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[Dup] Fix grammar in documents (onnx#4094)
* fix grammar in doc Signed-off-by: Chun-Wei Chen <[email protected]> * update docs Signed-off-by: Chun-Wei Chen <[email protected]>
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-402
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‎docs/Changelog.md

Lines changed: 226 additions & 226 deletions
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‎docs/Operators.md

Lines changed: 85 additions & 85 deletions
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‎docs/VersionConverter.md

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -32,7 +32,7 @@ ModelProto ConvertVersion(
3232
```
3333

3434
which accepts an input `ModelProto`, the initial opset version of the model,
35-
and the target opset verison, and which returns a new `ModelProto` which
35+
and the target opset version, and which returns a new `ModelProto` which
3636
is the result of apply all relevant adapters between initial_version and
3737
target_version. For a list of available passes, see
3838
[convert.h](/onnx/version_converter/convert.h).

‎onnx/defs/controlflow/defs.cc

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -646,7 +646,7 @@ ONNX_OPERATOR_SET_SCHEMA(
646646
static const char* scan_16_doc = R"DOC(
647647
Scan can be used to iterate over one or more scan_input tensors,
648648
constructing zero or more scan_output tensors. It combines ideas from general recurrences,
649-
functional programming constructs such as scan, fold, map, and zip and is intended to enable
649+
functional programming constructs such as scan, fold, map, and zip, and is intended to enable
650650
generalizations of RNN-like constructs for sequence-to-sequence processing.
651651
Other tensors (referred to as state_variables here) can be used to carry a state
652652
when iterating from one element to another (similar to hidden-state in RNNs, also referred

‎onnx/defs/controlflow/old.cc

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -340,7 +340,7 @@ void ScanInferenceFunctionOpset9(InferenceContext& ctx) {
340340
static const char* scan_opset8_doc = R"DOC(
341341
Scan can be used to iterate over one or more scan_input tensors,
342342
constructing zero or more scan_output tensors. It combines ideas from general recurrences,
343-
functional programming constructs such as scan, fold, map, and zip and is intended to enable
343+
functional programming constructs such as scan, fold, map, and zip, and is intended to enable
344344
generalizations of RNN-like constructs for sequence-to-sequence processing.
345345
Other tensors (referred to as state_variables here) can be used to carry a state
346346
when iterating from one element to another (similar to hidden-state in RNNs, also referred
@@ -1112,7 +1112,7 @@ ONNX_OPERATOR_SET_SCHEMA(
11121112
static const char* scan_9_doc = R"DOC(
11131113
Scan can be used to iterate over one or more scan_input tensors,
11141114
constructing zero or more scan_output tensors. It combines ideas from general recurrences,
1115-
functional programming constructs such as scan, fold, map, and zip and is intended to enable
1115+
functional programming constructs such as scan, fold, map, and zip, and is intended to enable
11161116
generalizations of RNN-like constructs for sequence-to-sequence processing.
11171117
Other tensors (referred to as state_variables here) can be used to carry a state
11181118
when iterating from one element to another (similar to hidden-state in RNNs, also referred
@@ -1985,7 +1985,7 @@ ONNX_OPERATOR_SET_SCHEMA(
19851985
static const char* scan_11_doc = R"DOC(
19861986
Scan can be used to iterate over one or more scan_input tensors,
19871987
constructing zero or more scan_output tensors. It combines ideas from general recurrences,
1988-
functional programming constructs such as scan, fold, map, and zip and is intended to enable
1988+
functional programming constructs such as scan, fold, map, and zip, and is intended to enable
19891989
generalizations of RNN-like constructs for sequence-to-sequence processing.
19901990
Other tensors (referred to as state_variables here) can be used to carry a state
19911991
when iterating from one element to another (similar to hidden-state in RNNs, also referred

‎onnx/defs/logical/defs.cc

Lines changed: 17 additions & 17 deletions
Original file line numberDiff line numberDiff line change
@@ -79,11 +79,11 @@ ONNX_OPERATOR_SET_SCHEMA(
7979
.TypeConstraint(
8080
"T",
8181
{"tensor(bool)"},
82-
"Constrains input to boolean tensor.")
