问题
I'm using TensorFlow r1.7 and python3.6.5. I am also very new to TensorFlow, so I'd like easy to read explanations if possible.
I'm trying to convert my input data into a dataset of tensors with this function tf.data.Dataset.from_tensor_slices(). I pass my tuple with mixed datatypes into this function. However, when running my code I get this error: ValueError: Can't convert Python sequence with mixed types to Tensor.
I want to know why I am receiving this error, and how I can convert my data to a dataset of tensors even with mixed datatypes.
Here's a printout of the top 5 entries in my tuple.
(13501, 2, None, 51, '2232', 'S35', '734.72', 'CLA', '240', 1035, 2060, 1252, 1182, 10, '967.28', '338.50', None, 14, 102, 3830)
(15124, 2, None, 57, '2641', 'S35', '234.80', 'DDA', '240', 743, 1597, 4706, 156, 0, None, None, None, 3, 27, 981)
(40035, 2, None, None, '21', 'K00', '60.06', 'CHK', '520', 76, 1863, 12, None, 1, '85.06', '25.00', None, 1, 5, 245)
(42331, 3, None, 62, '121', 'S50', '1859.01', 'ACT', '420', 952, 1583, 410, 255, 0, None, None, None, 6, 117, 1795)
(201721, 3, None, 42, '2472', 'S35', '1413.84', 'CLA', '350', 868, 1746, 963, 264, 0, None, None, None, 18, 65, 4510)
As you can see, I have a mix of integers, floats, and strings in my input data.
Here is a traceback of the error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/miikey101/Documents/Khalen_Case_Loader/tensorflow/k_means/k_means.py", line 10, in prepare_dataset
dataset = tf.data.Dataset.from_tensor_slices(dm_data)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/data/ops/dataset_ops.py", line 222, in from_tensor_slices
return TensorSliceDataset(tensors)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/data/ops/dataset_ops.py", line 1017, in __init__
for i, t in enumerate(nest.flatten(tensors))
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/data/ops/dataset_ops.py", line 1017, in <listcomp>
for i, t in enumerate(nest.flatten(tensors))
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 950, in convert_to_tensor
as_ref=False)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1040, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 235, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 185, in constant
t = convert_to_eager_tensor(value, ctx, dtype)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 131, in convert_to_eager_tensor
return ops.EagerTensor(value, context=handle, device=device, dtype=dtype)
ValueError: Can't convert Python sequence with mixed types to Tensor.
回答1:
In tensorflow you can't have a tensor with more than one data type.
Quoting the documentation:
It is not possible to have a tf.Tensor with more than one data type. It is possible, however, to serialize arbitrary data structures as strings and store those in tf.Tensors.
Hence a workaround could be to create a tensor with data type tf.String and, on the occurrence, cast the field to the desired data type
来源：https://stackoverflow.com/questions/49824872/convert-python-sequence-with-multiple-datatypes-to-tensor