Hi,
I am trying to train the ObjectDetection ML model from OOB models, but I’m getting the error, have checked all the documentations, community forums but could not find any solution for that, please help to resolve the same.
Error:
File “/microservice/yolov3/utils.py”, line 104, in load_yolo_weights conv_layer = model.get_layer(conv_layer_name) File “/home/aicenter/.local/lib/python3.8/site-packages/keras/engine/training.py”, line 2828, in get_layer raise ValueError(f’No such layer: {name}. Existing layers are: ’ ValueError: No such layer: conv2d_75. Existing layers are: [‘input_1’, ‘conv2d’, ‘batch_normalization’, ‘leaky_re_lu’, ‘zero_padding2d’, ‘conv2d_1’, ‘batch_normalization_1’, ‘leaky_re_lu_1’, ‘conv2d_2’, ‘batch_normalization_2’, ‘leaky_re_lu_2’, ‘conv2d_3’, ‘batch_normalization_3’, ‘leaky_re_lu_3’, ‘tf.operators.add’, ‘zero_padding2d_1’, ‘conv2d_4’, ‘batch_normalization_4’, ‘leaky_re_lu_4’, ‘conv2d_5’, ‘batch_normalization_5’, ‘leaky_re_lu_5’, ‘conv2d_6’, ‘batch_normalization_6’, ‘leaky_re_lu_6’, ‘tf.operators.add_1’, ‘conv2d_7’, ‘batch_normalization_7’, ‘leaky_re_lu_7’, ‘conv2d_8’, ‘batch_normalization_8’, ‘leaky_re_lu_8’, ‘tf.operators.add_2’, ‘zero_padding2d_2’, ‘conv2d_9’, ‘batch_normalization_9’, ‘leaky_re_lu_9’, ‘conv2d_10’, ‘batch_normalization_10’, ‘leaky_re_lu_10’, ‘conv2d_11’, ‘batch_normalization_11’, ‘leaky_re_lu_11’, ‘tf.operators.add_3’, ‘conv2d_12’, ‘batch_normalization_12’, ‘leaky_re_lu_12’, ‘conv2d_13’, ‘batch_normalization_13’, ‘leaky_re_lu_13’, ‘tf.operators.add_4’, ‘conv2d_14’, ‘batch_normalization_14’, ‘leaky_re_lu_14’, ‘conv2d_15’, ‘batch_normalization_15’, ‘leaky_re_lu_15’, ‘tf.operators.add_5’, ‘conv2d_16’, ‘batch_normalization_16’, ‘leaky_re_lu_16’, ‘conv2d_17’, ‘batch_normalization_17’, ‘leaky_re_lu_17’, ‘tf.operators.add_6’, ‘conv2d_18’, ‘batch_normalization_18’, ‘leaky_re_lu_18’, ‘conv2d_19’, ‘batch_normalization_19’, ‘leaky_re_lu_19’, ‘tf.operators.add_7’, ‘conv2d_20’, ‘batch_normalization_20’, ‘leaky_re_lu_20’, ‘conv2d_21’, ‘batch_normalization_21’, ‘leaky_re_lu_21’, ‘tf.operators.add_8’, ‘conv2d_22’, ‘batch_normalization_22’, ‘leaky_re_lu_22’, ‘conv2d_23’, ‘batch_normalization_23’, ‘leaky_re_lu_23’, ‘tf.operators.add_9’, ‘conv2d_24’, ‘batch_normalization_24’, ‘leaky_re_lu_24’, ‘conv2d_25’, ‘batch_normalization_25’, ‘leaky_re_lu_25’, ‘tf.operators.add_10’, ‘zero_padding2d_3’, ‘conv2d_26’, ‘batch_normalization_26’, ‘leaky_re_lu_26’, ‘conv2d_27’, ‘batch_normalization_27’, ‘leaky_re_lu_27’, ‘conv2d_28’, ‘batch_normalization_28’, ‘leaky_re_lu_28’, ‘tf.operators.add_11’, ‘conv2d_29’, ‘batch_normalization_29’, ‘leaky_re_lu_29’, ‘conv2d_30’, ‘batch_normalization_30’, ‘leaky_re_lu_30’, ‘tf.operators.add_12’, ‘conv2d_31’, ‘batch_normalization_31’, ‘leaky_re_lu_31’, ‘conv2d_32’, ‘batch_normalization_32’, ‘leaky_re_lu_32’, ‘tf.operators.add_13’, ‘conv2d_33’, ‘batch_normalization_33’, ‘leaky_re_lu_33’, ‘conv2d_34’, ‘batch_normalization_34’, ‘leaky_re_lu_34’, ‘tf.operators.add_14’, ‘conv2d_35’, ‘batch_normalization_35’, ‘leaky_re_lu_35’, ‘conv2d_36’, ‘batch_normalization_36’, ‘leaky_re_lu_36’, ‘tf.operators.add_15’, ‘conv2d_37’, ‘batch_normalization_37’, ‘leaky_re_lu_37’, ‘conv2d_38’, ‘batch_normalization_38’, ‘leaky_re_lu_38’, ‘tf.operators.add_16’, ‘conv2d_39’, ‘batch_normalization_39’, ‘leaky_re_lu_39’, ‘conv2d_40’, ‘batch_normalization_40’, ‘leaky_re_lu_40’, ‘tf.operators.add_17’, ‘conv2d_41’, ‘batch_normalization_41’, ‘leaky_re_lu_41’, ‘conv2d_42’, ‘batch_normalization_42’, ‘leaky_re_lu_42’, ‘tf.operators.add_18’, ‘zero_padding2d_4’, ‘conv2d_43’, ‘batch_normalization_43’, ‘leaky_re_lu_43’, ‘conv2d_44’, ‘batch_normalization_44’, ‘leaky_re_lu_44’, ‘conv2d_45’, ‘batch_normalization_45’, ‘leaky_re_lu_45’, ‘tf.operators.add_19’, ‘conv2d_46’, ‘batch_normalization_46’, ‘leaky_re_lu_46’, ‘conv2d_47’, ‘batch_normalization_47’, ‘leaky_re_lu_47’, ‘tf.operators.add_20’, ‘conv2d_48’, ‘batch_normalization_48’, ‘leaky_re_lu_48’, ‘conv2d_49’, ‘batch_normalization_49’, ‘leaky_re_lu_49’, ‘tf.operators.add_21’, ‘conv2d_50’, ‘batch_normalization_50’, ‘leaky_re_lu_50’, ‘conv2d_51’, ‘batch_normalization_51’, ‘leaky_re_lu_51’, ‘tf.operators.add_22’, ‘conv2d_52’, ‘batch_normalization_52’, ‘leaky_re_lu_52’, ‘conv2d_53’, ‘batch_normalization_53’, ‘leaky_re_lu_53’, ‘conv2d_54’, ‘batch_normalization_54’, ‘leaky_re_lu_54’, ‘conv2d_55’, ‘batch_normalization_55’, ‘leaky_re_lu_55’, ‘conv2d_56’, ‘batch_normalization_56’, ‘leaky_re_lu_56’, ‘conv2d_59’, ‘batch_normalization_58’, ‘leaky_re_lu_58’, ‘tf.image.resize’, ‘tf.concat’, ‘conv2d_60’, ‘batch_normalization_59’, ‘leaky_re_lu_59’, ‘conv2d_61’, ‘batch_normalization_60’, ‘leaky_re_lu_60’, ‘conv2d_62’, ‘batch_normalization_61’, ‘leaky_re_lu_61’, ‘conv2d_63’, ‘batch_normalization_62’, ‘leaky_re_lu_62’, ‘conv2d_64’, ‘batch_normalization_63’, ‘leaky_re_lu_63’, ‘conv2d_67’, ‘batch_normalization_65’, ‘leaky_re_lu_65’, ‘tf.image.resize_1’, ‘tf.concat_1’, ‘conv2d_68’, ‘batch_normalization_66’, ‘leaky_re_lu_66’, ‘conv2d_69’, ‘batch_normalization