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Improves onnx_simple_text_plot (#91)
* Improves onnx_simple_text_plot * add doc_string * improve display * add complex * add missing line * complex * complex * fix unwanted code
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11 files changed

+78
-9
lines changed

11 files changed

+78
-9
lines changed

‎onnx_array_api/_helpers.py

Lines changed: 4 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -40,6 +40,10 @@ def np_dtype_to_tensor_dtype(dtype: Any):
4040
dt = TensorProto.INT64
4141
elif dtype is float:
4242
dt = TensorProto.DOUBLE
43+
elif dtype == np.complex64:
44+
dt = TensorProto.COMPLEX64
45+
elif dtype == np.complex128:
46+
dt = TensorProto.COMPLEX128
4347
else:
4448
raise KeyError(f"Unable to guess type for dtype={dtype}.") # noqa: B904
4549
return dt

‎onnx_array_api/annotations.py

Lines changed: 2 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -64,6 +64,8 @@ def wrapper(self, *args: List[Any], **kwargs: Dict[str, Any]) -> Any:
6464
np.uint64: TensorProto.UINT64,
6565
np.bool_: TensorProto.BOOL,
6666
np.str_: TensorProto.STRING,
67+
np.complex64: TensorProto.COMPLEX64,
68+
np.complex128: TensorProto.COMPLEX128,
6769
}
6870

6971

‎onnx_array_api/array_api/__init__.py

Lines changed: 4 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -47,6 +47,8 @@ def _finfo(dtype):
4747
continue
4848
if isinstance(v, (np.float32, np.float64, np.float16)):
4949
d[k] = float(v)
50+
elif isinstance(v, (np.complex128, np.complex64)):
51+
d[k] = complex(v)
5052
else:
5153
d[k] = v
5254
d["dtype"] = DType(np_dtype_to_tensor_dtype(dt))
@@ -124,6 +126,8 @@ def _finalize_array_api(module, function_names, TEagerTensor):
124126
module.float16 = DType(TensorProto.FLOAT16)
125127
module.float32 = DType(TensorProto.FLOAT)
126128
module.float64 = DType(TensorProto.DOUBLE)
129+
module.complex64 = DType(TensorProto.COMPLEX64)
130+
module.complex128 = DType(TensorProto.COMPLEX128)
127131
module.int8 = DType(TensorProto.INT8)
128132
module.int16 = DType(TensorProto.INT16)
129133
module.int32 = DType(TensorProto.INT32)

‎onnx_array_api/array_api/_onnx_common.py

Lines changed: 2 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -93,6 +93,8 @@ def asarray(
9393
v = TEagerTensor(va)
9494
elif isinstance(a, float):
9595
v = TEagerTensor(np.array(a, dtype=np.float64))
96+
elif isinstance(a, complex):
97+
v = TEagerTensor(np.array(a, dtype=np.complex128))
9698
elif isinstance(a, bool):
9799
v = TEagerTensor(np.array(a, dtype=np.bool_))
98100
elif isinstance(a, str):

‎onnx_array_api/graph_api/graph_builder.py

Lines changed: 0 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -536,7 +536,6 @@ def make_nodes(
536536
if isinstance(value, TensorProto):
537537
value.name = name
538538
self.initializers_dict[name] = value
539-
540539
self.constants_[name] = None
541540
self.set_shape(name, builder._known_shapes[init])
542541
self.set_type(name, builder._known_types[init])

