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train · 13.6M rows

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id int64 0 10.8M	vector listlengths 1.54k 1.54k	ast_depth int64 3 164	ast_data stringlengths 297 510k	code stringlengths 60 56.5k
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"_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "S_OK", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "setExtJsPath", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "Params", "bases": [{"_type": "Name", "_fields": {"id": "object", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class Params(object): def __init__(self): self.version = False self.destination = False self.sourceURL = False self.name = False self.vcs = False self.vcsBranch = False self.vcsPath = False self.relNotes = False self.outRelNotes = False self.extensionVersion = None self.extensionSource = None self.extjspath = None def isOK(self): if not self.version: return S_ERROR("No version defined") if not self.sourceURL: return S_ERROR("No Source URL defined") if not self.name: return S_ERROR("No name defined") if self.vcs and self.vcs not in TarModuleCreator.VALID_VCS: return S_ERROR("Invalid VCS %s" % self.vcs) return S_OK() def setVersion(self, opVal): self.version = opVal return S_OK() def setDestination(self, opVal): self.destination = os.path.realpath(opVal) return S_OK() def setSourceURL(self, opVal): self.sourceURL = opVal return S_OK() def setName(self, opVal): self.name = opVal return S_OK() def setVCS(self, opVal): self.vcs = opVal.lower() if self.vcs == 'subversion': self.vcs = 'svn' elif self.vcs == 'mercurial': self.vcs = 'hg' return S_OK() def setVCSBranch(self, opVal): self.vcsBranch = opVal return S_OK() def setVCSPath(self, opVal): self.vcsPath = opVal return S_OK() def setReleaseNotes(self, opVal): self.relNotes = opVal return S_OK() def setOutReleaseNotes(self, opVal): self.outRelNotes = True return S_OK() def setExtensionVersion(self, opVal): self.extensionVersion = opVal return S_OK() def setExtensionSource(self, opVal): self.extensionSource = opVal return S_OK() def setExtJsPath(self, opVal): self.extjspath = opVal return S_OK()
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"ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "vcs", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": false}}}}], "name": "__discoverVCS", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __discoverVCS(self): sourceURL = self.params.sourceURL if os.path.expanduser(sourceURL).find("/") == 0: sourceURL = os.path.expanduser(sourceURL) self.params.vcs = "file" return True if sourceURL.find(".git") == len(sourceURL) - 4: self.params.vcs = "git" return True for vcs in TarModuleCreator.VALID_VCS: if sourceURL.find(vcs) == 0: self.params.vcs = vcs return True return False
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"type_comment": null}}], "name": "replaceKeywordsWithGit", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def replaceKeywordsWithGit(cls, dirToDo): for fileName in os.listdir(dirToDo): objPath = os.path.join(dirToDo, fileName) if os.path.isdir(objPath): TarModuleCreator.replaceKeywordsWithGit(objPath) elif os.path.isfile(objPath): if fileName.find('.py', len(fileName) - 3) == len(fileName) - 3: with open(objPath, "r") as fd: fileContents = fd.read() for keyWord, cmdArgs in (('$Id$', '--pretty="%h (%ad) %an <%aE>" --date=iso'), ('$SHA1$', '--pretty="%H"')): foundKeyWord = fileContents.find(keyWord) if foundKeyWord > -1: po2 = subprocess.Popen("git log -n 1 %s '%s' 2>/dev/null" % (cmdArgs, fileName), stdout=subprocess.PIPE, cwd=dirToDo, shell=True) po2.wait() if po2.returncode: continue toReplace = po2.stdout.read().strip() toReplace = "".join(i for i in toReplace if ord(i) < 128) fileContents = fileContents.replace(keyWord, toReplace) with open(objPath, "w") as fd: fd.write(fileContents)
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[], "target": {"_type": "Name", "_fields": {"id": "rawLine", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "relData", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "S_OK", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "__loadReleaseNotesFile", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __loadReleaseNotesFile(self): if not self.params.relNotes: relNotes = os.path.join(self.params.destination, self.params.name, "release.notes") else: relNotes = self.params.relNotes if not os.path.isfile(relNotes): return S_OK("") try: with open(relNotes, "r") as fd: releaseContents = fd.readlines() except Exception as excp: return S_ERROR("Could not open %s: %s" % (relNotes, excp)) gLogger.info("Loaded %s" % relNotes) relData = [] version = False feature = False lastKey = False for rawLine in releaseContents: line = rawLine.strip() if not line: continue if line[0] == "[" and line[-1] == "]": version = line[1:-1].strip() relData.append((version, {'comment': [], 'features': []})) feature = False lastKey = False continue if line[0] == "*": feature = line[1:].strip() relData[-1][1]['features'].append([feature, {}]) lastKey = False continue if not feature: relData[-1][1]['comment'].append(rawLine) continue keyDict = relData[-1][1]['features'][-1][1] foundKey = False for key in ('BUGFIX', 'BUG', 'FIX', "CHANGE", "NEW", "FEATURE"): if line.find("%s:" % key) == 0: line = line[len(key) + 2:].strip() elif line.find("%s " % key) == 0: line = line[len(key) + 1:].strip() else: continue foundKey = key break if foundKey in ('BUGFIX', 'BUG', 'FIX'): foundKey = 'BUGFIX' elif foundKey in ('NEW', 'FEATURE'): foundKey = 'FEATURE' if foundKey: if foundKey not in keyDict: keyDict[foundKey] = [] keyDict[foundKey].append(line) lastKey = foundKey elif lastKey: keyDict[lastKey][-1] += " %s" % line return S_OK(relData)
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{"id": "S_ERROR", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "excp", "type": {"_type": "Name", "_fields": {"id": "Exception", "ctx": {"_type": "Load", "_fields": {}}}}}}], "finalbody": []}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "S_OK", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "__generateRSTFile", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __generateRSTFile(self, releaseData, rstFileName, pkgVersion, singleVersion): rstData = [] parsedPkgVersion = Distribution.parseVersionString(pkgVersion) for version, verData in releaseData: if singleVersion and version != pkgVersion: continue if Distribution.parseVersionString(version) > parsedPkgVersion: continue versionLine = "Version %s" % version rstData.append("") rstData.append("=" * len(versionLine)) rstData.append(versionLine) rstData.append("=" * len(versionLine)) rstData.append("") if verData['comment']: rstData.append("\n".join(verData['comment'])) rstData.append("") for feature, featureData in verData['features']: if not featureData: continue rstData.append(feature) rstData.append("=" * len(feature)) rstData.append("") for key in sorted(featureData): rstData.append(key.capitalize()) rstData.append(":" * (len(key) + 5)) rstData.append("") for entry in featureData[key]: rstData.append(" - %s" % entry) rstData.append("") # Write releasenotes.rst try: rstFilePath = os.path.join(self.params.destination, self.params.name, rstFileName) with open(rstFilePath, "w") as fd: fd.write("\n".join(rstData)) except Exception as excp: return S_ERROR("Could not write %s: %s" % (rstFileName, excp)) return S_OK()
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{"id": "rstFileName", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "singleVersion", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "S_OK", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "__generateReleaseNotes", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __generateReleaseNotes(self): result = self.__loadReleaseNotesFile() if not result['OK']: return result releaseData = result['Value'] if not releaseData: gLogger.info("release.notes not found. Trying to find releasenotes.rst") for rstFileName in ("releasenotes.rst", "releasehistory.rst"): result = self.__compileReleaseNotes(rstFileName) if result['OK']: gLogger.notice("Compiled %s file!" % rstFileName) else: gLogger.warn(result['Message']) return S_OK() gLogger.info("Loaded release.notes") for rstFileName, singleVersion in (("releasenotes.rst", True), ("releasehistory.rst", False)): result = self.__generateRSTFile(releaseData, rstFileName, self.params.version, singleVersion) if not result['OK']: gLogger.error("Could not generate %s: %s" % (rstFileName, result['Message'])) continue result = self.__compileReleaseNotes(rstFileName) if not result['OK']: gLogger.error("Could not compile %s: %s" % (rstFileName, result['Message'])) continue gLogger.notice("Compiled %s file!" % rstFileName) return S_OK()
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"params", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": "Web"}}]}}]}}, "orelse": []}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "__generateTarball", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "create", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def create(self): if not isinstance(self.params, TarModuleCreator.Params): return S_ERROR("Argument is not a TarModuleCreator.Params object ") result = self.params.isOK() if not result['OK']: return result result = self.__checkDestination() if not result['OK']: return result result = self.__checkoutSource() if not result['OK']: return result shutil.rmtree("%s/docs" % self.params.destination, ignore_errors=True) result = self.__generateReleaseNotes() if not result['OK']: gLogger.error("Won't generate release notes: %s" % result['Message']) if 'Web' in self.params.name and self.params.name != 'Web': # if we have an extension, we have to download, because it will be # required to compile the code if self.params.extensionVersion and self.params.extensionSource: # if extensionSource is not provided, the default one is used. self.params.soureURL.... result = self.__checkoutSource("WebAppDIRAC", self.params.extensionSource, self.params.extensionVersion) if not result['OK']: return result retVal = self.__compileWebApp() if not retVal['OK']: # it can fail, if we do not have sencha cmd and extjs farmework installed gLogger.warn('Web is not compiled: %s' % retVal['Message']) return self.__generateTarball()
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[]}}], "type_ignores": []}}	def __iter__(self): current_kwargs = self._op_kwargs previous_next_token = None next_token = [None for _ in range(len(self._input_token))] # The number of items from result_key we've seen so far. total_items = 0 first_request = True primary_result_key = self.result_keys[0] starting_truncation = 0 self._inject_starting_params(current_kwargs) while True: response = self._make_request(current_kwargs) parsed = self._extract_parsed_response(response) if first_request: # The first request is handled differently. We could # possibly have a resume/starting token that tells us where # to index into the retrieved page. if self._starting_token is not None: starting_truncation = self._handle_first_request( parsed, primary_result_key, starting_truncation) first_request = False self._record_non_aggregate_key_values(parsed) current_response = primary_result_key.search(parsed) if current_response is None: current_response = [] num_current_response = len(current_response) truncate_amount = 0 if self._max_items is not None: truncate_amount = (total_items + num_current_response) \ - self._max_items if truncate_amount > 0: self._truncate_response(parsed, primary_result_key, truncate_amount, starting_truncation, next_token) yield response break else: yield response total_items += num_current_response next_token = self._get_next_token(parsed) if all(t is None for t in next_token): break if self._max_items is not None and \ total_items == self._max_items: # We're on a page boundary so we can set the current # next token to be the resume token. self.resume_token = next_token break if previous_next_token is not None and \ previous_next_token == next_token: message = ("The same next token was received " "twice: %s" % next_token) raise PaginationError(message=message) self._inject_token_into_kwargs(current_kwargs, next_token) previous_next_token = next_token
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{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Add", "_fields": {}}, "left": {"_type": "Name", "_fields": {"id": "amount_to_keep", "ctx": {"_type": "Load", "_fields": {}}}}, "right": {"_type": "Name", "_fields": {"id": "starting_truncation", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Name", "_fields": {"id": "str", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "append", "value": {"_type": "Name", "_fields": {"id": "next_token", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Name", "_fields": {"id": "next_token", "ctx": {"_type": "Load", "_fields": {}}}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "resume_token", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}], "name": "_truncate_response", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _truncate_response(self, parsed, primary_result_key, truncate_amount, starting_truncation, next_token): original = primary_result_key.search(parsed) if original is None: original = [] amount_to_keep = len(original) - truncate_amount truncated = original[:amount_to_keep] set_value_from_jmespath( parsed, primary_result_key.expression, truncated ) # The issue here is that even though we know how much we've truncated # we need to account for this globally including any starting # left truncation. For example: # Raw response: [0,1,2,3] # Starting index: 1 # Max items: 1 # Starting left truncation: [1, 2, 3] # End right truncation for max items: [1] # However, even though we only kept 1, this is post # left truncation so the next starting index should be 2, not 1 # (left_truncation + amount_to_keep). next_token.append(str(amount_to_keep + starting_truncation)) self.resume_token = next_token
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First we need to slice into the array and only return # the truncated amount. starting_truncation = self._parse_starting_token()[1] all_data = primary_result_key.search(parsed) set_value_from_jmespath( parsed, primary_result_key.expression, all_data[starting_truncation:] ) # We also need to truncate any secondary result keys # because they were not truncated in the previous last # response. for token in self.result_keys: if token == primary_result_key: continue set_value_from_jmespath(parsed, token.expression, []) return starting_truncation
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"orelse": []}}, {"_type": "Return", "_fields": {"value": {"_type": "Name", "_fields": {"id": "complete_result", "ctx": {"_type": "Load", "_fields": {}}}}}}], "name": "build_full_result", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def build_full_result(self): complete_result = {} # Prepopulate the result keys with an empty list. for result_expression in self.result_keys: set_value_from_jmespath(complete_result, result_expression.expression, []) for _, page in self: # We're incrementally building the full response page # by page. 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{"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}], "name": "__init__", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __init__(self, method, pagination_config): self._method = method self._pagination_cfg = pagination_config self._output_token = self._get_output_tokens(self._pagination_cfg) self._input_token = self._get_input_tokens(self._pagination_cfg) self._more_results = self._get_more_results_token(self._pagination_cfg) self._non_aggregate_keys = self._get_non_aggregate_keys( self._pagination_cfg) self._result_keys = self._get_result_keys(self._pagination_cfg) self._limit_key = self._get_limit_key(self._pagination_cfg)
10,818	[ 0.02674321085214615, 0.0017554756486788392, 0.009007477201521397, -0.03338247537612915, 0.025295395404100418, -0.008474888280034065, 0.038346413522958755, 0.04670237377285957, 0.057085275650024414, 0.03911168873310089, -0.008485229685902596, -0.004847595002502203, -0.031769197434186935, -0...	11	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "If", "_fields": {"body": [{"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": null}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Is", "_fields": {}}], "left": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_starting_token", "value": {"_type": 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[{"_type": "Raise", "_fields": {"exc": {"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "Bad starting token: %s"}}, "right": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_starting_token", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}], "func": {"_type": "Name", "_fields": {"id": "ValueError", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "cause": null}}], "name": null, "type": {"_type": "Name", "_fields": {"id": "ValueError", "ctx": {"_type": "Load", "_fields": {}}}}}}], "finalbody": []}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "parts", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "len", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "comparators": [{"_type": "BinOp", "_fields": {"op": {"_type": "Add", "_fields": {}}, "left": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_input_token", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Name", "_fields": {"id": "len", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "right": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}}}]}}, "orelse": []}}, {"_type": "For", "_fields": {"body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": null}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "append", "value": {"_type": "Name", "_fields": {"id": "next_token", "ctx": {"_type": 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{"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "next_token", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "index", "ctx": {"_type": "Load", "_fields": {}}}}]}}}}], "name": "_parse_starting_token", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _parse_starting_token(self): if self._starting_token is None: return None parts = self._starting_token.split('___') next_token = [] index = 0 if len(parts) == len(self._input_token) + 1: try: index = int(parts.pop()) except ValueError: raise ValueError("Bad starting token: %s" % self._starting_token) for part in parts: if part == 'None': next_token.append(None) else: next_token.append(part) return next_token, index
