def _tensorize()

in src/datasets/formatting/tf_formatter.py [0:0]

• 22 lines of code
• 15 McCabe index (conditional complexity)

    def _tensorize(self, value):
        import tensorflow as tf

        if value is None:
            return value

        default_dtype = {}

        if isinstance(value, (np.number, np.ndarray)) and np.issubdtype(value.dtype, np.integer):
            default_dtype = {"dtype": tf.int64}
        elif isinstance(value, (np.number, np.ndarray)) and np.issubdtype(value.dtype, np.floating):
            default_dtype = {"dtype": tf.float32}

        if config.PIL_AVAILABLE and "PIL" in sys.modules:
            import PIL.Image

            if isinstance(value, PIL.Image.Image):
                value = np.asarray(value)
        if config.TORCHVISION_AVAILABLE and "torchvision" in sys.modules:
            from torchvision.io import VideoReader

            if isinstance(value, VideoReader):
                return value  # TODO(QL): set output to tf tensors ?
        if config.TORCHCODEC_AVAILABLE and "torchcodec" in sys.modules:
            from torchcodec.decoders import AudioDecoder, VideoDecoder

            if isinstance(value, (VideoDecoder, AudioDecoder)):
                return value  # TODO(QL): set output to jax arrays ?

        return tf.convert_to_tensor(value, **{**default_dtype, **self.tf_tensor_kwargs})