diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 12b1be22dd3..1cbeb7360e2 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -21,6 +21,6 @@ repos: exclude: ^(docarray/proto/pb/docarray_pb2.py|docarray/proto/pb/docarray_pb2.py|docs/|docarray/resources/) - repo: https://github.com/charliermarsh/ruff-pre-commit - rev: v0.0.165 + rev: v0.0.243 hooks: - id: ruff \ No newline at end of file diff --git a/docarray/array/array_stacked.py b/docarray/array/array_stacked.py index d9f6ed83ebb..1270baa4c32 100644 --- a/docarray/array/array_stacked.py +++ b/docarray/array/array_stacked.py @@ -21,6 +21,7 @@ from docarray.typing import NdArray from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.utils._typing import is_tensor_union +from docarray.utils.misc import is_tf_available, is_torch_available if TYPE_CHECKING: from pydantic import BaseConfig @@ -28,20 +29,19 @@ from docarray.proto import DocumentArrayStackedProto -try: +torch_available = is_torch_available() +if torch_available: from docarray.typing import TorchTensor -except ImportError: +else: TorchTensor = None # type: ignore -try: +tf_available = is_tf_available() +if tf_available: import tensorflow as tf # type: ignore from docarray.typing import TensorFlowTensor - - tf_available = True -except (ImportError, TypeError): +else: TensorFlowTensor = None # type: ignore - tf_available = False T = TypeVar('T', bound='DocumentArrayStacked') IndexIterType = Union[slice, Iterable[int], Iterable[bool], None] diff --git a/docarray/documents/audio.py b/docarray/documents/audio.py index dcf3e47b3fa..f49797026ca 100644 --- a/docarray/documents/audio.py +++ b/docarray/documents/audio.py @@ -7,12 +7,17 @@ from docarray.typing.bytes.audio_bytes import AudioBytes from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.typing.tensor.audio.audio_tensor import AudioTensor -from docarray.utils.misc import is_torch_available +from docarray.utils.misc import is_tf_available, is_torch_available torch_available = is_torch_available() if torch_available: import torch +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf # type: ignore + + T = TypeVar('T', bound='Audio') @@ -102,7 +107,9 @@ def validate( if isinstance(value, str): value = cls(url=value) elif isinstance(value, (AbstractTensor, np.ndarray)) or ( - torch_available and isinstance(value, torch.Tensor) + torch_available + and isinstance(value, torch.Tensor) + or (tf_available and isinstance(value, tf.Tensor)) ): value = cls(tensor=value) diff --git a/docarray/documents/image.py b/docarray/documents/image.py index 4b75185f90d..b1b2b34985c 100644 --- a/docarray/documents/image.py +++ b/docarray/documents/image.py @@ -6,7 +6,7 @@ from docarray.typing import AnyEmbedding, ImageBytes, ImageUrl from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.typing.tensor.image.image_tensor import ImageTensor -from docarray.utils.misc import is_torch_available +from docarray.utils.misc import is_tf_available, is_torch_available T = TypeVar('T', bound='Image') @@ -14,6 +14,10 @@ if torch_available: import torch +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf # type: ignore + class Image(BaseDocument): """ @@ -91,8 +95,10 @@ def validate( ) -> T: if isinstance(value, str): value = cls(url=value) - elif isinstance(value, (AbstractTensor, np.ndarray)) or ( - torch_available and isinstance(value, torch.Tensor) + elif ( + isinstance(value, (AbstractTensor, np.ndarray)) + or (torch_available and isinstance(value, torch.Tensor)) + or (tf_available and isinstance(value, tf.Tensor)) ): value = cls(tensor=value) elif isinstance(value, bytes): diff --git a/docarray/documents/point_cloud.py b/docarray/documents/point_cloud.py index 23ec687ce57..36d28587a49 100644 --- a/docarray/documents/point_cloud.py +++ b/docarray/documents/point_cloud.py @@ -5,12 +5,16 @@ from docarray.base_document import BaseDocument from docarray.typing import AnyEmbedding, AnyTensor, PointCloud3DUrl from docarray.typing.tensor.abstract_tensor import AbstractTensor -from docarray.utils.misc import is_torch_available +from docarray.utils.misc import is_tf_available, is_torch_available torch_available = is_torch_available() if torch_available: import torch +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf # type: ignore + T = TypeVar('T', bound='PointCloud3D') @@ -100,7 +104,9 @@ def validate( if isinstance(value, str): value = cls(url=value) elif isinstance(value, (AbstractTensor, np.ndarray)) or ( - torch_available and isinstance(value, torch.Tensor) + torch_available + and isinstance(value, torch.Tensor) + or (tf_available and isinstance(value, tf.Tensor)) ): value = cls(tensor=value) diff --git a/docarray/documents/text.py b/docarray/documents/text.py index 92c42a54a3a..b10ad5d052f 100644 --- a/docarray/documents/text.py +++ b/docarray/documents/text.py @@ -74,7 +74,7 @@ class MultiModalDoc(BaseDocument): ) mmdoc.text_doc.text = mmdoc.text_doc.url.load() - #or + # or mmdoc.text_doc.bytes = mmdoc.text_doc.url.load_bytes() @@ -87,13 +87,13 @@ class MultiModalDoc(BaseDocument): .. code-block:: python - from docarray.documents Text + from docarray.documents import Text doc = Text(text='This is the main text', url='exampleurl.com') doc2 = Text(text='This is the main text', url='exampleurl.com') - doc == 'This is the main text' # True - doc == doc2 # False, their ids are not equivalent + doc == 'This is the main text' # True + doc == doc2 # False, their ids are not equivalent """ text: Optional[str] = None @@ -126,7 +126,7 @@ def __contains__(self, item: str) -> bool: """ This method makes `Text` behave the same as an `str`. - .. code-block:: python + .. code-block:: python from docarray.documents import Text diff --git a/docarray/documents/video.py b/docarray/documents/video.py index 3912ebc51ae..dbd34b9a013 100644 --- a/docarray/documents/video.py +++ b/docarray/documents/video.py @@ -8,12 +8,18 @@ from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.typing.tensor.video.video_tensor import VideoTensor from docarray.typing.url.video_url import VideoUrl -from docarray.utils.misc import is_torch_available +from docarray.utils.misc import is_tf_available, is_torch_available torch_available = is_torch_available() if torch_available: import torch + +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf # type: ignore + + T = TypeVar('T', bound='Video') @@ -106,7 +112,9 @@ def validate( if isinstance(value, str): value = cls(url=value) elif isinstance(value, (AbstractTensor, np.ndarray)) or ( - torch_available and isinstance(value, torch.Tensor) + torch_available + and isinstance(value, torch.Tensor) + or (tf_available and isinstance(value, tf.Tensor)) ): value = cls(tensor=value) diff --git a/docarray/typing/__init__.py b/docarray/typing/__init__.py index 29292965509..cd48ff7c26b 100644 --- a/docarray/typing/__init__.py +++ b/docarray/typing/__init__.py @@ -38,11 +38,10 @@ 'ImageNdArray', ] -try: - import torch # noqa: F401 -except ImportError: - pass -else: +from docarray.utils.misc import is_tf_available, is_torch_available + +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor import TorchEmbedding, TorchTensor # noqa: F401 from docarray.typing.tensor.audio.audio_torch_tensor import AudioTorchTensor # noqa from docarray.typing.tensor.image import ImageTorchTensor # noqa: F401 @@ -58,11 +57,20 @@ ] ) -try: - import tensorflow as tf # type: ignore # noqa: F401 -except (ImportError, TypeError): - pass -else: - from docarray.typing.tensor import TensorFlowTensor # noqa: F401 +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor import TensorFlowTensor + from docarray.typing.tensor.audio import AudioTensorFlowTensor # noqa: F401 + from docarray.typing.tensor.embedding import TensorFlowEmbedding # noqa: F401 + from docarray.typing.tensor.image import ImageTensorFlowTensor # noqa: F401 + from docarray.typing.tensor.video import VideoTensorFlowTensor # noqa - __all__.extend(['TensorFlowTensor']) + __all__.extend( + [ + 'TensorFlowTensor', + 'TensorFlowEmbedding', + 'AudioTensorFlowTensor', + 'ImageTensorFlowTensor', + 'VideoTensorFlowTensor', + ] + ) diff --git a/docarray/typing/tensor/__init__.py b/docarray/typing/tensor/__init__.py index fbd4e0b24ba..07a27292aee 100644 --- a/docarray/typing/tensor/__init__.py +++ b/docarray/typing/tensor/__init__.py @@ -13,22 +13,23 @@ 'TensorFlowTensor', ] -try: - import torch # noqa: F401 -except ImportError: - pass -else: +from docarray.utils.misc import is_tf_available, is_torch_available + +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.embedding import TorchEmbedding # noqa: F401 from docarray.typing.tensor.image import ImageTorchTensor # noqa: F401 from docarray.typing.tensor.torch_tensor import TorchTensor # noqa: F401 __all__.extend(['TorchEmbedding', 'TorchTensor', 'ImageTorchTensor']) -try: - import tensorflow as tf # type: ignore # noqa: F401 -except (ImportError, TypeError): - pass -else: + torch_available = is_torch_available() + + +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.embedding import TensorFlowEmbedding # noqa: F401 + from docarray.typing.tensor.image import ImageTensorFlowTensor # noqa: F401 from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor # noqa: F401 - __all__.extend(['TensorFlowTensor']) + __all__.extend(['TensorFlowEmbedding', 'TensorFlowTensor', 'ImageTensorFlowTensor']) diff --git a/docarray/typing/tensor/audio/__init__.py b/docarray/typing/tensor/audio/__init__.py index 66d897375ff..4b1b7edc34d 100644 --- a/docarray/typing/tensor/audio/__init__.py +++ b/docarray/typing/tensor/audio/__init__.py @@ -2,11 +2,19 @@ __all__ = ['AudioNdArray'] -try: - import torch # noqa: F401 -except ImportError: - pass -else: +from docarray.utils.misc import is_tf_available, is_torch_available + +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.audio.audio_torch_tensor import AudioTorchTensor # noqa __all__.extend(['AudioTorchTensor']) + + +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.audio.audio_tensorflow_tensor import ( # noqa + AudioTensorFlowTensor, + ) + + __all__.extend(['AudioTensorFlowTensor']) diff --git a/docarray/typing/tensor/audio/audio_ndarray.py b/docarray/typing/tensor/audio/audio_ndarray.py index 6d91e84cdcc..62ee30e2014 100644 --- a/docarray/typing/tensor/audio/audio_ndarray.py +++ b/docarray/typing/tensor/audio/audio_ndarray.py @@ -16,14 +16,12 @@ class AudioNdArray(AbstractAudioTensor, NdArray): from typing import Optional - from pydantic import parse_obj_as - - from docarray import Document + from docarray import BaseDocument from docarray.typing import AudioNdArray, AudioUrl import numpy as np - class MyAudioDoc(Document): + class MyAudioDoc(BaseDocument): title: str audio_tensor: Optional[AudioNdArray] url: Optional[AudioUrl] diff --git a/docarray/typing/tensor/audio/audio_tensor.py b/docarray/typing/tensor/audio/audio_tensor.py index c7d14cc1d18..188ccba26a5 100644 --- a/docarray/typing/tensor/audio/audio_tensor.py +++ b/docarray/typing/tensor/audio/audio_tensor.py @@ -1,13 +1,23 @@ from typing import Union from docarray.typing.tensor.audio.audio_ndarray import AudioNdArray +from docarray.utils.misc import is_tf_available, is_torch_available -try: - import torch # noqa: F401 -except ImportError: - AudioTensor = AudioNdArray - -else: +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.audio.audio_torch_tensor import AudioTorchTensor +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.audio.audio_tensorflow_tensor import ( + AudioTensorFlowTensor as AudioTFTensor, + ) + + +AudioTensor = AudioNdArray +if tf_available and torch_available: + AudioTensor = Union[AudioNdArray, AudioTorchTensor, AudioTFTensor] # type: ignore +elif tf_available: + AudioTensor = Union[AudioNdArray, AudioTFTensor] # type: ignore +elif torch_available: AudioTensor = Union[AudioNdArray, AudioTorchTensor] # type: ignore diff --git a/docarray/typing/tensor/audio/audio_tensorflow_tensor.py b/docarray/typing/tensor/audio/audio_tensorflow_tensor.py new file mode 100644 index 00000000000..4d7cf5f2957 --- /dev/null +++ b/docarray/typing/tensor/audio/audio_tensorflow_tensor.py @@ -0,0 +1,59 @@ +from typing import TypeVar + +from docarray.typing.proto_register import _register_proto +from docarray.typing.tensor.audio.abstract_audio_tensor import AbstractAudioTensor +from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor, metaTensorFlow + +T = TypeVar('T', bound='AudioTensorFlowTensor') + + +@_register_proto(proto_type_name='audio_tensorflow_tensor') +class AudioTensorFlowTensor( + AbstractAudioTensor, TensorFlowTensor, metaclass=metaTensorFlow +): + """ + Subclass of TensorFlowTensor, to represent an audio tensor. + Adds audio-specific features to the tensor. + + + EXAMPLE USAGE + + .. code-block:: python + + from typing import Optional + + import tensorflow as tf + from pydantic import parse_obj_as + + from docarray import BaseDocument + from docarray.typing import AudioTensorFlowTensor, AudioUrl + + + class MyAudioDoc(BaseDocument): + title: str + audio_tensor: Optional[AudioTensorFlowTensor] + url: Optional[AudioUrl] + bytes_: Optional[bytes] + + + doc_1 = MyAudioDoc( + title='my_first_audio_doc', + audio_tensor=tf.random.normal((1000, 2)), + ) + + doc_1.audio_tensor.save_to_wav_file(file_path='path/to/file_1.wav') + doc_1.bytes_ = doc_1.audio_tensor.to_bytes() + + + doc_2 = MyAudioDoc( + title='my_second_audio_doc', + url='https://www.kozco.com/tech/piano2.wav', + ) + + doc_2.audio_tensor = doc_2.url.load() + doc_2.audio_tensor.save_to_wav_file(file_path='path/to/file_2.wav') + doc_2.bytes_ = doc_1.audio_tensor.to_bytes() + + """ + + ... diff --git a/docarray/typing/tensor/audio/audio_torch_tensor.py b/docarray/typing/tensor/audio/audio_torch_tensor.py index a1700820dbe..efc86810b72 100644 --- a/docarray/typing/tensor/audio/audio_torch_tensor.py +++ b/docarray/typing/tensor/audio/audio_torch_tensor.py @@ -17,13 +17,12 @@ class AudioTorchTensor(AbstractAudioTensor, TorchTensor, metaclass=metaTorchAndN from typing import Optional import torch - from pydantic import parse_obj_as - from docarray import Document + from docarray import BaseDocument from docarray.typing import AudioTorchTensor, AudioUrl - class MyAudioDoc(Document): + class MyAudioDoc(BaseDocument): title: str audio_tensor: Optional[AudioTorchTensor] url: Optional[AudioUrl] diff --git a/docarray/typing/tensor/embedding/__init__.py b/docarray/typing/tensor/embedding/__init__.py index 014d34fdc96..6cc8b1d6008 100644 --- a/docarray/typing/tensor/embedding/__init__.py +++ b/docarray/typing/tensor/embedding/__init__.py @@ -3,11 +3,19 @@ __all__ = ['NdArrayEmbedding', 'AnyEmbedding'] -try: - import torch # noqa: F401 -except ImportError: - pass -else: +from docarray.utils.misc import is_tf_available, is_torch_available + +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.embedding.torch import TorchEmbedding # noqa F401 __all__.append('TorchEmbedding') + + +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.embedding.tensorflow import ( # noqa F401 + TensorFlowEmbedding, + ) + + __all__.append('TensorFlowEmbedding') diff --git a/docarray/typing/tensor/embedding/embedding.py b/docarray/typing/tensor/embedding/embedding.py index 5b6cca5bdc4..a8bb78a33d2 100644 --- a/docarray/typing/tensor/embedding/embedding.py +++ b/docarray/typing/tensor/embedding/embedding.py @@ -1,15 +1,27 @@ from typing import Union from docarray.typing.tensor.embedding.ndarray import NdArrayEmbedding +from docarray.utils.misc import is_tf_available, is_torch_available -try: - import torch # noqa: F401 -except ImportError: - AnyEmbedding = Union[NdArrayEmbedding] # type: ignore +torch_available = is_torch_available() +if torch_available: + from docarray.typing.tensor.embedding.torch import TorchEmbedding -else: - from docarray.typing.tensor.embedding.torch