compiled.py 17 KB

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  1. from modelverse_kernel.primitives import PrimitiveFinished
  2. import modelverse_jit.runtime as jit_runtime
  3. def reverseKeyLookup(a, b, **remainder):
  4. edges, = yield [("RO", [a])]
  5. expanded_edges = yield [("RE", [i]) for i in edges]
  6. for i, edge in enumerate(expanded_edges):
  7. if b == edge[1]:
  8. # Found our edge: edges[i]
  9. outgoing, = yield [("RO", [edges[i]])]
  10. result, = yield [("RE", [outgoing[0]])]
  11. raise PrimitiveFinished(result[1])
  12. result, = yield [("CNV", ["(unknown: %s)" % b])]
  13. raise PrimitiveFinished(result)
  14. def read_attribute(a, b, c, **remainder):
  15. model_dict, b_val, c_val, type_mapping = \
  16. yield [("RD", [a, "model"]),
  17. ("RV", [b]),
  18. ("RV", [c]),
  19. ("RD", [a, "type_mapping"]),
  20. ]
  21. model_instance, = \
  22. yield [("RD", [model_dict, b_val])]
  23. edges, = yield [("RO", [model_instance])]
  24. edge_types = yield [("RDN", [type_mapping, i]) for i in edges]
  25. type_edge_val = yield [("RE", [i]) for i in edge_types]
  26. src_nodes = set([i[0] for i in type_edge_val])
  27. found_edges = yield [("RDE", [i, c_val]) for i in src_nodes]
  28. for e1 in found_edges:
  29. if e1 is not None:
  30. # Found an edge!
  31. for i, e2 in enumerate(edge_types):
  32. if e1 == e2:
  33. # The instance of this edge is the one we want!
  34. edge = edges[i]
  35. edge_val, = yield [("RE", [edge])]
  36. result = edge_val[1]
  37. raise PrimitiveFinished(result)
  38. else:
  39. result, = yield [("RR", [])]
  40. raise PrimitiveFinished(result)
  41. raise Exception("Error in reading edge!")
  42. def precompute_cardinalities(a, **remainder):
  43. result, = yield [("CN", [])]
  44. # Read out all edges from the metamodel
  45. a, = yield [("RD", [a, "metamodel"])]
  46. model_dict, = yield [("RD", [a, "model"])]
  47. model_keys, = yield [("RDK", [model_dict])]
  48. type_mapping, = yield [("RD", [a, "type_mapping"])]
  49. elems = yield [("RDN", [model_dict, k]) for k in model_keys]
  50. model_keys_str = yield [("RV", [i]) for i in model_keys]
  51. elem_to_name = dict(zip(elems, model_keys_str))
  52. edges = yield [("RE", [i]) for i in elems]
  53. elems = [elems[i] for i, edge_val in enumerate(edges) if edge_val is not None]
  54. # Now we have all edges in the metamodel
  55. # Read out the type of the Association defining all cardinalities
  56. metamodel, = yield [("RD", [a, "metamodel"])]
  57. metametamodel, = yield [("RD", [metamodel, "metamodel"])]
  58. metametamodel_dict, = \
  59. yield [("RD", [metametamodel, "model"])]
  60. assoc, = yield [("RD", [metametamodel_dict, "Association"])]
  61. slc, suc, tlc, tuc = \
  62. yield [("RDE", [assoc, "source_lower_cardinality"]),
  63. ("RDE", [assoc, "source_upper_cardinality"]),
  64. ("RDE", [assoc, "target_lower_cardinality"]),
  65. ("RDE", [assoc, "target_upper_cardinality"]),
  66. ]
  67. # All that we now have to do is find, for each edge, whether or not it has an edge typed by any of these links!
  68. # Just find all links typed by these links!
