# tf.quantized_concat

tf.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: A Tensor of type int32. 0-D. The dimension along which to concatenate. Must be in the range [0, rank(values)).
• values: A list of at least 2 Tensor objects with the same type. The N Tensors to concatenate. Their ranks and types must match, and their sizes must match in all dimensions except concat_dim.
• input_mins: A list with the same length as values of Tensor objects with type float32. The minimum scalar values for each of the input tensors.
• input_maxes: A list with the same length as values of Tensor objects with type float32. 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: A Tensor. Has the same type as values.
• output_min: A Tensor of type float32.
• output_max: A Tensor of type float32.