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It uses the lower-cased object_name + "_set", # but this can be overridden with the "related_name" option. if self.field.rel.multiple: # If this is a symmetrical m2m relation on self, there is no reverse accessor. if getattr(self.field.rel, 'symmetrical', False) and self.model == self.parent_model: return None return self.field.rel.related_name or (self.opts.object_name.lower() + '_set') else: return self.field.rel.related_name or (self.opts.object_name.lower())
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"call", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_operation", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": null, "value": {"_type": "Name", "_fields": {"id": "current_kwargs", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}}}], "name": "_make_request", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}, {"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "response", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Return", "_fields": {"value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}, "value": {"_type": "Name", "_fields": {"id": "response", "ctx": {"_type": "Load", "_fields": {}}}}}}}}], "name": "_extract_parsed_response", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "DeprecatedPageIterator", "bases": [{"_type": "Name", "_fields": {"id": "PageIterator", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class DeprecatedPageIterator(PageIterator): def __init__(self, operation, endpoint, input_token, output_token, more_results, result_keys, non_aggregate_keys, limit_key, max_items, starting_token, page_size, op_kwargs): super(DeprecatedPageIterator, self).__init__( None, input_token, output_token, more_results, result_keys, non_aggregate_keys, limit_key, max_items, starting_token, page_size, op_kwargs) self._operation = operation self._endpoint = endpoint def _make_request(self, current_kwargs): return self._operation.call(self._endpoint, **current_kwargs) def _extract_parsed_response(self, response): return response[1]
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{}}, "elts": [{"_type": "Constant", "_fields": {"kind": null, "value": "name"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "ilike"}}, {"_type": "Name", "_fields": {"id": "name", "ctx": {"_type": "Load", "_fields": {}}}}]}}]}}, "right": {"_type": "Name", "_fields": {"id": "args", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "search", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "limit", "value": {"_type": "Name", "_fields": {"id": "limit", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "context", "value": {"_type": "Name", "_fields": {"id": "context", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "ids", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "cr", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "uid", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "ids", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "name_get", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "context", "value": {"_type": "Name", "_fields": {"id": "context", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}}}], "name": "name_search", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def name_search( self, cr, uid, name='', args=None, operator='ilike', context=None, limit=100): if args is None: args = [] ids = self.search( cr, uid, ['\|', ('code', 'ilike', name), ('name', 'ilike', name)] + args, limit=limit, context=context ) return self.name_get(cr, uid, ids, context=context)
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"arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "username"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "password"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "deviceType"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "outputfile"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "asNum"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg1"}}], "values": [{"_type": "Constant", "_fields": {"kind": null, "value": "admin"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "pass"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.39"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "g8272_cnos"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "test_log", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "vrf"}}]}}], "func": {"_type": "Name", "_fields": {"id": "set_module_args", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute_module", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "changed", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "BGP configurations accomplished"}}, "targets": [{"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "msg"}}, "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_cnos_bgp_vrf", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "TestCnosBgpModule", "bases": [{"_type": "Name", "_fields": {"id": "TestCnosModule", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class TestCnosBgpModule(TestCnosModule): module = cnos_bgp def setUp(self): super(TestCnosBgpModule, self).setUp() self.mock_run_cnos_commands = patch('ansible.module_utils.network.cnos.cnos.run_cnos_commands') self.run_cnos_commands = self.mock_run_cnos_commands.start() def tearDown(self): super(TestCnosBgpModule, self).tearDown() self.mock_run_cnos_commands.stop() def load_fixtures(self, commands=None, transport='cli'): self.run_cnos_commands.return_value = [load_fixture('cnos_bgp_config.cfg')] def test_bgp_neighbor(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'neighbor', 'bgpArg2': '10.241.107.40', 'bgpArg3': '13', 'bgpArg4': 'address-family', 'bgpArg5': 'ipv4', 'bgpArg6': 'next-hop-self'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result) def test_cnos_bgp_dampening(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'address-family', 'bgpArg2': 'ipv4', 'bgpArg3': 'dampening', 'bgpArg4': '13', 'bgpArg5': '233', 'bgpArg6': '333', 'bgpArg7': '15', 'bgpArg8': '33'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result) def test_cnos_bgp_network(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'address-family', 'bgpArg2': 'ipv4', 'bgpArg3': 'network', 'bgpArg4': '1.2.3.4/5', 'bgpArg5': 'backdoor'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result) def test_cnos_bgp_clusterid(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'cluster-id', 'bgpArg2': '10.241.107.40'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result) def test_cnos_bgp_graceful_restart(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'graceful-restart', 'bgpArg2': '333'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result) def test_cnos_bgp_routerid(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'router-id', 'bgpArg2': '1.2.3.4'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result) def test_cnos_bgp_vrf(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'vrf'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result)
10,825	[ 0.022048702463507652, -0.0013940305216237903, 0.04460897669196129, -0.005790342576801777, -0.03381483256816864, 0.020322151482105255, 0.002583432709798217, -0.004341957625001669, 0.03023383766412735, 0.03683310002088547, 0.002442750846967101, -0.0039199115708470345, -0.041104719042778015, ...	8	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "username"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "password"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, {"_type": "Constant", "_fields": 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{"kind": null, "value": "g8272_cnos"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "test_log", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "address-family"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "ipv4"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "dampening"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "13"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "233"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "333"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "15"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}]}}], "func": {"_type": "Name", "_fields": {"id": "set_module_args", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute_module", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "changed", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "BGP configurations accomplished"}}, "targets": [{"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "msg"}}, "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_cnos_bgp_dampening", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_cnos_bgp_dampening(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'address-family', 'bgpArg2': 'ipv4', 'bgpArg3': 'dampening', 'bgpArg4': '13', 'bgpArg5': '233', 'bgpArg6': '333', 'bgpArg7': '15', 'bgpArg8': '33'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result)
10,826	[ -0.029618989676237106, -0.022767193615436554, 0.039860621094703674, -0.00502765504643321, -0.026253195479512215, -0.013258825056254864, 0.0074287885800004005, 0.010103393346071243, 0.02560407668352127, 0.03214333578944206, -0.0029420647770166397, 0.005914181470870972, -0.028729457408189774, ...	8	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "username"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "password"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "deviceType"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "outputfile"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "asNum"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg1"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg2"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg3"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg4"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg5"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg6"}}], "values": [{"_type": "Constant", "_fields": {"kind": null, "value": "admin"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "pass"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.39"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "g8272_cnos"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "test_log", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "neighbor"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.40"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "13"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "address-family"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "ipv4"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "next-hop-self"}}]}}], "func": {"_type": "Name", "_fields": {"id": "set_module_args", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute_module", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "changed", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "BGP configurations accomplished"}}, "targets": [{"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "msg"}}, "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_bgp_neighbor", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_bgp_neighbor(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'neighbor', 'bgpArg2': '10.241.107.40', 'bgpArg3': '13', 'bgpArg4': 'address-family', 'bgpArg5': 'ipv4', 'bgpArg6': 'next-hop-self'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result)
10,827	[ 0.0023085286375135183, -0.02271580509841442, 0.029372280463576317, -0.02478722482919693, -0.011573190800845623, 0.006825215183198452, 0.016454994678497314, 0.006540103815495968, 0.008413692004978657, 0.030093787238001823, 0.004361039027571678, -0.004099201876670122, -0.035702913999557495, ...	8	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "username"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "password"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "deviceType"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "outputfile"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "asNum"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg1"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg2"}}], "values": [{"_type": "Constant", "_fields": {"kind": null, "value": "admin"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "pass"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.39"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "g8272_cnos"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "test_log", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "cluster-id"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.40"}}]}}], "func": {"_type": "Name", "_fields": {"id": "set_module_args", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute_module", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "changed", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "BGP configurations accomplished"}}, "targets": [{"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "msg"}}, "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_cnos_bgp_clusterid", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_cnos_bgp_clusterid(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'cluster-id', 'bgpArg2': '10.241.107.40'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result)
10,828	[ -0.006394602824002504, -0.01925661228597164, 0.03099016286432743, -0.02494744397699833, -0.01991184614598751, -0.011363464407622814, -0.012328114360570908, 0.013371636159718037, 0.014961186796426773, 0.04047892615199089, 0.0014621434966102242, -0.0056301625445485115, -0.015968305990099907, ...	8	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "username"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "password"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "deviceType"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "outputfile"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "asNum"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg1"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg2"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg3"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg4"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg5"}}], "values": [{"_type": "Constant", "_fields": {"kind": null, "value": "admin"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "pass"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.39"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "g8272_cnos"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "test_log", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "address-family"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "ipv4"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "network"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "1.2.3.4/5"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "backdoor"}}]}}], "func": {"_type": "Name", "_fields": {"id": "set_module_args", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute_module", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "changed", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "BGP configurations accomplished"}}, "targets": [{"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "msg"}}, "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_cnos_bgp_network", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_cnos_bgp_network(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'address-family', 'bgpArg2': 'ipv4', 'bgpArg3': 'network', 'bgpArg4': '1.2.3.4/5', 'bgpArg5': 'backdoor'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result)
10,829	[ 0.01513222511857748, 0.005048149731010199, 0.026010803878307343, -0.01974034309387207, -0.031413424760103226, 0.024751823395490646, -0.004397268407046795, 0.03984737768769264, 0.01889694668352604, 0.036767151206731796, 0.010261311195790768, 0.010707455687224865, -0.04209643229842186, 0.018...	8	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "username"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "password"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "deviceType"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "outputfile"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "asNum"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg1"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg2"}}], "values": [{"_type": "Constant", "_fields": {"kind": null, "value": "admin"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "pass"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.39"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "g8272_cnos"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "test_log", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "graceful-restart"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "333"}}]}}], "func": {"_type": "Name", "_fields": {"id": "set_module_args", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute_module", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "changed", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "BGP configurations accomplished"}}, "targets": [{"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "msg"}}, "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_cnos_bgp_graceful_restart", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_cnos_bgp_graceful_restart(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'graceful-restart', 'bgpArg2': '333'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result)