  69. types = yield [("RDN", [type_mapping, i]) for i in elems]
  70. cardinalities = {}
  71. for i, edge_type in enumerate(types):
  72. if edge_type == slc:
  73. t = "slc"
  74. elif edge_type == suc:
  75. t = "suc"
  76. elif edge_type == tlc:
  77. t = "tlc"
  78. elif edge_type == tuc:
  79. t = "tuc"
  80. else:
  81. continue
  82. # Found a link, so add it
  83. srcdst, = yield [("RE", [elems[i]])]
  84. source, destination = srcdst
  85. # The edge gives the "source" the cardinality found in "destination"
  86. cardinalities.setdefault(elem_to_name[source], {})[t] = destination
  87. # Now we have to translate the "cardinalities" Python dictionary to a Modelverse dictionary
  88. nodes = yield [("CN", []) for i in cardinalities]
  89. yield [("CD", [result, i, node]) for i, node in zip(cardinalities.keys(), nodes)]
  90. l = cardinalities.keys()
  91. values = yield [("RD", [result, i]) for i in l]
  92. for i, value in enumerate(values):
  93. cards = cardinalities[l[i]]
  94. yield [("CD", [value, card_type, cards[card_type]]) for card_type in cards]
  95. raise PrimitiveFinished(result)
  96. def set_copy(a, **remainder):
  97. b, = yield [("CN", [])]
  98. links, = yield [("RO", [a])]
  99. exp_links = yield [("RE", [i]) for i in links]
  100. _ = yield [("CE", [b, i[1]]) for i in exp_links]
  101. raise PrimitiveFinished(b)
  102. def allInstances(a, b, **remainder):
  103. b_val, = yield [("RV", [b])]
  104. model_dict,= yield [("RD", [a, "model"])]
  105. metamodel, = yield [("RD", [a, "metamodel"])]
  106. mm_dict, = yield [("RD", [metamodel, "model"])]
  107. typing, = yield [("RD", [a, "type_mapping"])]
  108. elem_keys, = yield [("RDK", [model_dict])]
  109. elems = yield [("RDN", [model_dict, i]) for i in elem_keys]
  110. mms = yield [("RDN", [typing, i]) for i in elems]
  111. # Have the type for each name
  112. types_to_name_nodes = {}
  113. for key, mm in zip(elem_keys, mms):
  114. types_to_name_nodes.setdefault(mm, set()).add(key)
  115. # And now we have the inverse mapping: for each type, we have the node containing the name
  116. # Get the inheritance link type
  117. inheritance_type, = yield [("RD", [metamodel, "inheritance"])]
  118. # Now we figure out which types are valid for the specified model
  119. desired_types = set()
  120. mm_element, = yield [("RD", [mm_dict, b_val])]
  121. work_list = []
  122. work_list.append(mm_element)
  123. mm_typing, = yield [("RD", [metamodel, "type_mapping"])]
  124. while work_list:
  125. mm_element = work_list.pop()
  126. if mm_element in desired_types:
  127. # Already been here, so stop
  128. continue
  129. # New element, so continue
  130. desired_types.add(mm_element)
  131. # Follow all inheritance links that COME IN this node, as all these are subtypes and should also match
  132. incoming, = yield [("RI", [mm_element])]
  133. for i in incoming:
  134. t, = yield [("RDN", [mm_typing, i])]
  135. if t == inheritance_type:
  136. e, = yield [("RE", [i])]
  137. # Add the source of the inheritance link to the work list
  138. work_list.append(e[0])
  139. # Now desired_types holds all the direct types that we are interested in!