82+
"Constrain input to boolean tensor.")
8383
.TypeConstraint(
8484
"T1",
8585
{"tensor(bool)"},
86-
"Constrains output to boolean tensor."));
86+
"Constrain output to boolean tensor."));
8787

8888
ONNX_OPERATOR_SET_SCHEMA(
8989
Or,
@@ -93,11 +93,11 @@ ONNX_OPERATOR_SET_SCHEMA(
9393
.TypeConstraint(
9494
"T",
9595
{"tensor(bool)"},
96-
"Constrains input to boolean tensor.")
96+
"Constrain input to boolean tensor.")
9797
.TypeConstraint(
9898
"T1",
9999
{"tensor(bool)"},
100-
"Constrains output to boolean tensor."));
100+
"Constrain output to boolean tensor."));
101101

102102
ONNX_OPERATOR_SET_SCHEMA(
103103
Xor,
@@ -107,11 +107,11 @@ ONNX_OPERATOR_SET_SCHEMA(
107107
.TypeConstraint(
108108
"T",
109109
{"tensor(bool)"},
110-
"Constrains input to boolean tensor.")
110+
"Constrain input to boolean tensor.")
111111
.TypeConstraint(
112112
"T1",
113113
{"tensor(bool)"},
114-
"Constrains output to boolean tensor."));
114+
"Constrain output to boolean tensor."));
115115

116116
ONNX_OPERATOR_SET_SCHEMA(
117117
Greater,
@@ -121,11 +121,11 @@ ONNX_OPERATOR_SET_SCHEMA(
121121
.TypeConstraint(
122122
"T",
123123
OpSchema::all_numeric_types_with_bfloat(),
124-
"Constrains input types to all numeric tensors.")
124+
"Constrain input types to all numeric tensors.")
125125
.TypeConstraint(
126126
"T1",
127127
{"tensor(bool)"},
128-
"Constrains output to boolean tensor."));
128+
"Constrain output to boolean tensor."));
129129

130130
ONNX_OPERATOR_SET_SCHEMA(
131131
Less,
@@ -135,11 +135,11 @@ ONNX_OPERATOR_SET_SCHEMA(
135135
.TypeConstraint(
136136
"T",
137137
OpSchema::all_numeric_types_with_bfloat(),
138-
"Constrains input types to all numeric tensors.")
138+
"Constrain input types to all numeric tensors.")
139139
.TypeConstraint(
140140
"T1",
141141
{"tensor(bool)"},
142-
"Constrains output to boolean tensor."));
142+
"Constrain output to boolean tensor."));
143143

144144
ONNX_OPERATOR_SET_SCHEMA(
145145
Equal,
@@ -161,11 +161,11 @@ ONNX_OPERATOR_SET_SCHEMA(
161161
"tensor(float)",
162162
"tensor(double)",
163163
"tensor(bfloat16)"},
164-
"Constrains input types to all numeric tensors.")
164+
"Constrain input types to all numeric tensors.")
165165
.TypeConstraint(
166166
"T1",
167167
{"tensor(bool)"},
168-
"Constrains output to boolean tensor."));
168+
"Constrain output to boolean tensor."));
169169

170170
static const char* Not_ver1_doc = R"DOC(
171171
Returns the negation of the input tensor element-wise.
@@ -197,7 +197,7 @@ ONNX_OPERATOR_SET_SCHEMA(
197197
.TypeConstraint(
198198
"T",
199199
{"tensor(bool)"},
200-
"Constrains input/output to boolean tensors.")
200+
"Constrain input/output to boolean tensors.")