import TorchEmbedding # noqa: F401 +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.embedding.tensorflow import ( + TensorFlowEmbedding as TFEmbedding, + ) + + +if tf_available and torch_available: + AnyEmbedding = Union[NdArrayEmbedding, TorchEmbedding, TFEmbedding] # type: ignore +elif tf_available: + AnyEmbedding = Union[NdArrayEmbedding, TFEmbedding] # type: ignore +elif torch_available: AnyEmbedding = Union[NdArrayEmbedding, TorchEmbedding] # type: ignore +else: + AnyEmbedding = Union[NdArrayEmbedding] # type: ignore __all__ = ['AnyEmbedding'] diff --git a/docarray/typing/tensor/embedding/tensorflow.py b/docarray/typing/tensor/embedding/tensorflow.py new file mode 100644 index 00000000000..a5e408d6055 --- /dev/null +++ b/docarray/typing/tensor/embedding/tensorflow.py @@ -0,0 +1,19 @@ +from typing import Any # noqa: F401 + +from docarray.typing.proto_register import _register_proto +from docarray.typing.tensor.embedding.embedding_mixin import EmbeddingMixin +from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor + +tensorflow_base = type(TensorFlowTensor) # type: Any +embedding_base = type(EmbeddingMixin) # type: Any + + +class metaTensorFlowAndEmbedding(tensorflow_base, embedding_base): + pass + + +@_register_proto(proto_type_name='tensorflow_embedding') +class TensorFlowEmbedding( + TensorFlowTensor, EmbeddingMixin, metaclass=metaTensorFlowAndEmbedding +): + alternative_type = TensorFlowTensor diff --git a/docarray/typing/tensor/image/__init__.py b/docarray/typing/tensor/image/__init__.py index 9e6b14ca526..03bd92a5342 100644 --- a/docarray/typing/tensor/image/__init__.py +++ b/docarray/typing/tensor/image/__init__.py @@ -3,11 +3,19 @@ __all__ = ['ImageNdArray', 'ImageTensor'] -try: - import torch # noqa: F401 -except ImportError: - pass -else: +from docarray.utils.misc import is_tf_available, is_torch_available + +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.image.image_torch_tensor import ImageTorchTensor # noqa __all__.extend(['ImageTorchTensor']) + + +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.image.image_tensorflow_tensor import ( # noqa + ImageTensorFlowTensor, + ) + + __all__.extend(['ImageTensorFlowTensor']) diff --git a/docarray/typing/tensor/image/abstract_image_tensor.py b/docarray/typing/tensor/image/abstract_image_tensor.py index a54f9c3da7d..538e509955d 100644 --- a/docarray/typing/tensor/image/abstract_image_tensor.py +++ b/docarray/typing/tensor/image/abstract_image_tensor.py @@ -1,11 +1,10 @@ import io -from abc import ABC, abstractmethod +from abc import ABC from docarray.typing.tensor.abstract_tensor import AbstractTensor class AbstractImageTensor(AbstractTensor, ABC): - @abstractmethod def to_bytes(self, format: str = 'PNG') -> bytes: """ Convert image tensor to bytes. diff --git a/docarray/typing/tensor/image/image_ndarray.py b/docarray/typing/tensor/image/image_ndarray.py index a4fb7c7329a..5912960b037 100644 --- a/docarray/typing/tensor/image/image_ndarray.py +++ b/docarray/typing/tensor/image/image_ndarray.py @@ -20,14 +20,11 @@ class ImageNdArray(AbstractImageTensor, NdArray): from typing import Optional - from pydantic import parse_obj_as - - from docarray import Document + from docarray import BaseDocument from docarray.typing import ImageNdArray, ImageUrl - import numpy as np - class MyImageDoc(Document): + class MyImageDoc(BaseDocument): title: str tensor: Optional[ImageNdArray] url: Optional[ImageUrl] @@ -37,7 +34,8 @@ class MyImageDoc(Document): # from url doc = MyImageDoc( title='my_second_audio_doc', - url='https://an.image.png', + url="https://upload.wikimedia.org/wikipedia/commons/8/80/" + "Dag_Sebastian_Ahlander_at_G%C3%B6teborg_Book_Fair_2012b.jpg", ) doc.tensor = doc.url.load() diff --git a/docarray/typing/tensor/image/image_tensor.py b/docarray/typing/tensor/image/image_tensor.py index b71b0c5f058..747b080b455 100644 --- a/docarray/typing/tensor/image/image_tensor.py +++ b/docarray/typing/tensor/image/image_tensor.py @@ -1,13 +1,23 @@ from typing import Union from docarray.typing.tensor.image.image_ndarray import ImageNdArray +from docarray.utils.misc import is_tf_available, is_torch_available -try: - import torch # noqa: F401 -except ImportError: - ImageTensor = ImageNdArray - -else: +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.image.image_torch_tensor import ImageTorchTensor + +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.image.image_tensorflow_tensor import ( + ImageTensorFlowTensor as ImageTFTensor, + ) + +ImageTensor = Union[ImageNdArray] # type: ignore +if tf_available and torch_available: + ImageTensor = Union[ImageNdArray, ImageTorchTensor, ImageTFTensor] # type: ignore +elif tf_available: + ImageTensor = Union[ImageNdArray, ImageTFTensor] # type: ignore +elif torch_available: ImageTensor = Union[ImageNdArray, ImageTorchTensor] # type: ignore diff --git a/docarray/typing/tensor/image/image_tensorflow_tensor.py b/docarray/typing/tensor/image/image_tensorflow_tensor.py new file mode 100644 index 00000000000..62660de7987 --- /dev/null +++ b/docarray/typing/tensor/image/image_tensorflow_tensor.py @@ -0,0 +1,48 @@ +from typing import TypeVar + +from docarray.typing.proto_register import _register_proto +from docarray.typing.tensor.image.abstract_image_tensor import AbstractImageTensor +from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor, metaTensorFlow + +T = TypeVar('T', bound='ImageTensorFlowTensor') + + +@_register_proto(proto_type_name='image_tensorflow_tensor') +class ImageTensorFlowTensor( + TensorFlowTensor, AbstractImageTensor, metaclass=metaTensorFlow +): + """ + Subclass of TensorFlowTensor, to represent an image tensor. + Adds image-specific features to the tensor. + For instance the ability convert the tensor back to image bytes which are + optimized to send over the wire + + + EXAMPLE USAGE + + .. code-block:: python + + from typing import Optional + + from docarray import BaseDocument + from docarray.typing import ImageTensorFlowTensor, ImageUrl + + + class MyImageDoc(BaseDocument): + title: str + tensor: Optional[ImageTensorFlowTensor] + url: Optional[ImageUrl] + bytes: Optional[bytes] + + + doc = MyImageDoc( + title='my_second_image_doc', + url="https://upload.wikimedia.org/wikipedia/commons/8/80/" + "Dag_Sebastian_Ahlander_at_G%C3%B6teborg_Book_Fair_2012b.jpg", + ) + doc.tensor = doc.url.load() + doc.bytes = doc.tensor.to_bytes() + + """ + + ... diff --git a/docarray/typing/tensor/image/image_torch_tensor.py b/docarray/typing/tensor/image/image_torch_tensor.py index 1c059217be2..bc5bdd640de 100644 --- a/docarray/typing/tensor/image/image_torch_tensor.py +++ b/docarray/typing/tensor/image/image_torch_tensor.py @@ -22,14 +22,11 @@ class ImageTorchTensor(AbstractImageTensor, TorchTensor, metaclass=metaTorchAndN from typing import Optional - import torch - from pydantic import parse_obj_as - - from docarray import Document + from docarray import BaseDocument from docarray.typing import ImageTorchTensor, ImageUrl - class MyImageDoc(Document): + class MyImageDoc(BaseDocument): title: str tensor: Optional[ImageTorchTensor] url: Optional[ImageUrl] @@ -38,7 +35,8 @@ class MyImageDoc(Document): doc = MyImageDoc( title='my_second_image_doc', - url='https://www.kozco.com/tech/piano2.wav', + url="https://upload.wikimedia.org/wikipedia/commons/8/80/" + "Dag_Sebastian_Ahlander_at_G%C3%B6teborg_Book_Fair_2012b.jpg", ) doc.tensor = doc.url.load() diff --git a/docarray/typing/tensor/tensor.py b/docarray/typing/tensor/tensor.py index 9d46e08a408..ffa67890c0e 100644 --- a/docarray/typing/tensor/tensor.py +++ b/docarray/typing/tensor/tensor.py @@ -1,31 +1,23 @@ from typing import Union from docarray.typing.tensor.ndarray import NdArray +from docarray.utils.misc import is_tf_available, is_torch_available -try: - import torch # noqa: F401 - +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.torch_tensor