  140. # Construct the result out of all models that are direct instances of our specified type
  141. final = set()
  142. for t in desired_types:
  143. final |= types_to_name_nodes.get(t, set())
  144. # Result is a Python set with nodes, so just make this a Mv set
  145. result, = yield [("CN", [])]
  146. v = yield [("RV", [i]) for i in final]
  147. _ = yield [("CE", [result, i]) for i in final]
  148. raise PrimitiveFinished(result)
  149. def add_AL(a, b, **remainder):
  150. worklist = [(b, "funcdef")]
  151. added = set()
  152. type_cache = {}
  153. model_dict, = yield [("RD", [a, "model"])]
  154. metamodel, = yield [("RD", [a, "metamodel"])]
  155. metamodel_dict, = yield [("RD", [metamodel, "model"])]
  156. type_map, = yield [("RD", [a, "type_mapping"])]
  157. outgoing, = yield [("RO", [model_dict])]
  158. edges = yield [("RE", [i]) for i in outgoing]
  159. added |= set([i[1] for i in edges])
  160. result, = yield [("CNV", ["__%s" % b])]
  161. # All the action language elements and their expected output links
  162. type_links = {
  163. "if": [("cond", ""), ("then", ""), ("else", ""), ("next", "")],
  164. "while": [("cond", ""), ("body", ""), ("next", "")],
  165. "assign": [("var", ""), ("value", ""), ("next", "")],
  166. "break": [("while", "while")],
  167. "continue": [("while", "while")],
  168. "return": [("value", "")],
  169. "resolve": [("var", "")],
  170. "access": [("var", "")],
  171. "constant": [("node", "")],
  172. "output": [("node", ""), ("next", "")],
  173. "global": [("var", "String"), ("next", "")],
  174. "param": [("name", "String"), ("value", ""), ("next_param", "param")],
  175. "funcdef": [("body", ""), ("next", "")],
  176. "call": [("func", ""), ("params", "param"), ("last_param", "param"), ("next", "")],
  177. }
  178. # Already add some often used types to the type cache, so we don't have to check for their presence
  179. to_str, string = yield [("RD", [metamodel_dict, "to_str"]),
  180. ("RD", [metamodel_dict, "String"])]
  181. type_cache = {"to_str": to_str,
  182. "String": string}
  183. while worklist:
  184. # Fetch the element and see if we need to add it
  185. worknode, expected_type = worklist.pop(0)
  186. if worknode in added:
  187. continue
  188. # Determine type of element
  189. if expected_type == "":
  190. value, = yield [("RV", [worknode])]
  191. if (isinstance(value, dict)) and ("value" in value):
  192. v = value["value"]
  193. if v in ["if", "while", "assign", "call", "break", "continue", "return", "resolve", "access", "constant", "global", "declare"]:
  194. expected_type = v
  195. else:
  196. expected_type = "Any"
  197. else:
  198. expected_type = "Any"
  199. # Fill the cache
  200. if expected_type not in type_cache:
  201. type_cache[expected_type], = yield [("RD", [metamodel_dict, expected_type])]
  202. # Need to add it now
  203. yield [("CD", [model_dict, "__%s" % worknode, worknode])]
  204. added.add(worknode)
  205. # NOTE can't just use CD here, as the key is a node and not a value
  206. t1, = yield [("CE", [type_map, type_cache[expected_type]])]
  207. t2, = yield [("CE", [t1, worknode])]
  208. if t1 is None or t2 is None:
  209. raise Exception("ERROR")
  210. # Now add all its outgoing links, depending on the type we actually saw
  211. links = type_links.get(expected_type, [])
  212. for link in links:
  213. link_name, destination_type = link
  214. # Check if the link actually exists
  215. destination, = yield [("RD", [worknode, link_name])]
  216. if destination is not None:
