added deprecation warnings to ml module

opensearch-project · Aug 2, 2022 · 35ccb3b · 35ccb3b
1 parent 727c0db
commit 35ccb3b
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Showing 11 changed files with 69 additions and 28 deletions.
diff --git a/eland/ml/_model_serializer.py b/eland/ml/_model_serializer.py
@@ -21,6 +21,8 @@
 from abc import ABC
 from typing import Any, Dict, List, Optional, Sequence
 
+from warnings import warn
+
 
 def add_if_exists(d: Dict[str, Any], k: str, v: Any) -> None:
     if v is not None:
@@ -34,6 +36,7 @@ def __init__(
         target_type: Optional[str] = None,
         classification_labels: Optional[Sequence[str]] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self._target_type = target_type
         self._feature_names = feature_names
         self._classification_labels = classification_labels
@@ -72,6 +75,7 @@ def __init__(
         leaf_value: Optional[List[float]] = None,
         number_samples: Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self._node_idx = node_idx
         self._decision_type = decision_type
         self._left_child = left_child
@@ -114,6 +118,7 @@ def __init__(
         tree_structure: Optional[Sequence[TreeNode]] = None,
         classification_labels: Optional[Sequence[str]] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(
             feature_names=feature_names,
             target_type=target_type,
@@ -139,6 +144,7 @@ def __init__(
         classification_labels: Optional[Sequence[str]] = None,
         classification_weights: Optional[Sequence[float]] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(
             feature_names=feature_names,
             target_type=target_type,

diff --git a/eland/ml/ml_model.py b/eland/ml/ml_model.py
@@ -26,6 +26,8 @@
 from .common import TYPE_CLASSIFICATION, TYPE_REGRESSION
 from .transformers import get_model_transformer
 
+from warnings import warn
+
 if TYPE_CHECKING:
     from elasticsearch import Elasticsearch
     from numpy.typing import ArrayLike, DTypeLike
@@ -52,7 +54,6 @@
     except ImportError:
         pass
 
-
 class MLModel:
     """
     A machine learning model managed by Elasticsearch.
@@ -79,6 +80,7 @@ def __init__(
         model_id: str
             The unique identifier of the trained inference model in Elasticsearch.
         """
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self._client: Elasticsearch = ensure_es_client(es_client)
         self._model_id = model_id
         self._trained_model_config_cache: Optional[Dict[str, Any]] = None

diff --git a/eland/ml/pytorch/_pytorch_model.py b/eland/ml/pytorch/_pytorch_model.py
@@ -35,6 +35,7 @@
 
 from eland.common import ensure_es_client
 from eland.ml.pytorch.nlp_ml_model import NlpTrainedModelConfig
+from warnings import warn
 
 if TYPE_CHECKING:
     from elasticsearch import Elasticsearch
@@ -57,6 +58,7 @@ def __init__(
         es_client: Union[str, List[str], Tuple[str, ...], "Elasticsearch"],
         model_id: str,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self._client: Elasticsearch = ensure_es_client(es_client)
         self.model_id = model_id
 

diff --git a/eland/ml/pytorch/nlp_ml_model.py b/eland/ml/pytorch/nlp_ml_model.py
@@ -16,6 +16,7 @@
 #  under the License.
 
 import typing as t
+from warnings import warn
 
 
 class NlpTokenizationConfig:
@@ -30,6 +31,7 @@ def __init__(
         ] = None,
         span: t.Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self.name = configuration_type
         self.with_special_tokens = with_special_tokens
         self.max_sequence_length = max_sequence_length
@@ -56,6 +58,7 @@ def __init__(
         ] = None,
         span: t.Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(
             configuration_type="roberta",
             with_special_tokens=with_special_tokens,
@@ -78,6 +81,7 @@ def __init__(
         ] = None,
         span: t.Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(
             configuration_type="bert",
             with_special_tokens=with_special_tokens,
@@ -100,6 +104,7 @@ def __init__(
         ] = None,
         span: t.Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(
             configuration_type="mpnet",
             with_special_tokens=with_special_tokens,
@@ -112,6 +117,7 @@ def __init__(
 
 class InferenceConfig:
     def __init__(self, *, configuration_type: str):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self.name = configuration_type
 