import TorchTensor # noqa: F401 - is_torch_available = True -except ImportError: - is_torch_available = False - -try: - import tensorflow as tf # type: ignore # noqa: F401 +tf_available = is_tf_available() +if tf_available: from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor # noqa: F401 - is_tf_available = True -except (ImportError, TypeError): - is_tf_available = False - -if is_torch_available and is_tf_available: +if torch_available and tf_available: AnyTensor = Union[NdArray, TorchTensor, TensorFlowTensor] -elif is_torch_available: +elif torch_available: AnyTensor = Union[NdArray, TorchTensor] # type: ignore -elif is_tf_available: +elif tf_available: AnyTensor = Union[NdArray, TensorFlowTensor] # type: ignore else: AnyTensor = Union[NdArray] # type: ignore diff --git a/docarray/typing/tensor/video/__init__.py b/docarray/typing/tensor/video/__init__.py index b2fb90cd1e5..add0c958d86 100644 --- a/docarray/typing/tensor/video/__init__.py +++ b/docarray/typing/tensor/video/__init__.py @@ -2,11 +2,19 @@ __all__ = ['VideoNdArray'] -try: - import torch # noqa: F401 -except ImportError: - pass -else: +from docarray.utils.misc import is_tf_available, is_torch_available + +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.video.video_torch_tensor import VideoTorchTensor # noqa __all__.extend(['VideoTorchTensor']) + + +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.video.video_tensorflow_tensor import ( # noqa: F401 + VideoTensorFlowTensor, + ) + + __all__.extend(['VideoTensorFlowTensor']) diff --git a/docarray/typing/tensor/video/video_ndarray.py b/docarray/typing/tensor/video/video_ndarray.py index 345499634e5..6a6beb87eb2 100644 --- a/docarray/typing/tensor/video/video_ndarray.py +++ b/docarray/typing/tensor/video/video_ndarray.py @@ -21,6 +21,39 @@ class VideoNdArray(NdArray, VideoTensorMixin): EXAMPLE USAGE + .. code-block:: python + + from typing import Optional + + import numpy as np + from pydantic import parse_obj_as + + from docarray import BaseDocument + from docarray.typing import VideoNdArray, VideoUrl + + + class MyVideoDoc(BaseDocument): + title: str + url: Optional[VideoUrl] + video_tensor: Optional[VideoNdArray] + + + doc_1 = MyVideoDoc( + title='my_first_video_doc', + video_tensor=np.random.random((100, 224, 224, 3)), + ) + + doc_1.video_tensor.save(file_path='file_1.wav') + + + doc_2 = MyVideoDoc( + title='my_second_video_doc', + url='https://www.kozco.com/tech/piano2.wav', + ) + + doc_2.video_tensor = parse_obj_as(VideoNdArray, doc_2.url.load()) + doc_2.video_tensor.save(file_path='file_2.wav') + """ @classmethod diff --git a/docarray/typing/tensor/video/video_tensor.py b/docarray/typing/tensor/video/video_tensor.py index ddf8cad3ee6..974f409fcb3 100644 --- a/docarray/typing/tensor/video/video_tensor.py +++ b/docarray/typing/tensor/video/video_tensor.py @@ -1,13 +1,24 @@ from typing import Union from docarray.typing.tensor.video.video_ndarray import VideoNdArray +from docarray.utils.misc import is_tf_available, is_torch_available -try: - import torch # noqa: F401 -except ImportError: - VideoTensor = VideoNdArray - -else: +torch_available = is_torch_available() +if torch_available: from docarray.typing.tensor.video.video_torch_tensor import VideoTorchTensor + +tf_available = is_tf_available() +if tf_available: + from docarray.typing.tensor.video.video_tensorflow_tensor import ( + VideoTensorFlowTensor as VideoTFTensor, + ) + +if tf_available and torch_available: + VideoTensor = Union[VideoNdArray, VideoTorchTensor, VideoTFTensor] # type: ignore +elif tf_available: + VideoTensor = Union[VideoNdArray, VideoTFTensor] # type: ignore +elif torch_available: VideoTensor = Union[VideoNdArray, VideoTorchTensor] # type: ignore +else: + VideoTensor = Union[VideoNdArray] # type: ignore diff --git a/docarray/typing/tensor/video/video_tensor_mixin.py b/docarray/typing/tensor/video/video_tensor_mixin.py index 1d4c2206e9d..9afed5df8d8 100644 --- a/docarray/typing/tensor/video/video_tensor_mixin.py +++ b/docarray/typing/tensor/video/video_tensor_mixin.py @@ -74,7 +74,7 @@ class MyDoc(BaseDocument): """ import av - np_tensor = self.get_comp_backend().to_numpy(array=self) # type: ignore + np_tensor = self.get_comp_backend().to_numpy(array=self) video_tensor = np_tensor.astype('uint8') with av.open(file_path, mode='w') as container: diff --git a/docarray/typing/tensor/video/video_tensorflow_tensor.py b/docarray/typing/tensor/video/video_tensorflow_tensor.py new file mode 100644 index 00000000000..a81fc377a44 --- /dev/null +++ b/docarray/typing/tensor/video/video_tensorflow_tensor.py @@ -0,0 +1,69 @@ +from typing import TYPE_CHECKING, Any, List, Tuple, Type, TypeVar, Union + +import numpy as np + +from docarray.typing.proto_register import _register_proto +from docarray.typing.tensor.tensorflow_tensor import TensorFlowTensor, metaTensorFlow +from docarray.typing.tensor.video.video_tensor_mixin import VideoTensorMixin + +T = TypeVar('T', bound='VideoTensorFlowTensor') + +if TYPE_CHECKING: + from pydantic import BaseConfig + from pydantic.fields import ModelField + + +@_register_proto(proto_type_name='video_tensorflow_tensor') +class VideoTensorFlowTensor( + TensorFlowTensor, VideoTensorMixin, metaclass=metaTensorFlow +): + """ + Subclass of TensorFlowTensor, to represent a video tensor. + Adds video-specific features to the tensor. + + EXAMPLE USAGE + + .. code-block:: python + + from typing import Optional + + import tensorflow as tf + from pydantic import parse_obj_as + + from docarray import BaseDocument + from docarray.typing import VideoTensorFlowTensor, VideoUrl + + + class MyVideoDoc(BaseDocument): + title: str + url: Optional[VideoUrl] + video_tensor: Optional[VideoTensorFlowTensor] + + + doc_1 = MyVideoDoc( + title='my_first_video_doc', + video_tensor=tf.random.normal((100, 224, 224, 3)), + ) + + doc_1.video_tensor.save(file_path='file_1.wav') + + + doc_2 = MyVideoDoc( + title='my_second_video_doc', + url='https://www.kozco.com/tech/piano2.wav', + ) + + doc_2.video_tensor = parse_obj_as(VideoTensorFlowTensor, doc_2.url.load()) + doc_2.video_tensor.save(file_path='file_2.wav') + + """ + + @classmethod + def validate( + cls: Type[T], + value: Union[T, np.ndarray, List[Any], Tuple[Any], Any], + field: 'ModelField', + config: 'BaseConfig', + ) -> T: + tensor = super().validate(value=value, field=field, config=config) + return cls.validate_shape(value=tensor) diff --git a/docarray/typing/tensor/video/video_torch_tensor.py b/docarray/typing/tensor/video/video_torch_tensor.py index 92a477915e9..caee4dfca19 100644 --- a/docarray/typing/tensor/video/video_torch_tensor.py +++ b/docarray/typing/tensor/video/video_torch_tensor.py @@ -21,6 +21,39 @@ class VideoTorchTensor(TorchTensor, VideoTensorMixin, metaclass=metaTorchAndNode EXAMPLE USAGE + .. code-block:: python + + from typing import Optional + + import torch + from pydantic import parse_obj_as + + from docarray import BaseDocument + from docarray.typing import VideoTorchTensor, VideoUrl + + + class MyVideoDoc(BaseDocument): + title: str + url: Optional[VideoUrl] + video_tensor: Optional[VideoTorchTensor] + + + doc_1 = MyVideoDoc( + title='my_first_video_doc', + video_tensor=torch.randn(size=(100, 224, 224, 3)), + ) + + doc_1.video_tensor.save(file_path='file_1.wav') + + + doc_2 = MyVideoDoc( + title='my_second_video_doc', + url='https://www.kozco.com/tech/piano2.wav', + ) + + doc_2.video_tensor = parse_obj_as(VideoTorchTensor, doc_2.url.load()) + doc_2.video_tensor.save(file_path='file_2.wav') + """ @classmethod diff --git a/docarray/utils/misc.py b/docarray/utils/misc.py index 939d2fe08c9..294d2c5ffec 100644 --- a/docarray/utils/misc.py +++ b/docarray/utils/misc.py @@ -6,5 +6,17 @@ torch_imported = True +try: + import tensorflow as tf # type: ignore # noqa: F401 +except (ImportError, TypeError): + tf_imported = False +else: + tf_imported = True + + def