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How to use _is_complex_type method in gabbi

Best Python code snippet using gabbi_python

emitter.py

Source:emitter.py

...354    raise NotImplementedError("Unsupported 'floor' operand: {x}")355  def _unary_negf(self, x: Value) -> Value:356    if _is_floating_point_type(x.type):357      return arith.NegFOp(x).result358    if _is_complex_type(x.type):359      return complex.NegOp(x).result360    raise NotImplementedError("Unsupported 'negf' operand: {x}")361  def _binary_add(self, lhs: Value, rhs: Value) -> Value:362    if _is_floating_point_type(lhs.type):363      return arith.AddFOp(lhs, rhs).result364    if _is_integer_type(lhs.type) or _is_index_type(lhs.type):365      return arith.AddIOp(lhs, rhs).result366    if _is_complex_type(lhs.type):367      return complex.AddOp(lhs, rhs).result368    raise NotImplementedError("Unsupported 'add' operands: {lhs}, {rhs}")369  def _binary_sub(self, lhs: Value, rhs: Value) -> Value:370    if _is_floating_point_type(lhs.type):371      return arith.SubFOp(lhs, rhs).result372    if _is_integer_type(lhs.type) or _is_index_type(lhs.type):373      return arith.SubIOp(lhs, rhs).result374    if _is_complex_type(lhs.type):375      return complex.SubOp(lhs, rhs).result376    raise NotImplementedError("Unsupported 'sub' operands: {lhs}, {rhs}")377  def _binary_mul(self, lhs: Value, rhs: Value) -> Value:378    if _is_floating_point_type(lhs.type):379      return arith.MulFOp(lhs, rhs).result380    if _is_integer_type(lhs.type) or _is_index_type(lhs.type):381      return arith.MulIOp(lhs, rhs).result382    if _is_complex_type(lhs.type):383      return complex.MulOp(lhs, rhs).result384    raise NotImplementedError("Unsupported 'mul' operands: {lhs}, {rhs}")385  def _binary_max_signed(self, lhs: Value, rhs: Value) -> Value:386    if _is_floating_point_type(lhs.type):387      return arith.MaxFOp(lhs, rhs).result388    if _is_integer_type(lhs.type) or _is_index_type(lhs.type):389      return arith.MaxSIOp(lhs, rhs).result390    raise NotImplementedError("Unsupported 'max' operands: {lhs}, {rhs}")391  def _binary_max_unsigned(self, lhs: Value, rhs: Value) -> Value:392    if _is_floating_point_type(lhs.type):393      return arith.MaxFOp(lhs, rhs).result394    if _is_integer_type(lhs.type) or _is_index_type(lhs.type):395      return arith.MaxUIOp(lhs, rhs).result396    raise NotImplementedError(397        "Unsupported 'max_unsigned' operands: {lhs}, {rhs}")398  def _binary_min_signed(self, lhs: Value, rhs: Value) -> Value:399    if _is_floating_point_type(lhs.type):400      return arith.MinFOp(lhs, rhs).result401    if _is_integer_type(lhs.type) or _is_index_type(lhs.type):402      return arith.MinSIOp(lhs, rhs).result403    raise NotImplementedError("Unsupported 'min' operands: {lhs}, {rhs}")404  def _binary_min_unsigned(self, lhs: Value, rhs: Value) -> Value:405    if _is_floating_point_type(lhs.type):406      return arith.MinFOp(lhs, rhs).result407    if _is_integer_type(lhs.type) or _is_index_type(lhs.type):408      return arith.MinUIOp(lhs, rhs).result409    raise NotImplementedError(410        "Unsupported 'min_unsigned' operands: {lhs}, {rhs}")411def _infer_structured_outs(412    op_config: LinalgStructuredOpConfig,413    in_arg_defs: Sequence[OperandDefConfig], ins: Sequence[Value],414    out_arg_defs: Sequence[OperandDefConfig],415    outs: Union[Sequence[Value], OpResultList]) -> Tuple[ValueList, List[Type]]:416  """Infers implicit outs and output types.417  Respects existing contents of outs if not empty.418  Returns:419    normalized outs, output types420  """421  # If outs were explicitly provided, we accept them verbatim.422  if outs:423    return outs, [out.type for out in outs]424  raise NotImplementedError(f"Output tensor inference not yet supported for "425                            "structured ops")426def _get_types_from_values(*values: Value) -> Sequence[Type]:427  types = []428  for v in values:429    types.append(v.type)430  return types431def _get_operand_def_names(*operand_configs: OperandDefConfig) -> Sequence[str]:432  return [odc.operand_def.name for odc in operand_configs]433def _add_type_mapping(operand_config: OperandDefConfig, operand_type: Type,434                      type_mapping: Dict[str, Type],435                      block_arg_types: Sequence[Type]):436  element_or_self_type = operand_type437  # Get the element type for tensor operands and the type itself for scalars.438  if operand_config.shape_map:439    try:440      element_or_self_type = ShapedType(operand_type).element_type441    except Exception as e:442      raise ValueError(f"Expected ShapedType but got {operand_type}") from e443  name = operand_config.type_var.name444  if name in type_mapping:445    if type_mapping[name] != element_or_self_type:446      raise ValueError(f"Cannot overwrite type mapping {name} = "447                       f"{type_mapping[name]} by type {element_or_self_type}")448  type_mapping[name] = element_or_self_type449  block_arg_types.append(element_or_self_type)450def _is_complex_type(t: Type) -> bool:451  return ComplexType.isinstance(t)452def _is_floating_point_type(t: Type) -> bool:453  # TODO: Create a FloatType in the Python API and implement the switch454  # there.455  return (F64Type.isinstance(t) or F32Type.isinstance(t) or456          F16Type.isinstance(t) or BF16Type.isinstance(t))457def _is_integer_type(t: Type) -> bool:458  return IntegerType.isinstance(t)459def _is_index_type(t: Type) -> bool:460  return IndexType.isinstance(t)461def _get_floating_point_width(t: Type) -> int:462  # TODO: Create a FloatType in the Python API and implement the switch463  # there.464  if F64Type.isinstance(t):...

