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How to use _parse_blob method in localstack

Best Python code snippet using localstack_python

caffe2parrots

Source:caffe2parrots

...58                self._net_dict['params'].append(59                            {'id': k.strip('@'), 'learning-policy': v }60                    )61    @staticmethod62    def _parse_blob(blob):63        flat_data = np.array(blob.data)64        sp = list(blob.shape.dim)65        if len(sp) == 0:66            sp = [blob.num, blob.channels, blob.height, blob.width]67        shaped_data = flat_data.reshape(sp)68        return shaped_data69    @staticmethod70    def _parse_filer(filler, param=None):71        lr = param['lr_mult'] if param and 'lr_mult' in param else 172        decay = param['decay_mult'] if param and 'decay_mult' in param else 173        if filler.type == "xavier":74            return {"init": "xavier()", "lr_mult":lr, "decay_mult":decay}75        elif filler.type == "gaussian":76            return {"init": "gauss({})".format(filler.std), "lr_mult":lr, "decay_mult":decay}77        elif filler.type == "constant":78            return {"init": "fill({})".format(filler.value), "lr_mult":lr, "decay_mult":decay}79        else:80            raise NotImplemented81    def _layer2dict(self, layer, version):82        attr_dict = {}83        params = []84        weight_params = []85        fillers = []86        for field, value in layer.ListFields():87            if field.name == 'top':88                tops = [v.replace('-', '_').replace('/', '_') for v in value]89            elif field.name == 'name':90                layer_name = str(value).replace('-', '_').replace('/', '_')91            elif field.name == 'bottom':92                bottoms = [v.replace('-', '_').replace('/', '_') for v in value]93            elif field.name == 'include':94                if value[0].phase == 1 and op == 'Data':95                    print 'found 1 testing data layer'96                    return None, dict(), dict(), False97            elif field.name == 'type':98                if version == 2:99                    op = value100                else:101                    raise NotImplemented102            elif field.name == 'param':103                params = [{k.name: v for k, v in x.ListFields()} for x in value]104            elif field.name == 'loss_weight':105                pass106            else:107                # other params108                try:109                    for f, v in value.ListFields():110                        if 'filler' in f.name:111                          continue112                        elif f.name == 'pool':113                          attr_dict['mode'] = 'max' if v == 0 else 'ave'114                        else:115                          attr_dict[f.name] = v116                    ## get filler options117                    fillers = filter(lambda x: 'filler' in x[0].name, value.ListFields())118                except:119                    print field.name, value120                    raise121        expr_temp = '{top} = {op}({input}{params})'122        if op == 'BN' and len(params) <= 2:123            # special treatment for BN's params124            params.append({})125        if op == 'Data':126            return tops, dict(), dict(), True127        else:128            # attach weights129            if layer.name in self._weight_dict:130                blobs = self._weight_dict[layer.name].blobs131            else:132                blobs = []133            blob_dict = {}134            init_dict = {}135            if len(params) == 0:136                param_str = ''137            else:138                param_str_list = []139                for i, p in enumerate(params):140                    if 'name' in p:141                        param_str_list.append('@' + p['name'].replace('/', '_'))142                    else:143                        param_str_list.append('@{}_{}'.format(layer_name, i))144                    if i < len(blobs):145                        blob_dict[param_str_list[i]] = self._parse_blob(blobs[i])146                        if op == 'BN' and i == 2:147                            # concatenate the mean and std into a single param148                            blob_dict[param_str_list[i]] = np.concatenate((self._parse_blob(blobs[i]).ravel(), self._parse_blob(blobs[i+1]).ravel()))149                    if i < len(fillers):150                        init_dict[param_str_list[i]] = self._parse_filer(fillers[i][1], p)151                param_str = ', ' + ','.join(param_str_list)152            expr = expr_temp.format(top=','.join(tops), input=','.join(bottoms), op=op,153                                    params=param_str)154            out_dict = {155                'id': layer_name,156                'expr': expr,157            }158            if len(attr_dict) > 0:159                out_dict['attrs'] = attr_dict160            return out_dict, blob_dict, init_dict, False161    @property162    def text_form(self):...

xpass

Source:xpass

...65        else:66            line = line.lstrip()67            parts = line.split("=")68            keychains[-1]["attributes"][parts[0]] = parts[1]69    def _parse_blob(content):70        return content[1:-1]71    def _parse_timedate(content):72        content = content.split("  ")[-1][1:-6]73        timedate = time.strptime(content, "%Y%m%d%H%M%S")74        return time.strftime("%Y-%m-%d %H:%M:%S", timedate)75    data = []76    for keychain in keychains:77        account = keychain.get("attributes", {}).get('"acct"<blob>', "")78        if _parse_blob(account) != LOGIN:79            continue80        if _parse_blob(keychain["attributes"]['"desc"<blob>']) != DESC:81            continue82        name = _parse_blob(keychain["attributes"]['"svce"<blob>'])83        mtime = _parse_timedate(keychain["attributes"]['"mdat"<timedate>'])84        data.append([name, mtime])85    print(tabulate(data, headers=["Name", "Date Modified"]))86@cli.command87def list():88    commands = [89        "security",90        "dump-keychain",91    ]92    proc = run_command(commands, capture_output=True)93    format_security_output(proc)94@cli.command95@click.argument("name")96def find(name):...

parse_md_supplement.py

Source:parse_md_supplement.py

...13def parse_markdown_supplement(data, filename):14    """Parse a supplemental markdown file. Returns a dict. """15    # Possible top-level headings:16    possible_h1s = ['description', 'jsonpayload', 'property_details', 'action_details']17    parsed = _parse_blob(data, marker='#--', filename=filename, limit_headings=possible_h1s)18    if parsed.get('property_details'):19        parsed['property_details'] = _parse_blob(parsed['property_details'], filename=filename, marker="##--")20    if parsed.get('action_details'):21        parsed['action_details'] = _parse_blob(parsed['action_details'], filename=filename, marker="##--")22    return parsed23def _parse_blob(blob, marker='#--', filename=None, limit_headings=None):24    marker_len = len(marker)25    text = []26    current_item = None27    parsed = {}28    # First pass: split into chunks by main heading:29    for raw_line in blob.splitlines():30        line = raw_line.strip('\r\n') # Keep other whitespace31        if line.startswith(marker):32            if current_item:33                current_content = '\n'.join(text)34                parsed[current_item] = current_content.strip()35            text = []36            next_item = line[marker_len:].strip()37            if limit_headings and next_item not in limit_headings:...

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