  217. # If so, we add it and continue
  218. edge, = yield [("RDE", [worknode, link_name])]
  219. edge_outlinks, = yield [("RO", [edge])]
  220. edge_outlink = edge_outlinks[0]
  221. edge_name, = yield [("RE", [edge_outlink])]
  222. edge_name = edge_name[1]
  223. # Now add: edge, edge_outlink, edge_name
  224. # Add 'edge'
  225. yield [("CD", [model_dict, "__%s" % edge, edge])]
  226. added.add(edge)
  227. link_type = "%s_%s" % (expected_type, link_name)
  228. if link_type not in type_cache:
  229. type_cache[link_type], = yield [("RD", [metamodel_dict, link_type])]
  230. t, = yield [("CE", [type_map, type_cache[link_type]])]
  231. yield [("CE", [t, edge])]
  232. # Add 'edge_outlink'
  233. yield [("CD", [model_dict, "__%s" % edge_outlink, edge_outlink])]
  234. added.add(edge_outlink)
  235. t, = yield [("CE", [type_map, type_cache["to_str"]])]
  236. yield [("CE", [t, edge_outlink])]
  237. # Add 'edge_name' (if not present)
  238. if edge_name not in added:
  239. yield [("CD", [model_dict, "__%s" % edge_name, edge_name])]
  240. t, = yield [("CE", [type_map, type_cache["String"]])]
  241. yield [("CE", [t, edge_name])]
  242. added.add(edge_name)
  243. # Add the destination to the worklist
  244. worklist.append((destination, destination_type))
  245. raise PrimitiveFinished(result)
  246. def get_superclasses(a, b, **remainder):
  247. inheritance, = yield [("RD", [a, "inheritance"])]
  248. model_dict, = yield [("RD", [a, "model"])]
  249. b_v, = yield [("RV", [b])]
  250. subclass, = yield [("RD", [model_dict, b_v])]
  251. type_mapping, = yield [("RD", [a, "type_mapping"])]
  252. names, = yield [("RDK", [model_dict])]
  253. elems = yield [("RDN", [model_dict, i]) for i in names]
  254. elem_to_name = dict(zip(elems, names))
  255. result, = yield [("CN", [])]
  256. worklist = [subclass]
  257. while worklist:
  258. subclass = worklist.pop()
  259. res = elem_to_name[subclass]
  260. yield [("CE", [result, res])]
  261. outgoing, = yield [("RO", [subclass])]
  262. types = yield [("RDN", [type_mapping, i]) for i in outgoing]
  263. for i, t in enumerate(types):
  264. if t == inheritance:
  265. # Found an inheritance link!
  266. elem = outgoing[i]
  267. srcdst, = yield [("RE", [elem])]
  268. src, dst = srcdst
  269. # Find elem in elems
  270. worklist.append(dst)
  271. raise PrimitiveFinished(result)
  272. def selectPossibleIncoming(a, b, c, **remainder):
  273. model_dict, = yield [("RD", [a, "model"])]
  274. limit_set_links, = \
  275. yield [("RO", [c])]
  276. limit_set = yield [("RE", [i]) for i in limit_set_links]
  277. limit_set_names = [i[1] for i in limit_set]
  278. name_values = yield [("RV", [i]) for i in limit_set_names]
  279. limit_set = yield [("RD", [model_dict, i]) for i in name_values]
  280. superclasses, = yield [("CALL_ARGS", [get_superclasses, (a, b)])]
  281. vals, = yield [("RO", [superclasses])]
  282. superclasses = yield [("RE", [i]) for i in vals]
  283. superclasses = [i[1] for i in superclasses]
  284. superclass_names = yield [("RV", [i]) for i in superclasses]
  285. elems = yield [("RD", [model_dict, i]) for i in superclass_names]
  286. result, = yield [("CN", [])]
  287. for i, edge in enumerate(limit_set):
  288. srcdst, = yield [("RE", [edge])]
  289. src, dst = srcdst
  290. if dst in elems:
  291. yield [("CE", [result, limit_set_names[i]])]
  292. raise PrimitiveFinished(result)
  293. def selectPossibleOutgoing(a, b, c, **remainder):
  294. model_dict, = yield [("RD", [a, "model"])]