201201
.TypeAndShapeInferenceFunction(unaryLogicalOpInference));
202202

203203
static const char* BitShift_ver11_doc = R"DOC(
@@ -278,11 +278,11 @@ ONNX_OPERATOR_SET_SCHEMA(
278278
.TypeConstraint(
279279
"T",
280280
OpSchema::all_numeric_types_with_bfloat(),
281-
"Constrains input types to all numeric tensors.")
281+
"Constrain input types to all numeric tensors.")
282282
.TypeConstraint(
283283
"T1",
284284
{"tensor(bool)"},
285-
"Constrains output to boolean tensor.")
285+
"Constrain output to boolean tensor.")
286286
.TypeAndShapeInferenceFunction(InferenceFunction())
287287
.FunctionBody(R"ONNX(
288288
{
@@ -300,11 +300,11 @@ ONNX_OPERATOR_SET_SCHEMA(
300300
.TypeConstraint(
301301
"T",
302302
OpSchema::all_numeric_types_with_bfloat(),
303-
"Constrains input types to all numeric tensors.")
303+
"Constrain input types to all numeric tensors.")
304304
.TypeConstraint(
305305
"T1",
306306
{"tensor(bool)"},
307-
"Constrains output to boolean tensor.")
307+
"Constrain output to boolean tensor.")
308308
.TypeAndShapeInferenceFunction(InferenceFunction())
309309
.FunctionBody(R"ONNX(
310310
{

‎onnx/defs/logical/old.cc

Lines changed: 28 additions & 28 deletions
Original file line numberDiff line numberDiff line change
@@ -47,11 +47,11 @@ ONNX_OPERATOR_SET_SCHEMA(
4747
.TypeConstraint(
4848
"T",
4949
OpSchema::all_numeric_types(),
50-
"Constrains input types to all numeric tensors.")
50+
"Constrain input types to all numeric tensors.")
5151
.TypeConstraint(
5252
"T1",
5353
{"tensor(bool)"},
54-
"Constrains output to boolean tensor."));
54+
"Constrain output to boolean tensor."));
5555

5656
ONNX_OPERATOR_SET_SCHEMA(
5757
Less,
@@ -61,11 +61,11 @@ ONNX_OPERATOR_SET_SCHEMA(
6161
.TypeConstraint(
6262
"T",
6363
OpSchema::all_numeric_types(),
64-
"Constrains input types to all numeric tensors.")
64+
"Constrain input types to all numeric tensors.")
6565
.TypeConstraint(
6666
"T1",
6767
{"tensor(bool)"},
68-
"Constrains output to boolean tensor."));
68+
"Constrain output to boolean tensor."));
6969

7070
ONNX_OPERATOR_SET_SCHEMA(
7171
Equal,
@@ -86,11 +86,11 @@ ONNX_OPERATOR_SET_SCHEMA(
8686
"tensor(float16)",
8787
"tensor(float)",
8888
"tensor(double)"},
89-
"Constrains input types to all numeric tensors.")
89+
"Constrain input types to all numeric tensors.")
9090
.TypeConstraint(
9191
"T1",
9292
{"tensor(bool)"},
93-
"Constrains output to boolean tensor."));
93+
"Constrain output to boolean tensor."));
9494

9595
inline void logicalOpInference_opset1(InferenceContext& ctx) {
9696
updateOutputElemType(ctx, 0, TensorProto::BOOL);
@@ -167,11 +167,11 @@ ONNX_OPERATOR_SET_SCHEMA(
167167
.TypeConstraint(
168168
"T",
169169
{"tensor(bool)"},
170-
"Constrains input to boolean tensor.")
170+
"Constrain input to boolean tensor.")
171171
.TypeConstraint(
172172
"T1",
173173
{"tensor(bool)"},
174-
"Constrains output to boolean tensor."));
174+
"Constrain output to boolean tensor."));
175175

176176
ONNX_OPERATOR_SET_SCHEMA(
177177
Or,
@@ -181,11 +181,11 @@ ONNX_OPERATOR_SET_SCHEMA(
181181
.TypeConstraint(
182182
"T",
183183
{"tensor(bool)"},
184-
"Constrains input to boolean tensor.")
