code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
values |
|---|---|---|---|---|---|---|---|
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_config.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1PredictorConfig):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_config.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1PredictorConfig):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_config.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_extension_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_extension_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1PredictorExtensionSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_extension_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_extension_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1PredictorExtensionSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_extension_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_extension_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_protocols.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_protocols.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1PredictorProtocols):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_protocols.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_protocols.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1PredictorProtocols):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_protocols.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_protocols.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1PredictorSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1PredictorSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_predictor_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_predictor_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_config.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1ResourceConfig):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_config.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1ResourceConfig):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_config.py | Apache-2.0 |
def name(self, name):
"""Sets the name of this V1beta1ResourceMetricSource.
name is the name of the resource in question. # noqa: E501
:param name: The name of this V1beta1ResourceMetricSource. # noqa: E501
:type: str
"""
if self.local_vars_configuration.client_side_v... | Sets the name of this V1beta1ResourceMetricSource.
name is the name of the resource in question. # noqa: E501
:param name: The name of this V1beta1ResourceMetricSource. # noqa: E501
:type: str
| name | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_metric_source.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_metric_source.py | Apache-2.0 |
def target(self, target):
"""Sets the target of this V1beta1ResourceMetricSource.
:param target: The target of this V1beta1ResourceMetricSource. # noqa: E501
:type: V1beta1MetricTarget
"""
if self.local_vars_configuration.client_side_validation and target is None: # noqa: E50... | Sets the target of this V1beta1ResourceMetricSource.
:param target: The target of this V1beta1ResourceMetricSource. # noqa: E501
:type: V1beta1MetricTarget
| target | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_metric_source.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_metric_source.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_metric_source.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_metric_source.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1ResourceMetricSource):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_metric_source.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_metric_source.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1ResourceMetricSource):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_resource_metric_source.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_resource_metric_source.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_scaler_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_scaler_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1ScalerSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_scaler_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_scaler_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1ScalerSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_scaler_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_scaler_spec.py | Apache-2.0 |
def auto_mount_service_account_token(self, auto_mount_service_account_token):
"""Sets the auto_mount_service_account_token of this V1beta1SecurityConfig.
:param auto_mount_service_account_token: The auto_mount_service_account_token of this V1beta1SecurityConfig. # noqa: E501
:type: bool
... | Sets the auto_mount_service_account_token of this V1beta1SecurityConfig.
:param auto_mount_service_account_token: The auto_mount_service_account_token of this V1beta1SecurityConfig. # noqa: E501
:type: bool
| auto_mount_service_account_token | python | kserve/kserve | python/kserve/kserve/models/v1beta1_security_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_security_config.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_security_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_security_config.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1SecurityConfig):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_security_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_security_config.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1SecurityConfig):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_security_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_security_config.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_service_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_service_config.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1ServiceConfig):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_service_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_service_config.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1ServiceConfig):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_service_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_service_config.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_sk_learn_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_sk_learn_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1SKLearnSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_sk_learn_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_sk_learn_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1SKLearnSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_sk_learn_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_sk_learn_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_storage_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_storage_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1StorageSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_storage_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_storage_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1StorageSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_storage_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_storage_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_tf_serving_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_tf_serving_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1TFServingSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_tf_serving_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_tf_serving_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1TFServingSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_tf_serving_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_tf_serving_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_torch_serve_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_torch_serve_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1TorchServeSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_torch_serve_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_torch_serve_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1TorchServeSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_torch_serve_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_torch_serve_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformers_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformers_config.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1TransformersConfig):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformers_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformers_config.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1TransformersConfig):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformers_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformers_config.py | Apache-2.0 |
def default_image_version(self, default_image_version):
"""Sets the default_image_version of this V1beta1TransformerConfig.
default transformer docker image version # noqa: E501
:param default_image_version: The default_image_version of this V1beta1TransformerConfig. # noqa: E501
:ty... | Sets the default_image_version of this V1beta1TransformerConfig.
