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1 change: 0 additions & 1 deletion _doc/examples/plot_onnx_diff.py
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Expand Up @@ -19,7 +19,6 @@
from onnx_array_api.reference import compare_onnx_execution
from onnx_array_api.plotting.text_plot import onnx_simple_text_plot


data = load_iris()
X_train, X_test = train_test_split(data.data)
model = GaussianMixture()
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1 change: 0 additions & 1 deletion _doc/examples/plot_optimization.py
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Expand Up @@ -29,7 +29,6 @@
from onnx_array_api.ext_test_case import measure_time
from onnx_array_api.ort.ort_optimizers import ort_optimized_model


filename = example_path("data/small.onnx")
optimized = filename + ".optimized.onnx"

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1 change: 0 additions & 1 deletion _doc/examples/plot_profiling.py
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Expand Up @@ -25,7 +25,6 @@
from onnx_array_api.ort.ort_profile import ort_profile, merge_ort_profile
from onnx_array_api.plotting.stat_plot import plot_ort_profile


suffix = ""
filename = example_path(f"data/small{suffix}.onnx")
optimized = filename + ".optimized.onnx"
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36 changes: 12 additions & 24 deletions _unittests/ut_graph_api/test_graph_builder.py
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Expand Up @@ -18,44 +18,38 @@ def call_optimizer(self, onx):
return gr.to_onnx()

def test_remove_unused_nodes(self):
model = onnx.parser.parse_model(
"""
model = onnx.parser.parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
four = Add(two, two)
z = Mul(x, x)
}"""
)
}""")
onx = self.call_optimizer(model)
self.assertEqual(len(onx.graph.node), 1)
self.assertEqual(onx.graph.node[0].op_type, "Mul")

def test_initializers(self):
model = onnx.parser.parse_model(
"""
model = onnx.parser.parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z)
<float two = {2.0}> {
four = Add(two, two)
z = Mul(x, x)
}"""
)
}""")
self.assertEqual(len(model.graph.initializer), 1)
onx = self.call_optimizer(model)
self.assertEqual(len(onx.graph.node), 1)
self.assertEqual(onx.graph.node[0].op_type, "Mul")
self.assertEqual(len(onx.graph.initializer), 0)

def test_keep_unused_outputs(self):
model = onnx.parser.parse_model(
"""
model = onnx.parser.parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[M] z) {
w1, w2, w3 = Split (x)
z = Mul(w3, w3)
}"""
)
}""")
onx = self.call_optimizer(model)
self.assertEqual(len(onx.graph.node), 2)
self.assertEqual(onx.graph.node[0].op_type, "Split")
Expand Down Expand Up @@ -381,30 +375,26 @@ def test_make_nodes_noprefix(self):
self.assertEqualArray(expected, got[0])

def test_node_pattern(self):
model = onnx.parser.parse_model(
"""
model = onnx.parser.parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
four = Add(two, two)
z = Mul(x, four)
}"""
)
}""")
gr = GraphBuilder(model)
p = gr.np(index=0)
r = repr(p)
self.assertEqual("NodePattern(index=0, op_type=None, name=None)", r)

def test_update_node_attribute(self):
model = onnx.parser.parse_model(
"""
model = onnx.parser.parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
four = Add(two, two)
z = Mul(x, four)
}"""
)
}""")
gr = GraphBuilder(model)
self.assertEqual(len(gr.nodes), 3)
m = gr.update_attribute(gr.np(op_type="Constant"), value_float=float(1))
Expand All @@ -416,15 +406,13 @@ def test_update_node_attribute(self):
self.assertIn("f: 1", str(node))

def test_delete_node_attribute(self):
model = onnx.parser.parse_model(
"""
model = onnx.parser.parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
four = Add(two, two)
z = Mul(x, four)
}"""
)
}""")
gr = GraphBuilder(model)
self.assertEqual(len(gr.nodes), 3)
m = gr.update_attribute(
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1 change: 0 additions & 1 deletion _unittests/ut_npx/test_sklearn_array_api.py
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Expand Up @@ -7,7 +7,6 @@
from onnx_array_api.ext_test_case import ExtTestCase, ignore_warnings
from onnx_array_api.npx.npx_numpy_tensors import EagerNumpyTensor


DEFAULT_OPSET = onnx_opset_version()


