这是我要尝试做的一个最小示例。在这里，我只使用常规的python数组来最小化代码，但我希望使用tensorflow张量来做到这一点。
import tensorflow as tf
c1 = [[5,8], [7,4]]
c2 = [6,9]
c3= tf.stack( [c1, c2] )
with tf.Session( ) as sess:
sess.run(tf.global_variables_initializer())
print(sess.run([ c3] ))
这是我得到的错误
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1658 try:
-> 1659 c_op = c_api.TF_FinishOperation(op_desc)
1660 except errors.InvalidArgumentError as e:
InvalidArgumentError: Shapes must be equal rank, but are 2 and 1
From merging shape 0 with other shapes. for 'stack_38' (op: 'Pack') with input shapes: [2,2], [2].
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-96-3acc40ce0738> in <module>()
1 c1 = [[5,8], [7,4]]
2 c2 = [6,9]
----> 3 c3= tf.stack( [c1, c2] )
4 with tf.Session( ) as sess:
5 sess.run(tf.global_variables_initializer())
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
178 """Call target, and fall back on dispatchers if there is a TypeError."""
179 try:
--> 180 return target(*args, **kwargs)
181 except (TypeError, ValueError):
182 # Note: convert_to_eager_tensor currently raises a ValueError, not a
/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/array_ops.py in stack(values, axis, name)
1003 expanded_num_dims))
1004
-> 1005 return gen_array_ops.pack(values, axis=axis, name=name)
1006
1007
/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/gen_array_ops.py in pack(values, axis, name)
5446 axis = _execute.make_int(axis, "axis")
5447 _, _, _op = _op_def_lib._apply_op_helper(
-> 5448 "Pack", values=values, axis=axis, name=name)
5449 _result = _op.outputs[:]
5450 _inputs_flat = _op.inputs
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
786 op = g.create_op(op_type_name, inputs, output_types, name=scope,
787 input_types=input_types, attrs=attr_protos,
--> 788 op_def=op_def)
789 return output_structure, op_def.is_stateful, op
790
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
499 'in a future version' if date is None else ('after %s' % date),
500 instructions)
--> 501 return func(*args, **kwargs)
502
503 doc = _add_deprecated_arg_notice_to_docstring(
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in create_op(***failed resolving arguments***)
3298 input_types=input_types,
3299 original_op=self._default_original_op,
-> 3300 op_def=op_def)
3301 self._create_op_helper(ret, compute_device=compute_device)
3302 return ret
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
1821 op_def, inputs, node_def.attr)
1822 self._c_op = _create_c_op(self._graph, node_def, grouped_inputs,
-> 1823 control_input_ops)
1824
1825 # Initialize self._outputs.
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1660 except errors.InvalidArgumentError as e:
1661 # Convert to ValueError for backwards compatibility.
-> 1662 raise ValueError(str(e))
1663
1664 return c_op
ValueError: Shapes must be equal rank, but are 2 and 1
From merging shape 0 with other shapes. for 'stack_38' (op: 'Pack') with input shapes: [2,2], [2].
我也尝试过使用不同的轴值以及tf.concat。似乎都需要相等的形状才能合并张量。
我正在寻找这样的结果
c3=[[5,8], [7,4], [6,9] ]
答案 0 :(得分：1)
我认为您想要的是tf.concat。因此，您需要数组具有相同的尺寸，而不是形状。因此，将c2提升为二维数组将解决此问题：
c1 = [[5,8], [7,4]]
# change c2 to be 2-D
c2 = [[6,9]]
# use concat
c3= tf.concat( [c1, c2], axis=0)
with tf.Session( ) as sess:
sess.run(tf.global_variables_initializer())
print(sess.run(c3))
请注意，如果使用张量，则可以使用tf.expand_dims(c2 ,0)将c2（如果是占位符/变量）提升为二维张量。