default transformer docker image version # noqa: E501
:param default_image_version: The default_image_version of this V1beta1TransformerConfig. # noqa: E501
:type: str
| default_image_version | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_config.py | Apache-2.0 |
def image(self, image):
"""Sets the image of this V1beta1TransformerConfig.
transformer docker image name # noqa: E501
:param image: The image of this V1beta1TransformerConfig. # noqa: E501
:type: str
"""
if self.local_vars_configuration.client_side_validation and ima... | Sets the image of this V1beta1TransformerConfig.
transformer docker image name # noqa: E501
:param image: The image of this V1beta1TransformerConfig. # noqa: E501
:type: str
| image | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_config.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_config.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1TransformerConfig):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_config.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1TransformerConfig):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_config.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_config.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1TransformerSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1TransformerSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_transformer_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_transformer_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_triton_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_triton_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1TritonSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_triton_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_triton_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1TritonSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_triton_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_triton_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_worker_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_worker_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1WorkerSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_worker_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_worker_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1WorkerSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_worker_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_worker_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1beta1_xg_boost_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_xg_boost_spec.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1beta1XGBoostSpec):
return False
return self.to_dict() == other.to_dict() | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_xg_boost_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_xg_boost_spec.py | Apache-2.0 |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1XGBoostSpec):
return True
return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | __ne__ | python | kserve/kserve | python/kserve/kserve/models/v1beta1_xg_boost_spec.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1beta1_xg_boost_spec.py | Apache-2.0 |
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.openapi_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if has... | Returns the model properties as a dict | to_dict | python | kserve/kserve | python/kserve/kserve/models/v1_time.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1_time.py | Apache-2.0 |
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, V1Time):
return False
return self.__dict__ == other.__dict__ | Returns true if both objects are equal | __eq__ | python | kserve/kserve | python/kserve/kserve/models/v1_time.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/models/v1_time.py | Apache-2.0 |
async def get_model(self, name: str) -> BaseKServeModel:
"""Get the model instance with the given name.
Args:
name (str): Model name.
Returns:
ModelHandleType: Instance of the model.
"""
model = self._model_registry.get_model(name)
if model is No... | Get the model instance with the given name.
Args:
name (str): Model name.
Returns:
ModelHandleType: Instance of the model.
| get_model | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
def get_binary_cloudevent(
body: Union[str, bytes, None], headers: Dict[str, str]
) -> CloudEvent:
"""Helper function to parse CloudEvent body and headers.
Args:
body (str|bytes|None): Request body.
headers (Dict[str, str]): Request headers.
Returns:
... | Helper function to parse CloudEvent body and headers.
Args:
body (str|bytes|None): Request body.
headers (Dict[str, str]): Request headers.
Returns:
CloudEvent: A CloudEvent instance parsed from http body and headers.
Raises:
InvalidInput: An er... | get_binary_cloudevent | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
async def live() -> Dict[str, str]:
"""Server live.
Returns ``{"status": "alive"}`` on successful invocation.
Primarily meant to be used for Kubernetes liveness check.
Returns:
Dict: {"status": "alive"}
"""
return {"status": "alive"} | Server live.
Returns ``{"status": "alive"}`` on successful invocation.
Primarily meant to be used for Kubernetes liveness check.
Returns:
Dict: {"status": "alive"}
| live | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
def metadata(self) -> Dict:
"""Server metadata.
Note:
Supports ``model_repository_extension`` as defined at Triton Server `Model Repository Extension`_.
Returns:
Returns a dict object with following fields:
- name (str): name of the server.
... | Server metadata.
Note:
Supports ``model_repository_extension`` as defined at Triton Server `Model Repository Extension`_.
Returns:
Returns a dict object with following fields:
- name (str): name of the server.
- version (str): server version numb... | metadata | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
async def model_metadata(self, model_name: str) -> Dict:
"""Get metadata for a specific model.
Args:
model_name (str): Model name
Returns:
Dict: dictionary with following fields:
- name (str): name of the model
- platform: "" (Empty Stri... | Get metadata for a specific model.
