Training is finished!
Exporting model...
Traceback (most recent call last):
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\train.py", line 382, in
main(args)
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\train.py", line 374, in main
model = Yolov4(args, training=False)
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\model\yolov4.py", line 11, in Yolov4
scaled_yolov4_csp_darknet53_outputs = scaled_yolov4_csp_darknet53(input,mode=args.model_type)
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\model\CSPDarknet53.py", line 35, in scaled_yolov4_csp_darknet53
x = conv2d_bn_mish(x, 32, (3, 3), name="first_block")
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\model\common.py", line 7, in conv2d_bn_mish
return x tf.math.tanh(tf.math.softplus(x))
File "C:\TensorFlowObjectDetection\TFODCourse\tfod\lib\site-packages\tensorflow\python\util\traceback_utils.py", line 153, in error_handler
raise e.with_traceback(filtered_tb) from None
File "C:\TensorFlowObjectDetection\TFODCourse\tfod\lib\site-packages\keras\layers\core\tf_op_layer.py", line 119, in handle
return TFOpLambda(op)(args, **kwargs)
File "C:\TensorFlowObjectDetection\TFODCourse\tfod\lib\site-packages\keras\utils\traceback_utils.py", line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
OverflowError: Exception encountered when calling layer "tf.math.softplus" (type TFOpLambda).
Python int too large to convert to C long
Call arguments received by layer "tf.math.softplus" (type TFOpLambda):
• features=tf.Tensor(shape=(None, None, None, 32), dtype=float32)
• name=None
I still have the checkpoints saved and a temp_model_variables.h5 has been created but I am unable to convert these into a saved model.
Hi,
I am seeing the following error:
Training is finished! Exporting model... Traceback (most recent call last): File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\train.py", line 382, in
main(args)
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\train.py", line 374, in main
model = Yolov4(args, training=False)
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\model\yolov4.py", line 11, in Yolov4
scaled_yolov4_csp_darknet53_outputs = scaled_yolov4_csp_darknet53(input,mode=args.model_type)
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\model\CSPDarknet53.py", line 35, in scaled_yolov4_csp_darknet53
x = conv2d_bn_mish(x, 32, (3, 3), name="first_block")
File "C:\TensorFlowObjectDetection\TFODCourse\Scaled_YOLOv4_tf2\model\common.py", line 7, in conv2d_bn_mish
return x tf.math.tanh(tf.math.softplus(x))
File "C:\TensorFlowObjectDetection\TFODCourse\tfod\lib\site-packages\tensorflow\python\util\traceback_utils.py", line 153, in error_handler
raise e.with_traceback(filtered_tb) from None
File "C:\TensorFlowObjectDetection\TFODCourse\tfod\lib\site-packages\keras\layers\core\tf_op_layer.py", line 119, in handle
return TFOpLambda(op)(args, **kwargs)
File "C:\TensorFlowObjectDetection\TFODCourse\tfod\lib\site-packages\keras\utils\traceback_utils.py", line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
OverflowError: Exception encountered when calling layer "tf.math.softplus" (type TFOpLambda).
Python int too large to convert to C long
Call arguments received by layer "tf.math.softplus" (type TFOpLambda): • features=tf.Tensor(shape=(None, None, None, 32), dtype=float32) • name=None
I still have the checkpoints saved and a temp_model_variables.h5 has been created but I am unable to convert these into a saved model.
Any advice?