serializer_utils.py

Source:serializer_utils.py

...7        self.payload = payload8        self.opts = opts9    def key_for_attribute(self, attribute):10        def transform_callback(acc, value, key):11            if self._is_complex_type(value):12                acc[self.key_for_attribute(key)] = self.key_for_attribute(value)13            else:14                acc[self.key_for_attribute(key)] = value15            return acc, value, key16        def map_function(item):17            if self._is_complex_type(item):18                return self.key_for_attribute(item)19            else:20                return item21        if _.is_dict(attribute):22            return _.transform(attribute, transform_callback)23        elif _.is_list(attribute):24            map(map_function, attribute)25        else:26            if _.is_function(self.opts.get('key_for_attribute')):27                return self.opts['key_for_attribute'](attribute)28            else:29                caserized = inflector.caserize(attribute, self.opts)30                return caserized31    def get_id(self):32        return self.opts.get('id', 'id')33    def _is_complex_type(self, obj):34        return _.is_list(obj) or _.is_dict(obj)35    def get_ref(self, current, item, opts):36        if _.is_function(opts.get('ref')):37            return opts['ref'](current, item)38        elif opts.get('ref') is True:39            if _.is_list(item):40                return map(lambda val: str(val), item)41            elif item:42                return str(item)43        elif isinstance(item, dict) and item.get(opts.get('ref')):44            return str(item[opts['ref']])45    def get_type(self, string, attr_val):46        type_ = None47        attr_val = attr_val or {}48        if _.is_function(self.opts.get('type_for_attribute')):49            type_ = self.opts['type_for_attribute'](string, attr_val)50        if (self.opts.get('pluralize_type') is None or self.opts.get('pluralize_type')) and type_ is None:51            type_ = inflector.pluralize(string)52        if type_ is None:53            type_ = string54        return type_55    def get_links(self, current, links, dest):56        def map_function(item):57            if _.is_function(item):58                return item(self.record, current, dest)59            else:60                return item61        return _.map_values(links, map_function)62    def get_meta(self, current, meta):63        def map_function(item):64            if _.is_function(item):65                return item(self.record, current)66            else:67                return item68        return _.map_values(meta, map_function)69    def pick(self, obj, attributes):70        def map_function(value, key):71            return self.key_for_attribute(key)72        return _.map_keys(_.pick(obj, attributes), map_function)73    def is_compound_document_included(self, included, item):74        return _.find(self.payload.get('included', {}), {75            'id': item.get('id'),76            'type': item.get('type')77        })78    def push_to_included(self, dest, include):79        if not self.is_compound_document_included(dest, include):80            if not dest.get('included'):81                dest['included'] = []82            dest['included'].append(include)83    def serialize(self, dest, current, attribute, opts):84        data = None85        if opts and opts.get('ref'):86            if not dest.get('relationships'):87                dest['relationships'] = {}88            def map_current(item):89                return self.serialize_ref(item, current, attribute, opts)90            if _.is_list(current.get(attribute)):91                data = map(map_current, current[attribute])92            else:93                data = self.serialize_ref(current[attribute], current,94                                         attribute, opts)95            dest['relationships'][self.key_for_attribute(attribute)] = {}96            if not