Args:
model_name (str): Model name
Returns:
Dict: dictionary with following fields:
- name (str): name of the model
- platform: "" (Empty String)
- inputs: Dict with below fields
... | model_metadata | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
async def ready(self) -> bool:
"""Server ready.
Returns ``True``. Primarily meant to be used as Kubernetes readiness check.
Returns:
bool: True
"""
# If predictor host is present, then it means this is a transformer,
# We should also need to check the predic... | Server ready.
Returns ``True``. Primarily meant to be used as Kubernetes readiness check.
Returns:
bool: True
| ready | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
async def model_ready(
self, model_name: str, disable_predictor_health_check: bool = False
) -> bool:
"""Check if a model is ready.
Args:
model_name (str): name of the model
disable_predictor_health_check (bool): Flag to disable predictor health
check for... | Check if a model is ready.
Args:
model_name (str): name of the model
disable_predictor_health_check (bool): Flag to disable predictor health
check for infer/predict requests.
Returns:
bool: True if the model is ready, False otherwise.
Raises:
... | model_ready | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
async def infer(
self,
model_name: str,
request: Union[Dict, InferRequest],
headers: Optional[Dict[str, str]] = None,
) -> Tuple[Union[Dict, InferResponse], Dict[str, str]]:
"""Performs inference on the specified model with the provided body and headers.
If the ``bod... | Performs inference on the specified model with the provided body and headers.
If the ``body`` contains an encoded `CloudEvent`_, then it will be decoded and processed.
The response body/headers will also be encoded as CloudEvents.
Args:
model_name (str): Model name.
req... | infer | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
async def explain(
self,
model_name: str,
request: Union[bytes, Dict, InferRequest],
headers: Optional[Dict[str, str]] = None,
) -> Tuple[Union[str, bytes, Dict, InferResponse], Dict[str, str]]:
"""Performs explanation for the specified model.
Args:
model... | Performs explanation for the specified model.
Args:
model_name (str): Model name to be used for explanation.
request (bytes|Dict): Request body data.
headers: (Optional[Dict[str, str]]): Request headers.
Returns:
Dict: Explanation result.
Raises... | explain | python | kserve/kserve | python/kserve/kserve/protocol/dataplane.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/dataplane.py | Apache-2.0 |
def serialize_byte_tensor(input_tensor: np.ndarray) -> np.ndarray:
"""
Serializes a bytes tensor into a flat numpy array of length prepended
bytes. The numpy array should use dtype of np.object. For np.bytes,
numpy will remove trailing zeros at the end of byte sequence and because
of this it should ... |
Serializes a bytes tensor into a flat numpy array of length prepended
bytes. The numpy array should use dtype of np.object. For np.bytes,
numpy will remove trailing zeros at the end of byte sequence and because
of this it should be avoided.
Args:
input_tensor : np.array
The byt... | serialize_byte_tensor | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def deserialize_bytes_tensor(encoded_tensor: bytes) -> np.ndarray:
"""
Deserializes an encoded bytes tensor into a
numpy array of dtype of python objects
Args:
encoded_tensor : bytes
The encoded bytes tensor where each element
has its length in first 4 bytes followed by
... |
Deserializes an encoded bytes tensor into a
numpy array of dtype of python objects
Args:
encoded_tensor : bytes
The encoded bytes tensor where each element
has its length in first 4 bytes followed by
the content
Returns:
string_tensor : np.array
... | deserialize_bytes_tensor | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def parameters(
self, params: Optional[Union[Dict, MessageMap[str, InferParameter]]]
):
"""Set the parameters of the inference input associated with this object.
Args:
params: parameters of the inference input
"""
self._parameters = params | Set the parameters of the inference input associated with this object.
Args:
params: parameters of the inference input
| parameters | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def as_string(self) -> List[List[str]]:
"""
Decodes the inference input data as a list of strings.
Returns:
List[List[str]]: The decoded data as a list of strings.
Raises:
InvalidInput: If the datatype of the inference input is not 'BYTES'.
"""
i... |
Decodes the inference input data as a list of strings.
Returns:
List[List[str]]: The decoded data as a list of strings.
