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darabos commited on
Commit
114fd1c
·
1 Parent(s): 6565904

Preserve order of inputs, outputs, and params.

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Files changed (19) hide show
  1. examples/Airlines demo.lynxkite.json +0 -0
  2. examples/Image processing.lynxkite.json +40 -40
  3. examples/Model definition.lynxkite.json +133 -123
  4. examples/Model use.lynxkite.json +711 -703
  5. examples/NetworkX demo.lynxkite.json +105 -105
  6. examples/Word2vec.lynxkite.json +54 -54
  7. examples/sql.lynxkite.json +0 -0
  8. lynxkite-app/web/src/workspace/nodes/LynxKiteNode.tsx +4 -4
  9. lynxkite-app/web/src/workspace/nodes/NodeWithParams.tsx +13 -13
  10. lynxkite-core/src/lynxkite/core/executors/one_by_one.py +5 -7
  11. lynxkite-core/src/lynxkite/core/executors/simple.py +3 -3
  12. lynxkite-core/src/lynxkite/core/ops.py +36 -27
  13. lynxkite-core/src/lynxkite/core/workspace.py +3 -2
  14. lynxkite-core/tests/test_ops.py +25 -31
  15. lynxkite-graph-analytics/src/lynxkite_graph_analytics/core.py +2 -2
  16. lynxkite-graph-analytics/src/lynxkite_graph_analytics/lynxkite_ops.py +3 -3
  17. lynxkite-graph-analytics/src/lynxkite_graph_analytics/networkx_ops.py +5 -4
  18. lynxkite-graph-analytics/src/lynxkite_graph_analytics/pytorch/pytorch_core.py +4 -4
  19. lynxkite-graph-analytics/src/lynxkite_graph_analytics/pytorch/pytorch_ops.py +2 -2
examples/Airlines demo.lynxkite.json CHANGED
The diff for this file is too large to render. See raw diff
 
examples/Image processing.lynxkite.json CHANGED
@@ -46,26 +46,26 @@
46
  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {},
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  "name": "Open image",
51
- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "right",
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  "type": {
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  "type": "None"
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  }
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  }
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- },
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- "params": {
61
- "filename": {
62
  "default": null,
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  "name": "filename",
64
  "type": {
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  "type": "<class 'str'>"
66
  }
67
  }
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- },
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  "type": "basic"
70
  },
71
  "params": {
@@ -91,18 +91,18 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "image": {
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  "name": "image",
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  "position": "left",
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  "type": {
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  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
100
  }
101
  }
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- },
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  "name": "View image",
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- "outputs": {},
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- "params": {},
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  "type": "image"
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  },
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  "params": {},
@@ -126,18 +126,18 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "image": {
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  "name": "image",
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  "position": "left",
133
  "type": {
134
  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
135
  }
136
  }
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- },
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  "name": "View image",
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- "outputs": {},
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- "params": {},
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  "type": "image"
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  },
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  "params": {},
@@ -163,26 +163,26 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "image": {
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  "name": "image",
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  "position": "left",
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  "type": {
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  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
172
  }
173
  }
174
- },
175
  "name": "To grayscale",
176
- "outputs": {
177
- "output": {
178
  "name": "output",
179
  "position": "right",
180
  "type": {
181
  "type": "None"
182
  }
183
  }
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- },
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- "params": {},
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  "type": "basic"
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  },
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  "params": {},
@@ -208,34 +208,34 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "image": {
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  "name": "image",
214
  "position": "left",
215
  "type": {
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  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
217
  }
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  }
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- },
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  "name": "Blur",
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- "outputs": {
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- "output": {
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  "name": "output",
224
  "position": "right",
225
  "type": {
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  "type": "None"
227
  }
228
  }
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- },
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- "params": {
231
- "radius": {
232
  "default": 5.0,
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  "name": "radius",
234
  "type": {
235
  "type": "<class 'float'>"
236
  }
237
  }
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- },
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  "type": "basic"
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  },
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  "params": {
@@ -263,26 +263,26 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "image": {
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  "name": "image",
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  "position": "left",
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  "type": {
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  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
272
  }
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  }
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- },
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  "name": "Flip vertically",
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- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "right",
280
  "type": {
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  "type": "None"
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  }
283
  }
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- },
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- "params": {},
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  "type": "basic"
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  },
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  "params": {},
 
46
  "error": null,
47
  "input_metadata": null,
48
  "meta": {
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+ "inputs": [],
50
  "name": "Open image",
51
+ "outputs": [
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+ {
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  "name": "output",
54
  "position": "right",
55
  "type": {
56
  "type": "None"
57
  }
58
  }
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+ ],
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+ "params": [
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+ {
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  "default": null,
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  "name": "filename",
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  "type": {
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  "type": "<class 'str'>"
66
  }
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  }
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+ ],
69
  "type": "basic"
70
  },
71
  "params": {
 
91
  "error": null,
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  "input_metadata": null,
93
  "meta": {
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+ "inputs": [
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+ {
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  "name": "image",
97
  "position": "left",
98
  "type": {
99
  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
100
  }
101
  }
102
+ ],
103
  "name": "View image",
104
+ "outputs": [],
105
+ "params": [],
106
  "type": "image"
107
  },
108
  "params": {},
 
126
  "error": null,
127
  "input_metadata": null,
128
  "meta": {
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+ "inputs": [
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+ {
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  "name": "image",
132
  "position": "left",
133
  "type": {
134
  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
135
  }
136
  }
137
+ ],
138
  "name": "View image",
139
+ "outputs": [],
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+ "params": [],
141
  "type": "image"
142
  },
143
  "params": {},
 
163
  "error": null,
164
  "input_metadata": null,
165
  "meta": {
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+ "inputs": [
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+ {
168
  "name": "image",
169
  "position": "left",
170
  "type": {
171
  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
172
  }
173
  }
174
+ ],
175
  "name": "To grayscale",
176
+ "outputs": [
177
+ {
178
  "name": "output",
179
  "position": "right",
180
  "type": {
181
  "type": "None"
182
  }
183
  }
184
+ ],
185
+ "params": [],
186
  "type": "basic"
187
  },
188
  "params": {},
 
208
  "error": null,
209
  "input_metadata": null,
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  "meta": {
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+ "inputs": [
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+ {
213
  "name": "image",
214
  "position": "left",
215
  "type": {
216
  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
217
  }
218
  }
219
+ ],
220
  "name": "Blur",
221
+ "outputs": [
222
+ {
223
  "name": "output",
224
  "position": "right",
225
  "type": {
226
  "type": "None"
227
  }
228
  }
229
+ ],
230
+ "params": [
231
+ {
232
  "default": 5.0,
233
  "name": "radius",
234
  "type": {
235
  "type": "<class 'float'>"
236
  }
237
  }
238
+ ],
239
  "type": "basic"
240
  },
241
  "params": {
 