184+
"Constrain input to boolean tensor.")
185185
.TypeConstraint(
186186
"T1",
187187
{"tensor(bool)"},
188-
"Constrains output to boolean tensor."));
188+
"Constrain output to boolean tensor."));
189189

190190
ONNX_OPERATOR_SET_SCHEMA(
191191
Xor,
@@ -195,11 +195,11 @@ ONNX_OPERATOR_SET_SCHEMA(
195195
.TypeConstraint(
196196
"T",
197197
{"tensor(bool)"},
198-
"Constrains input to boolean tensor.")
198+
"Constrain input to boolean tensor.")
199199
.TypeConstraint(
200200
"T1",
201201
{"tensor(bool)"},
202-
"Constrains output to boolean tensor."));
202+
"Constrain output to boolean tensor."));
203203

204204
ONNX_OPERATOR_SET_SCHEMA(
205205
Greater,
@@ -209,11 +209,11 @@ ONNX_OPERATOR_SET_SCHEMA(
209209
.TypeConstraint(
210210
"T",
211211
{"tensor(float16)", "tensor(float)", "tensor(double)"},
212-
"Constrains input to float tensors.")
212+
"Constrain input to float tensors.")
213213
.TypeConstraint(
214214
"T1",
215215
{"tensor(bool)"},
216-
"Constrains output to boolean tensor."));
216+
"Constrain output to boolean tensor."));
217217

218218
ONNX_OPERATOR_SET_SCHEMA(
219219
Less,
@@ -223,11 +223,11 @@ ONNX_OPERATOR_SET_SCHEMA(
223223
.TypeConstraint(
224224
"T",
225225
{"tensor(float16)", "tensor(float)", "tensor(double)"},
226-
"Constrains input to float tensors.")
226+
"Constrain input to float tensors.")
227227
.TypeConstraint(
228228
"T1",
229229
{"tensor(bool)"},
230-
"Constrains output to boolean tensor."));
230+
"Constrain output to boolean tensor."));
231231

232232
ONNX_OPERATOR_SET_SCHEMA(
233233
Equal,
@@ -237,11 +237,11 @@ ONNX_OPERATOR_SET_SCHEMA(
237237
.TypeConstraint(
238238
"T",
239239
{"tensor(bool)", "tensor(int32)", "tensor(int64)"},
240-
"Constrains input to integral tensors.")
240+
"Constrain input to integral tensors.")
241241
.TypeConstraint(
242242
"T1",
243243
{"tensor(bool)"},
244-
"Constrains output to boolean tensor."));
244+
"Constrain output to boolean tensor."));
245245

246246
ONNX_OPERATOR_SET_SCHEMA(
247247
Equal,
@@ -251,11 +251,11 @@ ONNX_OPERATOR_SET_SCHEMA(
251251
.TypeConstraint(
252252
"T",
253253
{"tensor(bool)", "tensor(int32)", "tensor(int64)"},
254-
"Constrains input to integral tensors.")
254+
"Constrain input to integral tensors.")
255255
.TypeConstraint(
256256
"T1",
257257
{"tensor(bool)"},
258-
"Constrains output to boolean tensor."));
258+
"Constrain output to boolean tensor."));
259259

260260
ONNX_OPERATOR_SET_SCHEMA(
261261
Greater,
@@ -265,11 +265,11 @@ ONNX_OPERATOR_SET_SCHEMA(
265265
.TypeConstraint(
266266
"T",
267267
{"tensor(float16)", "tensor(float)", "tensor(double)"},
268-
"Constrains input to float tensors.")
268+
"Constrain input to float tensors.")