     def to_dict(self) -> t.Dict[str, t.Any]:
@@ -133,6 +139,7 @@ def __init__(
         results_field: t.Optional[str] = None,
         num_top_classes: t.Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(configuration_type="text_classification")
         self.results_field = results_field
         self.num_top_classes = num_top_classes
@@ -151,6 +158,7 @@ def __init__(
         labels: t.Optional[t.Union[t.List[str], t.Tuple[str, ...]]] = None,
         hypothesis_template: t.Optional[str] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(configuration_type="zero_shot_classification")
         self.tokenization = tokenization
         self.hypothesis_template = hypothesis_template
@@ -168,6 +176,7 @@ def __init__(
         results_field: t.Optional[str] = None,
         num_top_classes: t.Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(configuration_type="fill_mask")
         self.num_top_classes = num_top_classes
         self.tokenization = tokenization
@@ -182,6 +191,7 @@ def __init__(
         classification_labels: t.Union[t.List[str], t.Tuple[str, ...]],
         results_field: t.Optional[str] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(configuration_type="ner")
         self.tokenization = tokenization
         self.classification_labels = classification_labels
@@ -195,6 +205,7 @@ def __init__(
         tokenization: NlpTokenizationConfig,
         results_field: t.Optional[str] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(configuration_type="pass_through")
         self.tokenization = tokenization
         self.results_field = results_field
@@ -210,6 +221,7 @@ def __init__(
         question: t.Optional[str] = None,
         num_top_classes: t.Optional[int] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(configuration_type="question_answering")
         self.tokenization = tokenization
         self.results_field = results_field
@@ -225,13 +237,15 @@ def __init__(
         tokenization: NlpTokenizationConfig,
         results_field: t.Optional[str] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(configuration_type="text_embedding")
         self.tokenization = tokenization
         self.results_field = results_field
 
 
 class TrainedModelInput:
     def __init__(self, *, field_names: t.List[str]):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self.field_names = field_names
 
     def to_dict(self) -> t.Dict[str, t.Any]:
@@ -250,6 +264,7 @@ def __init__(
         default_field_map: t.Optional[t.Mapping[str, str]] = None,
         tags: t.Optional[t.Union[t.List[str], t.Tuple[str, ...]]] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self.tags = tags
         self.default_field_map = default_field_map
         self.description = description

diff --git a/eland/ml/pytorch/traceable_model.py b/eland/ml/pytorch/traceable_model.py
@@ -21,6 +21,7 @@
 
 import torch  # type: ignore
 from torch import nn
+from warnings import warn
 
 TracedModelTypes = Union[
     torch.nn.Module,
@@ -37,6 +38,7 @@ def __init__(
         self,
         model: nn.Module,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self._model = model
 
     def quantize(self) -> None:

diff --git a/eland/ml/pytorch/transformers.py b/eland/ml/pytorch/transformers.py
@@ -55,6 +55,7 @@
     ZeroShotClassificationInferenceOptions,
 )
 from eland.ml.pytorch.traceable_model import TraceableModel
+from warnings import warn
 
 DEFAULT_OUTPUT_KEY = "sentence_embedding"
 SUPPORTED_TASK_TYPES = {
@@ -112,6 +113,7 @@ class TaskTypeError(Exception):
 
 
 def task_type_from_model_config(model_config: PretrainedConfig) -> Optional[str]:
+    warn('func is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
     if model_config.architectures is None:
         if model_config.name_or_path.startswith("sentence-transformers/"):
             return "text_embedding"
@@ -150,6 +152,7 @@ class _QuestionAnsweringWrapperModule(nn.Module):  # type: ignore
     """
 
     def __init__(self, model: PreTrainedModel):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__()
         self._hf_model = model
         self.config = model.config
@@ -174,6 +177,7 @@ def from_pretrained(model_id: str) -> Optional[Any]:
 
 class _QuestionAnsweringWrapper(_QuestionAnsweringWrapperModule):
     def __init__(self, model: PreTrainedModel):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(model=model)
 
     def forward(
@@ -204,6 +208,7 @@ def forward(
 
 class _TwoParameterQuestionAnsweringWrapper(_QuestionAnsweringWrapperModule):
     def __init__(self, model: PreTrainedModel):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(model=model)
 
     def forward(self, input_ids: Tensor, attention_mask: Tensor) -> Tensor:
@@ -225,6 +230,7 @@ class _DistilBertWrapper(nn.Module):  # type: ignore
     """
 
     def __init__(self, model: transformers.PreTrainedModel):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__()
         self._model = model
         self.config = model.config
@@ -256,6 +262,7 @@ class _SentenceTransformerWrapperModule(nn.Module):  # type: ignore
     """
 
     def __init__(self, model: PreTrainedModel, output_key: str = DEFAULT_OUTPUT_KEY):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__()
         self._hf_model = model
         self._st_model = SentenceTransformer(model.config.name_or_path)
@@ -310,6 +317,7 @@ def _replace_transformer_layer(self) -> None:
 
 class _SentenceTransformerWrapper(_SentenceTransformerWrapperModule):
     def __init__(self, model: PreTrainedModel, output_key: str = DEFAULT_OUTPUT_KEY):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(model=model, output_key=output_key)
 
     def forward(
@@ -337,6 +345,7 @@ def forward(
 
 class _TwoParameterSentenceTransformerWrapper(_SentenceTransformerWrapperModule):
     def __init__(self, model: PreTrainedModel, output_key: str = DEFAULT_OUTPUT_KEY):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__(model=model, output_key=output_key)
 
     def forward(self, input_ids: Tensor, attention_mask: Tensor) -> Tensor:
@@ -365,6 +374,7 @@ def __init__(
         self,
         model: Union[transformers.DPRContextEncoder, transformers.DPRQuestionEncoder],
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super().__init__()
         self._model = model
         self.config = model.config
@@ -419,6 +429,7 @@ def __init__(
             _DistilBertWrapper,
         ],
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         super(_TransformerTraceableModel, self).__init__(model=model)
         self._tokenizer = tokenizer
 
