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.