can not print the value of each tensor inside a transformation function for tf.dataset

Question

I am learning the tensorflow which version is 2.8.0 on my MacBook M1. I am learning COCO dataset, and extracting the data from TFRecordDataset for watching data detail.So, I want to debug or print the data value in the open_image function.

class DatasetTransformer:
    def __init__(self, config):
        self.INCLUDE_MASK = config.INCLUDE_MASK
        self.LABEL_HEIGHT = config.LABEL_HEIGHT
        self.LABEL_WIDTH = config.LABEL_WIDTH
        self.IMAGE_SIZE = config.IMAGE_SIZE

        self.PAF_GAUSSIAN_SIGMA_SQ = config.PAF_GAUSSIAN_SIGMA_SQ
        self.KPT_HEATMAP_GAUSSIAN_SIGMA_SQ = config.KPT_HEATMAP_GAUSSIAN_SIGMA_SQ

        self.PAF_NUM_FILTERS = config.PAF_NUM_FILTERS
        self.HEATMAP_NUM_FILTERS = config.HEATMAP_NUM_FILTERS

        self.JOINTS_DEF = config.JOINTS_DEF
        self.JOINTS_SIDES = config.JOINTS_SIDES
        self.KEYPOINTS_SIDES = config.KEYPOINTS_SIDES

        self.CONTRAST_RANGE = config.CONTRAST_RANGE
        self.BRIGHTNESS_RANGE = config.BRIGHTNESS_RANGE
        self.HUE_RANGE = config.HUE_RANGE
        self.SATURATION_RANGE = config.SATURATION_RANGE

        # for parsing TFrecords files
        self.feature_description = {
                'id'       : tf.io.FixedLenFeature([1], tf.int64),
                'image_raw': tf.io.FixedLenFeature([], tf.string),
                'size'     : tf.io.FixedLenFeature([2], tf.int64),
                'kpts'     : tf.io.FixedLenFeature([], tf.string),
                'joints'   : tf.io.FixedLenFeature([], tf.string),
                'mask'     : tf.io.FixedLenFeature([], tf.string)
                }



    def read_tfrecord(self, serialized_example):

        parsed = tf.io.parse_single_example(serialized_example, self.feature_description)
        idd = parsed['id']
        image_raw = parsed['image_raw']
        size = parsed['size']

        kpts = tf.io.parse_tensor(parsed['kpts'], tf.float32)
        joints = tf.io.parse_tensor(parsed['joints'], tf.float32)
        mask = tf.io.parse_tensor(parsed['mask'], tf.float32)
        mask = tf.ensure_shape(mask, ([self.LABEL_HEIGHT, self.LABEL_WIDTH]))
        mask = tf.expand_dims(mask, axis=-1)  # required to concat

        kpts = tf.RaggedTensor.from_tensor(kpts)
        joints = tf.RaggedTensor.from_tensor(joints)

        return {"id": idd, "image_raw": image_raw, "size": size, "kpts": kpts, "joints": joints, "mask": mask}


    def open_image(self, elem):

        image_raw = elem["image_raw"]
        image = tf.image.decode_jpeg(image_raw, channels=3)
        image = tf.image.convert_image_dtype(image, dtype=tf.float32)
        image = tf.image.resize(image, self.IMAGE_SIZE)

        new_elem = {}
        new_elem.update(elem)
        new_elem.pop("image_raw")

        new_elem["image"] = image

        print("debug:", new_elem["image"])


        return new_elem


def build_training_ds(tfrecord_filenames: list, config) -> tf.data.Dataset:
    dataset_transformer = DatasetTransformer(config)
    ds = tf.data.TFRecordDataset(tfrecord_filenames)
    ds = ds.map(dataset_transformer.read_tfrecord, num_parallel_calls=tf.data.experimental.AUTOTUNE)
    ds = ds.map(dataset_transformer.open_image, num_parallel_calls=tf.data.experimental.AUTOTUNE)

    return ds



dst = build_training_ds(tfrecord_files_train, cfg)

According to the print sentence in the open_image function above, it just give the output as below:

debug: Tensor("resize/Squeeze:0", shape=(368, 368, 3), dtype=float32)

Is that an output about an autograph? I want to print every tensor value in each ds.map iteration for debugging. Is there any way to solve it?

update: I have checked other questions, and someone suggested using tf.py_function, but I have no idea which data type to specify.

Answer 1

I figured a way to do it was like this

  function dot_click(e:InteractionEvent){
    for( i in 0...current_dots.length){
      if(current_dots[i] == e.currentTarget) {
         trace("Clicked")
      }
      
    }
  }

had to pass the interactive parameter