@@ -462,6 +473,8 @@ def _prepare_inputs(self) -> transformers.BatchEncoding:
 
 class _TraceableClassificationModel(_TransformerTraceableModel, ABC):
     def classification_labels(self) -> Optional[List[str]]:
+        warn('method is deprecated, this currently only supports ElasticSearch client', DeprecationWarning,
+             stacklevel=2)
         id_label_items = self._model.config.id2label.items()
         labels = [v for _, v in sorted(id_label_items, key=lambda kv: kv[0])]  # type: ignore
 
@@ -471,6 +484,8 @@ def classification_labels(self) -> Optional[List[str]]:
 
 class _TraceableFillMaskModel(_TransformerTraceableModel):
     def _prepare_inputs(self) -> transformers.BatchEncoding:
+        warn('method is deprecated, this currently only supports ElasticSearch client', DeprecationWarning,
+             stacklevel=2)
         return self._tokenizer(
             "Who was Jim Henson?",
             "[MASK] Henson was a puppeteer",
@@ -481,6 +496,8 @@ def _prepare_inputs(self) -> transformers.BatchEncoding:
 
 class _TraceableNerModel(_TraceableClassificationModel):
     def _prepare_inputs(self) -> transformers.BatchEncoding:
+        warn('method is deprecated, this currently only supports ElasticSearch client', DeprecationWarning,
+             stacklevel=2)
         return self._tokenizer(
             (
                 "Hugging Face Inc. is a company based in New York City. "
@@ -493,6 +510,8 @@ def _prepare_inputs(self) -> transformers.BatchEncoding:
 
 class _TraceableTextClassificationModel(_TraceableClassificationModel):
     def _prepare_inputs(self) -> transformers.BatchEncoding:
+        warn('method is deprecated, this currently only supports ElasticSearch client', DeprecationWarning,
+             stacklevel=2)
         return self._tokenizer(
             "This is an example sentence.",
             padding="max_length",
@@ -502,6 +521,8 @@ def _prepare_inputs(self) -> transformers.BatchEncoding:
 
 class _TraceableTextEmbeddingModel(_TransformerTraceableModel):
     def _prepare_inputs(self) -> transformers.BatchEncoding:
+        warn('method is deprecated, this currently only supports ElasticSearch client', DeprecationWarning,
+             stacklevel=2)
         return self._tokenizer(
             "This is an example sentence.",
             padding="max_length",
@@ -511,6 +532,8 @@ def _prepare_inputs(self) -> transformers.BatchEncoding:
 
 class _TraceableZeroShotClassificationModel(_TraceableClassificationModel):
     def _prepare_inputs(self) -> transformers.BatchEncoding:
+        warn('method is deprecated, this currently only supports ElasticSearch client', DeprecationWarning,
+             stacklevel=2)
         return self._tokenizer(
             "This is an example sentence.",
             "This example is an example.",
@@ -521,6 +544,8 @@ def _prepare_inputs(self) -> transformers.BatchEncoding:
 
 class _TraceableQuestionAnsweringModel(_TransformerTraceableModel):
     def _prepare_inputs(self) -> transformers.BatchEncoding:
+        warn('method is deprecated, this currently only supports ElasticSearch client', DeprecationWarning,
+             stacklevel=2)
         return self._tokenizer(
             "What is the meaning of life?"
             "The meaning of life, according to the hitchikers guide, is 42.",
@@ -531,6 +556,7 @@ def _prepare_inputs(self) -> transformers.BatchEncoding:
 
 class TransformerModel:
     def __init__(self, model_id: str, task_type: str, quantize: bool = False):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self._model_id = model_id
         self._task_type = task_type.replace("-", "_")
 

diff --git a/eland/ml/transformers/base.py b/eland/ml/transformers/base.py
@@ -18,6 +18,7 @@
 from typing import Any, Optional, Sequence
 
 from .._model_serializer import ModelSerializer
+from warnings import warn
 
 
 class ModelTransformer:
@@ -28,6 +29,7 @@ def __init__(
         classification_labels: Optional[Sequence[str]] = None,
         classification_weights: Optional[Sequence[float]] = None,
     ):
+        warn('class is deprecated, this currently only supports ElasticSearch client', DeprecationWarning, stacklevel=2)
         self._feature_names = feature_names
         self._model = model
         self._classification_labels = classification_labels