269269
.TypeConstraint(
270270
"T1",
271271
{"tensor(bool)"},
272-
"Constrains output to boolean tensor."));
272+
"Constrain output to boolean tensor."));
273273

274274
ONNX_OPERATOR_SET_SCHEMA(
275275
Less,
@@ -279,11 +279,11 @@ ONNX_OPERATOR_SET_SCHEMA(
279279
.TypeConstraint(
280280
"T",
281281
{"tensor(float16)", "tensor(float)", "tensor(double)"},
282-
"Constrains input to float tensors.")
282+
"Constrain input to float tensors.")
283283
.TypeConstraint(
284284
"T1",
285285
{"tensor(bool)"},
286-
"Constrains output to boolean tensor."));
286+
"Constrain output to boolean tensor."));
287287

288288

289289
// Shares same doc generator as newer opset 16 version.
@@ -297,11 +297,11 @@ ONNX_OPERATOR_SET_SCHEMA(
297297
.TypeConstraint(
298298
"T",
299299
OpSchema::all_numeric_types(),
300-
"Constrains input types to all numeric tensors.")
300+
"Constrain input types to all numeric tensors.")
301301
.TypeConstraint(
302302
"T1",
303303
{"tensor(bool)"},
304-
"Constrains output to boolean tensor.")
304+
"Constrain output to boolean tensor.")
305305
.TypeAndShapeInferenceFunction(InferenceFunction())
306306
.FunctionBody(R"ONNX(
307307
{
@@ -319,11 +319,11 @@ ONNX_OPERATOR_SET_SCHEMA(
319319
.TypeConstraint(
320320
"T",
321321
OpSchema::all_numeric_types(),
322-
"Constrains input types to all numeric tensors.")
322+
"Constrain input types to all numeric tensors.")
323323
.TypeConstraint(
324324
"T1",
325325
{"tensor(bool)"},
326-
"Constrains output to boolean tensor.")
326+
"Constrain output to boolean tensor.")
327327
.TypeAndShapeInferenceFunction(InferenceFunction())
328328
.FunctionBody(R"ONNX(
329329
{

‎onnx/defs/math/defs.cc

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1990,7 +1990,7 @@ static const char* Expand_ver13_doc = R"DOC(
19901990
Broadcast the input tensor following the given shape and the broadcast rule.
19911991
The broadcast rule is similar to numpy.array(input) * numpy.ones(shape):
19921992
Dimensions are right alignment;
1993-
Two corresponding dimension must have the same value, or one of them is equal to 1.
1993+
Two corresponding dimensions must have the same value, or one of them is equal to 1.
19941994
Also, this operator is similar to numpy.broadcast_to(input, shape),
19951995
but the major difference is numpy.broadcast_to() does not allow shape to be smaller than input.size().
19961996
It is possible that the output.shape is not equal to shape, when some dimensions in shape is equal to 1,

‎onnx/defs/math/old.cc

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -967,7 +967,7 @@ static const char* Expand_ver8_doc = R"DOC(
967967
Broadcast the input tensor following the given shape and the broadcast rule.
968968
The broadcast rule is similar to numpy.array(input) * numpy.ones(shape):
969969
Dimensions are right alignment;
970-
Two corresponding dimension must have the same value, or one of them is equal to 1.
970+
Two corresponding dimensions must have the same value, or one of them is equal to 1.
971971
Also, this operator is similar to numpy.broadcast_to(input, shape),
972972
but the major difference is numpy.broadcast_to() does not allow shape to be smaller than input.size().
973973
It is possible that the output.shape is not equal to shape, when some dimensions in shape is equal to 1,

‎onnx/defs/nn/defs.cc

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -2074,7 +2074,7 @@ ONNX_OPERATOR_SET_SCHEMA(
20742074
.TypeConstraint(
20752075
"T",
20762076
OpSchema::all_numeric_types(),
2077-
"Constrains input to only numeric types.")
2077+
"Constrain input to only numeric types.")
20782078
.TypeAndShapeInferenceFunction(propagateShapeAndTypeFromFirstInput));
20792079

20802080
static const char* Flatten_ver13_doc = R"DOC(

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