empty:{value!r}.")

 ifvalueisNone:
 raiseAssertionError(f"value is empty:{value!r}.")
 ifisinstance(value, (list,dict,tuple,set)):
 iflen(value)==0:
 ifvalue:
 raiseAssertionError(f"value is empty:{value!r}.")

 defassertStartsWith(self,prefix:str,full:str):
diff --git a/onnx_array_api/light_api/emitter.py b/onnx_array_api/light_api/emitter.py
 ifisinstance(v,str):
 return [],f"{v!r}"
 ifisinstance(v,np.ndarray):
 iflen(v.shape)==0:
 ifnotv.shape:
 return [],str(v)
 iflen(v.shape)==1:
 ifvalue[0].typein (
diff --git a/onnx_array_api/light_api/translate.py b/onnx_array_api/light_api/translate.py
 else:
 raiseValueError(f"Unexpected type{type(self.proto_)} for proto.")

 iflen(sparse_initializers)!=0:
 ifsparse_initializers:
 raiseNotImplementedError("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
                    [(var,i,None)foriinrange(var.n_var_outputs)]
                )

 iflen(possible_types)>0:
 ifpossible_types:
 # converts possibles types into a dictionary
 map_types= {}
 forvar,i,dtinpossible_types:
diff --git a/onnx_array_api/npx/npx_helper.py b/onnx_array_api/npx/npx_helper.py
 nodes= []
 modified=False
 fornodeingraph.node:
 iflen(set(node.input)&set_rep)==0:
 ifnot(set(node.input)&set_rep):
 modified=True
 new_inputs= [replacements.get(i,i)foriinnode.input]
 atts=_process_attributes(node.attribute)ornode.attribute
 ifnotmodified:
 returnNone

 iflen(set(i.nameforiingraph.input)&set_rep)==0:
 ifnot(set(i.nameforiingraph.input)&set_rep):
 returnmake_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
        """
        self.info("+", "to_jit", args=values, kwargs=kwargs)
        annotations = self.f.__annotations__
        iflen(annotations) > 0:
        if annotations:
            input_to_kwargs = {}
            kwargs_to_input = {}
            names = list(annotations.keys())
            if iname in constraints
        ]
        names = [i.name for i in inputs]
        iflen(new_kwargs) > 0:
        if new_kwargs:
            # An attribute is not named in the numpy API
            # but is the ONNX definition.
            iflen(kwargs) == 0:
            ifnot kwargs:
                kwargs = new_kwargs
            else:
                kwargs = kwargs.copy()
            target_opsets=self.target_opsets,
            ir_version=self.ir_version,
        )
        iflen(values) > 0andlen(values[0].shape) == 0:
        if valuesandnotvalues[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)
            iflen(shape) != 0:
            if shape:
                raise RuntimeError(
                    f"Shape mismatch, values[0]={values[0]} "
                    f"and inputs={onx.graph.input}."
                f"self.input_to_kwargs_ is not initialized for function {self.f} "
                f"from module {self.f.__module__!r}."
            )
        iflen(self.input_to_kwargs_) == 0:
        ifnotself.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
            )
 ifself.shape== (0,):
 returnFalse
 iflen(self.shape)!=0:
 ifself.shape:
 warnings.warn(
 f"Conversion to bool only works for scalar, not for{self!r}, "
 f"bool(...)={bool(self._tensor)}."

 def__int__(self):
 "Implicit conversion to int."
 iflen(self.shape)!=0:
 ifself.shape:
 raiseValueError(
 f"Conversion to bool only works for scalar, not for{self!r}."
            )

 def__float__(self):
 "Implicit conversion to float."
 iflen(self.shape)!=0:
 ifself.shape:
 raiseValueError(
 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
                    f"Mismatch number of outputs, expecting {len(outputs)}, "
                    f"got ({len(onx.output)})."
                )
            iflen(g.functions_) > 0:
            if g.functions_:
                return [g.functions_, onx]
            return onx


        if not isinstance(index, tuple):
            index = (index,)
        eliflen(index) == 0:
        elifnot index:
            # The array contains a scalar and it needs to be returned.
            return var(self, op="Identity")

        starts = np.array(starts, dtype=np.int64)
        axes = np.array(axes, dtype=np.int64)

