You can use tf.compat.as_str_any()
.
for i in x:
print(tf.compat.as_str_any(i))
Last updated 2022-06-28 UTC.
Convert raw bytes from input tensor into numeric tensors.
tf.io.decode_raw( input_bytes, out_type, little_endian = True, fixed_length = None, name = None )
Every component of the input tensor is interpreted as a sequence of bytes.
These bytes are then decoded as numbers in the format specified by out_type
.
tf.io.decode_raw(tf.constant("1"), tf.uint8)
<tf.Tensor: shape=(1,), dtype=uint8, numpy=array([49], dtype=uint8)>
tf.io.decode_raw(tf.constant("1,2"), tf.uint8)
<tf.Tensor: shape=(3,), dtype=uint8, numpy=array([49, 44, 50], dtype=uint8)>
Note that the rank of the output tensor is always one more than the input one:
tf.io.decode_raw(tf.constant(["1", "2"]), tf.uint8).shape
TensorShape([2, 1])
tf.io.decode_raw(tf.constant([
["1"],
["2"]
]), tf.uint8).shape
TensorShape([2, 1, 1])
The operation allows specifying endianness via the little_endian
parameter.
tf.io.decode_raw(tf.constant("\x0a\x0b"), tf.int16)
<tf.Tensor: shape=(1,), dtype=int16, numpy=array([2826], dtype=int16)>
hex(2826)
'0xb0a'
tf.io.decode_raw(tf.constant("\x0a\x0b"), tf.int16, little_endian=False)
<tf.Tensor: shape=(1,), dtype=int16, numpy=array([2571], dtype=int16)>
hex(2571)
'0xa0b'
If the elements of input_bytes
are of different length, you must specify
fixed_length
:
tf.io.decode_raw(tf.constant([["1"],["23"]]), tf.uint8, fixed_length=4)
<tf.Tensor: shape=(2, 1, 4), dtype=uint8, numpy=array([[[49, 0, 0, 0]], [[50, 51, 0, 0]]], dtype=uint8)>
will print list items as python strings. anycodings_tensorflow-datasets No need to use session. ,I have a list of bytes and I want to convert anycodings_tensorflow it to a list of strings, in python I use anycodings_tensorflow this decode function:,You can use tf.compat.as_str_any(). ,How to get soft delete enabled/disabled status for all keyvault present in one resouce using powershell script
I have a list of bytes and I want to convert anycodings_tensorflow it to a list of strings, in python I use anycodings_tensorflow this decode function:
x = [b '\xd8\xa8\xd9\x85\xd8\xb3\xd8\xa3\xd9\x84\xd8\xa9',
b '\xd8\xa5\xd9\x86\xd8\xb4\xd8\xa7\xd8\xa1',
b '\xd9\x82\xd8\xb6\xd8\xa7\xd8\xa1',
b '\xd8\xac\xd9\x86\xd8\xa7\xd8\xa6\xd9\x8a',
b '\xd8\xaf\xd9\x88\xd9\x84\xd9\x8a'
]
y = [a.decode("utf-8") for a in x]
You can use tf.compat.as_str_any().
for i in x:
print(tf.compat.as_str_any(i))
Last Updated : 23 Jun, 2022,GATE Live Course 2023
Output:
Input:
b'GeeksForGeeks'
<class 'bytes'>
Output:
GeeksForGeeks
<class 'str'>