class_docstr: FFmpegIOTensor
class_docstr_tok: ["FFmpegIOTensor"]
code: def __init__(self, filename, internal=False):
      with tf.name_scope("FFmpegIOTensor") as scope:
          from tensorflow_io.python.ops import (  # pylint: disable=import-outside-toplevel
              ffmpeg_ops,
          )
  
          resource, columns = ffmpeg_ops.io_ffmpeg_readable_init(
              filename,
              container=scope,
              shared_name=f"{filename}/{uuid.uuid4().hex}",
          )
          columns = [
              column.decode() for column in columns.numpy().tolist()
          ]
          elements = []
          for column in columns:
              shape, dtype, rate = ffmpeg_ops.io_ffmpeg_readable_spec(
                  resource, column
              )
              shape = tf.TensorShape(
                  [None if e < 0 else e for e in shape.numpy()]
              )
              dtype = tf.as_dtype(dtype.numpy())
              spec = tf.TensorSpec(shape, dtype, column)
              capacity = 1 if column.startswith("v:") else 4096
              function = _FFmpegIOTensorFunction(
                  ffmpeg_ops.io_ffmpeg_readable_read,
                  resource,
                  column,
                  shape,
                  dtype,
                  capacity=capacity,
              )
              function = io_tensor_ops._IOTensorIterablePartitionedFunction(  # pylint: disable=protected-access
                  function, shape
              )
              if column.startswith("v:"):
                  elements.append(
                      FFmpegVideoIOTensor(
                          spec, function, internal=internal
                      )
                  )
              elif column.startswith("a:"):
                  rate = rate.numpy()
                  elements.append(
                      FFmpegAudioIOTensor(
                          spec, function, rate, internal=internal
                      )
                  )
              else:
                  elements.append(
                      FFmpegSubtitleIOTensor(
                          spec, function, internal=internal
                      )
                  )
          spec = tuple(e.spec for e in elements)
          super().__init__(spec, columns, elements, internal=internal)
  
file_path: io/tensorflow_io/python/ops/ffmpeg_io_tensor_ops.py
imports: import uuid
  import tensorflow
  from tensorflow_io.python.ops import io_tensor_ops
label_desc: Use image node_id 1 to create a new FFmpegIOTensor object from inherited base classes: io_tensor_ops with example: obj = FFmpegIOTensor(filename, internal)