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1 change: 0 additions & 1 deletion _unittests/ut_ort/test_ort_optimizer.py
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Expand Up @@ -6,7 +6,6 @@
from onnx_array_api.ext_test_case import ExtTestCase
from onnx_array_api.ort.ort_optimizers import ort_optimized_model


DEFAULT_OPSET = onnx_opset_version()


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1 change: 0 additions & 1 deletion _unittests/ut_ort/test_sklearn_array_api_ort.py
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Expand Up @@ -7,7 +7,6 @@
from onnx_array_api.ext_test_case import ExtTestCase, skipif_ci_windows
from onnx_array_api.ort.ort_tensors import EagerOrtTensor, OrtTensor


DEFAULT_OPSET = onnx_opset_version()


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6 changes: 2 additions & 4 deletions _unittests/ut_plotting/test_graphviz.py
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Expand Up @@ -13,15 +13,13 @@
class TestGraphviz(ExtTestCase):
@classmethod
def _get_graph(cls):
return onnx.parser.parse_model(
"""
return onnx.parser.parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
four = Add(two, two)
z = Mul(x, x)
}"""
)
}""")

@skipif_ci_windows("graphviz not installed")
@skipif_ci_apple("graphviz not installed")
Expand Down
48 changes: 16 additions & 32 deletions _unittests/ut_plotting/test_text_plot.py
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Expand Up @@ -69,8 +69,7 @@ def test_onnx_text_plot_tree_cls_2(self):
model_def = load(f)
res = onnx_text_plot_tree(model_def.graph.node[0])
self.assertIn("n_classes=3", res)
expected = textwrap.dedent(
"""
expected = textwrap.dedent("""
n_classes=3
n_trees=1
----
Expand All @@ -92,8 +91,7 @@ def test_onnx_text_plot_tree_cls_2(self):
-f 0:0 1:0 2:1
+f 0:0 1:1 2:0
+f 0:1 1:0 2:0
"""
).strip(" \n\r")
""").strip(" \n\r")
res = res.replace("np.float32(", "").replace(")", "")
self.assertEqual(expected, res.strip(" \n\r"))

Expand All @@ -104,39 +102,33 @@ def test_onnx_simple_text_plot_kmeans(self):
model.fit(x)
onx = to_onnx(model, x.astype(numpy.float32), target_opset=15)
text = onnx_simple_text_plot(onx)
expected1 = textwrap.dedent(
"""
expected1 = textwrap.dedent("""
ReduceSumSquare(X, axes=[1], keepdims=1) -> Re_reduced0
Mul(Re_reduced0, Mu_Mulcst) -> Mu_C0
Gemm(X, Ge_Gemmcst, Mu_C0, alpha=-2.00, transB=1) -> Ge_Y0
Add(Re_reduced0, Ge_Y0) -> Ad_C01
Add(Ad_Addcst, Ad_C01) -> Ad_C0
Sqrt(Ad_C0) -> scores
ArgMin(Ad_C0, axis=1, keepdims=0) -> label
"""
).strip(" \n")
expected2 = textwrap.dedent(
"""
""").strip(" \n")
expected2 = textwrap.dedent("""
ReduceSumSquare(X, axes=[1], keepdims=1) -> Re_reduced0
Mul(Re_reduced0, Mu_Mulcst) -> Mu_C0
Gemm(X, Ge_Gemmcst, Mu_C0, alpha=-2.00, transB=1) -> Ge_Y0
Add(Re_reduced0, Ge_Y0) -> Ad_C01
Add(Ad_Addcst, Ad_C01) -> Ad_C0
Sqrt(Ad_C0) -> scores
ArgMin(Ad_C0, axis=1, keepdims=0) -> label
"""
).strip(" \n")
expected3 = textwrap.dedent(
"""
""").strip(" \n")
expected3 = textwrap.dedent("""
ReduceSumSquare(X, axes=[1], keepdims=1) -> Re_reduced0
Mul(Re_reduced0, Mu_Mulcst) -> Mu_C0
Gemm(X, Ge_Gemmcst, Mu_C0, alpha=-2.00, transB=1) -> Ge_Y0
Add(Re_reduced0, Ge_Y0) -> Ad_C01
Add(Ad_Addcst, Ad_C01) -> Ad_C0
ArgMin(Ad_C0, axis=1, keepdims=0) -> label
Sqrt(Ad_C0) -> scores
"""
).strip(" \n")
""").strip(" \n")
if expected1 not in text and expected2 not in text and expected3 not in text:
raise AssertionError(f"Unexpected value:\n{text}")