Raises:
InvalidInput: If the datatype of the inference input is not 'BYTES'.
| as_string | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def as_numpy(self) -> np.ndarray:
"""Decode the inference input data as numpy array.
Returns:
A numpy array of the inference input data
Raises:
InvalidInput: If the datatype of the inference input is not recognized.
"""
dtype = to_np_dtype(self.datatype)
... | Decode the inference input data as numpy array.
Returns:
A numpy array of the inference input data
Raises:
InvalidInput: If the datatype of the inference input is not recognized.
| as_numpy | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def set_data_from_numpy(self, input_tensor: np.ndarray, binary_data: bool = True):
"""Set the tensor data from the specified numpy array for input associated with this object.
Args:
input_tensor : The tensor data in numpy array format.
binary_data : Indicates whether to set data... | Set the tensor data from the specified numpy array for input associated with this object.
Args:
input_tensor : The tensor data in numpy array format.
binary_data : Indicates whether to set data for the input in binary format
or explicit tensor within JSON. The ... | set_data_from_numpy | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def __init__(self, name: str, parameters: Optional[Dict] = None):
"""
The RequestedOutput class represents an output that is requested as part of an inference request.
Args:
name (str): The name of the output.
parameters (Optional[Dict]): Additional parameters for the ou... |
The RequestedOutput class represents an output that is requested as part of an inference request.
Args:
name (str): The name of the output.
parameters (Optional[Dict]): Additional parameters for the output.
| __init__ | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def parameters(
self, params: Optional[Union[Dict, MessageMap[str, InferParameter]]]
):
"""Set the parameters of the inference input associated with this object.
Args:
params: parameters of the inference input
"""
self._parameters = params | Set the parameters of the inference input associated with this object.
Args:
params: parameters of the inference input
| parameters | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def binary_data(self) -> Optional[bool]:
"""Get the binary_data attribute from the parameters.
This attribute indicates whether the data for the input should be in binary format.
Returns:
bool or None: True if the data should be in binary format, False otherwise.
... | Get the binary_data attribute from the parameters.
This attribute indicates whether the data for the input should be in binary format.
Returns:
bool or None: True if the data should be in binary format, False otherwise.
If the binary_data attribute is not set, ... | binary_data | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def __init__(
self,
model_name: str,
infer_inputs: List[InferInput],
request_id: Optional[str] = None,
raw_inputs=None,
from_grpc: Optional[bool] = False,
parameters: Optional[Union[Dict, MessageMap[str, InferParameter]]] = None,
request_outputs: Optional[... | InferRequest Data Model.
Args:
model_name: The model name.
infer_inputs: The inference inputs for the model.
request_id: The id for the inference request.
raw_inputs: The binary data for the inference inputs.
from_grpc: Indicate if the data model is c... | __init__ | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def use_binary_outputs(self) -> bool:
"""This attribute is used to determine if all the outputs should be returned as raw binary format.
For REST,
Get the binary_data_output attribute from the parameters. This will be ovverided by the individual output's 'binary_data' parameter.
For ... | This attribute is used to determine if all the outputs should be returned as raw binary format.
For REST,
Get the binary_data_output attribute from the parameters. This will be ovverided by the individual output's 'binary_data' parameter.
For GRPC,
It is True, if the received inp... | use_binary_outputs | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def from_grpc(cls, request: ModelInferRequest) -> "InferRequest":
"""
Class method to construct an InferRequest object from a ModelInferRequest object.
Args:
request (ModelInferRequest): The gRPC ModelInferRequest object to be converted.
Returns:
InferRequest: T... |
Class method to construct an InferRequest object from a ModelInferRequest object.
Args:
request (ModelInferRequest): The gRPC ModelInferRequest object to be converted.
Returns:
InferRequest: The resulting InferRequest object.
| from_grpc | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def from_bytes(
cls, req_bytes: bytes, json_length: int, model_name: str
) -> "InferRequest":
"""The class method to construct the InferRequest object from REST raw request bytes.
