C4 W3 A1: Error in Tf function

def yolo_filter_boxes(boxes, box_confidence, box_class_probs, threshold = .6):
mentor edit: code removed


TypeError Traceback (most recent call last)
4 boxes = tf.random.normal([19, 19, 5, 4], mean=1, stddev=4, seed = 1)
5 box_class_probs = tf.random.normal([19, 19, 5, 80], mean=1, stddev=4, seed = 1)
----> 6 scores, boxes, classes = yolo_filter_boxes(boxes, box_confidence, box_class_probs, threshold = 0.5)
7 print("scores[2] = " + str(scores[2].numpy()))
8 print("boxes[2] = " + str(boxes[2].numpy()))

in yolo_filter_boxes(boxes, box_confidence, box_class_probs, threshold)
36 # same dimension as box_class_scores, and be True for the boxes you want to keep (with probability >= threshold)
37 ## (≈ 1 line)
—> 38 filtering_mask =(box_class_scores >= threshold)
40 # Step 4: Apply the mask to box_class_scores, boxes and box_classes

/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/gen_math_ops.py in greater_equal(x, y, name)
4053 _result = pywrap_tfe.TFE_Py_FastPathExecute(
4054 _ctx._context_handle, tld.device_name, “GreaterEqual”, name,
→ 4055 tld.op_callbacks, x, y)
4056 return _result
4057 except _core._NotOkStatusException as e:

TypeError: Cannot convert 0.5 to EagerTensor of dtype int64

Hii @Sanchay12,

I have moved this post to the DLS Course 4 category as other learners taking the same course might benefit from this.

Kindly make sure if you have any course-specific queries, explore the specialization category and post in the relevant course subcategory as course-specific mentors are actively answering the queries there. The General Discussions category is not monitored by our mentors.

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Happy Learning!!

There seems to be an error in your code for the box class scores.

is it something to do with reduce_max()?

I do not know for certain.

Yes, there is a problem in reduce_max(). The argument should be box_scores with axis = -1.