code stringlengths 3 6.57k |
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self.profilers.extend(other_config.profilers) |
any(runtime_kwargs.values() |
runtime_kwargs.get("run_name_template") |
runtime_kwargs.get("run_name_template") |
runtime_kwargs.get("expectation_suite_name") |
runtime_kwargs.get("expectation_suite_ge_cloud_id") |
runtime_kwargs.get("batch_request") |
runtime_kwargs.get("batch_request") |
nested_update(batch_request, runtime_batch_request) |
runtime_kwargs.get("action_list") |
runtime_kwargs.get("action_list") |
runtime_kwargs.get("evaluation_parameters") |
runtime_kwargs.get("evaluation_parameters") |
runtime_kwargs.get("runtime_configuration") |
runtime_kwargs.get("runtime_configuration") |
runtime_kwargs.get("validations") |
runtime_kwargs.get("validations") |
runtime_kwargs.get("profilers") |
self.profilers.extend(runtime_kwargs.get("profilers") |
ALEX (we still need the next two properties) |
get_config_class(cls) |
get_schema_class(cls) |
ge_cloud_id(self) |
ge_cloud_id(self, value: str) |
expectation_suite_ge_cloud_id(self) |
expectation_suite_ge_cloud_id(self, value: str) |
name(self) |
name(self, value: str) |
template_name(self) |
template_name(self, value: str) |
config_version(self) |
validations(self) |
profilers(self) |
module_name(self) |
module_name(self, value: str) |
class_name(self) |
class_name(self, value: str) |
run_name_template(self) |
run_name_template(self, value: str) |
batch_request(self) |
batch_request(self, value: dict) |
expectation_suite_name(self) |
expectation_suite_name(self, value: str) |
action_list(self) |
action_list(self, value: List[dict]) |
site_names(self) |
slack_webhook(self) |
notify_on(self) |
notify_with(self) |
base_action_list_dict.pop(other_action_name) |
list(base_action_list_dict.values() |
evaluation_parameters(self) |
runtime_configuration(self) |
CheckpointValidationConfig(DictDot) |
CheckpointValidationConfigSchema(Schema) |
DataContextConfigSchema() |
DatasourceConfigSchema() |
DataConnectorConfigSchema() |
AssetConfigSchema() |
SorterConfigSchema() |
AnonymizedUsageStatisticsConfigSchema() |
NotebookConfigSchema() |
CheckpointConfigSchema() |
ConcurrencyConfigSchema() |
Copyright (C) |
logging.getLogger(__name__) |
logger.setLevel(logging.DEBUG) |
logging.StreamHandler() |
ch.setLevel(logging.DEBUG) |
logging.Formatter('%(asctime) |
ch.setFormatter(formatter) |
logger.addHandler(ch) |
inference(x, num_output, wd, dropout_rate, is_training, transfer_mode= False, model_type= 'A') |
print('Unknown model type: ' + model_type + ' | Please specify a modelType A or B or D or E') |
enumerate(config) |
common.maxPool(network, 2, 2) |
tf.variable_scope('conv'+str(k) |
common.spatialConvolution(network, 3, 1, v, wd= wd) |
tf.nn.relu(network) |
common.flatten(network) |
tf.variable_scope('fc1') |
common.fullyConnected(network, 4096, wd= wd) |
tf.nn.relu(network) |
common.batchNormalization(network, is_training= is_training) |
tf.nn.dropout(network, dropout_rate) |
tf.variable_scope('fc2') |
common.fullyConnected(network, 4096, wd= wd) |
tf.nn.relu(network) |
common.batchNormalization(network, is_training= is_training) |
tf.nn.dropout(network, dropout_rate) |
tf.variable_scope('output') |
common.fullyConnected(network, num_output, wd= wd) |
tf.variable_scope('transfer_output') |
common.fullyConnected(network, num_output, wd= wd) |
get_parser() |
parser.add_argument("scp", type=str, nargs="+", help="Give wav.scp") |
argparse.FileType("w") |
main() |
get_parser() |
parser.parse_args() |
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