‎onnx_array_api/npx/npx_jit_eager.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -167,7 +167,7 @@ def make_key(self, *values: List[Any], **kwargs: Dict[str, Any]) -> Tuple[Any, .
167167
f"to the attribute list, v={v}."
168168
)
169169
res.append(v.key)
170-
elif isinstance(v, (int, float, bool, DType)):
170+
elif isinstance(v, (int, float, bool, complex, DType)):
171171
if iv in self.kwargs_to_input_:
172172
res.append(self.kwargs_to_input_[iv])
173173
res.append(type(v))
@@ -204,7 +204,7 @@ def make_key(self, *values: List[Any], **kwargs: Dict[str, Any]) -> Tuple[Any, .
204204
if k in self.kwargs_to_input_:
205205
res.append(type(v))
206206
res.append(v)
207-
elif isinstance(v, (int, float, str, type, bool, DType)):
207+
elif isinstance(v, (int, float, str, type, bool, complex, DType)):
208208
res.append(k)
209209
res.append(type(v))
210210
res.append(v)

‎onnx_array_api/npx/npx_numpy_tensors.py

Lines changed: 22 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -265,13 +265,35 @@ def __float__(self):
265265
DType(TensorProto.DOUBLE),
266266
DType(TensorProto.FLOAT16),
267267
DType(TensorProto.BFLOAT16),
268+
DType(TensorProto.COMPLEX64),
269+
DType(TensorProto.COMPLEX128),
268270
}:
269271
raise TypeError(
270272
f"Conversion to float only works for float scalar, "
271273
f"not for dtype={self.dtype}."
272274
)
273275
return float(self._tensor)
274276

277+
def __complex__(self):
278+
"Implicit conversion to complex."
279+
if self.shape:
280+
raise ValueError(
281+
f"Conversion to bool only works for scalar, not for {self!r}."
282+
)
283+
if self.dtype not in {
284+
DType(TensorProto.FLOAT),
285+
DType(TensorProto.DOUBLE),
286+
DType(TensorProto.FLOAT16),
287+
DType(TensorProto.BFLOAT16),
288+
DType(TensorProto.COMPLEX64),
289+
DType(TensorProto.COMPLEX128),
290+
}:
291+
raise TypeError(
292+
f"Conversion to float only works for float scalar, "
293+
f"not for dtype={self.dtype}."
294+
)
295+
return complex(self._tensor)
296+
275297
def __iter__(self):
276298
"""
277299
The :epkg:`Array API` does not define this function (2022/12).

‎onnx_array_api/npx/npx_var.py

Lines changed: 4 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1171,13 +1171,17 @@ def __init__(self, cst: Any):
11711171
Var.__init__(self, np.array(cst, dtype=np.int64), op="Identity")
11721172
elif isinstance(cst, float):
11731173
Var.__init__(self, np.array(cst, dtype=np.float64), op="Identity")
1174+
elif isinstance(cst, complex):
1175+
Var.__init__(self, np.array(cst, dtype=np.complex128), op="Identity")
11741176
elif isinstance(cst, list):
11751177
if all(isinstance(t, bool) for t in cst):
11761178
Var.__init__(self, np.array(cst, dtype=np.bool_), op="Identity")
11771179
elif all(isinstance(t, (int, bool)) for t in cst):
11781180
Var.__init__(self, np.array(cst, dtype=np.int64), op="Identity")
11791181
elif all(isinstance(t, (float, int, bool)) for t in cst):
11801182
Var.__init__(self, np.array(cst, dtype=np.float64), op="Identity")
1183+
elif all(isinstance(t, (float, int, bool, complex)) for t in cst):
1184+
Var.__init__(self, np.array(cst, dtype=np.complex128), op="Identity")
11811185
else:
11821186
raise ValueError(
11831187
f"Unable to convert cst (type={type(cst)}), value={cst}."

