使用tensorflow-1.5++多版本尝试过，与tensorflow-1.４ＡＰＩ不兼容（问题）
此错误搞了大半天，翻看了很多很多文章，头痛。。
ValueError: Tried to convert 't' to a tensor and failed. Error: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].
执行检测任务：
raini@biyuzhe:~/pro/tf_models/models/research$ CUDA_VISIBLE_DEVICES="" python object_detection/train.py \
> --logtostderr \
> --pipeline_config_path=/home/raini/pro/tf_models/byz/pet_test/pipeline.config \
> --train_dir=/media/raini/deepin/byz/dataset/pet-record
得到错误：
＃（condition, x, y）是我打印出来观察的，最后一个结果即报错的地方
/home/raini/app/anoconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from ._conv import register_converters as _register_converters WARNING:tensorflow:From /home/raini/pro/tf_models/models/research/object_detection/trainer.py:260: create_global_step (from tensorflow.contrib.framework.python.ops.variables) is deprecated and will be removed in a future version. Instructions for updating: Please switch to tf.train.create_global_step WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards. INFO:tensorflow:Scale of 0 disables regularizer. INFO:tensorflow:Scale of 0 disables regularizer. INFO:tensorflow:Scale of 0 disables regularizer. INFO:tensorflow:depth of additional conv before box predictor: 0 ========condition Tensor("Compare/IOU/Equal:0", shape=(?, ?), dtype=bool, device=/device:GPU:0) ========x Tensor("Compare/IOU/zeros_like:0", shape=(?, ?), dtype=float32, device=/device:GPU:0) ========y Tensor("Compare/IOU/truediv:0", shape=(?, ?), dtype=float32, device=/device:GPU:0) ========condition Tensor("GreaterEqual:0", shape=(?,), dtype=bool, device=/device:GPU:0) ========x Tensor("Encode/transpose:0", shape=(?, 4), dtype=float32, device=/device:GPU:0) ========y Tensor("Tile_3:0", shape=(?, 4), dtype=float32, device=/device:GPU:0) INFO:tensorflow:Scale of 0 disables regularizer. WARNING:tensorflow:From /home/raini/pro/tf_models/models/research/object_detection/core/box_predictor.py:407: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead INFO:tensorflow:Scale of 0 disables regularizer. ========condition Tensor("Loss/RPNLoss/Compare/IOU/Equal:0", shape=(?, ?), dtype=bool, device=/device:GPU:0) ========x Tensor("Loss/RPNLoss/Compare/IOU/zeros_like:0", shape=(?, ?), dtype=float32, device=/device:GPU:0) ========y Tensor("Loss/RPNLoss/Compare/IOU/truediv:0", shape=(?, ?), dtype=float32, device=/device:GPU:0) ========condition Tensor("Loss/RPNLoss/Match/cond/Cast_2:0", shape=(?,), dtype=bool, device=/device:GPU:0) ========x Tensor("Loss/RPNLoss/Match/cond/ArgMax_2:0", shape=(?,), dtype=int32, device=/device:GPU:0) ========y Tensor("Loss/RPNLoss/Match/cond/Add_1:0", shape=(?,), dtype=int32, device=/device:GPU:0) ========condition Tensor("Loss/RPNLoss/GreaterEqual:0", shape=(?,), dtype=bool, device=/device:GPU:0) ========x Tensor("Loss/RPNLoss/Encode/transpose:0", shape=(?, 4), dtype=float32, device=/device:GPU:0) ========y Tensor("Loss/RPNLoss/Tile:0", shape=(?, 4), dtype=float32, device=/device:GPU:0) WARNING:tensorflow:From /home/raini/pro/tf_models/models/research/object_detection/core/losses.py:317: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version. Instructions for updating: Future major versions of TensorFlow will allow gradients to flow into the labels input on backprop by default. See tf.nn.softmax_cross_entropy_with_logits_v2. ========condition Tensor("Loss/BoxClassifierLoss/Compare/IOU/Equal:0", shape=(?, 64), dtype=bool, device=/device:GPU:0) ========x Tensor("Loss/BoxClassifierLoss/Compare/IOU/zeros_like:0", shape=(?, 64), dtype=float32, device=/device:GPU:0) ========y Tensor("Loss/BoxClassifierLoss/Compare/IOU/truediv:0", shape=(?, 64), dtype=float32, device=/device:GPU:0) ========condition Tensor("Loss/BoxClassifierLoss/GreaterEqual:0", shape=(64,), dtype=bool, device=/device:GPU:0) ========x Tensor("Loss/BoxClassifierLoss/Encode/transpose:0", shape=(64, 4), dtype=float32, device=/device:GPU:0) ========y Tensor("Loss/BoxClassifierLoss/Tile_3:0", shape=(64, 4), dtype=float32, device=/device:GPU:0) ========condition Tensor("GreaterEqual_1:0", shape=(3,), dtype=bool, device=/device:CPU:0) ========x range(0, 3) ========y [0, 0, 0] Traceback (most recent call last): File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 510, in _apply_op_helper preferred_dtype=default_dtype) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1022, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 233, in _constant_tensor_conversion_function return constant(v, dtype=dtype, name=name) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 212, in constant value, dtype=dtype, shape=shape, verify_shape=verify_shape)) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 422, in make_tensor_proto _GetDenseDimensions(values))) ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted []. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 524, in _apply_op_helper values, as_ref=input_arg.is_ref).dtype.name File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1022, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 233, in _constant_tensor_conversion_function return constant(v, dtype=dtype, name=name) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 212, in constant value, dtype=dtype, shape=shape, verify_shape=verify_shape)) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py", line 422, in make_tensor_proto _GetDenseDimensions(values))) ValueError: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted []. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "object_detection/train.py", line 184, in <module> tf.app.run() File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 124, in run _sys.exit(main(argv)) File "object_detection/train.py", line 180, in main graph_hook_fn=graph_rewriter_fn) File "/home/raini/pro/tf_models/models/research/object_detection/trainer.py", line 298, in train train_config.optimizer) File "/home/raini/pro/tf_models/models/research/object_detection/builders/optimizer_builder.py", line 50, in build learning_rate = _create_learning_rate(config.learning_rate) File "/home/raini/pro/tf_models/models/research/object_detection/builders/optimizer_builder.py", line 109, in _create_learning_rate learning_rate_sequence, config.warmup) File "/home/raini/pro/tf_models/models/research/object_detection/utils/learning_schedules.py", line 169, in manual_stepping [0] * num_boundaries)) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 2540, in where return gen_math_ops._select(condition=condition, x=x, y=y, name=name) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py", line 4049, in _select "Select", condition=condition, t=x, e=y, name=name) File "/home/raini/app/anoconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 528, in _apply_op_helper (input_name, err)) ValueError: Tried to convert 't' to a tensor and failed. Error: Argument must be a dense tensor: range(0, 3) - got shape [3], but wanted [].
解决：
出错原因：知乎的大佬说是ｐython3的兼容问题
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解决办法：把research/object_detection/utils/learning_schedules.py文件的 第167-169行由
# ＃ 修改１６７－１６９ rate_index = tf.reduce_max(tf.where(tf.greater_equal(global_step, boundaries), range(num_boundaries), [0] * num_boundaries)) # ＃ 成 rate_index = tf.reduce_max(tf.where(tf.greater_equal(global_step, boundaries), list(range(num_boundaries)), [0] * num_boundaries))