Iterating over a symbolic tf.Tensor is not allowed: AutoGraph did convert this function

[saturn-drm]

Issue type

Bug

Have you reproduced the bug with TensorFlow Nightly?

No

Source

source

TensorFlow version

tf 2.9

Custom code

Yes

OS platform and distribution

Linux Ubuntu 22.04

Mobile device

No response

Python version

No response

Bazel version

No response

GCC/compiler version

No response

CUDA/cuDNN version

No response

GPU model and memory

No response

Current behavior?

I have a function as below. I have N = tf.shape(y_true)[0] where y_ture is <tf.Tensor 'y_true:0' shape=(None, 8, 6) dtype=float32>. I later iterate over N as for i in tf.range(N), but get an error.

def transform_targets_for_output(y_true, grid_size, anchor_idxs):
    # y_true: (N, boxes, (x1, y1, x2, y2, class, best_anchor))
    print('y-true',y_true)
    N = tf.shape(y_true)[0]
    print('%%%',N)

    # y_true_out: (N, grid, grid, anchors, [x1, y1, x2, y2, obj, class])
    y_true_out = tf.zeros(
        (N, grid_size, grid_size, tf.shape(anchor_idxs)[0], 6))

    anchor_idxs = tf.cast(anchor_idxs, tf.int32)

    indexes = tf.TensorArray(tf.int32, 1, dynamic_size=True)
    updates = tf.TensorArray(tf.float32, 1, dynamic_size=True)
    idx = 0
    for i in tf.range(N):
        for j in tf.range(tf.shape(y_true)[1]):
            if tf.equal(y_true[i][j][2], 0):
                continue
            anchor_eq = tf.equal(
                anchor_idxs, tf.cast(y_true[i][j][5], tf.int32))

            if tf.reduce_any(anchor_eq):
                box = y_true[i][j][0:4]
                box_xy = (y_true[i][j][0:2] + y_true[i][j][2:4]) / 2

                anchor_idx = tf.cast(tf.where(anchor_eq), tf.int32)
                grid_xy = tf.cast(box_xy // (1/grid_size), tf.int32)

                # grid[y][x][anchor] = (tx, ty, bw, bh, obj, class)
                indexes = indexes.write(
                    idx, [i, grid_xy[1], grid_xy[0], anchor_idx[0][0]])
                updates = updates.write(
                    idx, [box[0], box[1], box[2], box[3], 1, y_true[i][j][4]])
                idx += 1

    # tf.print(indexes.stack())
    # tf.print(updates.stack())

    return tf.tensor_scatter_nd_update(
        y_true_out, indexes.stack(), updates.stack())

But I get error like this:

raise e.with_traceback(filtered_tb) from None
  File "/home/shakey/yolov3-tf2/yolov3_tf2/dataset.py", line 42, in transform_targets_for_output
    for i in tf.range(N):
tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError: Iterating over a symbolic `tf.Tensor` is not allowed: AutoGraph did convert this function. This might indicate you are trying to use an unsupported feature.

How can I solve that?

Standalone code to reproduce the issue

nothing.

Relevant log output

No response

[Venkat6871]

Hi @saturn-drm ,

• Sorry for the delay, I tried to run your code on colab using TF v2.9, 2.16.1 and i am not facing any issue. Please find the gist here for reference.
• And it looks like you are using an older Version of Tensorflow (2.9). Many bugs have been fixed in the latest version. Can you please execute your code using Latest Version (2.16.1) and let us know if the issue still persists?

Thank you!

[saturn-drm]

Thank you for the reply. I will try it out as you recommended.

[google-ml-butler]

Are you satisfied with the resolution of your issue?
Yes
No