        iflen(needs_shape) > 0:
        if needs_shape:
            shape = self.shape
            conc = []
            for e in ends:
            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")
        iflen(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
    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
 fornodeinnodes:
 exp.append("")
 foroutinnode.output:
 iflen(out)>0andoutnotininter_vars:
 ifoutandoutnotininter_vars:
 inter_vars[out]=out
 sh=shapes.get(out,"")
 ifsh:
 f"{dot_name(subprefix)}{dot_name(inp2.name)};"
                    )
 forout1,out2inzip(body.output,node.output):
 iflen(out2)==0:
 ifnotout2:
 # Empty output, it cannot be used.
 continue
 exp.append(
 f"{dot_name(prefix)}{dot_name(node.name)};"
            )
 foroutinnode.output:
 iflen(out)==0:
 ifnotout:
 # 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
 defprocess_node(self):
 "node to string"
 ifself.nodes_modes=="LEAF":
 iflen(self.targets)==0:
 ifnotself.targets:
 text=f"{self.true_false}f"
 eliflen(self.targets)==1:
 t=self.targets[0]
 unknown.add(i)
 foriinn.output:
 known[i]=n
 iflen(unknown)>0:
 ifunknown:
 # These inputs are coming from the graph below.
 fornameinunknown:
 successors[name].append(parent_node_name)
 % (k,",".join(sequences[k]),list(sequences))
                )

 iflen(sequences)==0:
 ifnotsequences:
 raiseRuntimeError(# pragma: no cover
 "Unexpected empty sequence (len(possibles)=%d, "
 "len(done)=%d, len(nodes)=%d). This is usually due to "
 # if the sequence of successors is longer
 best=k
 eliflen(v)==len(sequences[best]):
 iflen(new_nodes)>0:
 ifnew_nodes:
 # then choose the next successor sharing input with
 # previous output
 so=set(new_nodes[-1].output)
 val=".%d"%att.type
 atts.append(f"{att.name}={val}")
 inputs=list(node.input)
 iflen(atts)>0:
 ifatts:
 inputs.extend(atts)
 ifnode.domainin ("","ai.onnx.ml"):
 domain=""
 indent=previous_indent
 else:
 inds= [indents.get(i,0)foriinnode.inputifinotininit_names]
 iflen(inds)==0:
 ifnotinds:
 indent=0
 else:
 mi=min(inds)
                        )
 add_break=True
 ifnotadd_breakandprevious_outisnotNone:
 iflen(set(node.input)&previous_out)==0:
 ifnot(set(node.input)&previous_out):
 ifverbose:
 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
        def _get_root(node, stor=None):
            if stor is not None:
                stor.append(node)
            iflen(node.called_by) == 0:
            ifnotnode.called_by:
                return node
            if len(node.called_by) == 1:
                return _get_root(node.called_by[0], stor=stor)
                        continue
                    child[key] = walk(n, roots_key, indent + 1)

            iflen(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
 def_process(value):
 cst=value[0]ifisinstance(value,np.ndarray)andvalue.size>0elsevalue
 ifisinstance(value,np.ndarray):
 iflen(value.shape)==0:
 ifnotvalue.shape:
 cst=value
 elifvalue.size>0:
 cst=value.ravel()[0]
diff --git a/onnx_array_api/validation/tools.py b/onnx_array_api/validation/tools.py
            doc_string=onx.doc_string,
            opset_imports=list(onx.opset_import),
        )
        iflen(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
        requirements = f.read().strip(" \n\r\t").split("\n")
 except FileNotFoundError:
    requirements = []
 iflen(requirements) == 0 or requirements == [""]:
 ifnot requirements or requirements == [""]:
    requirements = ["numpy", "scipy", "onnx"]

 try:
        for _ in [_.strip("\r\n ") for _ in f.readlines()]
        if _.startswith("__version__")
    ]
    iflen(line) > 0:
    if line:
        version_str = line[0].split("=")[1].strip('" ')
Original file line number	Diff line number	Diff line change
Expand Up		@@ -138,7 +138,7 @@ def list_ops_missing(self, n_inputs):
		methods.append("")
		new_missing.append(m)
		text = "\n".join(methods)
		iflen(new_missing) > 0:
		if new_missing:
		raise AssertionError(
		f"n_inputs={n_inputs}: missing method for operators "
		f"{new_missing}\n{text}"
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -344,7 +344,7 @@ def test_search_float32_into_fe5m2(self):
		add=value
		else:
		add=v-value
		iflen(w)>0:
		ifw:
		raiseAssertionError(
		f"A warning was thrown for v={v}, "
		f"value={value}, w={w[0]}."
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -26,7 +26,7 @@ def import_source(module_file_path, module_name):
		classTestDocumentationExamples(ExtTestCase):
		defrun_test(self,fold:str,name:str,verbose=0)->int:
		ppath=os.environ.get("PYTHONPATH","")
		iflen(ppath)==0:
		ifnotppath:
		os.environ["PYTHONPATH"]=ROOT
		elifROOTnotinppath:
		sep=";"ifis_windows()else":"
Expand All		@@ -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")
		iflen(st)>0and"Traceback"inst:
		ifstand"Traceback"inst:
		if'"dot" not found in path.'inst:
		# dot not installed, this part
		# is tested in onnx framework
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -226,9 +226,7 @@ def assertRaise(self, fct: Callable, exc_type: Exception):
		raiseAssertionError("No exception was raised.")

		defassertEmpty(self,value:Any):
		ifvalueisNone:
		return
		iflen(value)==0:
		ifnotvalue:
		return
		raiseAssertionError(f"value is not empty:{value!r}.")