10,830	[ -0.005822587292641401, -0.02086598612368107, 0.021595649421215057, -0.030787039548158646, -0.020465848967432976, -0.013522288762032986, -0.0018050314392894506, 0.014522632583975792, 0.009556221775710583, 0.026361990720033646, -0.007749719079583883, -0.0070906695909798145, -0.0228784419596195...	8	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "username"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "password"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "deviceType"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "outputfile"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "asNum"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg1"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "bgpArg2"}}], "values": [{"_type": "Constant", "_fields": {"kind": null, "value": "admin"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "pass"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "10.241.107.39"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "g8272_cnos"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "test_log", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "33"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "router-id"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "1.2.3.4"}}]}}], "func": {"_type": "Name", "_fields": {"id": "set_module_args", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute_module", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "changed", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": "BGP configurations accomplished"}}, "targets": [{"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "msg"}}, "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "expected_result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_cnos_bgp_routerid", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_cnos_bgp_routerid(self): set_module_args({'username': 'admin', 'password': 'pass', 'host': '10.241.107.39', 'deviceType': 'g8272_cnos', 'outputfile': self.test_log, 'asNum': '33', 'bgpArg1': 'router-id', 'bgpArg2': '1.2.3.4'}) result = self.execute_module(changed=True) expected_result = 'BGP configurations accomplished' self.assertEqual(result['msg'], expected_result)
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"_fields": {}}}}]}}, "orelse": []}}], "iter": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "data_geo_dims", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "enumerate", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "orelse": [], "target": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "dim_offset", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "dim_name", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "type_comment": null}}], "name": "_verify_data_geo_dims", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _verify_data_geo_dims(self, data, src_geo_dims): # verify that source dims are the same between geo and data data_geo_dims = tuple(d for d in data.dims if d in src_geo_dims) if data_geo_dims != src_geo_dims: raise ValueError("Data dimensions do not match source area dimensions.") # verify that the dims are next to each other first_dim_idx = data.dims.index(src_geo_dims[0]) num_dims = len(src_geo_dims) if data.dims[first_dim_idx:first_dim_idx + num_dims] != data_geo_dims: raise ValueError("Data's geolocation dimensions are not consecutive.") # verify that the dims are the same between src geom and data for dim_offset, dim_name in enumerate(data_geo_dims): geom_size = self.source_geo_def.shape[dim_offset] data_size = data.shape[first_dim_idx + dim_offset] if geom_size != data_size: raise ValueError("Input data shape is not equal to the shape of " "the source geometry: " f"{dim_name}={data_size} versus {geom_size}")
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{"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "With", "_fields": {"body": [{"_type": "With", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "NoNetworkFoundInMaximumAllowedAttempts", "value": {"_type": "Name", "_fields": {"id": "exc", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "allocate_partially_specified_segment", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "driver", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "session", "value": {"_type": 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[]}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "LOG", "value": {"_type": "Name", "_fields": {"id": "helpers", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "warning"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "object", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "patch", "value": {"_type": "Name", "_fields": {"id": "mock", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "optional_vars": {"_type": "Name", "_fields": {"id": "log_warning", "ctx": {"_type": "Store", "_fields": {}}}}}}], "type_comment": null}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Query", "value": {"_type": "Name", "_fields": {"id": "query", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "update"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "object", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "patch", "value": {"_type": "Name", "_fields": {"id": "mock", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "return_value", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}}}]}}, "optional_vars": null}}], "type_comment": null}}], "name": "test_allocate_partial_segment_all_attempts_fail", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "HelpersTest", "bases": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "SqlTestCase", "value": {"_type": "Name", "_fields": {"id": "testlib_api", "ctx": {"_type": "Load", "_fields": {}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class HelpersTest(testlib_api.SqlTestCase): def setUp(self): super(HelpersTest, self).setUp() self.driver = type_vlan.VlanTypeDriver() self.driver.network_vlan_ranges = NETWORK_VLAN_RANGES self.driver._sync_vlan_allocations() self.session = db.get_session() self.useFixture( fixtures.FakeLogger( name=helpers.__name__, format=base.LOG_FORMAT, level=std_logging.DEBUG )) def check_raw_segment(self, expected, observed): for key, value in expected.items(): self.assertEqual(value, observed[key]) def test_primary_keys(self): self.assertEqual(set(['physical_network', 'vlan_id']), self.driver.primary_keys) def test_allocate_specific_unallocated_segment_in_pools(self): expected = dict(physical_network=TENANT_NET, vlan_id=VLAN_MIN) observed = self.driver.allocate_fully_specified_segment(self.session, expected) self.check_raw_segment(expected, observed) def test_allocate_specific_allocated_segment_in_pools(self): raw_segment = dict(physical_network=TENANT_NET, vlan_id=VLAN_MIN) self.driver.allocate_fully_specified_segment(self.session, raw_segment) observed = self.driver.allocate_fully_specified_segment(self.session, raw_segment) self.assertIsNone(observed) def test_allocate_specific_finally_allocated_segment_in_pools(self): # Test case: allocate a specific unallocated segment in pools but # the segment is allocated concurrently between select and update raw_segment = dict(physical_network=TENANT_NET, vlan_id=VLAN_MIN) with mock.patch.object(query.Query, 'update', return_value=0): observed = self.driver.allocate_fully_specified_segment( self.session, raw_segment) self.assertIsNone(observed) def test_allocate_specific_unallocated_segment_outside_pools(self): expected = dict(physical_network=TENANT_NET, vlan_id=VLAN_OUTSIDE) observed = self.driver.allocate_fully_specified_segment(self.session, expected) self.check_raw_segment(expected, observed) def test_allocate_specific_allocated_segment_outside_pools(self): raw_segment = dict(physical_network=TENANT_NET, vlan_id=VLAN_OUTSIDE) self.driver.allocate_fully_specified_segment(self.session, raw_segment) observed = self.driver.allocate_fully_specified_segment(self.session, raw_segment) self.assertIsNone(observed) def test_allocate_specific_finally_unallocated_segment_outside_pools(self): # Test case: allocate a specific allocated segment in pools but # the segment is concurrently unallocated after select or update expected = dict(physical_network=TENANT_NET, vlan_id=VLAN_MIN) with mock.patch.object(self.driver.model, 'save'): observed = self.driver.allocate_fully_specified_segment( self.session, expected) self.check_raw_segment(expected, observed) def test_allocate_partial_segment_without_filters(self): expected = dict(physical_network=TENANT_NET) observed = self.driver.allocate_partially_specified_segment( self.session) self.check_raw_segment(expected, observed) def test_allocate_partial_segment_with_filter(self): expected = dict(physical_network=TENANT_NET) observed = self.driver.allocate_partially_specified_segment( self.session, expected) self.check_raw_segment(expected, observed) def test_allocate_partial_segment_no_resource_available(self): for i in range(VLAN_MIN, VLAN_MAX + 1): self.driver.allocate_partially_specified_segment(self.session) observed = self.driver.allocate_partially_specified_segment( self.session) self.assertIsNone(observed) def test_allocate_partial_segment_outside_pools(self): raw_segment = dict(physical_network='other_phys_net') observed = self.driver.allocate_partially_specified_segment( self.session, raw_segment) self.assertIsNone(observed) def test_allocate_partial_segment_first_attempt_fails(self): expected = dict(physical_network=TENANT_NET) with mock.patch.object(query.Query, 'update', side_effect=[0, 1]): observed = self.driver.allocate_partially_specified_segment( self.session, **expected) self.check_raw_segment(expected, observed) def test_allocate_partial_segment_all_attempts_fail(self): with mock.patch.object(query.Query, 'update', return_value=0): with mock.patch.object(helpers.LOG, 'warning') as log_warning: self.assertRaises( exc.NoNetworkFoundInMaximumAllowedAttempts, self.driver.allocate_partially_specified_segment, self.session) log_warning.assert_called_once_with(mock.ANY, mock.ANY)
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10,840	[ 0.030114509165287018, -0.006809985730797052, 0.01733865775167942, -0.00011834774340968579, 0.03830474242568016, -0.009656035341322422, 0.005138858687132597, 0.025300750508904457, 0.0013667024904862046, -0.021114377304911613, 0.06219102442264557, -0.036684948951005936, -0.04606151208281517, ...	9	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "dict", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "physical_network", "value": {"_type": "Name", "_fields": {"id": "TENANT_NET", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "vlan_id", "value": {"_type": "Name", "_fields": {"id": "VLAN_MIN", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "raw_segment", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "With", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "session", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "allocate_fully_specified_segment", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "driver", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": null, "value": {"_type": "Name", "_fields": {"id": "raw_segment", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "observed", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "observed", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertIsNone", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Query", "value": {"_type": "Name", "_fields": {"id": "query", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "update"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "object", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "patch", "value": {"_type": "Name", "_fields": {"id": "mock", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "return_value", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}}}]}}, "optional_vars": null}}], "type_comment": null}}], "name": "test_allocate_specific_finally_allocated_segment_in_pools", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_allocate_specific_finally_allocated_segment_in_pools(self): # Test case: allocate a specific unallocated segment in pools but # the segment is allocated concurrently between select and update raw_segment = dict(physical_network=TENANT_NET, vlan_id=VLAN_MIN) with mock.patch.object(query.Query, 'update', return_value=0): observed = self.driver.allocate_fully_specified_segment( self.session, **raw_segment) self.assertIsNone(observed)
10,841	[ 0.01137316320091486, 0.0018610348924994469, 0.04477603733539581, -0.01181795820593834, -0.00956309400498867, -0.015641959384083748, 0.013467405922710896, 0.02859043888747692, 0.005547583103179932, 0.011088987812399864, 0.04956993833184242, -0.023018144071102142, -0.028466884046792984, -0.0...	10	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "With", "_fields": {"body": [{"_type": "With", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "NoNetworkFoundInMaximumAllowedAttempts", "value": {"_type": "Name", "_fields": {"id": "exc", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "allocate_partially_specified_segment", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "driver", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "session", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertRaises", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "ANY", "value": {"_type": "Name", "_fields": {"id": "mock", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "ANY", "value": {"_type": "Name", "_fields": {"id": "mock", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assert_called_once_with", "value": {"_type": "Name", "_fields": {"id": "log_warning", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "LOG", "value": {"_type": "Name", "_fields": {"id": "helpers", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "warning"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "object", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "patch", "value": {"_type": "Name", "_fields": {"id": "mock", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "optional_vars": {"_type": "Name", "_fields": {"id": "log_warning", "ctx": {"_type": "Store", "_fields": {}}}}}}], "type_comment": null}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Query", "value": {"_type": "Name", "_fields": {"id": "query", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": "update"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "object", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "patch", "value": {"_type": "Name", "_fields": {"id": "mock", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "return_value", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}}}]}}, "optional_vars": null}}], "type_comment": null}}], "name": "test_allocate_partial_segment_all_attempts_fail", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test_allocate_partial_segment_all_attempts_fail(self): with mock.patch.object(query.Query, 'update', return_value=0): with mock.patch.object(helpers.LOG, 'warning') as log_warning: self.assertRaises( exc.NoNetworkFoundInMaximumAllowedAttempts, self.driver.allocate_partially_specified_segment, self.session) log_warning.assert_called_once_with(mock.ANY, mock.ANY)
10,842	[ 0.06080109626054764, 0.024536600336432457, -0.02653724141418934, -0.03587356582283974, -0.016258083283901215, 0.0056196171790361404, 0.022110534831881523, -0.019247548654675484, 0.015292257070541382, -0.01836220733821392, 0.057627663016319275, -0.022823406383395195, -0.00221766484901309, 0...	10	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "fileobj", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "fileobj", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "OggPage", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "While", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "fileobj", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "OggPage", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "Speex "}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "startswith", "value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "packets", "value": {"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}, "keywords": []}}}}, "orelse": []}}, {"_type": "If", "_fields": {"body": [{"_type": "Raise", "_fields": {"exc": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "page has ID header, but doesn't start a stream"}}], "func": {"_type": "Name", "_fields": {"id": "OggSpeexHeaderError", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "cause": null}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "first", "value": {"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "orelse": []}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Slice", "_fields": {"step": null, "lower": {"_type": "Constant", "_fields": {"kind": null, "value": 36}}, "upper": {"_type": "Constant", "_fields": {"kind": null, "value": 40}}}}, "value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "packets", "value": {"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "uint_le", "value": {"_type": "Name", "_fields": {"id": "cdata", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "sample_rate", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Slice", "_fields": {"step": null, "lower": {"_type": "Constant", "_fields": {"kind": null, "value": 48}}, "upper": {"_type": "Constant", "_fields": {"kind": null, "value": 52}}}}, "value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "packets", "value": {"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "uint_le", "value": {"_type": "Name", "_fields": {"id": "cdata", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "channels", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 0}}, {"_type": "Call", "_fields": {"args": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Slice", "_fields": {"step": null, "lower": {"_type": "Constant", "_fields": {"kind": null, "value": 52}}, "upper": {"_type": "Constant", "_fields": {"kind": null, "value": 56}}}}, "value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "packets", "value": {"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int_le", "value": {"_type": "Name", "_fields": {"id": "cdata", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}], "func": {"_type": "Name", "_fields": {"id": "max", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "bitrate", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "serial", "value": {"_type": "Name", "_fields": {"id": "page", "ctx": {"_type": "Load", "_fields": {}}}}}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "serial", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}], "name": "__init__", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __init__(self, fileobj): page = OggPage(fileobj) while not page.packets[0].startswith("Speex "): page = OggPage(fileobj) if not page.first: raise OggSpeexHeaderError( "page has ID header, but doesn't start a stream") self.sample_rate = cdata.uint_le(page.packets[0][36:40]) self.channels = cdata.uint_le(page.packets[0][48:52]) self.bitrate = max(0, cdata.int_le(page.packets[0][52:56])) self.serial = page.serial