  295. limit_set_links, = \
  296. yield [("RO", [c])]
  297. limit_set = yield [("RE", [i]) for i in limit_set_links]
  298. limit_set_names = \
  299. [i[1] for i in limit_set]
  300. name_values = yield [("RV", [i]) for i in limit_set_names]
  301. limit_set = yield [("RD", [model_dict, i]) for i in name_values]
  302. superclasses, = yield [("CALL_ARGS", [get_superclasses, (a, b)])]
  303. vals, = yield [("RO", [superclasses])]
  304. superclasses = yield [("RE", [i]) for i in vals]
  305. superclasses = [i[1] for i in superclasses]
  306. superclass_names = yield [("RV", [i]) for i in superclasses]
  307. elems = yield [("RD", [model_dict, i]) for i in superclass_names]
  308. result, = yield [("CN", [])]
  309. for i, edge in enumerate(limit_set):
  310. srcdst, = yield [("RE", [edge])]
  311. src, dst = srcdst
  312. if src in elems:
  313. yield [("CE", [result, limit_set_names[i]])]
  314. raise PrimitiveFinished(result)
  315. def check_symbols(a, b, c, **remainder):
  316. symbols = {}
  317. function_name, = yield [("RV", [b])]
  318. symbols[function_name] = False
  319. object_links, = yield [("RO", [c])]
  320. set_elements = yield [("RE", [i]) for i in object_links]
  321. set_elements = [i[1] for i in set_elements]
  322. set_values = yield [("RV", [i]) for i in set_elements]
  323. set_elements = yield [("RD", [a, i]) for i in set_values]
  324. symbols_set = yield [("RD", [i, "symbols"]) for i in set_elements]
  325. all_keys = yield [("RDK", [i]) for i in symbols_set]
  326. for i, s in zip(all_keys, symbols_set):
  327. # For each object we have found
  328. keys = yield [("RV", [j]) for j in i]
  329. values = yield [("RD", [s, j]) for j in keys]
  330. values = yield [("RV", [j]) for j in values]
  331. for key, value in zip(keys, values):
  332. k = key
  333. v = value
  334. if v and symbols.get(k, False):
  335. result = yield [("CNV", ["ERROR: multiple definition of symbol " + str(key)])]
  336. raise PrimitiveFinished(result)
  337. elif v and not symbols.get(k, False):
  338. symbols[k] = True
  339. elif not v and k not in symbols:
  340. symbols[k] = False
  341. for i, j in symbols.items():
  342. if i == "input" or i == "output":
  343. continue
  344. if not j:
  345. result, = yield [("CNV", ["ERROR: undefined symbol " + str(i)])]
  346. raise PrimitiveFinished(result)
  347. result, = yield [("CNV", ["OK"])]
  348. raise PrimitiveFinished(result)
  349. def construct_const(**remainder):
  350. v, = yield [("CNV", [{"value": "constant"}])]
  351. # Get input: keep trying until we get something
  352. inp, = yield [("CALL_KWARGS", [jit_runtime.get_input, remainder])]
  353. yield [("CD", [v, "node", inp])]
  354. raise PrimitiveFinished(v)
  355. def instantiated_name(a, b, **remainder):
  356. name_value, = yield [("RV", [b])]
  357. if name_value == "":
  358. b, = yield [("CNV", ["__" + str(a)])]
  359. raise PrimitiveFinished(b)
  360. def retype(a, b, c, **remainder):
  361. tm, = yield [("RD", [a, "type_mapping"])]
  362. m, = yield [("RD", [a, "model"])]
  363. mm, = yield [("RD", [a, "metamodel"])]
  364. mm_dict, = yield [("RD", [mm, "model"])]
  365. c_val, = yield [("RV", [c])]
  366. mm_ref, = yield [("RD", [mm_dict, c_val])]
  367. b_val, = yield [("RV", [b])]
  368. m_ref, = yield [("RD", [m, b_val])]
  369. prev_edge, = yield [("RDNE", [tm, m_ref])]
  370. if prev_edge is not None:
  371. yield [("DE", [prev_edge])]
  372. t, = yield [("CE", [tm, mm_ref])]
  373. yield [("CE", [t, m_ref])]
  374. raise PrimitiveFinished(None)