tf.quantized_concat
tf.quantized_concat
tf.quantized_concat
quantized_concat( concat_dim, values, input_mins, input_maxes, name=None )
Defined in tensorflow/python/ops/gen_array_ops.py
.
See the guide: Tensor Transformations > Slicing and Joining
Concatenates quantized tensors along one dimension.
Args:
-
concat_dim
: ATensor
of typeint32
. 0-D. The dimension along which to concatenate. Must be in the range [0, rank(values)). -
values
: A list of at least 2Tensor
objects with the same type. TheN
Tensors to concatenate. Their ranks and types must match, and their sizes must match in all dimensions exceptconcat_dim
. -
input_mins
: A list with the same length asvalues
ofTensor
objects with typefloat32
. The minimum scalar values for each of the input tensors. -
input_maxes
: A list with the same length asvalues
ofTensor
objects with typefloat32
. The maximum scalar values for each of the input tensors. -
name
: A name for the operation (optional).
Returns:
A tuple of Tensor
objects (output, output_min, output_max).
-
output
: ATensor
. Has the same type asvalues
. ATensor
with the concatenation of values stacked along theconcat_dim
dimension. This tensor's shape matches that ofvalues
except inconcat_dim
where it has the sum of the sizes. -
output_min
: ATensor
of typefloat32
. The float value that the minimum quantized output value represents. -
output_max
: ATensor
of typefloat32
. The float value that the maximum quantized output value represents.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/quantized_concat