‎onnx_array_api/plotting/text_plot.py

Lines changed: 28 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -824,7 +824,10 @@ def str_node(indent, node):
824824
rows.append(f"opset: domain={opset.domain!r} version={opset.version!r}")
825825
if hasattr(model, "graph"):
826826
if model.doc_string:
827-
rows.append(f"doc_string: {model.doc_string}")
827+
if len(model.doc_string) < 55:
828+
rows.append(f"doc_string: {model.doc_string}")
829+
else:
830+
rows.append(f"doc_string: {model.doc_string[:55]}...")
828831
main_model = model
829832
model = model.graph
830833
else:
@@ -861,9 +864,16 @@ def str_node(indent, node):
861864
else:
862865
content = ""
863866
line_name_new[init.name] = len(rows)
867+
if init.doc_string:
868+
t = (
869+
f"init: name={init.name!r} type={_get_type(init)} "
870+
f"shape={_get_shape(init)}{content}"
871+
)
872+
rows.append(f"{t}{' ' * max(0, 70 - len(t))}-- {init.doc_string}")
873+
continue
864874
rows.append(
865-
"init: name=%r type=%r shape=%r%s"
866-
% (init.name, _get_type(init), _get_shape(init), content)
875+
f"init: name={init.name!r} type={_get_type(init)} "
876+
f"shape={_get_shape(init)}{content}"
867877
)
868878
if level == 0:
869879
rows.append("----- main graph ----")
@@ -1044,7 +1054,10 @@ def _mark_link(rows, lengths, r1, r2, d):
10441054
for fct in main_model.functions:
10451055
rows.append(f"----- function name={fct.name} domain={fct.domain}")
10461056
if fct.doc_string:
1047-
rows.append(f"----- doc_string: {fct.doc_string}")
1057+
if len(fct.doc_string) < 55:
1058+
rows.append(f"----- doc_string: {fct.doc_string}")
1059+
else:
1060+
rows.append(f"----- doc_string: {fct.doc_string[:55]}...")
10481061
res = onnx_simple_text_plot(
10491062
fct,
10501063
verbose=verbose,
@@ -1103,10 +1116,19 @@ def onnx_text_plot_io(model, verbose=False, att_display=None):
11031116
)
11041117
# initializer
11051118
for init in model.initializer:
1119+
1120+
if init.doc_string:
1121+
t = (
1122+
f"init: name={init.name!r} type={_get_type(init)} "
1123+
f"shape={_get_shape(init)}"
1124+
)
1125+
rows.append(f"{t}{' ' * max(0, 70 - len(t))}-- {init.doc_string}")
1126+
continue
11061127
rows.append(
1107-
"init: name=%r type=%r shape=%r"
1108-
% (init.name, _get_type(init), _get_shape(init))
1128+
f"init: name={init.name!r} type={_get_type(init)} "
1129+
f"shape={_get_shape(init)}"
11091130
)
1131+
11101132
# outputs
11111133
for out in model.output:
11121134
rows.append(

‎onnx_array_api/reference/evaluator_yield.py

Lines changed: 6 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -485,6 +485,12 @@ def generate_input(info: ValueInfoProto) -> np.ndarray:
485485
return (value.astype(np.float16) / p).astype(np.float16).reshape(new_shape)
486486
if elem_type == TensorProto.DOUBLE:
487487
return (value.astype(np.float64) / p).astype(np.float64).reshape(new_shape)
488+
if elem_type == TensorProto.COMPLEX64:
489+
return (value.astype(np.complex64) / p).astype(np.complex64).reshape(new_shape)
490+
if elem_type == TensorProto.COMPLEX128:
491+
return (
492+
(value.astype(np.complex128) / p).astype(np.complex128).reshape(new_shape)
493+
)
488494
raise RuntimeError(f"Unexpected element_type {elem_type} for info={info}")
489495

490496

‎onnx_array_api/reference/ops/op_constant_of_shape.py

Lines changed: 4 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -19,6 +19,8 @@ def _process(value):
1919
cst = np.int64(cst)
2020
elif isinstance(cst, float):
2121
cst = np.float64(cst)
22+
elif isinstance(cst, complex):
23+
cst = np.complex128(cst)
2224
elif cst is None:
2325
cst = np.float32(0)
2426
if not isinstance(
@@ -27,6 +29,8 @@ def _process(value):
2729
np.float16,
2830
np.float32,
2931
np.float64,
32+
np.complex64,
33+
np.complex128,
3034
np.int64,
3135
np.int32,
3236
np.int16,

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