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"_fields": {}}}}}}, "keywords": []}}}}, "keywords": []}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "must_next", "value": {"_type": "Call", "_fields": {"args": [{"_type": "Lambda", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "p", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "CONTENT_ALERT", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "comparators": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "content_type", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "record", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "dtls", "value": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}]}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "filter", "value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "COMMISSIONER", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "filter_wpan_dst64", "value": {"_type": "Name", "_fields": {"id": "pkts", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, "keywords": []}}}}, "keywords": []}}}}], "name": "verify", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "Cert_8_1_01_Commissioning", "bases": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "TestCase", "value": {"_type": "Name", "_fields": {"id": "thread_cert", "ctx": {"_type": "Load", "_fields": {}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class Cert_8_1_01_Commissioning(thread_cert.TestCase): SUPPORT_NCP = False TOPOLOGY = { COMMISSIONER: { 'name': 'COMMISSIONER', 'networkkey': '00112233445566778899aabbccddeeff', 'mode': 'rdn', }, JOINER: { 'name': 'JOINER', 'networkkey': 'deadbeefdeadbeefdeadbeefdeadbeef', 'mode': 'rdn', }, } def test(self): self.nodes[COMMISSIONER].interface_up() self.nodes[COMMISSIONER].thread_start() self.simulator.go(config.LEADER_STARTUP_DELAY) self.assertEqual(self.nodes[COMMISSIONER].get_state(), 'leader') self.nodes[COMMISSIONER].commissioner_start() self.simulator.go(3) self.nodes[COMMISSIONER].commissioner_add_joiner(self.nodes[JOINER].get_eui64(), 'PSKD01') self.nodes[JOINER].interface_up() self.nodes[JOINER].joiner_start('PSKD01') self.simulator.go(10) self.simulator.read_cert_messages_in_commissioning_log([COMMISSIONER, JOINER]) self.assertEqual( self.nodes[JOINER].get_networkkey(), self.nodes[COMMISSIONER].get_networkkey(), ) joiner_messages = self.simulator.get_messages_sent_by(JOINER) commissioner_messages = self.simulator.get_messages_sent_by(COMMISSIONER) # 5.8,9,10,11 # - Joiner command.check_joiner_commissioning_messages(joiner_messages.commissioning_messages) # - Commissioner command.check_commissioner_commissioning_messages(commissioner_messages.commissioning_messages) # As commissioner is also joiner router command.check_joiner_router_commissioning_messages(commissioner_messages.commissioning_messages) self.nodes[JOINER].thread_start() self.simulator.go(5) self.assertEqual(self.nodes[JOINER].get_state(), 'router') def verify(self, pv): pkts = pv.pkts pv.summary.show() COMMISSIONER = pv.vars['COMMISSIONER'] COMMISSIONER_VERSION = pv.vars['COMMISSIONER_VERSION'] JOINER_VERSION = pv.vars['JOINER_VERSION'] # Step 3: Joiner sends MLE Discovery Request # MLE Discovery Request message MUST have these values: # - MLE Security Suite: 255 (No MLE Security) # - Thread Discovery TLV # Sub-TLVs: # - Discovery Request TLV # - Protocol Version: 2 or 3 # (depends on the Thread stack version in testing) pkts.filter_mle_cmd(MLE_DISCOVERY_REQUEST).\ filter_LLARMA().\ filter(lambda p: [THREAD_DISCOVERY_TLV] == p.mle.tlv.type and\ [NM_DISCOVERY_REQUEST_TLV] == p.thread_meshcop.tlv.type and\ p.thread_meshcop.tlv.discovery_req_ver == JOINER_VERSION ).\ must_next() # Step 4: Commissioner sends MLE Discovery Response # MLE Discovery Response message MUST have these values: # - MLE Security Suite: 255 (No MLE Security) # - Source Address in IEEE 802.15.4 header MUST be set to # the MAC Extended Address (64-bit) # - Destination Address in IEEE 802.15.4 header MUST be # set to Discovery Request Source Address # - Thread Discovery TLV # Sub-TLVs: # - Discovery Request TLV # - Protocol Version: 2 or 3 # (depends on the Thread stack version in testing) # - Extended PAN ID TLV # - Joiner UDP Port TLV # - Network Name TLV # - Steering Data TLV # - Commissioner UDP Port TLV (optional) _rs_pkt = pkts.filter_wpan_src64(COMMISSIONER).\ filter_mle_cmd(MLE_DISCOVERY_RESPONSE).\ filter(lambda p: { NM_EXTENDED_PAN_ID_TLV, NM_NETWORK_NAME_TLV, NM_STEERING_DATA_TLV, NM_JOINER_UDP_PORT_TLV, NM_DISCOVERY_RESPONSE_TLV } <= set(p.thread_meshcop.tlv.type) and\ p.thread_meshcop.tlv.discovery_rsp_ver == COMMISSIONER_VERSION ).\ must_next() # Step 5: Verify the following details occur in the exchange between # Joiner and the Commissioner # 1. UDP port (Specified by the Commissioner: in Discovery Response) # is used as destination port for UDP datagrams from Joiner to # the Commissioner. # 2. Joiner sends an initial DTLS-ClientHello handshake record to the # Commissioner pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_CLIENT_HELLO] and\ p.udp.srcport in _rs_pkt.thread_meshcop.tlv.udp_port and\ p.udp.dstport in _rs_pkt.thread_meshcop.tlv.udp_port ).\ must_next() # 3. The Commissioner receives the initial DTLS-ClientHello handshake # record and sends a DTLS-HelloVerifyRequest handshake record Joiner _pkt = pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_HELLO_VERIFY_REQUEST]).\ must_next() _pkt.must_verify(lambda p: p.dtls.handshake.cookie is not None) # 4. Joiner receives the DTLS-HelloVerifyRequest handshake record and sends # a subsequent DTLS-ClientHello handshake record in one UDP datagram to the # Commissioner # Verify that both DTLS-HelloVerifyRequest and subsequent DTLS-ClientHello # contain the same cookie pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_CLIENT_HELLO] and\ p.dtls.handshake.cookie == _pkt.dtls.handshake.cookie ).\ must_next() # 5. Commissioner must correctly receive the subsequent DTLSClientHello # handshake record and then send, in order, DTLSServerHello, # DTLS-ServerKeyExchange and DTLSServerHelloDone handshake records to Joiner pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_SERVER_HELLO, HANDSHAKE_SERVER_KEY_EXCHANGE, HANDSHAKE_SERVER_HELLO_DONE] ).\ must_next() # 6. Joiner receives the DTLS-ServerHello, DTLSServerKeyExchange and # DTLS-ServerHelloDone handshake records and sends, in order, # a DTLS-ClientKeyExchange handshake record, # a DTLS-ChangeCipherSpec record and # an encrypted DTLS-Finished handshake record to the Commissioner. pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_CLIENT_KEY_EXCHANGE] and\ { CONTENT_CHANGE_CIPHER_SPEC, CONTENT_HANDSHAKE } == set(p.dtls.record.content_type) ).\ must_next() # 7. Commissioner receives the DTLS-ClientKeyExchange handshake record, the # DTLS-ChangeCipherSpec record and the encrypted DTLS-Finished handshake record, # and sends a DTLS-ChangeCipherSpec record and an encrypted DTLSFinished handshake # record in that order to Joiner pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: { CONTENT_CHANGE_CIPHER_SPEC, CONTENT_HANDSHAKE } == set(p.dtls.record.content_type) ).\ must_next() # 8. Joiner receives the DTLS-ChangeCipherSpec record and the encrypted DTLS-Finished # handshake record and sends a JOIN_FIN.req message in an encrypted DTLS-ApplicationData # record in a single UDP datagram to Commissioner. pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: [CONTENT_APPLICATION_DATA] == p.dtls.record.content_type ).\ must_next() # 9. Commissioner receives the encrypted DTLS-ApplicationData record and sends a # JOIN_FIN.rsp message in an encrypted DTLS-ApplicationData record in a single # UDP datagram to Joiner pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: [CONTENT_APPLICATION_DATA] == p.dtls.record.content_type ).\ must_next() # 10. Commissioner sends an encrypted JOIN_ENT.ntf message to Joiner # 11. Joiner receives the encrypted JOIN_ENT.ntf message and sends an encrypted # JOIN_ENT.ntf dummy response to Commissioner # Check Step 8 ~ 11 in test() # 12. Joiner sends an encrypted DTLS-Alert record with a code of 0 (close_notify) # to Commissioner pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: [CONTENT_ALERT] == p.dtls.record.content_type ).\ must_next()
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{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "record", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "dtls", "value": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}]}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "filter", "value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "COMMISSIONER", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "filter_wpan_dst64", "value": {"_type": "Name", "_fields": {"id": "pkts", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, "keywords": []}}}}, "keywords": []}}}}], "name": "verify", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def verify(self, pv): pkts = pv.pkts pv.summary.show() COMMISSIONER = pv.vars['COMMISSIONER'] COMMISSIONER_VERSION = pv.vars['COMMISSIONER_VERSION'] JOINER_VERSION = pv.vars['JOINER_VERSION'] # Step 3: Joiner sends MLE Discovery Request # MLE Discovery Request message MUST have these values: # - MLE Security Suite: 255 (No MLE Security) # - Thread Discovery TLV # Sub-TLVs: # - Discovery Request TLV # - Protocol Version: 2 or 3 # (depends on the Thread stack version in testing) pkts.filter_mle_cmd(MLE_DISCOVERY_REQUEST).\ filter_LLARMA().\ filter(lambda p: [THREAD_DISCOVERY_TLV] == p.mle.tlv.type and\ [NM_DISCOVERY_REQUEST_TLV] == p.thread_meshcop.tlv.type and\ p.thread_meshcop.tlv.discovery_req_ver == JOINER_VERSION ).\ must_next() # Step 4: Commissioner sends MLE Discovery Response # MLE Discovery Response message MUST have these values: # - MLE Security Suite: 255 (No MLE Security) # - Source Address in IEEE 802.15.4 header MUST be set to # the MAC Extended Address (64-bit) # - Destination Address in IEEE 802.15.4 header MUST be # set to Discovery Request Source Address # - Thread Discovery TLV # Sub-TLVs: # - Discovery Request TLV # - Protocol Version: 2 or 3 # (depends on the Thread stack version in testing) # - Extended PAN ID TLV # - Joiner UDP Port TLV # - Network Name TLV # - Steering Data TLV # - Commissioner UDP Port TLV (optional) _rs_pkt = pkts.filter_wpan_src64(COMMISSIONER).\ filter_mle_cmd(MLE_DISCOVERY_RESPONSE).\ filter(lambda p: { NM_EXTENDED_PAN_ID_TLV, NM_NETWORK_NAME_TLV, NM_STEERING_DATA_TLV, NM_JOINER_UDP_PORT_TLV, NM_DISCOVERY_RESPONSE_TLV } <= set(p.thread_meshcop.tlv.type) and\ p.thread_meshcop.tlv.discovery_rsp_ver == COMMISSIONER_VERSION ).\ must_next() # Step 5: Verify the following details occur in the exchange between # Joiner and the Commissioner # 1. UDP port (Specified by the Commissioner: in Discovery Response) # is used as destination port for UDP datagrams from Joiner to # the Commissioner. # 2. Joiner sends an initial DTLS-ClientHello handshake record to the # Commissioner pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_CLIENT_HELLO] and\ p.udp.srcport in _rs_pkt.thread_meshcop.tlv.udp_port and\ p.udp.dstport in _rs_pkt.thread_meshcop.tlv.udp_port ).\ must_next() # 3. The Commissioner receives the initial DTLS-ClientHello handshake # record and sends a DTLS-HelloVerifyRequest handshake record Joiner _pkt = pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_HELLO_VERIFY_REQUEST]).\ must_next() _pkt.must_verify(lambda p: p.dtls.handshake.cookie is not None) # 4. Joiner receives the DTLS-HelloVerifyRequest handshake record and sends # a subsequent DTLS-ClientHello handshake record in one UDP datagram to the # Commissioner # Verify that both DTLS-HelloVerifyRequest and subsequent DTLS-ClientHello # contain the same cookie pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_CLIENT_HELLO] and\ p.dtls.handshake.cookie == _pkt.dtls.handshake.cookie ).\ must_next() # 5. Commissioner must correctly receive the subsequent DTLSClientHello # handshake record and then send, in order, DTLSServerHello, # DTLS-ServerKeyExchange and DTLSServerHelloDone handshake records to Joiner pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_SERVER_HELLO, HANDSHAKE_SERVER_KEY_EXCHANGE, HANDSHAKE_SERVER_HELLO_DONE] ).\ must_next() # 6. Joiner receives the DTLS-ServerHello, DTLSServerKeyExchange and # DTLS-ServerHelloDone handshake records and sends, in order, # a DTLS-ClientKeyExchange handshake record, # a DTLS-ChangeCipherSpec record and # an encrypted DTLS-Finished handshake record to the Commissioner. pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: p.dtls.handshake.type == [HANDSHAKE_CLIENT_KEY_EXCHANGE] and\ { CONTENT_CHANGE_CIPHER_SPEC, CONTENT_HANDSHAKE } == set(p.dtls.record.content_type) ).\ must_next() # 7. Commissioner receives the DTLS-ClientKeyExchange handshake record, the # DTLS-ChangeCipherSpec record and the encrypted DTLS-Finished handshake record, # and sends a DTLS-ChangeCipherSpec record and an encrypted DTLSFinished handshake # record in that order to Joiner pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: { CONTENT_CHANGE_CIPHER_SPEC, CONTENT_HANDSHAKE } == set(p.dtls.record.content_type) ).\ must_next() # 8. Joiner receives the DTLS-ChangeCipherSpec record and the encrypted DTLS-Finished # handshake record and sends a JOIN_FIN.req message in an encrypted DTLS-ApplicationData # record in a single UDP datagram to Commissioner. pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: [CONTENT_APPLICATION_DATA] == p.dtls.record.content_type ).\ must_next() # 9. Commissioner receives the encrypted DTLS-ApplicationData record and sends a # JOIN_FIN.rsp message in an encrypted DTLS-ApplicationData record in a single # UDP datagram to Joiner pkts.filter_wpan_src64(COMMISSIONER).\ filter(lambda p: [CONTENT_APPLICATION_DATA] == p.dtls.record.content_type ).\ must_next() # 10. Commissioner sends an encrypted JOIN_ENT.ntf message to Joiner # 11. Joiner receives the encrypted JOIN_ENT.ntf message and sends an encrypted # JOIN_ENT.ntf dummy response to Commissioner # Check Step 8 ~ 11 in test() # 12. Joiner sends an encrypted DTLS-Alert record with a code of 0 (close_notify) # to Commissioner pkts.filter_wpan_dst64(COMMISSIONER).\ filter(lambda p: [CONTENT_ALERT] == p.dtls.record.content_type ).\ must_next()
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{"ctx": {"_type": "Load", "_fields": {}}, "attr": "commissioning_messages", "value": {"_type": "Name", "_fields": {"id": "joiner_messages", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "check_joiner_commissioning_messages", "value": {"_type": "Name", "_fields": {"id": "command", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "commissioning_messages", "value": {"_type": "Name", "_fields": {"id": "commissioner_messages", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "check_commissioner_commissioning_messages", "value": {"_type": "Name", "_fields": {"id": "command", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "commissioning_messages", "value": {"_type": "Name", "_fields": {"id": "commissioner_messages", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "check_joiner_router_commissioning_messages", "value": {"_type": "Name", "_fields": {"id": "command", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "thread_start", "value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Name", "_fields": {"id": "JOINER", "ctx": {"_type": "Load", "_fields": {}}}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "nodes", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 5}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "go", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "simulator", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "get_state", "value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Name", "_fields": {"id": "JOINER", "ctx": {"_type": "Load", "_fields": {}}}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "nodes", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}, "keywords": []}}, {"_type": "Constant", "_fields": {"kind": null, "value": "router"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def test(self): self.nodes[COMMISSIONER].interface_up() self.nodes[COMMISSIONER].thread_start() self.simulator.go(config.LEADER_STARTUP_DELAY) self.assertEqual(self.nodes[COMMISSIONER].get_state(), 'leader') self.nodes[COMMISSIONER].commissioner_start() self.simulator.go(3) self.nodes[COMMISSIONER].commissioner_add_joiner(self.nodes[JOINER].get_eui64(), 'PSKD01') self.nodes[JOINER].interface_up() self.nodes[JOINER].joiner_start('PSKD01') self.simulator.go(10) self.simulator.read_cert_messages_in_commissioning_log([COMMISSIONER, JOINER]) self.assertEqual( self.nodes[JOINER].get_networkkey(), self.nodes[COMMISSIONER].get_networkkey(), ) joiner_messages = self.simulator.get_messages_sent_by(JOINER) commissioner_messages = self.simulator.get_messages_sent_by(COMMISSIONER) # 5.8,9,10,11 # - Joiner command.check_joiner_commissioning_messages(joiner_messages.commissioning_messages) # - Commissioner command.check_commissioner_commissioning_messages(commissioner_messages.commissioning_messages) # As commissioner is also joiner router command.check_joiner_router_commissioning_messages(commissioner_messages.commissioning_messages) self.nodes[JOINER].thread_start() self.simulator.go(5) self.assertEqual(self.nodes[JOINER].get_state(), 'router')
