69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Embedder options data class."""
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import dataclasses
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from typing import Any, Optional
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from mediapipe.tasks.cc.components.processors.proto import embedder_options_pb2
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from mediapipe.tasks.python.core.optional_dependencies import doc_controls
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_EmbedderOptionsProto = embedder_options_pb2.EmbedderOptions
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@dataclasses.dataclass
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class EmbedderOptions:
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"""Shared options used by all embedding extraction tasks.
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Attributes:
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l2_normalize: Whether to normalize the returned feature vector with L2 norm.
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Use this option only if the model does not already contain a native
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L2_NORMALIZATION TF Lite Op. In most cases, this is already the case and
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L2 norm is thus achieved through TF Lite inference.
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quantize: Whether the returned embedding should be quantized to bytes via
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scalar quantization. Embeddings are implicitly assumed to be unit-norm and
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therefore any dimension is guaranteed to have a value in [-1.0, 1.0]. Use
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the l2_normalize option if this is not the case.
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"""
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l2_normalize: Optional[bool] = None
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quantize: Optional[bool] = None
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@doc_controls.do_not_generate_docs
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def to_pb2(self) -> _EmbedderOptionsProto:
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"""Generates a EmbedderOptions protobuf object."""
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return _EmbedderOptionsProto(
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l2_normalize=self.l2_normalize, quantize=self.quantize)
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@classmethod
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@doc_controls.do_not_generate_docs
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def create_from_pb2(cls, pb2_obj: _EmbedderOptionsProto) -> 'EmbedderOptions':
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"""Creates a `EmbedderOptions` object from the given protobuf object."""
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return EmbedderOptions(
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l2_normalize=pb2_obj.l2_normalize, quantize=pb2_obj.quantize)
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def __eq__(self, other: Any) -> bool:
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"""Checks if this object is equal to the given object.
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Args:
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other: The object to be compared with.
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Returns:
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True if the objects are equal.
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"""
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if not isinstance(other, EmbedderOptions):
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return False
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return self.to_pb2().__eq__(other.to_pb2())
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