263
  "error": null,
264
  "input_metadata": null,
265
  "meta": {
266
+ "inputs": [
267
+ {
268
  "name": "image",
269
  "position": "left",
270
  "type": {
271
  "type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
272
  }
273
  }
274
+ ],
275
  "name": "Flip vertically",
276
+ "outputs": [
277
+ {
278
  "name": "output",
279
  "position": "right",
280
  "type": {
281
  "type": "None"
282
  }
283
  }
284
+ ],
285
+ "params": [],
286
  "type": "basic"
287
  },
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  "params": {},
examples/Model definition.lynxkite.json CHANGED
@@ -81,26 +81,20 @@
81
  "error": null,
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  "input_metadata": null,
83
  "meta": {
84
- "inputs": {
85
- "loss": {
 
86
  "name": "loss",
87
  "position": "bottom",
88
  "type": {
89
  "type": "tensor"
90
  }
91
  }
92
- },
93
  "name": "Optimizer",
94
- "outputs": {},
95
- "params": {
96
- "lr": {
97
- "default": 0.001,
98
- "name": "lr",
99
- "type": {
100
- "type": "<class 'float'>"
101
- }
102
- },
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- "type": {
104
  "default": "AdamW",
105
  "name": "type",
106
  "type": {
@@ -114,15 +108,22 @@
114
  "Galore AdamW"
115
  ]
116
  }
 
 
 
 
 
 
 
117
  }
118
- },
119
  "type": "basic"
120
  },
121
  "params": {
122
  "lr": "0.1",
123
  "type": "SGD"
124
  },
125
- "status": "planned",
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  "title": "Optimizer"
127
  },
128
  "dragHandle": ".bg-primary",
@@ -130,7 +131,7 @@
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  "id": "Optimizer 2",
131
  "position": {
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  "x": 359.75221367487865,
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- "y": -1560.7604266065723
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  },
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  "type": "basic",
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  "width": 232.0
@@ -143,28 +144,29 @@
143
  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "x": {
 
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  "name": "x",
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  "position": "bottom",
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  "type": {
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  "type": "<class 'inspect._empty'>"
152
  }
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  }
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- },
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  "name": "Activation",
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- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "top",
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  "type": {
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  "type": "None"
162
  }
163
  }
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- },
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- "params": {
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- "type": {
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- "default": "ReLU",
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  "name": "type",
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  "type": {
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  "enum": [
@@ -175,13 +177,13 @@
175
  ]
176
  }
177
  }
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- },
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  "type": "basic"
180
  },
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  "params": {
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  "type": "Leaky_ReLU"
183
  },
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- "status": "planned",
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  "title": "Activation"
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  },
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  "dragHandle": ".bg-primary",
@@ -202,40 +204,41 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {},
 
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  "name": "Input: tensor",
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- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "top",
211
  "type": {
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  "type": "tensor"
213
  }
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  }
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- },
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- "params": {
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- "name": {
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  "default": null,
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  "name": "name",
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  "type": {
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  "type": "None"
222
  }
223
  }
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- },
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  "type": "basic"
226
  },
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  "params": {
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  "name": "Y"
229
  },
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- "status": "planned",
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  "title": "Input: tensor"
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  },
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  "dragHandle": ".bg-primary",
234
  "height": 200.0,
235
  "id": "Input: tensor 3",
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  "position": {
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- "x": 485.8840220312055,
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- "y": -268.0485936515193
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  },
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  "type": "basic",
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  "width": 200.0
@@ -248,45 +251,46 @@
248
  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "x": {
 
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  "name": "x",
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  "position": "bottom",
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  "type": {
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  "type": "<class 'inspect._empty'>"
257
  }
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  },
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- "y": {
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  "name": "y",
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  "position": "bottom",
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  "type": {
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  "type": "<class 'inspect._empty'>"
264
  }
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  }
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- },
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  "name": "MSE loss",
268
- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "top",
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  "type": {
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  "type": "None"
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  }
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  }
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- },
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- "params": {},
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  "type": "basic"
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  },
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  "params": {},
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- "status": "planned",
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  "title": "MSE loss"
283
  },
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  "dragHandle": ".bg-primary",
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  "height": 200.0,
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  "id": "MSE loss 2",
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  "position": {
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- "x": 384.54674698852955,
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- "y": -1184.4701545316577
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  },
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  "type": "basic",
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  "width": 200.0
@@ -299,48 +303,49 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "input": {
 
304
  "name": "input",
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  "position": "top",
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  "type": {
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  "type": "tensor"
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  }
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  }
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- },
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  "name": "Repeat",
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- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "bottom",
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  "type": {
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  "type": "tensor"
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  }
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  }
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- },
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- "params": {
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- "same_weights": {
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- "default": false,
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- "name": "same_weights",
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- "type": {
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- "type": "<class 'bool'>"
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- }
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- },
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- "times": {
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  "default": 1.0,
331
  "name": "times",
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  "type": {
333
  "type": "<class 'int'>"
334
  }
 
 
 
 
 
 
 
335
  }
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- },
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  "type": "basic"
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  },
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  "params": {
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  "same_weights": false,
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  "times": "2"
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  },
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- "status": "planned",
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  "title": "Repeat"
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  },
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  "dragHandle": ".bg-primary",
@@ -361,51 +366,52 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "x": {
 
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  "name": "x",
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  "position": "bottom",
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  "type": {
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  "type": "<class 'inspect._empty'>"
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  }
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  }
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- },
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  "name": "Linear",
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- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "top",
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  "type": {
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  "type": "None"
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  }
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  }
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- },
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- "params": {
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- "output_dim": {
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  "default": 1024.0,
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  "name": "output_dim",
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  "type": {
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  "type": "<class 'int'>"
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  }
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  }
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- },
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  "type": "basic"
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  },
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  "params": {
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  "output_dim": "4"
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  },
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- "status": "planned",
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  "title": "Linear"
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  },
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  "dragHandle": ".bg-primary",
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- "height": 200.0,
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  "id": "Linear 1",
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  "position": {
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  "x": 98.54861342271252,
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  "y": 14.121603973834155
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  },
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  "type": "basic",
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- "width": 200.0
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  },
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  {
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  "data": {
@@ -415,32 +421,33 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {},
 
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  "name": "Input: tensor",
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- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "top",
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  "type": {
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  "type": "tensor"
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  }
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  }
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- },
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- "params": {
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- "name": {
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  "default": null,
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  "name": "name",
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  "type": {
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  "type": "None"
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  }
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  }
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- },
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  "type": "basic"
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  },
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  "params": {
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  "name": "X"
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  },
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- "status": "planned",
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  "title": "Input: tensor"
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  },
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  "dragHandle": ".bg-primary",
@@ -461,48 +468,49 @@
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  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {},
 