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%s' % item continue elif not isinstance(value, (str, text_type, int, float, bool)): continue yield '%s: %r' % (key, value)
10,849	[ 0.02752399444580078, 0.021248292177915573, 0.040210988372564316, 0.04346505552530289, -0.0032782801426947117, 0.026923542842268944, 0.05698493495583534, 0.05442816764116287, 0.01741313934326172, 0.042264148592948914, -0.004481607582420111, 0.024521728977560997, 0.032327618449926376, 0.0043...	9	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "cmd", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "cwd", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [{"_type": "Constant", "_fields": {"kind": null, "value": null}}], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "cmd", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Popen", "value": {"_type": "Name", "_fields": {"id": "subprocess", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "shell", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}, {"_type": "keyword", "_fields": {"arg": "cwd", "value": {"_type": "Name", "_fields": {"id": "cwd", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "wait", "value": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "If", "_fields": {"body": [{"_type": "Raise", "_fields": {"exc": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "CalledProcessError", "value": {"_type": "Name", "_fields": {"id": "subprocess", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "returncode", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "returncode", "value": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "keyword", "_fields": {"arg": "cmd", "value": {"_type": "Name", "_fields": {"id": "cmd", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "cause": null}}], "test": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "returncode", "value": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": []}}, {"_type": "Return", "_fields": {"value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "returncode", "value": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}}}}}], "name": "run_shell", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def run_shell(cmd, cwd=None): p = subprocess.Popen(cmd, shell=True, cwd=cwd) p.wait() if p.returncode: raise subprocess.CalledProcessError(returncode=p.returncode, cmd=cmd) return p.returncode
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{"_type": "Constant", "_fields": {"kind": null, "value": "toolchains/arm-linux-androideabi-4.8/prebuilt/%s/arm-linux-androideabi/bin/strip"}}, "right": {"_type": "Name", "_fields": {"id": "sys_folder_name", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "path", "value": {"_type": "Name", "_fields": {"id": "os", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "strip_cmd_path", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "If", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "%s -S %s/armeabi/*.a"}}, "right": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "strip_cmd_path", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "prebuilt_dir", "ctx": {"_type": "Load", "_fields": {}}}}]}}}}, "targets": [{"_type": "Name", "_fields": {"id": "strip_cmd", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "strip_cmd", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "run_shell", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "test": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "strip_cmd_path", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "exists", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "path", "value": {"_type": "Name", "_fields": {"id": "os", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "orelse": []}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "disable_strip", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "orelse": []}}], "name": "build_android", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def build_android(self): # build .a for android console_dir = os.path.join(self.engine_dir, CONSOLE_PATH) cmd_path = os.path.join(console_dir, "cocos") proj_path = os.path.join(self.engine_dir, TESTS_PROJ_PATH) # Add multi ABI in Application.mk mk_file = os.path.join(proj_path, MK_PATH) f = open(mk_file) file_content = f.read() f.close() self.modify_mk(mk_file) # build it build_cmd = "%s compile -s %s -p android --ndk-mode release -j 4" % (cmd_path, proj_path) run_shell(build_cmd) f = open(mk_file, "w") f.write(file_content) f.close() # copy .a to prebuilt dir obj_dir = os.path.join(proj_path, ANDROID_A_PATH) prebuilt_dir = os.path.join(self.tool_dir, "prebuilt", "android") copy_cfg = { "from": obj_dir, "to": prebuilt_dir, "include": [ ".a$" ] } excopy.copy_files_with_config(copy_cfg, obj_dir, prebuilt_dir) if not self.disable_strip: # strip the android libs ndk_root = os.environ["NDK_ROOT"] if os_is_win32(): if self.is_32bit_windows(): bit_str = "" else: bit_str = "-x86_64" sys_folder_name = "windows%s" % bit_str elif os_is_mac(): sys_folder_name = "darwin-x86_64" strip_cmd_path = os.path.join(ndk_root, "toolchains/arm-linux-androideabi-4.8/prebuilt/%s/arm-linux-androideabi/bin/strip" % sys_folder_name) if os.path.exists(strip_cmd_path): strip_cmd = "%s -S %s/armeabi/*.a" % (strip_cmd_path, prebuilt_dir) run_shell(strip_cmd)
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"decorator_list": []}}], "type_ignores": []}}	def build_ios_mac(self): for key in self.xcode_proj_info.keys(): output_dir = self.xcode_proj_info[key][Generator.KEY_OUTPUT_DIR] proj_path = os.path.join(self.engine_dir, key) ios_out_dir = os.path.join(self.tool_dir, output_dir, "ios") mac_out_dir = os.path.join(self.tool_dir, output_dir, "mac") ios_sim_libs_dir = os.path.join(ios_out_dir, "simulator") ios_dev_libs_dir = os.path.join(ios_out_dir, "device") for target in self.xcode_proj_info[key][Generator.KEY_TARGETS]: build_cmd = Generator.XCODE_CMD_FMT % (proj_path, "%s iOS" % target, "-sdk iphonesimulator", ios_sim_libs_dir) run_shell(build_cmd, self.tool_dir) build_cmd = Generator.XCODE_CMD_FMT % (proj_path, "%s iOS" % target, "-sdk iphoneos", ios_dev_libs_dir) run_shell(build_cmd, self.tool_dir) build_cmd = Generator.XCODE_CMD_FMT % (proj_path, "%s Mac" % target, "", mac_out_dir) run_shell(build_cmd, self.tool_dir) # generate fat libs for iOS for lib in os.listdir(ios_sim_libs_dir): sim_lib = os.path.join(ios_sim_libs_dir, lib) dev_lib = os.path.join(ios_dev_libs_dir, lib) output_lib = os.path.join(ios_out_dir, lib) lipo_cmd = "lipo -create -output \"%s\" \"%s\" \"%s\"" % (output_lib, sim_lib, dev_lib) run_shell(lipo_cmd) # remove the simulator & device libs in iOS shutil.rmtree(ios_sim_libs_dir) shutil.rmtree(ios_dev_libs_dir) if not self.disable_strip: # strip the libs ios_strip_cmd = "xcrun -sdk iphoneos strip -S %s/.a" % ios_out_dir run_shell(ios_strip_cmd) mac_strip_cmd = "xcrun strip -S %s/.a" % mac_out_dir run_shell(mac_strip_cmd)
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"_fields": {"kind": null, "value": "Win32 build succeeded."}}], "func": {"_type": "Name", "_fields": {"id": "print", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "build_win32", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def build_win32(self): print("Building Win32") for key in self.win32_proj_info.keys(): output_dir = self.win32_proj_info[key][Generator.KEY_OUTPUT_DIR] proj_path = os.path.join(self.engine_dir, key) require_vs_version = self.get_required_vs_version(proj_path) needUpgrade, vs_command = self.get_vs_cmd_path(require_vs_version) # get the build folder & win32 output folder build_folder_path = os.path.join(os.path.dirname(proj_path), "Release.win32") if os.path.exists(build_folder_path): shutil.rmtree(build_folder_path) os.makedirs(build_folder_path) win32_output_dir = os.path.join(self.tool_dir, output_dir) if os.path.exists(win32_output_dir): shutil.rmtree(win32_output_dir) os.makedirs(win32_output_dir) # upgrade projects if needUpgrade: commandUpgrade = ' '.join([ "\"%s\"" % vs_command, "\"%s\"" % proj_path, "/Upgrade" ]) run_shell(commandUpgrade) if self.use_incredibuild: # use incredibuild, build whole sln build_cmd = " ".join([ "BuildConsole", "%s" % proj_path, "/build", "/cfg=\"Release\|Win32\"" ]) run_shell(build_cmd) if not self.use_incredibuild: # build the projects for proj_name in self.win32_proj_info[key][Generator.KEY_TARGETS]: self.build_win32_proj(vs_command, proj_path, proj_name, "build") lib_file_path = os.path.join(build_folder_path, "%s.lib" % proj_name) if not os.path.exists(lib_file_path): # if the lib is not generated, rebuild the project self.build_win32_proj(vs_command, proj_path, proj_name, "rebuild") if not os.path.exists(lib_file_path): raise Exception("Library %s not generated as expected!" % lib_file_path) # copy the libs into prebuilt dir for file_name in os.listdir(build_folder_path): file_path = os.path.join(build_folder_path, file_name) shutil.copy(file_path, win32_output_dir) print("Win32 build succeeded.")
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"Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "k", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Name", "_fields": {"id": "k", "ctx": {"_type": "Load", "_fields": {}}}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "query", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}]}}}}, "generators": [{"_type": "comprehension", "_fields": {"ifs": [], "iter": {"_type": "Name", "_fields": {"id": "keys", "ctx": {"_type": "Load", "_fields": {}}}}, "target": {"_type": "Name", "_fields": {"id": "k", "ctx": {"_type": "Store", "_fields": {}}}}, "is_async": 0}}]}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "&"}}}}, "keywords": []}}}}, "target": {"_type": "Name", "_fields": {"id": "s", "ctx": {"_type": "Store", "_fields": {}}}}}}], "test": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "query", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": []}}, {"_type": "Return", "_fields": {"value": {"_type": "Name", "_fields": {"id": "s", "ctx": {"_type": "Load", "_fields": {}}}}}}], "name": "__to_string__", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __to_string__(self, hide_password=True): s = self.drivername + "://" if self.username is not None: s += _rfc_1738_quote(self.username) if self.password is not None: s += ':' + ('***' if hide_password else _rfc_1738_quote(self.password)) s += "@" if self.host is not None: if ':' in self.host: s += "[%s]" % self.host else: s += self.host if self.port is not None: s += ':' + str(self.port) if self.database is not None: s += '/' + self.database if self.query: keys = list(self.query) keys.sort() s += '?' + "&".join("%s=%s" % (k, self.query[k]) for k in keys) return s
10,858	[ 0.011506077833473682, 0.03748371824622154, 0.01492626965045929, -0.004282653331756592, -0.026036949828267097, -0.0245344378054142, 0.017931293696165085, -0.03149344027042389, -0.040034033358097076, -0.01875174418091774, -0.022003892809152603, -0.018000489100813866, 0.007912900298833847, -0...	8	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "build_ios_mac", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "test": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "os_is_mac", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "orelse": []}}, {"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "build_win32", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "test": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "os_is_win32", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "orelse": []}}, {"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "build_android", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "no_android", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "orelse": []}}], "name": "build_all_libs", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def build_all_libs(self): if os_is_mac(): # build for iOS & Mac self.build_ios_mac() if os_is_win32(): # build for win32 self.build_win32() if not self.no_android: self.build_android()
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null, "value": "ipv4host"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pop", "value": {"_type": "Name", "_fields": {"id": "components", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "ipv4host", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "ipv6host"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pop", "value": {"_type": "Name", "_fields": {"id": "components", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "ipv6host", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "BoolOp", "_fields": {"op": {"_type": "Or", "_fields": {}}, "values": [{"_type": "Name", "_fields": {"id": "ipv4host", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "ipv6host", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "targets": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "host"}}, "value": {"_type": "Name", "_fields": {"id": "components", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "name"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pop", "value": {"_type": "Name", "_fields": {"id": "components", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "name", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "name", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "URL", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": null, "value": {"_type": "Name", "_fields": {"id": "components", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "IsNot", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": null}}]}}, "orelse": [{"_type": "Raise", "_fields": {"exc": {"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "Could not parse rfc1738 URL from string '%s'"}}, "right": {"_type": "Name", "_fields": {"id": "name", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "ArgumentError", "value": {"_type": "Name", "_fields": {"id": "exc", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "cause": null}}]}}], "name": "_parse_rfc1738_args", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _parse_rfc1738_args(name): pattern = re.compile(r''' (?P<name>[\w\+]+):// (?: (?P<username>[^:/]) (?::(?P<password>.))? @)? (?: (?: \[(?P<ipv6host>[^/]+)\] \| (?P<ipv4host>[^/:]+) )? (?::(?P<port>[^/]))? )? (?:/(?P<database>.))? ''', re.X) m = pattern.match(name) if m is not None: components = m.groupdict() if components['database'] is not None: tokens = components['database'].split('?', 2) components['database'] = tokens[0] query = (len(tokens) > 1 and dict(util.parse_qsl(tokens[1]))) or None if util.py2k and query is not None: query = dict((k.encode('ascii'), query[k]) for k in query) else: query = None components['query'] = query if components['username'] is not None: components['username'] = _rfc_1738_unquote(components['username']) if components['password'] is not None: components['password'] = _rfc_1738_unquote(components['password']) ipv4host = components.pop('ipv4host') ipv6host = components.pop('ipv6host') components['host'] = ipv4host or ipv6host name = components.pop('name') return URL(name, **components) else: raise exc.ArgumentError( "Could not parse rfc1738 URL from string '%s'" % name)
10,860	[ 0.01013138797134161, 0.029417453333735466, -0.03026217594742775, -0.01977706141769886, -0.0025988409761339426, -0.00033145450288429856, -0.04126468300819397, -0.008336353115737438, -0.024391356855630875, 0.025932975113391876, 0.0010954992612823844, -0.006045043934136629, 0.010115549899637699...	9	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "name", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "(\\w+)://(.*)"}}, {"_type": "Name", "_fields": {"id": "name", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "match", "value": {"_type": "Name", "_fields": {"id": "re", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "If", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 1}}, {"_type": "Constant", "_fields": {"kind": null, "value": 2}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "group", "value": {"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "name", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "args", "ctx": {"_type": "Store", "_fields": {}}}}]}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "args", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "parse_qsl", "value": {"_type": "Name", "_fields": {"id": "util", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}], "func": {"_type": "Name", "_fields": {"id": "dict", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "opts", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "name", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Starred", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "value": {"_type": "Name", "_fields": {"id": "opts", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Name", "_fields": {"id": "URL", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "IsNot", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": null}}]}}, "orelse": [{"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": null}}}}]}}], "name": "_parse_keyvalue_args", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _parse_keyvalue_args(name): m = re.match(r'(\w+)://(.)', name) if m is not None: (name, args) = m.group(1, 2) opts = dict(util.parse_qsl(args)) return URL(name, opts) else: return None