Args:
req_bytes (bytes): The raw InferRequest in bytes.
json_length (int): The length o... | The class method to construct the InferRequest object from REST raw request bytes.
Args:
req_bytes (bytes): The raw InferRequest in bytes.
json_length (int): The length of the json bytes.
model_name (str): The name of the model.
Returns:
InferRequest: Th... | from_bytes | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def from_inference_request(
cls, request: InferenceRequest, model_name: str
) -> "InferRequest":
"""The class method to construct the InferRequest object from InferenceRequest object.
Args:
request (InferenceRequest): The InferenceRequest object.
model_name (str): Th... | The class method to construct the InferRequest object from InferenceRequest object.
Args:
request (InferenceRequest): The InferenceRequest object.
model_name (str): The name of the model.
Returns:
InferRequest: The resulting InferRequest object.
Raises:
... | from_inference_request | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def to_rest(self) -> Tuple[Union[bytes, Dict], Optional[int]]:
"""
Converts the InferRequest object to v2 REST InferRequest Dict or bytes.
This method is used to convert the InferRequest object into a format that can be sent over a REST API.
Returns:
Tuple[Union[bytes, Dict]... |
Converts the InferRequest object to v2 REST InferRequest Dict or bytes.
This method is used to convert the InferRequest object into a format that can be sent over a REST API.
Returns:
Tuple[Union[bytes, Dict], Optional[int]]: A tuple containing the InferRequest in bytes or Dict and... | to_rest | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def to_grpc(self) -> ModelInferRequest:
"""Converts the InferRequest object to gRPC ModelInferRequest type.
Returns:
ModelInferRequest gRPC type converted from InferRequest object.
"""
infer_inputs = []
raw_input_contents = []
for infer_input in self.inputs:
... | Converts the InferRequest object to gRPC ModelInferRequest type.
Returns:
ModelInferRequest gRPC type converted from InferRequest object.
| to_grpc | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def as_dataframe(self) -> pd.DataFrame:
"""Decode the tensor inputs as pandas dataframe.
Returns:
The inference input data as pandas dataframe
"""
dfs = []
for input in self.inputs:
input_data = input.data
if input.datatype == "BYTES":
... | Decode the tensor inputs as pandas dataframe.
Returns:
The inference input data as pandas dataframe
| as_dataframe | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def get_input_by_name(self, name: str) -> Optional[InferInput]:
"""Find an input Tensor in the InferenceRequest that has the given name
Args:
name : str
name of the input Tensor object
Returns:
InferInput
The InferInput with the specified n... | Find an input Tensor in the InferenceRequest that has the given name
Args:
name : str
name of the input Tensor object
Returns:
InferInput
The InferInput with the specified name, or None if no
input with this name exists
| get_input_by_name | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def __init__(
self,
name: str,
shape: List[int],
datatype: str,
data: Union[List, np.ndarray, InferTensorContents] = None,
parameters: Optional[Union[Dict, MessageMap[str, InferParameter]]] = None,
):
"""An object of InferOutput class is used to describe the o... | An object of InferOutput class is used to describe the output tensor for an inference response.
Args:
name : The name of inference output whose data will be described by this object.
shape : The shape of the associated inference output.
datatype : The data type of the associ... | __init__ | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def as_numpy(self) -> np.ndarray:
"""Decode the tensor output data as numpy array.
Returns:
The numpy array of the associated inference output data.
"""
dtype = to_np_dtype(self.datatype)
if dtype is None:
raise InvalidInput("invalid datatype in the input... | Decode the tensor output data as numpy array.
Returns:
The numpy array of the associated inference output data.
| as_numpy | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def set_data_from_numpy(self, output_tensor: np.ndarray, binary_data: bool = True):
"""Set the tensor data from the specified numpy array for the inference output associated with this object.
Args:
output_tensor : The tensor data in numpy array format.
binary_data : Indicates wh... | Set the tensor data from the specified numpy array for the inference output associated with this object.