_67’, ‘leaky_re_lu_67’, ‘conv2d_70’, ‘batch_normalization_68’, ‘leaky_re_lu_68’, ‘conv2d_71’, ‘batch_normalization_69’, ‘leaky_re_lu_69’, ‘conv2d_72’, ‘batch_normalization_70’, ‘leaky_re_lu_70’, ‘conv2d_73’, ‘conv2d_65’, ‘conv2d_57’, ‘batch_normalization_71’, ‘batch_normalization_64’, ‘batch_normalization_57’, ‘leaky_re_lu_71’, ‘leaky_re_lu_64’, ‘leaky_re_lu_57’, ‘conv2d_74’, ‘conv2d_66’, ‘conv2d_58’, ‘tf.compat.v1.shape’, ‘tf.compat.v1.shape_1’, ‘tf.compat.v1.shape_2’, ‘tf.operators.getitem_1’, ‘tf.operators.getitem_10’, ‘tf.operators.getitem_19’, ‘tf.range_1’, ‘tf.range’, ‘tf.range_3’, ‘tf.range_2’, ‘tf.range_5’, ‘tf.range_4’, ‘tf.expand_dims_1’, ‘tf.expand_dims’, ‘tf.expand_dims_3’, ‘tf.expand_dims_2’, ‘tf.expand_dims_5’, ‘tf.expand_dims_4’, ‘tf.tile_1’, ‘tf.tile’, ‘tf.tile_4’, ‘tf.tile_3’, ‘tf.tile_7’, ‘tf.tile_6’, ‘tf.operators.getitem_6’, ‘tf.operators.getitem_7’, ‘tf.operators.getitem_15’, ‘tf.operators.getitem_16’, ‘tf.operators.getitem_24’, ‘tf.operators.getitem_25’, ‘tf.operators.getitem’, ‘tf.concat_2’, ‘tf.operators.getitem_9’, ‘tf.concat_5’, ‘tf.operators.getitem_18’, ‘tf.concat_8’, ‘tf.reshape’, ‘tf.operators.getitem_8’, ‘tf.reshape_1’, ‘tf.operators.getitem_17’, ‘tf.reshape_2’, ‘tf.operators.getitem_26’, ‘tf.operators.getitem_2’, ‘tf.tile_2’, ‘tf.operators.getitem_3’, ‘tf.operators.getitem_11’, ‘tf.tile_5’, ‘tf.operators.getitem_12’, ‘tf.operators.getitem_20’, ‘tf.tile_8’, ‘tf.operators.getitem_21’, ‘tf.math.sigmoid’, ‘tf.cast’, ‘tf.math.exp’, ‘tf.math.sigmoid_3’, ‘tf.cast_1’, ‘tf.math.exp_1’, ‘tf.math.sigmoid_6’, ‘tf.cast_2’, ‘tf.math.exp_2’, ‘tf.operators.add_23’, ‘tf.math.multiply_1’, ‘tf.operators.add_24’, ‘tf.math.multiply_4’, ‘tf.operators.add_25’, ‘tf.math.multiply_7’, ‘tf.math.multiply’, ‘tf.math.multiply_2’, ‘tf.operators.getitem_4’, ‘tf.operators.getitem_5’, ‘tf.math.multiply_3’, ‘tf.math.multiply_5’, ‘tf.operators.getitem_13’, ‘tf.operators.getitem_14’, ‘tf.math.multiply_6’, ‘tf.math.multiply_8’, ‘tf.operators.getitem_22’, ‘tf.operators.getitem_23’, ‘tf.concat_3’, ‘tf.math.sigmoid_1’, ‘tf.math.sigmoid_2’, ‘tf.concat_6’, ‘tf.math.sigmoid_4’, ‘tf.math.sigmoid_5’, ‘tf.concat_9’, ‘tf.math.sigmoid_7’, ‘tf.math.sigmoid_8’, ‘tf.concat_4’, ‘tf.concat_7’, ‘tf.concat_10’]. 2023-12-01 07:14:48,509 - UiPath_core.trainer_run:main:107 - INFO: Job run stopped.
Yoichi
Gautham_Pattabiraman
Anil_G
lrtetala
ashokkarale
Angel_Meseguer_piqueras
FINNNNNNNN
kardelencihangir
ayumi.ouchi
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