Expand All		@@ -240,7 +238,7 @@ def assertNotEmpty(self, value: Any):
		ifvalueisNone:
		raiseAssertionError(f"value is empty:{value!r}.")
		ifisinstance(value, (list,dict,tuple,set)):
		iflen(value)==0:
		ifvalue:
		raiseAssertionError(f"value is empty:{value!r}.")

		defassertStartsWith(self,prefix:str,full:str):
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -85,7 +85,7 @@ def render_attribute_value(self, value: Any) -> Tuple[List[str], str]:
		ifisinstance(v,str):
		return [],f"{v!r}"
		ifisinstance(v,np.ndarray):
		iflen(v.shape)==0:
		ifnotv.shape:
		return [],str(v)
		iflen(v.shape)==1:
		ifvalue[0].typein (
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -51,7 +51,7 @@ def export(self, as_str, single_line: bool = False) -> Union[str, List[str]]:
		else:
		raiseValueError(f"Unexpected type{type(self.proto_)} for proto.")

		iflen(sparse_initializers)!=0:
		ifsparse_initializers:
		raiseNotImplementedError("Sparse initializer not supported yet.")

		rows.extend(
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -919,7 +919,7 @@ def to_onnx(
		[(var,i,None)foriinrange(var.n_var_outputs)]
		)

		iflen(possible_types)>0:
		ifpossible_types:
		# converts possibles types into a dictionary
		map_types= {}
		forvar,i,dtinpossible_types:
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -47,7 +47,7 @@ def _process_attributes(attributes):
		nodes= []
		modified=False
		fornodeingraph.node:
		iflen(set(node.input)&set_rep)==0:
		ifnot(set(node.input)&set_rep):
		modified=True
		new_inputs= [replacements.get(i,i)foriinnode.input]
		atts=_process_attributes(node.attribute)ornode.attribute
Expand All		@@ -66,7 +66,7 @@ def _process_attributes(attributes):
		ifnotmodified:
		returnNone

		iflen(set(i.nameforiingraph.input)&set_rep)==0:
		ifnot(set(i.nameforiingraph.input)&set_rep):
		returnmake_graph(nodes,graph.name,graph.input,graph.output)

		new_inputs= []
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -253,7 +253,7 @@ def to_jit(self, values, *kwargs):
		"""
		self.info("+", "to_jit", args=values, kwargs=kwargs)
		annotations = self.f.__annotations__
		iflen(annotations) > 0:
		if annotations:
		input_to_kwargs = {}
		kwargs_to_input = {}
		names = list(annotations.keys())
Expand DownExpand Up		@@ -352,10 +352,10 @@ def to_jit(self, values, *kwargs):
		if iname in constraints
		]
		names = [i.name for i in inputs]
		iflen(new_kwargs) > 0:
		if new_kwargs:
		# An attribute is not named in the numpy API
		# but is the ONNX definition.
		iflen(kwargs) == 0:
		ifnot kwargs:
		kwargs = new_kwargs
		else:
		kwargs = kwargs.copy()
Expand All		@@ -375,13 +375,13 @@ def to_jit(self, values, *kwargs):
		target_opsets=self.target_opsets,
		ir_version=self.ir_version,
		)
		iflen(values) > 0andlen(values[0].shape) == 0:
		if valuesandnotvalues[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)
		iflen(shape) != 0:
		if shape:
		raise RuntimeError(
		f"Shape mismatch, values[0]={values[0]} "
		f"and inputs={onx.graph.input}."
Expand DownExpand Up		@@ -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}."
		)
		iflen(self.input_to_kwargs_) == 0:
		ifnotself.input_to_kwargs_:
		return values, kwargs
		new_values = []
		new_kwargs = kwargs.copy()
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -220,7 +220,7 @@ def __bool__(self):
		)
		ifself.shape== (0,):
		returnFalse
		iflen(self.shape)!=0:
		ifself.shape:
		warnings.warn(
		f"Conversion to bool only works for scalar, not for{self!r}, "
		f"bool(...)={bool(self._tensor)}."
Expand All		@@ -233,7 +233,7 @@ def __bool__(self):

		def__int__(self):
		"Implicit conversion to int."
		iflen(self.shape)!=0:
		ifself.shape:
		raiseValueError(
		f"Conversion to bool only works for scalar, not for{self!r}."
		)
Expand All		@@ -255,7 +255,7 @@ def __int__(self):

		def__float__(self):
		"Implicit conversion to float."
		iflen(self.shape)!=0:
		ifself.shape:
		raiseValueError(
		f"Conversion to bool only works for scalar, not for{self!r}."
		)
Expand Down