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"type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def __init__(self, field, op1, value1, op2=None, value2=None): from_value = to_value = include_lower = include_upper = None for op, value in ((op1, value1), (op2, value2)): if op == "gt": from_value = value include_lower = False elif op == "gte": from_value = value include_lower = True if op == "lt": to_value = value include_upper = False elif op == "lte": to_value = value include_upper = True super(ESRangeOp, self).__init__(field, from_value, to_value, include_lower, include_upper)
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[]}}}}], "name": "__init__", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "ESRangeOp", "bases": [{"_type": "Name", "_fields": {"id": "ESRange", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class ESRangeOp(ESRange): def __init__(self, field, op1, value1, op2=None, value2=None): from_value = to_value = include_lower = include_upper = None for op, value in ((op1, value1), (op2, value2)): if op == "gt": from_value = value include_lower = False elif op == "gte": from_value = value include_lower = True if op == "lt": to_value = value include_upper = False elif op == "lte": to_value = value include_upper = True super(ESRangeOp, self).__init__(field, from_value, to_value, include_lower, include_upper)
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x[x < thresh] = 0 non_zero = np.where(x) x_indices = np.vstack(non_zero).astype(index_dtype).T x_values = x[non_zero] x_shape = x.shape return sparse_tensor.SparseTensor( indices=x_indices, values=x_values, dense_shape=x_shape), x_values
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"value": 7}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "constant", "value": {"_type": "Name", "_fields": {"id": "constant_op", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "z", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "With", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Compare", "_fields": {"ops": [{"_type": "Lt", "_fields": {}}, {"_type": "Lt", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "z", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "_", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "TypeError", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertRaises", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "optional_vars": null}}], "type_comment": null}}], "name": "testUsingAsPythonValueFails", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "LogicalOpTest", "bases": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "TestCase", "value": {"_type": "Name", "_fields": {"id": "test", "ctx": {"_type": "Load", "_fields": {}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class LogicalOpTest(test.TestCase): def _compareBinary(self, x, y, np_func, tf_func, use_gpu=False): np_ans = np_func(x, y) with self.test_session(use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = tf_func(inx, iny) tf_val = out.eval() self.assertEqual(out.dtype, dtypes_lib.bool) self.assertAllEqual(np_ans, tf_val) self.assertShapeEqual(np_ans, out) def _not(self, x, use_gpu=False): np_ans = np.logical_not(x) with self.test_session(use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()): out = math_ops.logical_not(ops.convert_to_tensor(x)) tf_val = out.eval() self.assertEqual(out.dtype, dtypes_lib.bool) self.assertAllEqual(np_ans, tf_val) self.assertShapeEqual(np_ans, out) def testScalar(self): data = [np.array([True]), np.array([False])] for use_gpu in [True, False]: for x in data: self._not(x, use_gpu) for x in data: for y in data: self._compareBinary(x, y, np.logical_and, math_ops.logical_and, use_gpu) self._compareBinary(x, y, np.logical_or, math_ops.logical_or, use_gpu) self._compareBinary(x, y, np.logical_xor, math_ops.logical_xor, use_gpu) def testTensor(self): x = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) y = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) for use_gpu in [True, False]: self._not(x, use_gpu) self._compareBinary(x, y, np.logical_and, math_ops.logical_and, use_gpu) self._compareBinary(x, y, np.logical_or, math_ops.logical_or, use_gpu) self._compareBinary(x, y, np.logical_xor, math_ops.logical_xor, use_gpu) def testBCast(self): shapes = [ ([1, 3, 2], [1]), ([1, 3, 2], [2]), ([1, 3, 2], [3, 2]), ([1, 3, 2], [3, 1]), ([1, 3, 2], [1, 3, 2]), ([1, 3, 2], [2, 3, 1]), ([1, 3, 2], [2, 1, 1]), ([1, 3, 2], [1, 3, 1]), ([2, 1, 5], [2, 3, 1]), ([2, 0, 5], [2, 0, 1]), ([2, 3, 0], [2, 3, 1]), ] for (xs, ys) in shapes: x = np.random.randint(0, 2, np.prod(xs)).astype(np.bool).reshape(xs) y = np.random.randint(0, 2, np.prod(ys)).astype(np.bool).reshape(ys) for use_gpu in [True, False]: self._compareBinary(x, y, np.logical_and, math_ops.logical_and, use_gpu) self._compareBinary(x, y, np.logical_or, math_ops.logical_or, use_gpu) self._compareBinary(x, y, np.logical_xor, math_ops.logical_xor, use_gpu) def testShapeMismatch(self): x = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) y = np.random.randint(0, 2, 6).astype(np.bool).reshape(3, 2, 1) for f in [math_ops.logical_and, math_ops.logical_or, math_ops.logical_xor]: with self.assertRaisesWithPredicateMatch( ValueError, lambda e: "Dimensions must" in str(e)): f(x, y) def testUsingAsPythonValueFails(self): # Ensure that we raise an error when the user attempts to treat a # `Tensor` as a Python `bool`. b = constant_op.constant(False) with self.assertRaises(TypeError): if b: pass x = constant_op.constant(3) y = constant_op.constant(4) with self.assertRaises(TypeError): if x > y: pass z = constant_op.constant(7) # The chained comparison should fail because Python computes `x < # y` and short-circuits the comparison with `z` if it is `False`. with self.assertRaises(TypeError): _ = x < y < z
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{"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "out", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertShapeEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "_not", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _not(self, x, use_gpu=False): np_ans = np.logical_not(x) with self.test_session(use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()): out = math_ops.logical_not(ops.convert_to_tensor(x)) tf_val = out.eval() self.assertEqual(out.dtype, dtypes_lib.bool) self.assertAllEqual(np_ans, tf_val) self.assertShapeEqual(np_ans, out)
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"Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "use_gpu", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testTensor", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testTensor(self): x = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) y = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) for use_gpu in [True, False]: self._not(x, use_gpu) self._compareBinary(x, y, np.logical_and, math_ops.logical_and, use_gpu) self._compareBinary(x, y, np.logical_or, math_ops.logical_or, use_gpu) self._compareBinary(x, y, np.logical_xor, math_ops.logical_xor, use_gpu)
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{"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "z", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "With", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Compare", "_fields": {"ops": [{"_type": "Lt", "_fields": {}}, {"_type": "Lt", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "z", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "_", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "TypeError", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertRaises", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "optional_vars": null}}], "type_comment": null}}], "name": "testUsingAsPythonValueFails", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testUsingAsPythonValueFails(self): # Ensure that we raise an error when the user attempts to treat a # `Tensor` as a Python `bool`. b = constant_op.constant(False) with self.assertRaises(TypeError): if b: pass x = constant_op.constant(3) y = constant_op.constant(4) with self.assertRaises(TypeError): if x > y: pass z = constant_op.constant(7) # The chained comparison should fail because Python computes `x < # y` and short-circuits the comparison with `z` if it is `False`. with self.assertRaises(TypeError): _ = x < y < z
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{"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "xs", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "ys", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "type_comment": null}}], "name": "testBCast", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testBCast(self): shapes = [ ([1, 3, 2], [1]), ([1, 3, 2], [2]), ([1, 3, 2], [3, 2]), ([1, 3, 2], [3, 1]), ([1, 3, 2], [1, 3, 2]), ([1, 3, 2], [2, 3, 1]), ([1, 3, 2], [2, 1, 1]), ([1, 3, 2], [1, 3, 1]), ([2, 1, 5], [2, 3, 1]), ([2, 0, 5], [2, 0, 1]), ([2, 3, 0], [2, 3, 1]), ] for (xs, ys) in shapes: x = np.random.randint(0, 2, np.prod(xs)).astype(np.bool).reshape(xs) y = np.random.randint(0, 2, np.prod(ys)).astype(np.bool).reshape(ys) for use_gpu in [True, False]: self._compareBinary(x, y, np.logical_and, math_ops.logical_and, use_gpu) self._compareBinary(x, y, np.logical_or, math_ops.logical_or, use_gpu) self._compareBinary(x, y, np.logical_xor, math_ops.logical_xor, use_gpu)
10,873	[ -0.008368788287043571, -0.02861911989748478, 0.008188934996724129, -0.009402942843735218, 0.059576328843832016, -0.0033806755673140287, -0.0025994388852268457, -0.0005381540977396071, 0.034441862255334854, 0.03929789364337921, 0.004431691952049732, -0.01823260448873043, 0.009060097858309746,...	11	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "c", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "x", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "y", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "use_gpu", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": 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"attr": "test_session", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "use_gpu", "value": {"_type": "Name", "_fields": {"id": "use_gpu", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "force_gpu", "value": {"_type": "BoolOp", "_fields": {"op": {"_type": "And", "_fields": {}}, "values": [{"_type": "Name", "_fields": {"id": "use_gpu", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "is_gpu_available", "value": {"_type": "Name", "_fields": {"id": "test_util", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}]}}}}]}}, "optional_vars": null}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "np_ans", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_ans", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertAllEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "np_ans", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "out", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertShapeEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "_compare", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _compare(self, c, x, y, use_gpu): np_ans = np.where(c, x, y) with self.test_session(use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()): out = array_ops.where(c, x, y) tf_ans = out.eval() self.assertAllEqual(np_ans, tf_ans) self.assertShapeEqual(np_ans, out)
10,874	[ 0.005190915893763304, 0.022927291691303253, 0.012527530081570148, -0.018564173951745033, 0.057377997785806656, 0.02464863285422325, 0.0350244864821434, -0.020321374759078026, 0.047575924545526505, 0.01597020961344242, 0.008971288800239563, -0.02780442126095295, -0.006126296706497669, 0.047...	10	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "c", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "x", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "y", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "numeric_gradient_type", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [{"_type": "Constant", "_fields": {"kind": null, "value": null}}], 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{"id": "inyf", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "where", "value": {"_type": "Name", "_fields": {"id": "array_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "outf", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "inxf", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "s", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "outf", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "s", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "compute_gradient", "value": {"_type": "Name", "_fields": {"id": 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{"kind": null, "value": 0.00001}}}}, {"_type": "keyword", "_fields": {"arg": "atol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.00001}}}}]}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "dtype", "value": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}}}, "comparators": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": []}}]}}]}}], "name": "_compareGradientX", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _compareGradientX(self, c, x, y, numeric_gradient_type=None): with self.cached_session(): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = array_ops.where(c, inx, iny) s = list(np.shape(c)) jacob_t, jacob_n = gradient_checker.compute_gradient( inx, s, out, s, x_init_value=x) if numeric_gradient_type is not None: xf = x.astype(numeric_gradient_type) yf = y.astype(numeric_gradient_type) inxf = ops.convert_to_tensor(xf) inyf = ops.convert_to_tensor(yf) outf = array_ops.where(c, inxf, inyf) _, jacob_n = gradient_checker.compute_gradient( inxf, s, outf, s, x_init_value=xf) jacob_n = jacob_n.astype(x.dtype) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
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"_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "rtol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.00001}}}}, {"_type": "keyword", "_fields": {"arg": "atol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.00001}}}}]}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "dtype", "value": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}}}, "comparators": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": []}}]}}]}}], "name": "_compareGradientY", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _compareGradientY(self, c, x, y, numeric_gradient_type=None): with self.cached_session(): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = array_ops.where(c, inx, iny) s = list(np.shape(c)) jacob_t, jacob_n = gradient_checker.compute_gradient( iny, s, out, s, x_init_value=y, delta=1.0) if numeric_gradient_type is not None: xf = x.astype(numeric_gradient_type) yf = y.astype(numeric_gradient_type) inxf = ops.convert_to_tensor(xf) inyf = ops.convert_to_tensor(yf) outf = array_ops.where(c, inxf, inyf) _, jacob_n = gradient_checker.compute_gradient( inyf, s, outf, s, x_init_value=yf) jacob_n = jacob_n.astype(x.dtype) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
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"elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex128", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testScalar", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testScalar(self): c = True x = np.random.rand(1, 3, 2) * 100 y = np.random.rand(1, 3, 2) * 100 for t in [ np.float16, np.float32, np.float64, np.int32, np.int64, np.complex64, np.complex128 ]: xt = x.astype(t) yt = y.astype(t) self._compare(c, xt, yt, use_gpu=False) if t in [np.float16, np.float32, np.float64]: self._compare(c, xt, yt, use_gpu=True)
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"ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "yt", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientX", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "c", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "xt", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "yt", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientY", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}]}}], "iter": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testGradients", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testGradients(self): c = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) x = np.random.rand(1, 3, 2) * 100 y = np.random.rand(1, 3, 2) * 100 for t in [np.float16, np.float32, np.float64]: xt = x.astype(t) yt = y.astype(t) if t == np.float16: # Compare fp16 theoretical gradients to fp32 numerical gradients, # since fp16 numerical gradients are too imprecise unless great # care is taken with choosing the inputs and the delta. This is # a weaker check (in particular, it does not test the op itself, # only its gradient), but it's much better than nothing. self._compareGradientX(c, xt, yt, np.float) self._compareGradientY(c, xt, yt, np.float) else: self._compareGradientX(c, xt, yt) self._compareGradientY(c, xt, yt)
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"Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex128", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testBasic", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testBasic(self): c = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) x = np.random.rand(1, 3, 2) * 100 y = np.random.rand(1, 3, 2) * 100 for t in [ np.float16, np.float32, np.float64, np.int32, np.int64, np.complex64, np.complex128 ]: xt = x.astype(t) yt = y.astype(t) self._compare(c, xt, yt, use_gpu=False) if t in [np.float16, np.float32, np.float64]: self._compare(c, xt, yt, use_gpu=True)