is_torch_available(): return torch_imported + + +def is_tf_available(): + return tf_imported diff --git a/poetry.lock b/poetry.lock index 0eb00f44dad..9a7ae4d2baf 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,5 +1,3 @@ -# This file is automatically @generated by Poetry and should not be changed by hand. - 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diff --git a/tests/integrations/document/test_proto.py b/tests/integrations/document/test_proto.py index b024876c6bf..94b902efe79 100644 --- a/tests/integrations/document/test_proto.py +++ b/tests/integrations/document/test_proto.py @@ -18,6 +18,14 @@ TorchTensor, ) from docarray.typing.tensor import NdArrayEmbedding +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + + from docarray.typing import TensorFlowEmbedding, TensorFlowTensor @pytest.mark.proto @@ -112,7 +120,50 @@ class MyDoc(BaseDocument): assert (doc.embedding == np.zeros((3, 224, 224))).all() - assert (doc.embedding == np.zeros((3, 224, 224))).all() - assert doc.bytes_ == b'hello' assert doc.img_bytes == b'img' + + +@pytest.mark.tensorflow +def test_tensorflow_types(): + class NestedDoc(BaseDocument): + tensor: TensorFlowTensor + + class MyDoc(BaseDocument): + tf_tensor: TensorFlowTensor + tf_tensor_param: TensorFlowTensor[224, 224, 3] + generic_tf_tensor: AnyTensor + embedding: AnyEmbedding + tf_embedding: TensorFlowEmbedding[128] + nested_docs: DocumentArray[NestedDoc] + + doc = MyDoc( + tf_tensor=tf.zeros((3, 224, 224)), + tf_tensor_param=tf.zeros((3, 224, 224)), + generic_tf_tensor=tf.zeros((3, 224, 224)), + embedding=tf.zeros((3, 224, 224)), + tf_embedding=tf.zeros((128,)), + nested_docs=DocumentArray[NestedDoc]([NestedDoc(tensor=tf.zeros((128,)))]), + ) + doc = doc.to_protobuf() + doc = MyDoc.from_protobuf(doc) + + assert tnp.allclose(doc.tf_tensor.tensor, tf.zeros((3, 224, 224))) + assert isinstance(doc.tf_tensor.tensor, tf.Tensor) + assert isinstance(doc.tf_tensor, TensorFlowTensor) + + assert tnp.allclose(doc.tf_tensor_param.tensor, tf.zeros((224, 224, 3))) + assert isinstance(doc.tf_tensor_param.tensor, tf.Tensor) + assert isinstance(doc.tf_tensor_param, TensorFlowTensor) + + assert tnp.allclose(doc.generic_tf_tensor.tensor, tf.zeros((3, 224, 224))) + assert isinstance(doc.generic_tf_tensor.tensor, tf.Tensor) + assert isinstance(doc.generic_tf_tensor, TensorFlowTensor) + + assert tnp.allclose(doc.tf_embedding.tensor, tf.zeros((128,))) + assert isinstance(doc.tf_embedding.tensor, tf.Tensor) + assert isinstance(doc.tf_embedding, TensorFlowTensor) + + assert tnp.allclose(doc.embedding.tensor, tf.zeros((3, 224, 224))) + assert isinstance(doc.embedding.tensor, tf.Tensor) + assert isinstance(doc.embedding, TensorFlowTensor) diff --git a/tests/integrations/predefined_document/test_audio.py b/tests/integrations/predefined_document/test_audio.py index 67e37cea984..70bc153159f 100644 --- a/tests/integrations/predefined_document/test_audio.py +++ b/tests/integrations/predefined_document/test_audio.py @@ -10,8 +10,17 @@ from docarray.documents import Audio from docarray.typing import AudioUrl from docarray.typing.tensor.audio import AudioNdArray, AudioTorchTensor +from docarray.utils.misc import is_tf_available from tests import TOYDATA_DIR +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + + from docarray.typing.tensor import TensorFlowTensor + from docarray.typing.tensor.audio import AudioTensorFlowTensor + LOCAL_AUDIO_FILES = [ str(TOYDATA_DIR / 'hello.wav'), str(TOYDATA_DIR / 'olleh.wav'), @@ -67,6 +76,29 @@ def test_save_audio_torch_tensor(file_url, tmpdir): assert torch.allclose(audio.tensor, audio_from_file.tensor) +@pytest.mark.tensorflow +@pytest.mark.slow +@pytest.mark.internet +@pytest.mark.parametrize('file_url', LOCAL_AUDIO_FILES) +def test_save_audio_tensorflow(file_url, tmpdir): + tmp_file = str(tmpdir / 'tmp.wav') + + audio = Audio(url=file_url) + audio.tensor = AudioTensorFlowTensor(tensor=tf.constant(audio.url.load())) + assert isinstance(audio.tensor, TensorFlowTensor) + assert isinstance(audio.tensor, AudioTensorFlowTensor) + assert isinstance(audio.tensor.tensor, tf.Tensor) + + audio.tensor.save_to_wav_file(tmp_file) + assert os.path.isfile(tmp_file) + + audio_from_file = Audio(url=tmp_file) + audio_from_file.tensor = AudioTensorFlowTensor( + tensor=tf.constant(audio_from_file.url.load()) + ) + assert tnp.allclose(audio.tensor.tensor, audio_from_file.tensor.tensor) + + @pytest.mark.slow @pytest.mark.internet @pytest.mark.parametrize( @@ -95,6 +127,12 @@ def test_audio_torch(): assert (audio.tensor == torch.zeros(10, 10, 3)).all() +@pytest.mark.tensorflow +def test_audio_tensorflow(): + audio = parse_obj_as(Audio, tf.zeros((10, 10, 3))) + assert tnp.allclose(audio.tensor.tensor, tf.zeros((10, 10, 3))) + + def test_audio_bytes(): audio = parse_obj_as(Audio, torch.zeros(10, 10, 3)) audio.bytes = audio.tensor.to_bytes() diff --git a/tests/integrations/predefined_document/test_image.py b/tests/integrations/predefined_document/test_image.py index 64c28a7e9fb..95f36a2e729 100644 --- a/tests/integrations/predefined_document/test_image.py +++ b/tests/integrations/predefined_document/test_image.py @@ -5,6 +5,12 @@ from docarray import BaseDocument from docarray.documents import Image +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp REMOTE_JPG = ( 'https://upload.wikimedia.org/wikipedia/commons/8/80/' @@ -37,6 +43,12 @@ def test_image_torch(): assert (image.tensor == torch.zeros(10, 10, 3)).all() +@pytest.mark.tensorflow +def test_image_tensorflow(): + image = Image(tensor=tf.zeros((10, 10, 3))) + assert tnp.allclose(image.tensor.tensor, tf.zeros((10, 10, 3))) + + def test_image_shortcut_doc(): class MyDoc(BaseDocument): image: Image diff --git a/tests/integrations/predefined_document/test_point_cloud.py b/tests/integrations/predefined_document/test_point_cloud.py index ad8f0c4a80f..9399131b8d3 100644 --- a/tests/integrations/predefined_document/test_point_cloud.py +++ b/tests/integrations/predefined_document/test_point_cloud.py @@ -5,8 +5,14 @@ from docarray import BaseDocument from docarray.documents import PointCloud3D +from docarray.utils.misc import is_tf_available from tests import TOYDATA_DIR +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + LOCAL_OBJ_FILE = str(TOYDATA_DIR / 'tetrahedron.obj') REMOTE_OBJ_FILE = 'https://people.sc.fsu.edu/~jburkardt/data/obj/al.obj' @@ -24,26 +30,46 @@ def test_point_cloud(file_url): def test_point_cloud_np(): - image = parse_obj_as(PointCloud3D, np.zeros((10, 10, 3))) - assert (image.tensor == np.zeros((10, 10, 3))).all() + pc = parse_obj_as(PointCloud3D, np.zeros((10, 10, 3))) + assert (pc.tensor == np.zeros((10, 10, 3))).all() def test_point_cloud_torch(): - image = parse_obj_as(PointCloud3D, torch.zeros(10, 10, 3)) - assert (image.tensor == torch.zeros(10, 10, 3)).all() + pc = parse_obj_as(PointCloud3D, torch.zeros(10, 10, 3)) + assert (pc.tensor == torch.zeros(10, 10, 3)).all() + + +@pytest.mark.tensorflow +def test_point_cloud_tensorflow(): + pc = parse_obj_as(PointCloud3D, tf.zeros((10, 10, 3))) + assert tnp.allclose(pc.tensor.tensor, tf.zeros((10, 10, 3))) def test_point_cloud_shortcut_doc(): class MyDoc(BaseDocument): - image: PointCloud3D - image2: PointCloud3D - image3: PointCloud3D + pc: PointCloud3D + pc2: PointCloud3D + pc3: PointCloud3D + + doc = MyDoc( + pc='http://myurl.ply', + pc2=np.zeros((10, 10, 3)), + pc3=torch.zeros(10, 10, 3), + ) + assert doc.pc.url == 'http://myurl.ply' + assert (doc.pc2.tensor == np.zeros((10, 10, 3))).all() + assert (doc.pc3.tensor == torch.zeros(10, 10, 3)).all() + + +@pytest.mark.tensorflow +def test_point_cloud_shortcut_doc_tf(): + class MyDoc(BaseDocument): + pc: PointCloud3D + pc2: PointCloud3D doc = MyDoc( - image='http://myurl.ply', - image2=np.zeros((10, 10, 3)), - image3=torch.zeros(10, 10, 3), + pc='http://myurl.ply', + pc2=tf.zeros((10, 10, 3)), ) - assert doc.image.url == 'http://myurl.ply' - assert (doc.image2.tensor == np.zeros((10, 10, 3))).all() - assert (doc.image3.tensor == torch.zeros(10, 10, 3)).all() + assert doc.pc.url == 'http://myurl.ply' + assert tnp.allclose(doc.pc2.tensor.tensor, tf.zeros((10, 10, 3))) diff --git a/tests/integrations/predefined_document/test_video.py b/tests/integrations/predefined_document/test_video.py index 4dd806afbc1..01bd5fc103d 100644 --- a/tests/integrations/predefined_document/test_video.py +++ b/tests/integrations/predefined_document/test_video.py @@ -6,8 +6,15 @@ from docarray import BaseDocument from docarray.documents import Video from docarray.typing import AudioNdArray, NdArray, VideoNdArray +from docarray.utils.misc import is_tf_available from tests import TOYDATA_DIR +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + + LOCAL_VIDEO_FILE = str(TOYDATA_DIR / 'mov_bbb.mp4') REMOTE_VIDEO_FILE = 'https://github.com/docarray/docarray/blob/feat-rewrite-v2/tests/toydata/mov_bbb.mp4?raw=true' # noqa: E501 @@ -25,26 +32,32 @@ def test_video(file_url): def test_video_np(): - image = parse_obj_as(Video, np.zeros((10, 10, 3))) - assert (image.tensor == np.zeros((10, 10, 3))).all() + video = parse_obj_as(Video, np.zeros((10, 10, 3))) + assert (video.tensor == np.zeros((10, 10, 3))).all() def test_video_torch(): - image = parse_obj_as(Video, torch.zeros(10, 10, 3)) - assert (image.tensor == torch.zeros(10, 10, 3)).all() + video = parse_obj_as(Video, torch.zeros(10, 10, 3)) + assert (video.tensor == torch.zeros(10, 10, 3)).all() + + +@pytest.mark.tensorflow +def test_video_tensorflow(): + video = parse_obj_as(Video, tf.zeros((10, 10, 3))) + assert tnp.allclose(video.tensor.tensor, tf.zeros((10, 10, 3))) def test_video_shortcut_doc(): class MyDoc(BaseDocument): - image: Video - image2: Video - image3: Video + video: Video + video2: Video + video3: Video doc = MyDoc( - image='http://myurl.mp4', - image2=np.zeros((10, 10, 3)), - image3=torch.zeros(10, 10, 3), + video='http://myurl.mp4', + video2=np.zeros((10, 10, 3)), + video3=torch.zeros(10, 10, 3), ) - assert doc.image.url == 'http://myurl.mp4' - assert (doc.image2.tensor == np.zeros((10, 10, 3))).all() - assert (doc.image3.tensor == torch.zeros(10, 10, 3)).all() + assert doc.video.url == 'http://myurl.mp4' + assert (doc.video2.tensor == np.zeros((10, 10, 3))).all() + assert (doc.video3.tensor == torch.zeros(10, 10, 3)).all() diff --git a/tests/integrations/typing/test_tensor.py b/tests/integrations/typing/test_tensor.py index afd0095bd87..a2c92f4090e 100644 --- a/tests/integrations/typing/test_tensor.py +++ b/tests/integrations/typing/test_tensor.py @@ -4,13 +4,15 @@ from docarray import BaseDocument from docarray.typing import AnyTensor, NdArray, TorchTensor +from docarray.utils.misc import is_tf_available -try: +tf_available = is_tf_available() +if tf_available: import tensorflow as tf import tensorflow._api.v2.experimental.numpy as tnp # type: ignore from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): +else: TensorFlowTensor = None @@ -32,7 +34,7 @@ class MyDocument(BaseDocument): @pytest.mark.tensorflow -def test_set_tensor(): +def test_set_tensor_tensorflow(): class MyDocument(BaseDocument): tensor: AnyTensor diff --git a/tests/integrations/typing/test_tensorflow_tensor.py b/tests/integrations/typing/test_tensorflow_tensor.py index c82e9f63394..b0337df749d 100644 --- a/tests/integrations/typing/test_tensorflow_tensor.py +++ b/tests/integrations/typing/test_tensorflow_tensor.py @@ -1,14 +1,14 @@ import pytest from docarray import BaseDocument +from docarray.utils.misc import is_tf_available -try: +tf_available = is_tf_available() +if tf_available: import tensorflow as tf import tensorflow._api.v2.experimental.numpy as tnp # type: ignore - from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass + from docarray.typing import TensorFlowEmbedding, TensorFlowTensor @pytest.mark.tensorflow @@ -21,3 +21,16 @@ class MyDocument(BaseDocument): assert isinstance(doc.t, TensorFlowTensor) assert isinstance(doc.t.tensor, tf.Tensor) assert tnp.allclose(doc.t.tensor, tf.zeros((3, 224, 224))) + + +@pytest.mark.tensorflow +def test_set_tf_embedding(): + class MyDocument(BaseDocument): + embedding: TensorFlowEmbedding + + doc = MyDocument(embedding=tf.zeros((128,))) + + assert isinstance(doc.embedding, TensorFlowTensor) + assert isinstance(doc.embedding, TensorFlowEmbedding) + assert isinstance(doc.embedding.tensor, tf.Tensor) + assert tnp.allclose(doc.embedding.tensor, tf.zeros((128,))) diff --git a/tests/integrations/typing/test_tensors_interop.py b/tests/integrations/typing/test_tensors_interop.py index 991ab080e85..d59751f21af 100644 --- a/tests/integrations/typing/test_tensors_interop.py +++ b/tests/integrations/typing/test_tensors_interop.py @@ -1,4 +1,5 @@ import numpy as np +import pytest import torch from docarray.typing import ( @@ -7,6 +8,13 @@ NdArrayEmbedding, TorchEmbedding, ) +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + + from docarray.typing import AudioTensorFlowTensor, TensorFlowEmbedding def test_torch_tensors_interop(): @@ -19,6 +27,16 @@ def test_torch_tensors_interop(): assert t_result.shape == (128,) +@pytest.mark.tensorflow +def test_tensorflow_tensors_interop(): + t1 = AudioTensorFlowTensor(tf.random.normal((128,))) + t2 = TensorFlowEmbedding(tf.random.normal((128,))) + + t_result = t1.tensor + t2.tensor + assert isinstance(t_result, tf.Tensor) + assert t_result.shape == (128,) + + def test_np_arrays_interop(): t1 = AudioNdArray((128,)) t2 = NdArrayEmbedding((128,)) diff --git a/tests/units/array/test_array.py b/tests/units/array/test_array.py index 69b6231140b..d69514caab7 100644 --- a/tests/units/array/test_array.py +++ b/tests/units/array/test_array.py @@ -6,11 +6,11 @@ from docarray import BaseDocument, DocumentArray from docarray.typing import NdArray, TorchTensor +from docarray.utils.misc import is_tf_available -try: +tf_available = is_tf_available() +if tf_available: from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass @pytest.fixture() diff --git a/tests/units/array/test_array_stacked_tf.py b/tests/units/array/test_array_stacked_tf.py index b7c4570d31c..86a6662ba09 100644 --- a/tests/units/array/test_array_stacked_tf.py +++ b/tests/units/array/test_array_stacked_tf.py @@ -5,14 +5,14 @@ from docarray import BaseDocument, DocumentArray from docarray.array import DocumentArrayStacked from docarray.typing import AnyTensor, NdArray +from docarray.utils.misc import is_tf_available -try: +tf_available = is_tf_available() +if tf_available: import tensorflow as tf import tensorflow._api.v2.experimental.numpy as tnp from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass @pytest.fixture() diff --git a/tests/units/computation_backends/tensorflow_backend/test_basics.py b/tests/units/computation_backends/tensorflow_backend/test_basics.py index 7c896749647..fca2237cdd1 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_basics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_basics.py @@ -1,13 +1,14 @@ import numpy as np import pytest -try: +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: import tensorflow as tf from docarray.computation.tensorflow_backend import TensorFlowCompBackend from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass @pytest.mark.tensorflow diff --git a/tests/units/computation_backends/tensorflow_backend/test_metrics.py b/tests/units/computation_backends/tensorflow_backend/test_metrics.py index 354b61612e5..863dd18fe4c 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_metrics.py +++ b/tests/units/computation_backends/tensorflow_backend/test_metrics.py @@ -1,13 +1,16 @@ import pytest -try: +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: import tensorflow as tf from docarray.computation.tensorflow_backend import TensorFlowCompBackend from docarray.typing import TensorFlowTensor metrics = TensorFlowCompBackend.Metrics -except (ImportError, TypeError): +else: metrics = None diff --git a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py index 0eb789b9e1d..feac992d760 100644 --- a/tests/units/computation_backends/tensorflow_backend/test_retrieval.py +++ b/tests/units/computation_backends/tensorflow_backend/test_retrieval.py @@ -1,13 +1,14 @@ import pytest -try: +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: import tensorflow as tf import tensorflow._api.v2.experimental.numpy as tnp from docarray.computation.tensorflow_backend import TensorFlowCompBackend from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass @pytest.mark.tensorflow diff --git a/tests/units/document/test_update.py b/tests/units/document/test_update.py index 90e2d813f9f..15c7a745890 100644 --- a/tests/units/document/test_update.py +++ b/tests/units/document/test_update.py @@ -1,12 +1,14 @@ +from typing import Dict, List, Optional, Set + import pytest -from typing import Optional, List, Dict, Set + from docarray import BaseDocument, DocumentArray from docarray.documents import Image class InnerDoc(BaseDocument): integer: int - l: List + inner_list: List class MMDoc(BaseDocument): @@ -33,7 +35,7 @@ def doc1(): [MMDoc(id='a', matches=DocumentArray[MMDoc]([MMDoc()]))] ), test_set={'a', 'a'}, - inner_doc=InnerDoc(integer=2, l=['c', 'd']), + inner_doc=InnerDoc(integer=2, inner_list=['c', 'd']), test_dict={'a': 0, 'b': 2, 'd': 4, 'z': 3}, ) @@ -51,7 +53,7 @@ def doc2(doc1): [MMDoc(id='a', matches=DocumentArray[MMDoc]([MMDoc()]))] ), test_set={'a', 'b'}, - inner_doc=InnerDoc(integer=3, l=['a', 'b']), + inner_doc=InnerDoc(integer=3, inner_list=['a', 'b']), test_dict={'a': 10, 'b': 10, 'c': 3, 'z': None}, ) @@ -68,7 +70,7 @@ def test_update_complex(doc1, doc2): assert len(doc1.matches_with_same_id) == 1 assert len(doc1.matches_with_same_id[0].matches) == 2 assert doc1.inner_doc.integer == 3 - assert doc1.inner_doc.l == ['c', 'd', 'a', 'b'] + assert doc1.inner_doc.inner_list == ['c', 'd', 'a', 'b'] assert doc1.test_dict == {'a': 10, 'b': 10, 'c': 3, 'd': 4, 'z': None} diff --git a/tests/units/typing/tensor/test_audio_tensor.py b/tests/units/typing/tensor/test_audio_tensor.py index 341c226b35d..a1690432948 100644 --- a/tests/units/typing/tensor/test_audio_tensor.py +++ b/tests/units/typing/tensor/test_audio_tensor.py @@ -8,6 +8,14 @@ from docarray import BaseDocument from docarray.typing.tensor.audio.audio_ndarray import AudioNdArray from docarray.typing.tensor.audio.audio_torch_tensor import AudioTorchTensor +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + + from docarray.typing.tensor.audio import AudioTensorFlowTensor @pytest.mark.parametrize( @@ -27,6 +35,17 @@ class MyAudioDoc(BaseDocument): assert (doc.tensor == tensor).all() +@pytest.mark.tensorflow +def test_set_audio_tensorflow_tensor(): + class MyAudioDoc(BaseDocument): + tensor: AudioTensorFlowTensor + + doc = MyAudioDoc(tensor=tf.zeros((1000, 2))) + assert isinstance(doc.tensor, AudioTensorFlowTensor) + assert isinstance(doc.tensor.tensor, tf.Tensor) + assert tnp.allclose(doc.tensor.tensor, tf.zeros((1000, 2))) + + @pytest.mark.parametrize( 'cls_tensor,tensor', [ @@ -40,6 +59,12 @@ def test_validation(cls_tensor, tensor): assert isinstance(arr, cls_tensor) +@pytest.mark.tensorflow +def test_validation_tensorflow(): + arr = parse_obj_as(AudioTensorFlowTensor, tf.zeros((1000, 2))) + assert isinstance(arr, AudioTensorFlowTensor) + + @pytest.mark.parametrize( 'cls_tensor,tensor', [ @@ -68,6 +93,13 @@ def test_proto_tensor(cls_tensor, tensor, proto_key): assert proto_key in str(proto) +@pytest.mark.tensorflow +def test_proto_tensor_tensorflow(): + tensor = parse_obj_as(AudioTensorFlowTensor, tf.zeros((1000, 2))) + proto = tensor._to_node_protobuf() + assert AudioTensorFlowTensor._proto_type_name in str(proto) + + @pytest.mark.parametrize( 'cls_tensor,tensor', [ @@ -80,3 +112,11 @@ def test_save_audio_tensor_to_wav_file(cls_tensor, tensor, tmpdir): audio_tensor = parse_obj_as(cls_tensor, tensor) audio_tensor.save_to_wav_file(tmp_file) assert os.path.isfile(tmp_file) + + +@pytest.mark.tensorflow +def test_save_audio_tensorflow_tensor_to_wav_file(tmpdir): + tmp_file = str(tmpdir / 'tmp.wav') + audio_tensor = parse_obj_as(AudioTensorFlowTensor, tf.zeros((1000, 2))) + audio_tensor.save_to_wav_file(tmp_file) + assert os.path.isfile(tmp_file) diff --git a/tests/units/typing/tensor/test_tensor_flow_tensor.py b/tests/units/typing/tensor/test_tensor_flow_tensor.py index e1727acabb9..8aa1a3cae5c 100644 --- a/tests/units/typing/tensor/test_tensor_flow_tensor.py +++ b/tests/units/typing/tensor/test_tensor_flow_tensor.py @@ -4,15 +4,15 @@ from pydantic.tools import parse_obj_as from docarray.base_document.io.json import orjson_dumps +from docarray.utils.misc import is_tf_available -try: +tf_available = is_tf_available() +if tf_available: import tensorflow as tf import tensorflow._api.v2.experimental.numpy as tnp # type: ignore from tensorflow.python.framework.errors_impl import InvalidArgumentError from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): - pass @pytest.mark.tensorflow diff --git a/tests/units/typing/tensor/test_video_tensor.py b/tests/units/typing/tensor/test_video_tensor.py index d7baf131a39..c5fc4ea93d2 100644 --- a/tests/units/typing/tensor/test_video_tensor.py +++ b/tests/units/typing/tensor/test_video_tensor.py @@ -12,6 +12,14 @@ VideoNdArray, VideoTorchTensor, ) +from docarray.utils.misc import is_tf_available + +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + import tensorflow._api.v2.experimental.numpy as tnp + + from docarray.typing.tensor.video import VideoTensorFlowTensor @pytest.mark.parametrize( @@ -32,6 +40,18 @@ class MyVideoDoc(BaseDocument): assert (doc.tensor == tensor).all() +@pytest.mark.tensorflow +def test_set_video_tensor_tensorflow(): + class MyVideoDoc(BaseDocument): + tensor: VideoTensorFlowTensor + + doc = MyVideoDoc(tensor=tf.zeros((1, 224, 224, 3))) + + assert isinstance(doc.tensor, VideoTensorFlowTensor) + assert isinstance(doc.tensor.tensor, tf.Tensor) + assert tnp.allclose(doc.tensor.tensor, tf.zeros((1, 224, 224, 3))) + + @pytest.mark.parametrize( 'cls_tensor,tensor', [ @@ -45,6 +65,18 @@ def test_validation(cls_tensor, tensor): assert isinstance(arr, cls_tensor) +@pytest.mark.tensorflow +def test_validation_tensorflow(): + arr = parse_obj_as(VideoTensorFlowTensor, np.zeros((1, 224, 224, 3))) + assert isinstance(arr, VideoTensorFlowTensor) + + arr = parse_obj_as(VideoTensorFlowTensor, tf.zeros((1, 224, 224, 3))) + assert isinstance(arr, VideoTensorFlowTensor) + + arr = parse_obj_as(VideoTensorFlowTensor, torch.zeros((1, 224, 224, 3))) + assert isinstance(arr, VideoTensorFlowTensor) + + @pytest.mark.parametrize( 'cls_tensor,tensor', [ @@ -78,6 +110,13 @@ def test_proto_tensor(cls_tensor, tensor, proto_key): assert proto_key in str(proto) +@pytest.mark.tensorflow +def test_proto_tensor_tensorflow(): + tensor = parse_obj_as(VideoTensorFlowTensor, tf.zeros((1, 224, 224, 3))) + proto = tensor._to_node_protobuf() + assert VideoTensorFlowTensor._proto_type_name in str(proto) + + @pytest.mark.parametrize( 'video_tensor', [ @@ -91,6 +130,14 @@ def test_save_video_tensor_to_file(video_tensor, tmpdir): assert os.path.isfile(tmp_file) +@pytest.mark.tensorflow +def test_save_video_tensorflow_tensor_to_file(tmpdir): + tmp_file = str(tmpdir / 'tmp.mp4') + video_tensor = parse_obj_as(VideoTensorFlowTensor, tf.zeros((1, 224, 224, 3))) + video_tensor.save(tmp_file) + assert os.path.isfile(tmp_file) + + @pytest.mark.parametrize( 'video_tensor', [ diff --git a/tests/units/typing/url/test_audio_url.py b/tests/units/typing/url/test_audio_url.py index 1647f349e1a..9122b749a1d 100644 --- a/tests/units/typing/url/test_audio_url.py +++ b/tests/units/typing/url/test_audio_url.py @@ -8,8 +8,15 @@ from docarray import BaseDocument from docarray.base_document.io.json