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  "name": "Constant vector",
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- "outputs": {
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- "output": {
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  "name": "output",
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  "position": "top",
470
  "type": {
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  "type": "None"
472
  }
473
  }
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- },
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- "params": {
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- "size": {
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- "default": 1.0,
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- "name": "size",
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  "type": {
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  "type": "<class 'int'>"
481
  }
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  },
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- "value": {
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- "default": 0.0,
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- "name": "value",
486
  "type": {
487
  "type": "<class 'int'>"
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  }
489
  }
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- },
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  "type": "basic"
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  },
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  "params": {
494
  "size": "1",
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  "value": "1"
496
  },
497
- "status": "planned",
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  "title": "Constant vector"
499
  },
500
  "dragHandle": ".bg-primary",
501
  "height": 258.0,
502
  "id": "Constant vector 1",
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  "position": {
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- "x": 886.708922897265,
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- "y": -298.4394167425953
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  },
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  "type": "basic",
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  "width": 238.0
@@ -515,45 +523,46 @@
515
  "error": null,
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  "input_metadata": null,
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  "meta": {
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- "inputs": {
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- "a": {
 
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- "n_neighbors": {
12320
  "default": 15.0,
12321
  "name": "n_neighbors",
12322
  "type": {
12323
  "type": "<class 'int'>"
12324
  }
12325
  },
12326
- "table_name": {
12327
  "default": "nodes",
12328
  "name": "table_name",
12329
  "type": {
12330
  "type": "<class 'str'>"
12331
  }
12332
  },
12333
- "vector_column": {
12334
  "default": "",
12335
  "name": "vector_column",
12336
  "type": {
12337
  "type": "<class 'str'>"
12338
  }
12339
  }
12340
- },
12341
  "type": "visualization"
12342
  },
12343
  "params": {
@@ -12367,18 +12367,18 @@
12367
  "error": null,
12368
  "input_metadata": [],
12369
  "meta": {
12370
- "inputs": {},
12371
  "name": "Word2vec for the top 1000 words",
12372
- "outputs": {
12373
- "output": {
12374
  "name": "output",
12375
  "position": "right",
12376
  "type": {
12377
  "type": "None"
12378
  }
12379
  }
12380
- },
12381
- "params": {},
12382
  "type": "basic"
12383
  },
12384
  "params": {},
@@ -12405,34 +12405,34 @@
12405
  {}
12406
  ],
12407
  "meta": {
12408
- "inputs": {
12409
- "df": {
12410
  "name": "df",
12411
  "position": "left",
12412
  "type": {
12413
  "type": "<class 'pandas.core.frame.DataFrame'>"
12414
  }
12415
  }
12416
- },
12417
  "name": "Take first N",
12418
- "outputs": {
12419
- "output": {
12420
  "name": "output",
12421
  "position": "right",
12422
  "type": {
12423
  "type": "None"
12424
  }
12425
  }
12426
- },
12427
- "params": {
12428
- "n": {
12429
  "default": 10.0,
12430
  "name": "n",
12431
  "type": {
12432
  "type": "<class 'int'>"
12433
  }
12434
  }
12435
- },
12436
  "type": "basic"
12437
  },
12438
  "params": {
@@ -12461,34 +12461,34 @@
12461
  {}
12462
  ],
12463
  "meta": {
12464
- "inputs": {
12465
- "df": {
12466
  "name": "df",
12467
  "position": "left",
12468
  "type": {
12469
  "type": "<class 'pandas.core.frame.DataFrame'>"
12470
  }
12471
  }
12472
- },
12473
  "name": "Sample N",
12474
- "outputs": {
12475
- "output": {
12476
  "name": "output",
12477
  "position": "right",
12478
  "type": {
12479
  "type": "None"
12480
  }
12481
  }
12482
- },
12483
- "params": {
12484
- "n": {
12485
  "default": 10.0,
12486
  "name": "n",
12487
  "type": {
12488
  "type": "<class 'int'>"
12489
  }
12490
  }
12491
- },
12492
  "type": "basic"
12493
  },
12494
  "params": {
@@ -12939,26 +12939,26 @@
12939
  }
12940
  ],
12941
  "meta": {
12942
- "inputs": {
12943
- "bundle": {
12944
  "name": "bundle",
12945
  "position": "left",
12946
  "type": {
12947
  "type": "<class 'lynxkite_graph_analytics.core.Bundle'>"
12948
  }
12949
  }
12950
- },
12951
  "name": "View tables",
12952
- "outputs": {},
12953
- "params": {
12954
- "limit": {
12955
  "default": 100.0,
12956
  "name": "limit",
12957
  "type": {
12958
  "type": "<class 'int'>"
12959
  }
12960
  }
12961
- },
12962
  "position": {
12963
  "x": 356.0,
12964
  "y": 478.0
 
6107
  }
6108
  ],
6109
  "meta": {
6110
+ "inputs": [
6111
+ {
6112
  "name": "bundle",
6113
  "position": "left",
6114
  "type": {
6115
  "type": "<class 'lynxkite_graph_analytics.core.Bundle'>"
6116
  }
6117
  }
6118
+ ],
6119
  "name": "View vectors",
6120
+ "outputs": [],
6121
+ "params": [
6122
+ {
6123
  "default": "",
6124
  "name": "label_column",
6125
  "type": {
6126
  "type": "<class 'str'>"
6127
  }
6128
  },
6129
+ {
6130
  "default": "euclidean",
6131
  "name": "metric",
6132
  "type": {
 
6149
  ]
6150
  }
6151
  },
6152
+ {
6153
  "default": 0.1,
6154
  "name": "min_dist",
6155
  "type": {
6156
  "type": "<class 'float'>"
6157
  }
6158
  },
6159
+ {
6160
  "default": 15.0,
6161
  "name": "n_neighbors",
6162
  "type": {
6163
  "type": "<class 'int'>"
6164
  }
6165
  },
6166
+ {
6167
  "default": "nodes",
6168
  "name": "table_name",
6169
  "type": {
6170
  "type": "<class 'str'>"
6171
  }
6172
  },
6173
+ {
6174
  "default": "",
6175
  "name": "vector_column",
6176
  "type": {
6177
  "type": "<class 'str'>"
6178
  }
6179
  }
6180
+ ],
6181
  "type": "visualization"
6182
  },
6183
  "params": {
 
12267
  }
12268
  ],
12269
  "meta": {
12270
+ "inputs": [
12271
+ {
12272
  "name": "bundle",
12273
  "position": "left",
12274
  "type": {
12275
  "type": "<class 'lynxkite_graph_analytics.core.Bundle'>"
12276
  }
12277
  }
12278
+ ],
12279
  "name": "View vectors",
12280
+ "outputs": [],
12281
+ "params": [
12282
+ {
12283
  "default": "",
12284
  "name": "label_column",
12285
  "type": {
12286
  "type": "<class 'str'>"
12287
  }
12288
  },
12289
+ {
12290
  "default": "euclidean",
12291
  "name": "metric",
12292
  "type": {
 
12309
  ]
12310
  }
12311
  },
12312
+ {
12313
  "default": 0.1,
12314
  "name": "min_dist",
12315
  "type": {
12316
  "type": "<class 'float'>"
12317
  }
12318
  },
12319
+ {
12320
  "default": 15.0,
12321
  "name": "n_neighbors",
12322
  "type": {
12323
  "type": "<class 'int'>"
12324
  }
12325
  },
12326
+ {
12327
  "default": "nodes",
12328
  "name": "table_name",
12329
  "type": {
12330
  "type": "<class 'str'>"
12331
  }
12332
  },
12333
+ {
12334
  "default": "",
12335
  "name": "vector_column",
12336
  "type": {
12337
  "type": "<class 'str'>"
12338
  }
12339
  }
12340
+ ],
12341
  "type": "visualization"
12342
  },
12343
  "params": {
 
12367
  "error": null,
12368
  "input_metadata": [],
12369
  "meta": {
12370
+ "inputs": [],
12371
  "name": "Word2vec for the top 1000 words",
12372
+ "outputs": [
12373
+ {
12374
  "name": "output",
12375
  "position": "right",
12376
  "type": {
12377
  "type": "None"
12378
  }
12379
  }
12380
+ ],
12381
+ "params": [],
12382
  "type": "basic"
12383
  },
12384
  "params": {},
 
12405
  {}
12406
  ],
12407
  "meta": {
12408
+ "inputs": [
12409
+ {
12410
  "name": "df",
12411
  "position": "left",
12412
  "type": {
12413
  "type": "<class 'pandas.core.frame.DataFrame'>"
12414
  }
12415
  }
12416
+ ],
12417
  "name": "Take first N",
12418
+ "outputs": [
12419
+ {
12420
  "name": "output",
12421
  "position": "right",
12422
  "type": {
12423
  "type": "None"
12424
  }
12425
  }
12426
+ ],
12427
+ "params": [
12428
+ {
12429
  "default": 10.0,
12430
  "name": "n",
12431
  "type": {
12432
  "type": "<class 'int'>"
12433
  }
12434
  }
12435
+ ],
12436
  "type": "basic"
12437
  },
12438
  "params": {
 
12461
  {}
12462
  ],
12463
  "meta": {
12464
+ "inputs": [
12465
+ {
12466
  "name": "df",
12467
  "position": "left",
12468
  "type": {
12469
  "type": "<class 'pandas.core.frame.DataFrame'>"
12470
  }
12471
  }
12472
+ ],
12473
  "name": "Sample N",
12474
+ "outputs": [
12475
+ {
12476
  "name": "output",
12477
  "position": "right",
12478
  "type": {
12479
  "type": "None"
12480
  }
12481
  }
12482
+ ],
12483
+ "params": [
12484
+ {
12485
  "default": 10.0,
12486
  "name": "n",
12487
  "type": {
12488
  "type": "<class 'int'>"
12489
  }
12490
  }
12491
+ ],
12492
  "type": "basic"
12493
  },
12494
  "params": {
 
12939
  }
12940
  ],
12941
  "meta": {
12942
+ "inputs": [
12943
+ {
12944
  "name": "bundle",
12945
  "position": "left",
12946
  "type": {
12947
  "type": "<class 'lynxkite_graph_analytics.core.Bundle'>"
12948
  }
12949
  }
12950
+ ],
12951
  "name": "View tables",
12952
+ "outputs": [],
12953
+ "params": [
12954
+ {
12955
  "default": 100.0,
12956
  "name": "limit",
12957
  "type": {
12958
  "type": "<class 'int'>"
12959
  }
12960
  }
12961
+ ],
12962
  "position": {
12963
  "x": 356.0,
12964
  "y": 478.0
examples/sql.lynxkite.json CHANGED
The diff for this file is too large to render. See raw diff
 
lynxkite-app/web/src/workspace/nodes/LynxKiteNode.tsx CHANGED
@@ -14,7 +14,7 @@ interface LynxKiteNodeProps {
14
  children: any;
15
  }
16
 
17
- function getHandles(inputs: object, outputs: object) {
18
  const handles: {
19
  position: "top" | "bottom" | "left" | "right";
20
  name: string;
@@ -23,10 +23,10 @@ function getHandles(inputs: object, outputs: object) {
23
  showLabel: boolean;
24
  type: "source" | "target";
25
  }[] = [];
26
- for (const e of Object.values(inputs)) {
27
  handles.push({ ...e, type: "target" });
28
  }
29
- for (const e of Object.values(outputs)) {
30
  handles.push({ ...e, type: "source" });
31
  }
32
  const counts = { top: 0, bottom: 0, left: 0, right: 0 };
@@ -53,7 +53,7 @@ function LynxKiteNodeComponent(props: LynxKiteNodeProps) {
53
  const reactFlow = useReactFlow();
54
  const data = props.data;
55
  const expanded = !data.collapsed;
56
- const handles = getHandles(data.meta?.value?.inputs || {}, data.meta?.value?.outputs || {});
57
  function titleClicked() {
58
  reactFlow.updateNodeData(props.id, { collapsed: expanded });
59
  }
 
14
  children: any;
15
  }
16
 
17
+ function getHandles(inputs: any[], outputs: any[]) {
18
  const handles: {
19
  position: "top" | "bottom" | "left" | "right";
20
  name: string;
 
23
  showLabel: boolean;
24
  type: "source" | "target";
25
  }[] = [];
26
+ for (const e of inputs) {
27
  handles.push({ ...e, type: "target" });
28
  }
29
+ for (const e of outputs) {
30
  handles.push({ ...e, type: "source" });
31
  }
32
  const counts = { top: 0, bottom: 0, left: 0, right: 0 };
 
53
  const reactFlow = useReactFlow();
54
  const data = props.data;
55
  const expanded = !data.collapsed;
56
+ const handles = getHandles(data.meta?.value?.inputs || [], data.meta?.value?.outputs || []);
57
  function titleClicked() {
58
  reactFlow.updateNodeData(props.id, { collapsed: expanded });
59
  }
lynxkite-app/web/src/workspace/nodes/NodeWithParams.tsx CHANGED
@@ -31,23 +31,21 @@ export function NodeWithParams(props: any) {
31
  __execution_delay: opts.delay || 0,
32
  });
33
  }
34
- const params = props.data?.params ? Object.entries(props.data.params) : [];
35
-
36
  return (
37
  <>
38
- {props.collapsed && params.length > 0 && (
39
  <div className="params-expander" onClick={() => setCollapsed(!collapsed)}>
40
  <Triangle className={`flippy ${collapsed ? "flippy-90" : ""}`} />
41
  </div>
42
  )}
43
  {!collapsed &&
44
- params.map(([name, value]) =>
45
- metaParams?.[name]?.type === "group" ? (
46
  <NodeGroupParameter
47
- key={name}
48
- value={value}
49
  data={props.data}
50
- meta={metaParams?.[name]}
51
  setParam={(name: string, value: any, opts?: UpdateOptions) =>
52
  setParam(name, value, opts || {})
53
  }
@@ -55,12 +53,14 @@ export function NodeWithParams(props: any) {
55
  />
56
  ) : (
57
  <NodeParameter
58
- name={name}
59
- key={name}
60
- value={value}
61
  data={props.data}
62
- meta={metaParams?.[name]}
63
- onChange={(value: any, opts?: UpdateOptions) => setParam(name, value, opts || {})}
 