opts.get('ignore_relationship_data'):97                dest['relationships'][self.key_for_attribute(attribute)]['data'] = data98            if opts.get('relationship_links'):99                dest['relationships'][self.key_for_attribute(attribute)]['links'] = \100                    self.get_links(current[attribute], opts['relationship_links'], dest)101            if opts.get('relationship_meta'):102                dest['relationships'][self.key_for_attribute(attribute)]['meta'] = \103                    self.get_meta(current['attribute'], opts['relationship_meta'])104        else:105            if _.is_list(current[attribute]):106                if len(current[attribute]) and _.is_dict(current[attribute][0]):107                    def map_current(item):108                        return self.serialize_nested(item, current, attribute,109                                                    opts)110                    data = map(map_current, current[attribute])111                else:112                    data = current[attribute]113                dest['attributes'][self.key_for_attribute(attribute)] = data114            elif _.is_dict(current[attribute]):115                data = self.serialize_nested(current[attribute], current,116                                            attribute, opts)117                dest['attributes'][self.key_for_attribute(attribute)] = data118            else:119                dest['attributes'][self.key_for_attribute(attribute)] = current[attribute]120    def serialize_ref(self, dest, current, attribute, opts):121        id_ = self.get_ref(current, dest, opts)122        type_ = self.get_type(attribute, dest)123        relationships = []124        included_attrs = []125        if opts.get('attributes'):126            relationships = filter(lambda x: opts.get(x), opts['attributes'])127            included_attrs = filter(lambda x: opts.get(x) is None, opts['attributes'])128        included = { 'type': type_, 'id': id_ }129        if included_attrs:130            included['attributes'] = self.pick(dest, included_attrs)131        for rel in relationships:132            if self._is_complex_type(dest[rel]):133                self.serialize(included, dest, rel, opts[rel])134        if included_attrs and (opts.get('included') is None or135                               opts.get('included') is True):136            if opts.get('included_links'):137                included['links'] = self.get_links(dest, opts['included_links'])138            if id_ is not None:139                self.push_to_included(self.payload, included)140        if id_ is not None:141            return { 'type': type_, 'id': id_ }142        else:143            return None144    def serialize_nested(self, dest, current, attribute, opts):145        embeds = []146        attributes = []147        if opts and opts.get('attributes'):148            embeds = filter(lambda x: opts.get(x), opts['attributes'])149            attributes = filter(lambda x: opts.get(x) is None, opts['attributes'])150        else:151            attributes = _.keys(dest)152        ret = {}153        if attributes:154            ret['attributes'] = self.pick(dest, attributes)155        for embed in embeds:156            if self._is_complex_type(dest[embed]):157                self.serialize(ret, dest, embed, opts[embed])158        return ret['attributes']159    def perform(self):160        if self.record is None:161            return None162        data = {163            'type': self.get_type(self.collection_name, self.record),164            'id': str(self.record[self.get_id()])165        }166        if self.opts.get('data_links'):167            data['links'] = self.get_links(self.record, self.opts['data_links'], None)168        for attr in self.opts.get('attributes', []):169            splitted_attributes = attr.split(':')170            if len(splitted_attributes) and splitted_attributes[0] in self.record:...

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