import orjson_dumps from docarray.typing import AudioTorchTensor, AudioUrl +from docarray.utils.misc import is_tf_available from tests import TOYDATA_DIR +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + + from docarray.typing.tensor.audio import AudioTensorFlowTensor + AUDIO_FILES = [ str(TOYDATA_DIR / 'hello.wav'), str(TOYDATA_DIR / 'olleh.wav'), @@ -47,6 +54,25 @@ class MyAudioDoc(BaseDocument): assert isinstance(doc.tensor, AudioTorchTensor) +@pytest.mark.tensorflow +@pytest.mark.slow +@pytest.mark.internet +@pytest.mark.parametrize( + 'file_url', + [*AUDIO_FILES, REMOTE_AUDIO_FILE], +) +def test_load_audio_url_to_audio_tensorflow_tensor_field(file_url): + class MyAudioDoc(BaseDocument): + audio_url: AudioUrl + tensor: Optional[AudioTensorFlowTensor] + + doc = MyAudioDoc(audio_url=file_url) + doc.tensor = doc.audio_url.load() + + assert isinstance(doc.tensor, AudioTensorFlowTensor) + assert isinstance(doc.tensor.tensor, tf.Tensor) + + @pytest.mark.slow @pytest.mark.internet @pytest.mark.parametrize( diff --git a/tests/units/typing/url/test_video_url.py b/tests/units/typing/url/test_video_url.py index b1df8dc0a84..7a92e672cab 100644 --- a/tests/units/typing/url/test_video_url.py +++ b/tests/units/typing/url/test_video_url.py @@ -14,8 +14,15 @@ VideoTorchTensor, VideoUrl, ) +from docarray.utils.misc import is_tf_available from tests import TOYDATA_DIR +tf_available = is_tf_available() +if tf_available: + import tensorflow as tf + + from docarray.typing.tensor.video import VideoTensorFlowTensor + LOCAL_VIDEO_FILE = str(TOYDATA_DIR / 'mov_bbb.mp4') REMOTE_VIDEO_FILE = 'https://github.com/docarray/docarray/blob/feat-rewrite-v2/tests/toydata/mov_bbb.mp4?raw=true' # noqa: E501 @@ -80,6 +87,25 @@ class MyVideoDoc(BaseDocument): assert isinstance(doc.tensor, VideoTorchTensor) +@pytest.mark.tensorflow +@pytest.mark.slow +@pytest.mark.internet +@pytest.mark.parametrize( + 'file_url', + [LOCAL_VIDEO_FILE, REMOTE_VIDEO_FILE], +) +def test_load_video_url_to_video_tensorflow_tensor_field(file_url): + class MyVideoDoc(BaseDocument): + video_url: VideoUrl + tensor: Optional[VideoTensorFlowTensor] + + doc = MyVideoDoc(video_url=file_url) + doc.tensor = doc.video_url.load().video + + assert isinstance(doc.tensor, VideoTensorFlowTensor) + assert isinstance(doc.tensor.tensor, tf.Tensor) + + def test_json_schema(): schema_json_of(VideoUrl) diff --git a/tests/units/util/test_filter.py b/tests/units/util/test_filter.py index 8b070c2fa64..ccce5a6eb67 100644 --- a/tests/units/util/test_filter.py +++ b/tests/units/util/test_filter.py @@ -1,7 +1,8 @@ -import pytest import json +from typing import Any, Dict, List, Optional + +import pytest -from typing import Optional, List, Dict, Any from docarray import BaseDocument, DocumentArray from docarray.documents import Image, Text from docarray.utils.filter import filter @@ -59,9 +60,9 @@ def test_empty_filter(docs, dict_api): @pytest.mark.parametrize('dict_api', [True, False]) def test_simple_filter(docs, dict_api): if dict_api: - method = lambda query: filter(docs, query) + method = lambda query: filter(docs, query) # noqa: E731 else: - method = lambda query: filter(docs, json.dumps(query)) + method = lambda query: filter(docs, json.dumps(query)) # noqa: E731 result = method({'text': {'$eq': 'Text of Document 1'}}) assert len(result) == 1 @@ -128,9 +129,9 @@ def test_simple_filter(docs, dict_api): @pytest.mark.parametrize('dict_api', [True, False]) def test_nested_filter(docs, dict_api): if dict_api: - method = lambda query: filter(docs, query) + method = lambda query: filter(docs, query) # noqa: E731 else: - method = lambda query: filter(docs, json.dumps(query)) + method = lambda query: filter(docs, json.dumps(query)) # noqa: E731 result = method({'dictionary.a': {'$eq': 0}}) assert len(result) == 2 @@ -157,9 +158,9 @@ def test_nested_filter(docs, dict_api): @pytest.mark.parametrize('dict_api', [True, False]) def test_array_simple_filters(docs, dict_api): if dict_api: - method = lambda query: filter(docs, query) + method = lambda query: filter(docs, query) # noqa: E731 else: - method = lambda query: filter(docs, json.dumps(query)) + method = lambda query: filter(docs, json.dumps(query)) # noqa: E731 # SIZE DOES NOT SEEM TO WORK result = method({'sub_docs': {'$size': 2}}) @@ -179,9 +180,9 @@ def test_placehold_filter(dict_api): ) if dict_api: - method = lambda query: filter(docs, query) + method = lambda query: filter(docs, query) # noqa: E731 else: - method = lambda query: filter(docs, json.dumps(query)) + method = lambda query: filter(docs, json.dumps(query)) # noqa: E731 # DOES NOT SEEM TO WORK result = method({'text': {'$eq': '{text_doc}'}}) @@ -194,9 +195,9 @@ def test_placehold_filter(dict_api): @pytest.mark.parametrize('dict_api', [True, False]) def test_logic_filter(docs, dict_api): if dict_api: - method = lambda query: filter(docs, query) + method = lambda query: filter(docs, query) # noqa: E731 else: - method = lambda query: filter(docs, json.dumps(query)) + method = lambda query: filter(docs, json.dumps(query)) # noqa: E731 result = method( { '$or': { @@ -275,9 +276,9 @@ class MyDocument(BaseDocument): } if dict_api: - method = lambda query: filter(docs, query) + method = lambda query: filter(docs, query) # noqa: E731 else: - method = lambda query: filter(docs, json.dumps(query)) + method = lambda query: filter(docs, json.dumps(query)) # noqa: E731 results = method(query) assert len(results) == 1 diff --git a/tests/units/util/test_reduce.py b/tests/units/util/test_reduce.py index 7e82ddf181c..6a02adbd8cc 100644 --- a/tests/units/util/test_reduce.py +++ b/tests/units/util/test_reduce.py @@ -1,5 +1,7 @@ +from typing import Dict, List, Optional, Set + import pytest -from typing import Optional, List, Dict, Set + from docarray import BaseDocument, DocumentArray from docarray.documents import Image from docarray.utils.reduce import reduce, reduce_all @@ -7,7 +9,7 @@ class InnerDoc(BaseDocument): integer: int - l: List + inner_list: List class MMDoc(BaseDocument): @@ -34,7 +36,7 @@ def doc1(): [MMDoc(id='a', matches=DocumentArray[MMDoc]([MMDoc()]))] ), test_set={'a', 'a'}, - inner_doc=InnerDoc(integer=2, l=['c', 'd']), + inner_doc=InnerDoc(integer=2, inner_list=['c', 'd']), test_dict={'a': 0, 'b': 2, 'd': 4, 'z': 3}, ) @@ -52,7 +54,7 @@ def doc2(doc1): [MMDoc(id='a', matches=DocumentArray[MMDoc]([MMDoc()]))] ), test_set={'a', 'b'}, - inner_doc=InnerDoc(integer=3, l=['a', 'b']), + inner_doc=InnerDoc(integer=3, inner_list=['a', 'b']), test_dict={'a': 10, 'b': 10, 'c': 3, 'z': None}, ) @@ -83,7 +85,7 @@ def test_reduce(doc1, doc2): assert len(merged_doc.matches_with_same_id) == 1 assert len(merged_doc.matches_with_same_id[0].matches) == 2 assert merged_doc.inner_doc.integer == 3 - assert merged_doc.inner_doc.l == ['c', 'd', 'a', 'b'] + assert merged_doc.inner_doc.inner_list == ['c', 'd', 'a', 'b'] def test_reduce_all(doc1, doc2): @@ -117,4 +119,4 @@ def test_reduce_all(doc1, doc2): assert len(merged_doc.matches_with_same_id) == 1 assert len(merged_doc.matches_with_same_id[0].matches) == 2 assert merged_doc.inner_doc.integer == 3 - assert merged_doc.inner_doc.l == ['c', 'd', 'a', 'b', 'c', 'd', 'a', 'b'] + assert merged_doc.inner_doc.inner_list == ['c', 'd', 'a', 'b', 'c', 'd', 'a', 'b'] diff --git a/tests/units/util/test_typing.py b/tests/units/util/test_typing.py index 66eb135d7ff..2db742522f5 100644 --- a/tests/units/util/test_typing.py +++ b/tests/units/util/test_typing.py @@ -5,10 +5,12 @@ from docarray.typing import NdArray, TorchTensor from docarray.typing.tensor.abstract_tensor import AbstractTensor from docarray.utils._typing import is_tensor_union, is_type_tensor +from docarray.utils.misc import is_tf_available -try: +tf_available = is_tf_available() +if tf_available: from docarray.typing import TensorFlowTensor -except (ImportError, TypeError): +else: TensorFlowTensor = None