 
64
  />
65
  ),
66
  )}
 
31
  __execution_delay: opts.delay || 0,
32
  });
33
  }
 
 
34
  return (
35
  <>
36
+ {props.collapsed && metaParams.length > 0 && (
37
  <div className="params-expander" onClick={() => setCollapsed(!collapsed)}>
38
  <Triangle className={`flippy ${collapsed ? "flippy-90" : ""}`} />
39
  </div>
40
  )}
41
  {!collapsed &&
42
+ metaParams.map((meta: any) =>
43
+ meta.type === "group" ? (
44
  <NodeGroupParameter
45
+ key={meta.name}
46
+ value={props.data.params[meta.name]}
47
  data={props.data}
48
+ meta={meta}
49
  setParam={(name: string, value: any, opts?: UpdateOptions) =>
50
  setParam(name, value, opts || {})
51
  }
 
53
  />
54
  ) : (
55
  <NodeParameter
56
+ name={meta.name}
57
+ key={meta.name}
58
+ value={props.data.params[meta.name]}
59
  data={props.data}
60
+ meta={meta}
61
+ onChange={(value: any, opts?: UpdateOptions) =>
62
+ setParam(meta.name, value, opts || {})
63
+ }
64
  />
65
  ),
66
  )}
lynxkite-core/src/lynxkite/core/executors/one_by_one.py CHANGED
@@ -46,7 +46,7 @@ def register(env: str, cache: bool = True):
46
  ops.EXECUTORS[env] = lambda ws: execute(ws, ops.CATALOGS[env], cache=cache)
47
 
48
 
49
- def get_stages(ws, catalog):
50
  """Inputs on top/bottom are batch inputs. We decompose the graph into a DAG of components along these edges."""
51
  nodes = {n.id: n for n in ws.nodes}
52
  batch_inputs = {}
@@ -57,8 +57,7 @@ def get_stages(ws, catalog):
57
  inputs.setdefault(edge.target, []).append(edge.source)
58
  node = nodes[edge.target]
59
  op = catalog[node.data.title]
60
- i = op.inputs[edge.targetHandle]
61
- if i.position in "top or bottom":
62
  batch_inputs.setdefault(edge.target, []).append(edge.source)
63
  stages = []
64
  for bt, bss in batch_inputs.items():
@@ -110,7 +109,7 @@ async def execute(ws: workspace.Workspace, catalog, cache=None):
110
  continue
111
  node.publish_error(None)
112
  # Start tasks for nodes that have no non-batch inputs.
113
- if all([i.position in "top or bottom" for i in op.inputs.values()]):
114
  tasks[node.id] = [NO_INPUT]
115
  batch_inputs = {}
116
  # Run the rest until we run out of tasks.
@@ -132,7 +131,7 @@ async def execute(ws: workspace.Workspace, catalog, cache=None):
132
  for task in ts:
133
  try:
134
  inputs = []
135
- for i in op.inputs.values():
136
  if i.position in "top or bottom":
137
  assert (n, i.name) in batch_inputs, f"{i.name} is missing"
138
  inputs.append(batch_inputs[(n, i.name)])
@@ -165,8 +164,7 @@ async def execute(ws: workspace.Workspace, catalog, cache=None):
165
  for edge in edges[node.id]:
166
  t = nodes[edge.target]
167
  op = catalog[t.data.title]
168
- i = op.inputs[edge.targetHandle]
169
- if i.position in "top or bottom":
170
  batch_inputs.setdefault((edge.target, edge.targetHandle), []).extend(
171
  results
172
  )
 
46
  ops.EXECUTORS[env] = lambda ws: execute(ws, ops.CATALOGS[env], cache=cache)
47
 
48
 
49
+ def get_stages(ws, catalog: ops.Catalog):
50
  """Inputs on top/bottom are batch inputs. We decompose the graph into a DAG of components along these edges."""
51
  nodes = {n.id: n for n in ws.nodes}
52
  batch_inputs = {}
 
57
  inputs.setdefault(edge.target, []).append(edge.source)
58
  node = nodes[edge.target]
59
  op = catalog[node.data.title]
60
+ if op.get_input(edge.targetHandle).position in "top or bottom":
 
61
  batch_inputs.setdefault(edge.target, []).append(edge.source)
62
  stages = []
63
  for bt, bss in batch_inputs.items():
 
109
  continue
110
  node.publish_error(None)
111
  # Start tasks for nodes that have no non-batch inputs.
112
+ if all([i.position in "top or bottom" for i in op.inputs]):
113
  tasks[node.id] = [NO_INPUT]
114
  batch_inputs = {}
115
  # Run the rest until we run out of tasks.
 
131
  for task in ts:
132
  try:
133
  inputs = []
134
+ for i in op.inputs:
135
  if i.position in "top or bottom":
136
  assert (n, i.name) in batch_inputs, f"{i.name} is missing"
137
  inputs.append(batch_inputs[(n, i.name)])
 
164
  for edge in edges[node.id]:
165
  t = nodes[edge.target]
166
  op = catalog[t.data.title]
167
+ if op.get_input(edge.targetHandle).position in "top or bottom":
 
168
  batch_inputs.setdefault((edge.target, edge.targetHandle), []).extend(
169
  results
170
  )
lynxkite-core/src/lynxkite/core/executors/simple.py CHANGED
@@ -37,7 +37,7 @@ async def execute(ws: workspace.Workspace, catalog: ops.Catalog):
37
  try:
38
  inputs = []
39
  missing = []
40
- for i in op.inputs.values():
41
  edges = in_edges[node_id]
42
  if i.name in edges and edges[i.name] in outputs:
43
  inputs.append(outputs[edges[i.name]])
@@ -50,11 +50,11 @@ async def execute(ws: workspace.Workspace, catalog: ops.Catalog):
50
  result.output = await await_if_needed(result.output)
51
  result.display = await await_if_needed(result.display)
52
  if len(op.outputs) == 1:
53
- [output] = list(op.outputs.values())
54
  outputs[node_id, output.name] = result.output
55
  elif len(op.outputs) > 1:
56
  assert type(result.output) is dict, "An op with multiple outputs must return a dict"
57
- for output in op.outputs.values():
58
  outputs[node_id, output.name] = result.output[output.name]
59
  node.publish_result(result)
60
  except Exception as e:
 
37
  try:
38
  inputs = []
39
  missing = []
40
+ for i in op.inputs:
41
  edges = in_edges[node_id]
42
  if i.name in edges and edges[i.name] in outputs:
43
  inputs.append(outputs[edges[i.name]])
 