Expand Down Expand Up @@ -165,17 +157,15 @@ def test_onnx_simple_text_plot_toy(self):
{"X": x.astype(numpy.float32)}, outputs={"Y": x}, target_opset=15
)
text = onnx_simple_text_plot(onx, verbose=False)
expected = textwrap.dedent(
"""
expected = textwrap.dedent("""
Add(X, Ad_Addcst) -> Ad_C0
Abs(Ad_C0) -> Ab_Y0
Identity(Ad_Addcst) -> Su_Subcst
Sub(X, Su_Subcst) -> Su_C0
Abs(Su_C0) -> Ab_Y02
Div(Ab_Y0, Ab_Y02) -> Di_C0
Abs(Di_C0) -> Y
"""
).strip(" \n")
""").strip(" \n")
self.assertIn(expected, text)
text2, out, err = self.capture(lambda: onnx_simple_text_plot(onx, verbose=True))
self.assertEqual(text, text2)
Expand All @@ -188,11 +178,9 @@ def test_onnx_simple_text_plot_leaky(self):
{"X": FloatTensorType()}, outputs={"Y": FloatTensorType()}, target_opset=15
)
text = onnx_simple_text_plot(onx)
expected = textwrap.dedent(
"""
expected = textwrap.dedent("""
LeakyRelu(X, alpha=0.50) -> Y
"""
).strip(" \n")
""").strip(" \n")
self.assertIn(expected, text)

def test_onnx_text_plot_io(self):
Expand All @@ -201,11 +189,9 @@ def test_onnx_text_plot_io(self):
{"X": FloatTensorType()}, outputs={"Y": FloatTensorType()}, target_opset=15
)
text = onnx_text_plot_io(onx)
expected = textwrap.dedent(
"""
expected = textwrap.dedent("""
input:
"""
).strip(" \n")
""").strip(" \n")
self.assertIn(expected, text)

def test_onnx_simple_text_plot_if(self):
Expand Down Expand Up @@ -244,11 +230,9 @@ def test_onnx_simple_text_plot_if(self):
{"x1": x1, "x2": x2}, target_opset=opv, outputs=[("y", FloatTensorType())]
)
text = onnx_simple_text_plot(model_def)
expected = textwrap.dedent(
"""
expected = textwrap.dedent("""
input:
"""
).strip(" \n")
""").strip(" \n")
self.assertIn(expected, text)
self.assertIn("If(Gr_C0, else_branch=G1, then_branch=G2)", text)

Expand Down
30 changes: 9 additions & 21 deletions _unittests/ut_reference/test_evaluator_yield.py
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Expand Up @@ -431,55 +431,43 @@ def test_distance_sequence_str(self):
005=|RESULTfloat322:2x2CEIOLinearRegressioY1|RESULTfloat322:2x2CEIOLinearRegressioY1
006~|RESULTfloat322:2x2CEIOAbsY|RESULTfloat322:2x3CEIPAbsZ
007~|OUTPUTfloat322:2x2CEIOY|OUTPUTfloat322:2x2CEIPY
""".replace(
" ", ""
).strip(
"\n "
)
""".replace(" ", "").strip("\n ")
self.maxDiff = None
self.assertEqual(expected, text.replace(" ", "").strip("\n"))

def test_compare_execution(self):
m1 = parse_model(
"""
m1 = parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
four = Add(two, two)
z = Mul(x, x)
}"""
)
m2 = parse_model(
"""
}""")
m2 = parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
z = Mul(x, x)
}"""
)
}""")
res1, res2, align, dc = compare_onnx_execution(m1, m2)
text = dc.to_str(res1, res2, align)
self.assertIn("CAAA Constant", text)
self.assertEqual(len(align), 5)

def test_compare_execution_discrepancies(self):
m1 = parse_model(
"""
m1 = parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
four = Add(two, two)
z = Mul(x, x)
}"""
)
m2 = parse_model(
"""
}""")
m2 = parse_model("""
<ir_version: 8, opset_import: [ "": 18]>
agraph (float[N] x) => (float[N] z) {
two = Constant <value_float=2.0> ()
z = Mul(x, x)
}"""
)
}""")
res1, res2, align, dc = compare_onnx_execution(m1, m2, keep_tensor=True)
text = dc.to_str(res1, res2, align)
print(text)
Expand Down
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