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"_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "astype", "value": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "xt", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "astype", "value": {"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "yt", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "eval", "value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "c", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "xt", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "yt", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "where", "value": {"_type": "Name", "_fields": {"id": "array_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "z", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "z_expected", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "z", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertAllEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "cached_session", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "optional_vars": null}}], "type_comment": null}}], "name": "testEmptyTensor", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testEmptyTensor(self): c = np.random.randint(0, 3, 0).astype(np.bool).reshape(1, 3, 0) x = np.random.rand(1, 3, 0) * 100 y = np.random.rand(1, 3, 0) * 100 z_expected = np.zeros((1, 3, 0), dtype=np.float32) with self.cached_session(): xt = x.astype(np.float32) yt = y.astype(np.float32) z = array_ops.where(c, xt, yt).eval() self.assertAllEqual(z_expected, z)
10,880	[ -0.01342038530856371, -0.011753406375646591, 0.05972132086753845, 0.030827023088932037, 0.017201285809278488, 0.006072996184229851, -0.00115888228174299, 0.01803477481007576, -0.01881994679570198, 0.023784643039107323, 0.010062268935143948, -0.01606580801308155, 0.030174728482961655, 0.033...	12	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 1}}, {"_type": "Constant", "_fields": {"kind": null, "value": 3}}, {"_type": "Constant", "_fields": {"kind": null, "value": 2}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": 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"ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "BinOp", "_fields": {"op": {"_type": "Mult", "_fields": {}}, "left": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 1}}, {"_type": "Constant", "_fields": {"kind": null, "value": 3}}, {"_type": "Constant", "_fields": {"kind": null, "value": 2}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "rand", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "random", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "right": {"_type": "Constant", "_fields": {"kind": null, "value": 100}}}}, "targets": [{"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "BinOp", 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{"id": "c", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "xt", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "yt", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "where", "value": {"_type": "Name", "_fields": {"id": "array_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "ValueError", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertRaises", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "optional_vars": null}}], "type_comment": null}}], "iter": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex128", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testShapeMismatch", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testShapeMismatch(self): c = np.random.randint(0, 2, 6).astype(np.bool).reshape(1, 3, 2) x = np.random.rand(1, 3, 2) * 100 y = np.random.rand(2, 5, 3) * 100 for t in [ np.float16, np.float32, np.float64, np.int32, np.int64, np.complex64, np.complex128 ]: xt = x.astype(t) yt = y.astype(t) with self.assertRaises(ValueError): array_ops.where(c, xt, yt)
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iny) s = list(np.shape(x)) jacob_t, jacob_n = gradient_checker.compute_gradient( inx, s, out, s, x_init_value=x) if numeric_gradient_type is not None: xf = x.astype(numeric_gradient_type) yf = y.astype(numeric_gradient_type) inxf = ops.convert_to_tensor(xf) inyf = ops.convert_to_tensor(yf) outf = array_ops.where(c, inxf, inyf) _, jacob_n = gradient_checker.compute_gradient( inxf, s, outf, s, x_init_value=xf) jacob_n = jacob_n.astype(x.dtype) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
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"_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "is_gpu_available", "value": {"_type": "Name", "_fields": {"id": "test_util", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}]}}}}]}}, "optional_vars": null}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "np_ans", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_ans", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertAllEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "np_ans", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "out", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertShapeEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "_compare", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _compare(self, c, x, y, use_gpu): np_ans = np.dstack( [x_i if c_i else y_i for c_i, x_i, y_i in zip(c, x, y)]).transpose( [2, 0, 1]) with self.test_session(use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()): out = array_ops.where(c, x, y) tf_ans = out.eval() self.assertAllEqual(np_ans, tf_ans) self.assertShapeEqual(np_ans, out)
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iny) s = list(np.shape(x)) jacob_t, jacob_n = gradient_checker.compute_gradient( iny, s, out, s, x_init_value=y) if numeric_gradient_type is not None: xf = x.astype(numeric_gradient_type) yf = y.astype(numeric_gradient_type) inxf = ops.convert_to_tensor(xf) inyf = ops.convert_to_tensor(yf) outf = array_ops.where(c, inxf, inyf) _, jacob_n = gradient_checker.compute_gradient( inyf, s, outf, s, x_init_value=yf) jacob_n = jacob_n.astype(x.dtype) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
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{"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex128", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testBasic", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testBasic(self): c = np.random.randint(0, 2, 16).astype(np.bool) x = np.random.rand(16, 2, 8) * 100 y = np.random.rand(16, 2, 8) * 100 for t in [ np.float16, np.float32, np.float64, np.int32, np.int64, np.complex64, np.complex128 ]: xt = x.astype(t) yt = y.astype(t) self._compare(c, xt, yt, use_gpu=False) if t in [np.float16, np.float32, np.float64]: self._compare(c, xt, yt, use_gpu=True)
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{"_type": "Constant", "_fields": {"kind": null, "value": 2}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "rand", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "random", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "right": {"_type": "Constant", "_fields": {"kind": null, "value": 100}}}}, "targets": [{"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "BinOp", "_fields": {"op": {"_type": "Mult", "_fields": {}}, "left": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 16}}, {"_type": "Constant", "_fields": {"kind": null, "value": 3}}, {"_type": "Constant", "_fields": {"kind": null, "value": 2}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", 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"_fields": {"id": "array_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "ValueError", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertRaises", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "optional_vars": null}}], "type_comment": null}}], "iter": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex128", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testShapeMismatch", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testShapeMismatch(self): c = np.random.randint(0, 2, 8).astype(np.bool) x = np.random.rand(16, 3, 2) * 100 y = np.random.rand(16, 3, 2) * 100 for t in [ np.float16, np.float32, np.float64, np.int32, np.int64, np.complex64, np.complex128 ]: xt = x.astype(t) yt = y.astype(t) with self.assertRaises(ValueError): array_ops.where(c, xt, yt)
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{"_type": "Constant", "_fields": {"kind": null, "value": 8}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "rand", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "random", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "right": {"_type": "Constant", "_fields": {"kind": null, "value": 100}}}}, "targets": [{"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "BinOp", "_fields": {"op": {"_type": "Mult", "_fields": {}}, "left": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 16}}, {"_type": "Constant", "_fields": {"kind": null, "value": 2}}, {"_type": "Constant", "_fields": {"kind": null, "value": 8}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", 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"_fields": {}}}}}}, "keywords": []}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "c", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "xt", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "yt", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientX", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "c", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "xt", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "yt", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientY", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}]}}], "iter": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "t", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testGradients", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testGradients(self): c = np.random.randint(0, 2, 16).astype(np.bool) x = np.random.rand(16, 2, 8) * 100 y = np.random.rand(16, 2, 8) * 100 for t in [np.float16, np.float32, np.float64]: xt = x.astype(t) yt = y.astype(t) if t == np.float16: # Compare fp16 theoretical gradients to fp32 numerical gradients, # since fp16 numerical gradients are too imprecise unless great # care is taken with choosing the inputs and the delta. This is # a weaker check (in particular, it does not test the op itself, # only its gradient), but it's much better than nothing. self._compareGradientX(c, xt, yt, np.float) self._compareGradientY(c, xt, yt, np.float) else: self._compareGradientX(c, xt, yt) self._compareGradientY(c, xt, yt)
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sess.run([omin, omax]) self.assertAllEqual(np_min, tf_min) self.assertAllEqual(np_max, tf_max)
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{"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientY", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "testGradients", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "MinMaxOpTest", "bases": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "TestCase", "value": {"_type": "Name", "_fields": {"id": "test", "ctx": {"_type": "Load", "_fields": {}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class MinMaxOpTest(test.TestCase): def _compare(self, x, y, use_gpu): np_min, np_max = np.minimum(x, y), np.maximum(x, y) with self.test_session( use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()) as sess: inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) omin, omax = math_ops.minimum(inx, iny), math_ops.maximum(inx, iny) tf_min, tf_max = sess.run([omin, omax]) self.assertAllEqual(np_min, tf_min) self.assertAllEqual(np_max, tf_max) def testBasic(self): x = np.random.rand(1, 3, 2) * 100. y = np.random.rand(1, 3, 2) * 100. for t in [np.float16, np.float32, np.float64, np.int32, np.int64]: self._compare(x.astype(t), y.astype(t), use_gpu=False) self._compare(x.astype(t), y.astype(t), use_gpu=True) def testDifferentShapes(self): x = np.random.rand(1, 3, 2) * 100. y = np.random.rand(2) * 100. # should broadcast for t in [np.float16, np.float32, np.float64, np.int32, np.int64]: self._compare(x.astype(t), y.astype(t), use_gpu=False) self._compare(x.astype(t), y.astype(t), use_gpu=True) def testScalar(self): x = np.random.rand(1, 3, 2) * 100. y = np.asscalar(np.random.rand(1) * 100.) # should broadcast # dropped np.float64, int64 because TF automatically converts to 32 bit for t in [np.float32, np.int32]: self._compare(x.astype(t), t(y), use_gpu=False) self._compare(x.astype(t), t(y), use_gpu=True) def _compareGradientX(self, func, x, y): with self.cached_session(): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = func(inx, iny) s = list(np.shape(x)) jacob_t, jacob_n = gradient_checker.compute_gradient( inx, s, out, s, x_init_value=x) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5) def _compareGradientY(self, func, x, y): with self.cached_session(): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = func(inx, iny) s = list(np.shape(x)) jacob_t, jacob_n = gradient_checker.compute_gradient( iny, s, out, s, x_init_value=y) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5) def testGradients(self): x = np.random.rand(1, 3, 2) * 100. # ensure x != y y = x + (np.random.randint(2, size=x.shape) - .5) * 2 # -1 or +1 self._compareGradientX(math_ops.maximum, x, y) self._compareGradientY(math_ops.maximum, x, y) self._compareGradientX(math_ops.minimum, x, y) self._compareGradientY(math_ops.minimum, x, y)
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"_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "jacob_t", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "jacob_n", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertAllClose", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "rtol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.00001}}}}, {"_type": "keyword", "_fields": {"arg": "atol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.00001}}}}]}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "dtype", "value": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}}}, "comparators": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": []}}]}}]}}], "name": "_compareGradientX", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _compareGradientX(self, func, x, y): with self.cached_session(): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = func(inx, iny) s = list(np.shape(x)) jacob_t, jacob_n = gradient_checker.compute_gradient( inx, s, out, s, x_init_value=x) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
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[]}}, "targets": [{"_type": "Name", "_fields": {"id": "s", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "iny", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "s", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "out", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "s", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "compute_gradient", "value": {"_type": "Name", "_fields": {"id": "gradient_checker", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "x_init_value", "value": {"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Tuple", "_fields": {"ctx": {"_type": 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"_fields": {"args": [{"_type": "Name", "_fields": {"id": "jacob_t", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "jacob_n", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertAllClose", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "rtol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.001}}}}, {"_type": "keyword", "_fields": {"arg": "atol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.001}}}}]}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "dtype", "value": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}}}, "comparators": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "jacob_t", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "jacob_n", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertAllClose", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "rtol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.00001}}}}, {"_type": "keyword", "_fields": {"arg": "atol", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 0.00001}}}}]}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "dtype", "value": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}}}, "comparators": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": []}}]}}]}}], "name": "_compareGradientY", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _compareGradientY(self, func, x, y): with self.cached_session(): inx = ops.convert_to_tensor(x) iny = ops.convert_to_tensor(y) out = func(inx, iny) s = list(np.shape(x)) jacob_t, jacob_n = gradient_checker.compute_gradient( iny, s, out, s, x_init_value=y) if x.dtype == np.float16: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float32: self.assertAllClose(jacob_t, jacob_n, rtol=1e-3, atol=1e-3) elif x.dtype == np.float64: self.assertAllClose(jacob_t, jacob_n, rtol=1e-5, atol=1e-5)
10,891	[ -0.037782806903123856, -0.007788342423737049, 0.06958416849374771, -0.028511563315987587, 0.049346938729286194, -0.004380163736641407, 0.026866666972637177, -0.016885126009583473, 0.034866850823163986, 0.023664100095629692, -0.013209029100835323, -0.00022917197202332318, -0.03995108231902122...	11	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "BinOp", "_fields": {"op": {"_type": "Mult", "_fields": {}}, "left": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 1}}, {"_type": "Constant", "_fields": {"kind": null, "value": 3}}, {"_type": "Constant", "_fields": {"kind": null, "value": 2}}], "func": 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"value": {"_type": "Name", "_fields": {"id": "math_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientX", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "maximum", "value": {"_type": "Name", "_fields": {"id": "math_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientY", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "minimum", "value": {"_type": "Name", "_fields": {"id": "math_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientX", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "minimum", "value": {"_type": "Name", "_fields": {"id": "math_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "y", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareGradientY", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "testGradients", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testGradients(self): x = np.random.rand(1, 3, 2) * 100. # ensure x != y y = x + (np.random.randint(2, size=x.shape) - .5) * 2 # -1 or +1 self._compareGradientX(math_ops.maximum, x, y) self._compareGradientY(math_ops.maximum, x, y) self._compareGradientX(math_ops.minimum, x, y) self._compareGradientY(math_ops.minimum, x, y)