50
  result.output = await await_if_needed(result.output)
51
  result.display = await await_if_needed(result.display)
52
  if len(op.outputs) == 1:
53
+ [output] = op.outputs
54
  outputs[node_id, output.name] = result.output
55
  elif len(op.outputs) > 1:
56
  assert type(result.output) is dict, "An op with multiple outputs must return a dict"
57
+ for output in op.outputs:
58
  outputs[node_id, output.name] = result.output[output.name]
59
  node.publish_result(result)
60
  except Exception as e:
lynxkite-core/src/lynxkite/core/ops.py CHANGED
@@ -163,9 +163,9 @@ def _param_to_type(name, value, type):
163
  class Op(BaseConfig):
164
  func: typing.Callable = pydantic.Field(exclude=True)
165
  name: str
166
- params: dict[str, Parameter | ParameterGroup]
167
- inputs: dict[str, Input]
168
- outputs: dict[str, Output]
169
  # TODO: Make type an enum with the possible values.
170
  type: str = "basic" # The UI to use for this operation.
171
  color: str = "orange" # The color of the operation in the UI.
@@ -189,14 +189,26 @@ class Op(BaseConfig):
189
  res.display = res.output
190
  return res
191
 
192
- def convert_params(self, params):
 
 
 
 
 
 
 
 
 
 
 
 
 
 
193
  """Returns the parameters converted to the expected type."""
194
- res = {}
195
- for p in params:
196
- if p in self.params:
197
- res[p] = _param_to_type(p, params[p], self.params[p].type)
198
- else:
199
- res[p] = params[p]
200
  return res
201
 
202
 
@@ -218,21 +230,21 @@ def op(
218
  func = mem.cache(func)
219
  func = _global_slow(func)
220
  # Positional arguments are inputs.
221
- inputs = {
222
- name: Input(name=name, type=param.annotation)
223
  for name, param in sig.parameters.items()
224
  if param.kind not in (param.KEYWORD_ONLY, param.VAR_KEYWORD)
225
- }
226
- _params = {}
227
  for n, param in sig.parameters.items():
228
  if param.kind == param.KEYWORD_ONLY and not n.startswith("_"):
229
- _params[n] = Parameter.basic(n, param.default, param.annotation)
230
  if params:
231
- _params.update(params)
232
  if outputs:
233
- _outputs = {name: Output(name=name, type=None) for name in outputs}
234
  else:
235
- _outputs = {"output": Output(name="output", type=None)} if view == "basic" else {}
236
  _view = view
237
  if view == "matplotlib":
238
  _view = "image"
@@ -255,6 +267,7 @@ def op(
255
 
256
 
257
  def matplotlib_to_image(func):
 
258
  import matplotlib.pyplot as plt
259
  import base64
260
  import io
@@ -278,7 +291,7 @@ def input_position(**kwargs):
278
  def decorator(func):
279
  op = func.__op__
280
  for k, v in kwargs.items():
281
- op.inputs[k].position = v
282
  return func
283
 
284
  return decorator
@@ -290,7 +303,7 @@ def output_position(**kwargs):
290
  def decorator(func):
291
  op = func.__op__
292
  for k, v in kwargs.items():
293
- op.outputs[k].position = v
294
  return func
295
 
296
  return decorator
@@ -307,13 +320,9 @@ def register_passive_op(env: str, name: str, inputs=[], outputs=["output"], para
307
  op = Op(
308
  func=no_op,
309
  name=name,
310
- params={p.name: p for p in params},
311
- inputs=dict(
312
- (i, Input(name=i, type=None)) if isinstance(i, str) else (i.name, i) for i in inputs
313
- ),
314
- outputs=dict(
315
- (o, Output(name=o, type=None)) if isinstance(o, str) else (o.name, o) for o in outputs
316
- ),
317
  **kwargs,
318
  )
319
  CATALOGS.setdefault(env, {})
 
163
  class Op(BaseConfig):
164
  func: typing.Callable = pydantic.Field(exclude=True)
165
  name: str
166
+ params: list[Parameter | ParameterGroup]
167
+ inputs: list[Input]
168
+ outputs: list[Output]
169
  # TODO: Make type an enum with the possible values.
170
  type: str = "basic" # The UI to use for this operation.
171
  color: str = "orange" # The color of the operation in the UI.
 
189
  res.display = res.output
190
  return res
191
 
192
+ def get_input(self, name: str):
193
+ """Returns the input with the given name."""
194
+ for i in self.inputs:
195
+ if i.name == name:
196
+ return i
197
+ raise ValueError(f"Input {name} not found in operation {self.name}.")
198
+
199
+ def get_output(self, name: str):
200
+ """Returns the output with the given name."""
201
+ for o in self.outputs:
202
+ if o.name == name:
203
+ return o
204
+ raise ValueError(f"Output {name} not found in operation {self.name}.")
205
+
206
+ def convert_params(self, params: dict[str, typing.Any]):
207
  """Returns the parameters converted to the expected type."""
208
+ res = dict(params)
209
+ for p in self.params:
210
+ if p.name in params:
211
+ res[p.name] = _param_to_type(p.name, params[p.name], p.type)
 
 
212
  return res
213
 
214
 
 
230
  func = mem.cache(func)
231
  func = _global_slow(func)
232
  # Positional arguments are inputs.
233
+ inputs = [
234
+ Input(name=name, type=param.annotation)
235
  for name, param in sig.parameters.items()
236
  if param.kind not in (param.KEYWORD_ONLY, param.VAR_KEYWORD)
237
+ ]
238
+ _params = []
239
  for n, param in sig.parameters.items():
240
  if param.kind == param.KEYWORD_ONLY and not n.startswith("_"):
241
+ _params.append(Parameter.basic(n, param.default, param.annotation))
242
  if params:
243
+ _params.extend(params)
244
  if outputs:
245
+ _outputs = [Output(name=name, type=None) for name in outputs]
246
  else:
247
+ _outputs = [Output(name="output", type=None)] if view == "basic" else []
248
  _view = view
249
  if view == "matplotlib":
250
  _view = "image"
 
267
 
268
 
269
  def matplotlib_to_image(func):
270
+ """Decorator for converting a matplotlib figure to an image."""
271
  import matplotlib.pyplot as plt
272
  import base64
273
  import io
 
291
  def decorator(func):
292
  op = func.__op__
293
  for k, v in kwargs.items():
294
+ op.get_input(k).position = v
295
  return func
296
 
297
  return decorator
 
303
  def decorator(func):
304
  op = func.__op__
305
  for k, v in kwargs.items():
306
+ op.get_output(k).position = v
307
  return func
308
 
309
  return decorator
 
320
  op = Op(
321
  func=no_op,
322
  name=name,
323
+ params=params,
324
+ inputs=[Input(name=i, type=None) if isinstance(i, str) else i for i in inputs],
325
+ outputs=[Output(name=o, type=None) if isinstance(o, str) else o for o in outputs],
 
 
 
 
326
  **kwargs,
327
  )
328
  CATALOGS.setdefault(env, {})
lynxkite-core/src/lynxkite/core/workspace.py CHANGED
@@ -107,9 +107,9 @@ class Workspace(BaseConfig):
107
  for n in self.nodes:
108
  if n.id in _ops:
109
  for h in _ops[n.id].inputs:
110
- valid_targets.add((n.id, h))
111
  for h in _ops[n.id].outputs:
112
- valid_sources.add((n.id, h))
113
  edges = [
114
  edge
115
  for edge in self.edges
@@ -197,6 +197,7 @@ def update_metadata(ws: Workspace) -> Workspace:
197
  else:
198
  data.error = "Unknown operation."
199
  if hasattr(node, "_crdt"):
 
