python – 在Tensorflow中打印张量的值

概述以下是我的完整代码的链接： https://github.com/roshanDD/YAD2K/blob/master/yad2k/models/keras_yolo.py#L253 我只想打印张量的值,称为true_areas.我运行了我的代码： sess = tf.InteractiveSession()true_areas = true_wh[..., 0] * true_wh[..., 以下是我的完整代码的链接：

https://github.com/roshanDD/YAD2K/blob/master/yad2k/models/keras_yolo.py#L253

我只想打印张量的值,称为true_areas.我运行了我的代码：

sess = tf.InteractiveSession()true_areas = true_wh[...,0] * true_wh[...,1]tf.Print(true_areas,[true_areas],message = "This is True Areas: ")b = tf.add(true_areas,true_areas).eval()

但它给了我错误：

Caused by op 'input_2',defined at:  file "learning.py",line 358,in <module>    _main(args)  file "learning.py",line 66,in _main    model_body,model = create_model(anchors,class_names)  file "learning.py",line 185,in create_model    Boxes_input = input(shape=(None,5))  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/keras/engine/topology.py",line 1388,in input    input_tensor=tensor)  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/keras/engine/topology.py",line 1299,in __init__    name=self.name)  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py",line 349,in placeholder    x = tf.placeholder(dtype,shape=shape,name=name)  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py",line 1507,in placeholder    name=name)  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py",line 1997,in _placeholder    name=name)  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py",line 768,in apply_op    op_def=op_def)  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/tensorflow/python/framework/ops.py",line 2336,in create_op    original_op=self._default_original_op,op_def=op_def)  file "/home/ubuntu/anaconda2/envs/py35/lib/python3.5/site-packages/tensorflow/python/framework/ops.py",line 1228,in __init__    self._traceback = _extract_stack()InvalIDArgumentError (see above for traceback): You must Feed a value for placeholder tensor 'input_2' with dtype float     [[Node: input_2 = Placeholder[dtype=DT_float,shape=[],_device="/job:localhost/replica:0/task:0/cpu:0"]()]]

它正在谈论的占位符是什么？

解决方法 错误消息告诉您,您在代码中的某个位置定义了一个名为input_2的 tf.placeholder().

如果要评估依赖于此占位符的图形,则需要向此占位符提供feed值.它应该看起来像这样：

b = tf.add(true_areas,true_areas).eval({input_2: someinputValues})

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