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{"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareUnary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "testOverloadComparisons", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "MathOpsOverloadTest", "bases": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "TestCase", "value": {"_type": "Name", "_fields": {"id": "test", "ctx": {"_type": "Load", "_fields": {}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class MathOpsOverloadTest(test.TestCase): def _computeTensorAndLiteral(self, x, y, dtype, func): with self.test_session(use_gpu=False): inx = ops.convert_to_tensor(x, dtype=dtype) z = func(inx, y) # Should use __add__, __sub__, etc. return z.eval() def _computeLiteralAndTensor(self, x, y, dtype, func): with self.test_session(use_gpu=False): iny = ops.convert_to_tensor(y, dtype=dtype) z = func(x, iny) # Should use __radd__, __rsub__, etc. return z.eval() def _compareBinary(self, x, y, dtype, np_func, tf_func): np_ans = np_func(x, y).astype(dtype.as_numpy_dtype) self.assertAllClose(np_ans, self._computeTensorAndLiteral(x, y, dtype, tf_func)) self.assertAllClose(np_ans, self._computeLiteralAndTensor(x, y, dtype, tf_func)) def _compareUnary(self, x, dtype, np_func, tf_func): np_ans = np_func(x).astype(dtype.as_numpy_dtype) with self.test_session(use_gpu=False): self.assertAllClose(np_ans, tf_func(ops.convert_to_tensor(x, dtype=dtype)).eval()) def testOverload(self): dtypes = [ dtypes_lib.float16, dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.int32, dtypes_lib.int64, dtypes_lib.complex64, dtypes_lib.complex128, ] funcs = [ (np.add, _ADD), (np.subtract, _SUB), (np.multiply, _MUL), (np.power, _POW), (np.true_divide, _TRUEDIV), (np.floor_divide, _FLOORDIV), ] for dtype in dtypes: for np_func, tf_func in funcs: if dtype in (dtypes_lib.complex64, dtypes_lib.complex128) and tf_func == _FLOORDIV: continue # floordiv makes no sense for complex self._compareBinary(10, 5, dtype, np_func, tf_func) # Mod only works for int32 and int64. for dtype in [dtypes_lib.int32, dtypes_lib.int64]: self._compareBinary(10, 3, dtype, np.mod, _MOD) def testOverloadComparisons(self): dtypes = [ dtypes_lib.float16, dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.int32, dtypes_lib.int64, ] funcs = [ (np.less, _LT), (np.less_equal, _LE), (np.greater, _GT), (np.greater_equal, _GE), ] for dtype in dtypes: for np_func, tf_func in funcs: self._compareBinary(10, 5, dtype, np_func, tf_func) logical_funcs = [(np.logical_and, _AND), (np.logical_or, _OR), (np.logical_xor, _XOR), (np.equal, math_ops.equal), (np.not_equal, math_ops.not_equal)] for np_func, tf_func in logical_funcs: self._compareBinary(True, False, dtypes_lib.bool, np_func, tf_func) self._compareBinary(True, True, dtypes_lib.bool, np_func, tf_func) self._compareBinary(False, False, dtypes_lib.bool, np_func, tf_func) self._compareBinary(False, True, dtypes_lib.bool, np_func, tf_func) self._compareBinary([True, True, False, False], [True, False, True, False], dtypes_lib.bool, np_func, tf_func) self._compareUnary(True, dtypes_lib.bool, np.logical_not, _INV) self._compareUnary(False, dtypes_lib.bool, np.logical_not, _INV) self._compareUnary([True, False], dtypes_lib.bool, np.logical_not, _INV)
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"_fields": {"ops": [{"_type": "In", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex64", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "complex128", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}]}}, {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Name", "_fields": {"id": "_FLOORDIV", "ctx": {"_type": "Load", "_fields": {}}}}]}}]}}, "orelse": []}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 10}}, {"_type": "Constant", "_fields": {"kind": null, "value": 5}}, {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "iter": {"_type": "Name", "_fields": {"id": "funcs", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "type_comment": null}}], "iter": {"_type": "Name", "_fields": {"id": "dtypes", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}, {"_type": "For", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 10}}, {"_type": "Constant", "_fields": {"kind": null, "value": 3}}, {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "mod", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_MOD", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "iter": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int32", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int64", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testOverload", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testOverload(self): dtypes = [ dtypes_lib.float16, dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.int32, dtypes_lib.int64, dtypes_lib.complex64, dtypes_lib.complex128, ] funcs = [ (np.add, _ADD), (np.subtract, _SUB), (np.multiply, _MUL), (np.power, _POW), (np.true_divide, _TRUEDIV), (np.floor_divide, _FLOORDIV), ] for dtype in dtypes: for np_func, tf_func in funcs: if dtype in (dtypes_lib.complex64, dtypes_lib.complex128) and tf_func == _FLOORDIV: continue # floordiv makes no sense for complex self._compareBinary(10, 5, dtype, np_func, tf_func) # Mod only works for int32 and int64. for dtype in [dtypes_lib.int32, dtypes_lib.int64]: self._compareBinary(10, 3, dtype, np.mod, _MOD)
10,894	[ 0.005695545580238104, -0.001287756604142487, 0.03151952475309372, -0.03432348370552063, 0.024196680635213852, 0.03757808357477188, 0.020566552877426147, 0.006553006824105978, 0.006747030653059483, 0.05039618909358978, 0.011491232551634312, 0.004537659697234631, -0.014533028937876225, 0.000...	9	{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int32", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "int64", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "dtypes", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "less", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_LT", "ctx": {"_type": "Load", "_fields": {}}}}]}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "less_equal", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_LE", "ctx": {"_type": "Load", "_fields": {}}}}]}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "greater", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_GT", "ctx": {"_type": "Load", "_fields": {}}}}]}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "greater_equal", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_GE", "ctx": {"_type": "Load", "_fields": {}}}}]}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "funcs", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "For", "_fields": {"body": [{"_type": "For", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 10}}, {"_type": "Constant", "_fields": {"kind": null, "value": 5}}, {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "iter": {"_type": "Name", "_fields": {"id": "funcs", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "type_comment": null}}], "iter": {"_type": "Name", "_fields": {"id": "dtypes", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "logical_and", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_AND", "ctx": {"_type": "Load", "_fields": {}}}}]}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "logical_or", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_OR", "ctx": {"_type": "Load", "_fields": {}}}}]}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "logical_xor", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_XOR", "ctx": {"_type": "Load", "_fields": {}}}}]}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "equal", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "equal", "value": {"_type": "Name", "_fields": {"id": "math_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "not_equal", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "not_equal", "value": {"_type": "Name", "_fields": {"id": "math_ops", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "logical_funcs", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "For", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": false}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": false}}, {"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}]}}, {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}, {"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}]}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareBinary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "iter": {"_type": "Name", "_fields": {"id": "logical_funcs", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "np_func", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "tf_func", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "logical_not", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_INV", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareUnary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": false}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "logical_not", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_INV", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareUnary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Constant", "_fields": {"kind": null, "value": true}}, {"_type": "Constant", "_fields": {"kind": null, "value": false}}]}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bool", "value": {"_type": "Name", "_fields": {"id": "dtypes_lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "logical_not", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "_INV", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compareUnary", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "testOverloadComparisons", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def testOverloadComparisons(self): dtypes = [ dtypes_lib.float16, dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.int32, dtypes_lib.int64, ] funcs = [ (np.less, _LT), (np.less_equal, _LE), (np.greater, _GT), (np.greater_equal, _GE), ] for dtype in dtypes: for np_func, tf_func in funcs: self._compareBinary(10, 5, dtype, np_func, tf_func) logical_funcs = [(np.logical_and, _AND), (np.logical_or, _OR), (np.logical_xor, _XOR), (np.equal, math_ops.equal), (np.not_equal, math_ops.not_equal)] for np_func, tf_func in logical_funcs: self._compareBinary(True, False, dtypes_lib.bool, np_func, tf_func) self._compareBinary(True, True, dtypes_lib.bool, np_func, tf_func) self._compareBinary(False, False, dtypes_lib.bool, np_func, tf_func) self._compareBinary(False, True, dtypes_lib.bool, np_func, tf_func) self._compareBinary([True, True, False, False], [True, False, True, False], dtypes_lib.bool, np_func, tf_func) self._compareUnary(True, dtypes_lib.bool, np.logical_not, _INV) self._compareUnary(False, dtypes_lib.bool, np.logical_not, _INV) self._compareUnary([True, False], dtypes_lib.bool, np.logical_not, _INV)
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{"_type": "Constant", "_fields": {"kind": null, "value": 8}}, {"_type": "Constant", "_fields": {"kind": null, "value": 63}}, {"_type": "Constant", "_fields": {"kind": null, "value": 64}}, {"_type": "Constant", "_fields": {"kind": null, "value": 65}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "size", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "iter": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float16", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float32", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "float64", "value": {"_type": "Name", "_fields": {"id": "np", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "dtype", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "testSqrt", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "IsFiniteInfNanTest", "bases": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "TestCase", "value": {"_type": "Name", "_fields": {"id": "test", "ctx": {"_type": "Load", "_fields": {}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class IsFiniteInfNanTest(test.TestCase): def _compare(self, x, use_gpu): np_finite, np_inf, np_nan = np.isfinite(x), np.isinf(x), np.isnan(x) with self.test_session( use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()) as sess: inx = ops.convert_to_tensor(x) ofinite, oinf, onan = math_ops.is_finite(inx), math_ops.is_inf( inx), math_ops.is_nan(inx) tf_finite, tf_inf, tf_nan = sess.run([ofinite, oinf, onan]) self.assertAllEqual(np_inf, tf_inf) self.assertAllEqual(np_nan, tf_nan) self.assertAllEqual(np_finite, tf_finite) self.assertShapeEqual(np_inf, oinf) self.assertShapeEqual(np_nan, onan) self.assertShapeEqual(np_finite, ofinite) def _testDtype(self, dtype): fi = np.finfo(dtype) data = np.array([ 0, -1, 1, fi.resolution, -fi.resolution, fi.min, fi.max, -np.inf, np.inf, np.nan ]).astype(dtype) self._compare(data, use_gpu=False) self._compare(data, use_gpu=True) def testHalf(self): self._testDtype(np.float16) def testFloat(self): self._testDtype(np.float32) def testDouble(self): self._testDtype(np.float64) def testSqrt(self): for dtype in [np.float16, np.float32, np.float64]: fi = np.finfo(dtype) for size in [1, 3, 4, 7, 8, 63, 64, 65]: # For float32 Eigen uses Carmack's fast vectorized sqrt algorithm. # It is not accurate for very large arguments, so we test for # fi.max/100 instead of fi.max here. for value in [fi.min, -2, -1, 0, fi.tiny, 1, 2, 1000, fi.max / 100]: x = np.full((size,), value, dtype=dtype) np_y = np.sqrt(x) np_nan = np.isnan(np_y) with self.test_session(force_gpu=test_util.is_gpu_available()): tf_y = math_ops.sqrt(x) tf_nan = math_ops.is_nan(tf_y) if value < 0: self.assertAllEqual(np_nan, tf_nan.eval()) else: self.assertAllCloseAccordingToType(np_y, tf_y.eval())
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"_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "np_finite", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "ofinite", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertShapeEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "_compare", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _compare(self, x, use_gpu): np_finite, np_inf, np_nan = np.isfinite(x), np.isinf(x), np.isnan(x) with self.test_session( use_gpu=use_gpu, force_gpu=use_gpu and test_util.is_gpu_available()) as sess: inx = ops.convert_to_tensor(x) ofinite, oinf, onan = math_ops.is_finite(inx), math_ops.is_inf( inx), math_ops.is_nan(inx) tf_finite, tf_inf, tf_nan = sess.run([ofinite, oinf, onan]) self.assertAllEqual(np_inf, tf_inf) self.assertAllEqual(np_nan, tf_nan) self.assertAllEqual(np_finite, tf_finite) self.assertShapeEqual(np_inf, oinf) self.assertShapeEqual(np_nan, onan) self.assertShapeEqual(np_finite, ofinite)
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[fi.min, -2, -1, 0, fi.tiny, 1, 2, 1000, fi.max / 100]: x = np.full((size,), value, dtype=dtype) np_y = np.sqrt(x) np_nan = np.isnan(np_y) with self.test_session(force_gpu=test_util.is_gpu_available()): tf_y = math_ops.sqrt(x) tf_nan = math_ops.is_nan(tf_y) if value < 0: self.assertAllEqual(np_nan, tf_nan.eval()) else: self.assertAllCloseAccordingToType(np_y, tf_y.eval())
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{"_type": "Load", "_fields": {}}, "attr": "_compare", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "use_gpu", "value": {"_type": "Constant", "_fields": {"kind": null, "value": false}}}}]}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "data", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_compare", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "use_gpu", "value": {"_type": "Constant", "_fields": {"kind": null, "value": true}}}}]}}}}], "name": "_testDtype", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}	def _testDtype(self, dtype): fi = np.finfo(dtype) data = 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{}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}	class RoundingTest(test.TestCase): def _compare_values(self, x, y=None): y = np.rint(x) if y is None else np.asarray(y) with self.cached_session() as sess: tf_rint = math_ops.rint(x) np_rint = sess.run(tf_rint) self.assertAllEqual(y, np_rint) self.assertShapeEqual(y, tf_rint) def _compare(self, x): np_floor, np_ceil = np.floor(x), np.ceil(x) with self.cached_session() as sess: inx = ops.convert_to_tensor(x) ofloor, oceil = math_ops.floor(inx), math_ops.ceil(inx) tf_floor, tf_ceil = sess.run([ofloor, oceil]) self.assertAllEqual(np_floor, tf_floor) self.assertAllEqual(np_ceil, tf_ceil) self.assertShapeEqual(np_floor, ofloor) self.assertShapeEqual(np_ceil, oceil) def _testDtype(self, dtype): data = (np.arange(-3, 3) / 4.).reshape(1, 3, 2).astype(dtype) self._compare(data) # TODO: rint op is not supported for float16 if dtype is np.float16: return self._compare_values(data) x = [0.5, 0.5000001] y = [0.0, 1.0] self._compare_values(x, y=y) # numpy example x = [-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0] y = [-2., -2., -0., 0., 2., 2., 2.] self._compare_values(x, y=y) def testTypes(self): for dtype in [np.float16, np.float32, np.float64]: self._testDtype(dtype)