200
  node._crdt["data"]["error"] = "Unknown operation."
201
  return ws
202
 
 
107
  for n in self.nodes:
108
  if n.id in _ops:
109
  for h in _ops[n.id].inputs:
110
+ valid_targets.add((n.id, h.name))
111
  for h in _ops[n.id].outputs:
112
+ valid_sources.add((n.id, h.name))
113
  edges = [
114
  edge
115
  for edge in self.edges
 
197
  else:
198
  data.error = "Unknown operation."
199
  if hasattr(node, "_crdt"):
200
+ node._crdt["data"]["meta"] = {}
201
  node._crdt["data"]["error"] = "Unknown operation."
202
  return ws
203
 
lynxkite-core/tests/test_ops.py CHANGED
@@ -9,12 +9,12 @@ def test_op_decorator_no_params_no_types_default_positions():
9
  return a + b
10
 
11
  assert add.__op__.name == "add"
12
- assert add.__op__.params == {}
13
- assert add.__op__.inputs == {
14
- "a": ops.Input(name="a", type=inspect._empty, position="left"),
15
- "b": ops.Input(name="b", type=inspect._empty, position="left"),
16
- }
17
- assert add.__op__.outputs == {"result": ops.Output(name="result", type=None, position="right")}
18
  assert add.__op__.type == "basic"
19
  assert ops.CATALOGS["test"]["add"] == add.__op__
20
 
@@ -27,12 +27,12 @@ def test_op_decorator_custom_positions():
27
  return a + b
28
 
29
  assert add.__op__.name == "add"
30
- assert add.__op__.params == {}
31
- assert add.__op__.inputs == {
32
- "a": ops.Input(name="a", type=inspect._empty, position="right"),
33
- "b": ops.Input(name="b", type=inspect._empty, position="top"),
34
- }
35
- assert add.__op__.outputs == {"result": ops.Output(name="result", type=None, position="bottom")}
36
  assert add.__op__.type == "basic"
37
  assert ops.CATALOGS["test"]["add"] == add.__op__
38
 
@@ -43,16 +43,12 @@ def test_op_decorator_with_params_and_types_():
43
  return a * b
44
 
45
  assert multiply.__op__.name == "multiply"
46
- assert multiply.__op__.params == {
47
- "param": ops.Parameter(name="param", default="param", type=str)
48
- }
49
- assert multiply.__op__.inputs == {
50
- "a": ops.Input(name="a", type=int, position="left"),
51
- "b": ops.Input(name="b", type=float, position="left"),
52
- }
53
- assert multiply.__op__.outputs == {
54
- "result": ops.Output(name="result", type=None, position="right")
55
- }
56
  assert multiply.__op__.type == "basic"
57
  assert ops.CATALOGS["test"]["multiply"] == multiply.__op__
58
 
@@ -68,16 +64,14 @@ def test_op_decorator_with_complex_types():
68
  return color.name
69
 
70
  assert complex_op.__op__.name == "color_op"
71
- assert complex_op.__op__.params == {}
72
- assert complex_op.__op__.inputs == {
73
- "color": ops.Input(name="color", type=Color, position="left"),
74
- "color_list": ops.Input(name="color_list", type=list[Color], position="left"),
75
- "color_dict": ops.Input(name="color_dict", type=dict[str, Color], position="left"),
76
- }
77
  assert complex_op.__op__.type == "basic"
78
- assert complex_op.__op__.outputs == {
79
- "result": ops.Output(name="result", type=None, position="right")
80
- }
81
  assert ops.CATALOGS["test"]["color_op"] == complex_op.__op__
82
 
83
 
 
9
  return a + b
10
 
11
  assert add.__op__.name == "add"
12
+ assert add.__op__.params == []
13
+ assert add.__op__.inputs == [
14
+ ops.Input(name="a", type=inspect._empty, position="left"),
15
+ ops.Input(name="b", type=inspect._empty, position="left"),
16
+ ]
17
+ assert add.__op__.outputs == [ops.Output(name="result", type=None, position="right")]
18
  assert add.__op__.type == "basic"
19
  assert ops.CATALOGS["test"]["add"] == add.__op__
20
 
 
27
  return a + b
28
 
29
  assert add.__op__.name == "add"
30
+ assert add.__op__.params == []
31
+ assert add.__op__.inputs == [
32
+ ops.Input(name="a", type=inspect._empty, position="right"),
33
+ ops.Input(name="b", type=inspect._empty, position="top"),
34
+ ]
35
+ assert add.__op__.outputs == [ops.Output(name="result", type=None, position="bottom")]
36
  assert add.__op__.type == "basic"
37
  assert ops.CATALOGS["test"]["add"] == add.__op__
38
 
 
43
  return a * b
44
 
45
  assert multiply.__op__.name == "multiply"
46
+ assert multiply.__op__.params == [ops.Parameter(name="param", default="param", type=str)]
47
+ assert multiply.__op__.inputs == [
48
+ ops.Input(name="a", type=int, position="left"),
49
+ ops.Input(name="b", type=float, position="left"),
50
+ ]
51
+ assert multiply.__op__.outputs == [ops.Output(name="result", type=None, position="right")]
 
 
 
 
52
  assert multiply.__op__.type == "basic"
53
  assert ops.CATALOGS["test"]["multiply"] == multiply.__op__
54
 
 
64
  return color.name
65
 
66
  assert complex_op.__op__.name == "color_op"
67
+ assert complex_op.__op__.params == []
68
+ assert complex_op.__op__.inputs == [
69
+ ops.Input(name="color", type=Color, position="left"),
70
+ ops.Input(name="color_list", type=list[Color], position="left"),
71
+ ops.Input(name="color_dict", type=dict[str, Color], position="left"),
72
+ ]
73
  assert complex_op.__op__.type == "basic"
74
+ assert complex_op.__op__.outputs == [ops.Output(name="result", type=None, position="right")]
 
 
75
  assert ops.CATALOGS["test"]["color_op"] == complex_op.__op__
76
 
77
 
lynxkite-graph-analytics/src/lynxkite_graph_analytics/core.py CHANGED
@@ -150,7 +150,7 @@ def disambiguate_edges(ws: workspace.Workspace):
150
  for edge in reversed(ws.edges):
151
  dst_node = nodes[edge.target]
152
  op = catalog.get(dst_node.data.title)
153
- if op.inputs[edge.targetHandle].type == list[Bundle]:
154
  # Takes multiple bundles as an input. No need to disambiguate.
155
  continue
156
  if (edge.target, edge.targetHandle) in seen:
@@ -201,7 +201,7 @@ async def _execute_node(node, ws, catalog, outputs):
201
  # Convert inputs types to match operation signature.
202
  try:
203
  inputs = []
204
- for p in op.inputs.values():
205
  if p.name not in input_map:
206
  node.publish_error(f"Missing input: {p.name}")
207
  return
 