Args:
output_tensor : The tensor data in numpy array format.
binary_data : Indicates whether to set data for the input in binary format
or explicit tensor w... | set_data_from_numpy | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def __init__(
self,
response_id: str,
model_name: str,
infer_outputs: List[InferOutput],
model_version: Optional[str] = None,
raw_outputs=None,
from_grpc: Optional[bool] = False,
parameters: Optional[Union[Dict, MessageMap[str, InferParameter]]] = None,
... | The InferResponse Data Model
Args:
response_id: The id of the inference response.
model_name: The name of the model.
infer_outputs: The inference outputs of the inference response.
model_version: The version of the model.
raw_outputs: The raw binary d... | __init__ | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def from_grpc(cls, response: ModelInferResponse) -> "InferResponse":
"""The class method to construct the InferResponse object from gRPC message type.
Args:
response: The GRPC response as ModelInferResponse object.
Returns:
InferResponse object.
"""
infer... | The class method to construct the InferResponse object from gRPC message type.
Args:
response: The GRPC response as ModelInferResponse object.
Returns:
InferResponse object.
| from_grpc | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def from_rest(cls, response: Dict) -> "InferResponse":
"""The class method to construct the InferResponse object from REST message type.
Args:
response: The response as a dict.
Returns:
InferResponse object.
"""
infer_outputs = [
InferOutput(
... | The class method to construct the InferResponse object from REST message type.
Args:
response: The response as a dict.
Returns:
InferResponse object.
| from_rest | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def from_bytes(
cls,
res_bytes: bytes,
json_length: int,
) -> "InferResponse":
"""
Class method to construct an InferResponse object from raw response bytes.
This method is used to convert the raw response bytes received from a REST API into an InferResponse object.
... |
Class method to construct an InferResponse object from raw response bytes.
This method is used to convert the raw response bytes received from a REST API into an InferResponse object.
Args:
res_bytes (bytes): The raw response bytes received from the REST API.
json_lengt... | from_bytes | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def to_rest(self) -> Tuple[Union[bytes, Dict], Optional[int]]:
"""
Converts the InferResponse object to v2 REST InferResponse Dict or bytes.
This method is used to convert the InferResponse object into a format that can be sent over a REST API.
Returns:
Tuple[Union[bytes, Di... |
Converts the InferResponse object to v2 REST InferResponse Dict or bytes.
This method is used to convert the InferResponse object into a format that can be sent over a REST API.
Returns:
Tuple[Union[bytes, Dict], Optional[int]]: A tuple containing the InferResponse in bytes or Dict... | to_rest | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
def to_grpc(self) -> ModelInferResponse:
"""Converts the InferResponse object to gRPC ModelInferResponse type.
Returns:
The ModelInferResponse gRPC message.
Raises:
InvalidInput: If the output data is not a List or if the datatype is invalid.
"""
infer_ou... | Converts the InferResponse object to gRPC ModelInferResponse type.
Returns:
The ModelInferResponse gRPC message.
Raises:
InvalidInput: If the output data is not a List or if the datatype is invalid.
| to_grpc | python | kserve/kserve | python/kserve/kserve/protocol/infer_type.py | https://github.com/kserve/kserve/blob/master/python/kserve/kserve/protocol/infer_type.py | Apache-2.0 |
Subsets and Splits
Django Code with Docstrings
Filters Python code examples from Django repository that contain Django-related code, helping identify relevant code snippets for understanding Django framework usage patterns.
SQL Console for Shuu12121/python-treesitter-filtered-datasetsV2
Retrieves specific code examples from the Flask repository but doesn't provide meaningful analysis or patterns beyond basic data retrieval.
HTTPX Repo Code and Docstrings
Retrieves specific code examples from the httpx repository, which is useful for understanding how particular libraries are used but doesn't provide broader analytical insights about the dataset.
Requests Repo Docstrings & Code
Retrieves code examples with their docstrings and file paths from the requests repository, providing basic filtering but limited analytical value beyond finding specific code samples.
Quart Repo Docstrings & Code
Retrieves code examples with their docstrings from the Quart repository, providing basic code samples but offering limited analytical value for understanding broader patterns or relationships in the dataset.