tf.io.decode_raw | TensorFlow v2.16.1 (original) (raw)
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
)
Used in the notebooks
| Used in the guide |
|---|
| Introduction to Tensors |
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])
This is because each byte in the input is converted to a new value on the output (if output type is uint8 or int8, otherwise chunks of inputs get coverted to a new value):
tf.io.decode_raw(tf.constant("123"), tf.uint8)
<tf.Tensor: shape=(3,), dtype=uint8, numpy=array([49, 50, 51], dtype=uint8)>
tf.io.decode_raw(tf.constant("1234"), tf.uint8)
<tf.Tensor: shape=(4,), dtype=uint8, numpy=array([49, 50, 51, 52], ...
# chuncked output
tf.io.decode_raw(tf.constant("12"), tf.uint16)
<tf.Tensor: shape=(1,), dtype=uint16, numpy=array([12849], dtype=uint16)>
tf.io.decode_raw(tf.constant("1234"), tf.uint16)
<tf.Tensor: shape=(2,), dtype=uint16, numpy=array([12849, 13363], ...
# int64 output
tf.io.decode_raw(tf.constant("12345678"), tf.int64)
<tf.Tensor: ... numpy=array([4050765991979987505])>
tf.io.decode_raw(tf.constant("1234567887654321"), tf.int64)
<tf.Tensor: ... numpy=array([4050765991979987505, 3544952156018063160])>
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 specifyfixed_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)>
If the fixed_length value is larger that the length of the out_type dtype, multiple values are generated:
tf.io.decode_raw(tf.constant(["1212"]), tf.uint16, fixed_length=4)
<tf.Tensor: shape=(1, 2), dtype=uint16, numpy=array([[12849, 12849]], ...
If the input value is larger than fixed_length, it is truncated:
x=''.join([chr(1), chr(2), chr(3), chr(4)])
tf.io.decode_raw(x, tf.uint16, fixed_length=2)
<tf.Tensor: shape=(1,), dtype=uint16, numpy=array([513], dtype=uint16)>
hex(513)
'0x201'
If little_endian and fixed_length are specified, truncation to the fixed length occurs before endianness conversion:
x=''.join([chr(1), chr(2), chr(3), chr(4)])
tf.io.decode_raw(x, tf.uint16, fixed_length=2, little_endian=False)
<tf.Tensor: shape=(1,), dtype=uint16, numpy=array([258], dtype=uint16)>
hex(258)
'0x102'
If input values all have the same length, then specifying fixed_lengthequal to the size of the strings should not change output:
x = ["12345678", "87654321"]
tf.io.decode_raw(x, tf.int16)
<tf.Tensor: shape=(2, 4), dtype=int16, numpy=
array([[12849, 13363, 13877, 14391],
[14136, 13622, 13108, 12594]], dtype=int16)>
tf.io.decode_raw(x, tf.int16, fixed_length=len(x[0]))
<tf.Tensor: shape=(2, 4), dtype=int16, numpy=
array([[12849, 13363, 13877, 14391],
[14136, 13622, 13108, 12594]], dtype=int16)>
| Args | |
|---|---|
| input_bytes | Each element of the input Tensor is converted to an array of bytes.Currently, this must be a tensor of strings (bytes), although semantically the operation should support any input. |
| out_type | DType of the output. Acceptable types are half, float, double,int32, uint16, uint8, int16, int8, int64. |
| little_endian | Whether the input_bytes data is in little-endian format. Data will be converted into host byte order if necessary. |
| fixed_length | If set, the first fixed_length bytes of each element will be converted. Data will be zero-padded or truncated to the specified length.fixed_length must be a multiple of the size of out_type. fixed_length must be specified if the elements of input_bytes are of variable length. |
| name | A name for the operation (optional). |
| Returns |
|---|
| A Tensor object storing the decoded bytes. |