150
  for edge in reversed(ws.edges):
151
  dst_node = nodes[edge.target]
152
  op = catalog.get(dst_node.data.title)
153
+ if op.get_input(edge.targetHandle).type == list[Bundle]:
154
  # Takes multiple bundles as an input. No need to disambiguate.
155
  continue
156
  if (edge.target, edge.targetHandle) in seen:
 
201
  # Convert inputs types to match operation signature.
202
  try:
203
  inputs = []
204
+ for p in op.inputs:
205
  if p.name not in input_map:
206
  node.publish_error(f"Missing input: {p.name}")
207
  return
lynxkite-graph-analytics/src/lynxkite_graph_analytics/lynxkite_ops.py CHANGED
@@ -29,8 +29,8 @@ class FileFormat(enum.StrEnum):
29
 
30
  @op(
31
  "Import file",
32
- params={
33
- "file_format": ops.ParameterGroup(
34
  name="file_format",
35
  selector=ops.Parameter(name="file_format", type=FileFormat, default=FileFormat.csv),
36
  groups={
@@ -44,7 +44,7 @@ class FileFormat(enum.StrEnum):
44
  },
45
  default=FileFormat.csv,
46
  ),
47
- },
48
  )
49
  def import_file(
50
  *, file_path: str, table_name: str, file_format: FileFormat, **kwargs
 
29
 
30
  @op(
31
  "Import file",
32
+ params=[
33
+ ops.ParameterGroup(
34
  name="file_format",
35
  selector=ops.Parameter(name="file_format", type=FileFormat, default=FileFormat.csv),
36
  groups={
 
44
  },
45
  default=FileFormat.csv,
46
  ),
47
+ ],
48
  )
49
  def import_file(
50
  *, file_path: str, table_name: str, file_format: FileFormat, **kwargs
lynxkite-graph-analytics/src/lynxkite_graph_analytics/networkx_ops.py CHANGED
@@ -201,18 +201,19 @@ def _get_params(func) -> dict | None:
201
  types[k] = param.annotation
202
  if k in ["i", "j", "n"]:
203
  types[k] = int
204
- params = {}
205
  for name, param in sig.parameters.items():
206
  _type = types.get(name, _UNSUPPORTED)
207
  if _type is _UNSUPPORTED:
208
  raise UnsupportedParameterType(name)
209
  if _type is _SKIP or _type in [nx.Graph, nx.DiGraph]:
210
  continue
211
- params[name] = ops.Parameter.basic(
212
  name=name,
213
  default=str(param.default) if type(param.default) in [str, int, float] else None,
214
  type=_type,
215
  )
 
216
  return params
217
 
218
 
@@ -252,7 +253,7 @@ def register_networkx(env: str):
252
  params = _get_params(func)
253
  except UnsupportedParameterType:
254
  continue
255
- inputs = {k: ops.Input(name=k, type=nx.Graph) for k in func.graphs}
256
  nicename = "NX › " + name.replace("_", " ").title()
257
  for a, b in _REPLACEMENTS:
258
  nicename = nicename.replace(a, b)
@@ -261,7 +262,7 @@ def register_networkx(env: str):
261
  name=nicename,
262
  params=params,
263
  inputs=inputs,
264
- outputs={"output": ops.Output(name="output", type=nx.Graph)},
265
  type="basic",
266
  )
267
  cat[nicename] = op
 
201
  types[k] = param.annotation
202
  if k in ["i", "j", "n"]:
203
  types[k] = int
204
+ params = []
205
  for name, param in sig.parameters.items():
206
  _type = types.get(name, _UNSUPPORTED)
207
  if _type is _UNSUPPORTED:
208
  raise UnsupportedParameterType(name)
209
  if _type is _SKIP or _type in [nx.Graph, nx.DiGraph]:
210
  continue
211
+ p = ops.Parameter.basic(
212
  name=name,
213
  default=str(param.default) if type(param.default) in [str, int, float] else None,
214
  type=_type,
215
  )
216
+ params.append(p)
217
  return params
218
 
219
 
 
253
  params = _get_params(func)
254
  except UnsupportedParameterType:
255
  continue
256
+ inputs = [ops.Input(name=k, type=nx.Graph) for k in func.graphs]
257
  nicename = "NX › " + name.replace("_", " ").title()
258
  for a, b in _REPLACEMENTS:
259
  nicename = nicename.replace(a, b)
 
262
  name=nicename,
263
  params=params,
264
  inputs=inputs,
265
+ outputs=[ops.Output(name="output", type=nx.Graph)],
266
  type="basic",
267
  )
268
  cat[nicename] = op
lynxkite-graph-analytics/src/lynxkite_graph_analytics/pytorch/pytorch_core.py CHANGED
@@ -20,9 +20,9 @@ def op(name, weights=False, **kwargs):
20
  def decorator(func):
21
  _op(func)
22
  op = func.__op__
23
- for p in op.inputs.values():
24
  p.position = "bottom"
25
- for p in op.outputs.values():
26
  p.position = "top"
27
  return func
28
 
@@ -302,8 +302,8 @@ class ModelBuilder:
302
 
303
  def run_op(self, node_id: str, op: ops.Op, params) -> Layer:
304
  """Returns the layer produced by this op."""
305
- inputs = [_to_id(*i) for n in op.inputs for i in self.in_edges[node_id][n]]
306
- outputs = [_to_id(node_id, n) for n in op.outputs]
307
  if op.func == ops.no_op:
308
  module = torch.nn.Identity()
309
  else:
 
20
  def decorator(func):
21
  _op(func)
22
  op = func.__op__
23
+ for p in op.inputs:
24
  p.position = "bottom"
25
+ for p in op.outputs:
26
  p.position = "top"
27
  return func
28
 
 
302
 
303
  def run_op(self, node_id: str, op: ops.Op, params) -> Layer:
304
  """Returns the layer produced by this op."""
305
+ inputs = [_to_id(*i) for n in op.inputs for i in self.in_edges[node_id][n.name]]
306
+ outputs = [_to_id(node_id, n.name) for n in op.outputs]
307
  if op.func == ops.no_op:
308
  module = torch.nn.Identity()
309
  else:
lynxkite-graph-analytics/src/lynxkite_graph_analytics/pytorch/pytorch_ops.py CHANGED
@@ -150,9 +150,9 @@ ops.register_passive_op(
150
 
151
  def _set_handle_positions(op):
152
  op: ops.Op = op.__op__
153
- for v in op.outputs.values():
154
  v.position = "top"
155
- for v in op.inputs.values():
156
  v.position = "bottom"
157
 
158
 
 
150
 
151
  def _set_handle_positions(op):
152
  op: ops.Op = op.__op__
153
+ for v in op.outputs:
154
  v.position = "top"
155
+ for v in op.inputs:
156
  v.position = "bottom"
157
 
158