conv_utils.py

# Copyright 2022 The KerasCV Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


def normalize_tuple(value, n, name, allow_zero=False):
    """Transforms non-negative/positive integer/integers into an integer tuple.
    Args:
      value: The value to validate and convert. Could an int, or any iterable of
        ints.
      n: The size of the tuple to be returned.
      name: The name of the argument being validated, e.g. "strides" or
        "kernel_size". This is only used to format error messages.
      allow_zero: Default to False. A ValueError will raised if zero is received
        and this param is False.
    Returns:
      A tuple of n integers.
    Raises:
      ValueError: If something else than an int/long or iterable thereof or a
      negative value is
        passed.
    """
    error_msg = (
        f"The `{name}` argument must be a tuple of {n} " f"integers. Received: {value}"
    )

    if isinstance(value, int):
        value_tuple = (value,) * n
    else:
        try:
            value_tuple = tuple(value)
        except TypeError:
            raise ValueError(error_msg)
        if len(value_tuple) != n:
            raise ValueError(error_msg)
        for single_value in value_tuple:
            try:
                int(single_value)
            except (ValueError, TypeError):
                error_msg += (
                    f"including element {single_value} of " f"type {type(single_value)}"
                )
                raise ValueError(error_msg)

    if allow_zero:
        unqualified_values = {v for v in value_tuple if v < 0}
        req_msg = ">= 0"
    else:
        unqualified_values = {v for v in value_tuple if v <= 0}
        req_msg = "> 0"

    if unqualified_values:
        error_msg += (
            f" including {unqualified_values}"
            f" that does not satisfy the requirement `{req_msg}`."
        )
        raise ValueError(error_msg)

    return value_tuple