TensorFlow 中检查张量中元素的正、负性 tf.assert_positive、tf.assert_negative 等的基本用法及实例代码

本文链接：https://blog.youkuaiyun.com/sdnuwjw/article/details/86630202

本文详细介绍了TensorFlow中tf.debugging命名空间下的多种断言操作，包括判断张量元素是否为正、非正、负、非负，以及更多数值验证函数，如检查张量是否包含NaN或Inf，确保张量元素相等或比较大小，静态断言张量类型，检查张量秩等。这些函数有助于在TensorFlow模型训练和调试过程中进行数据验证。

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（1）tf.assert_positive

tf..debugging.assert_positive

tf.debugging.assert_positive(
    x,
    data=None,
    summarize=None,
    message=None,
    name=None
)

判断输入张量 x 的元素都大于 0，否则抛出错误 InvalidArgumentError

通常可以用于给某个操作添加依赖条件，如：

with tf.control_dependencies([tf.assert_positive(x)]):
  output = tf.reduce_sum(x)

（2）tf.assert_non_positive

tf.debugging.assert_non_positive

同理，判断输入张量 x 的元素都非正数，否则抛出错误 InvalidArgumentError

（3）tf.assert_negative

tf.debugging.assert_negative

同理，判断输入张量 x 的元素都小于 0，否则抛出错误 InvalidArgumentError

（4）tf.assert_non_negative

tf.debugging.assert_non_negative

同理，判断输入张量 x 的元素都非负数，否则抛出错误 InvalidArgumentError

这些断言操作都在命名空间 tf.debugging 下

https://tensorflow.google.cn/api_docs/python/tf/debugging

Assert(...): Asserts that the given condition is true.

assert_all_finite(...): Assert that the tensor does not contain any NaN's or Inf's.

assert_equal(...): Assert the condition x == y holds element-wise.

assert_greater(...): Assert the condition x > y holds element-wise.

assert_greater_equal(...): Assert the condition x >= y holds element-wise.

assert_integer(...): Assert that x is of integer dtype.

assert_less(...): Assert the condition x < y holds element-wise.

assert_less_equal(...): Assert the condition x <= y holds element-wise.

assert_near(...): Assert the condition x and y are close element-wise.

assert_negative(...): Assert the condition x < 0 holds element-wise.

assert_non_negative(...): Assert the condition x >= 0 holds element-wise. assert_non_positive(...):

Assert the condition x <= 0 holds element-wise. assert_none_equal(...):

Assert the condition x != y holds for all elements. assert_positive(...):

Assert the condition x > 0 holds element-wise.

assert_proper_iterable(...): Static assert that values is a "proper" iterable.

assert_rank(...): Assert x has rank equal to rank.

assert_rank_at_least(...): Assert x has rank equal to rank or higher.

assert_rank_in(...): Assert x has rank in ranks.

assert_same_float_dtype(...): Validate and return float type based on tensors and dtype.

assert_scalar(...) assert_type(...): Statically asserts that the given Tensor is of the specified type.

check_numerics(...): Checks a tensor for NaN and Inf values.

is_finite(...): Returns which elements of x are finite. is_inf(...): Returns which elements of x are Inf.

is_nan(...): Returns which elements of x are NaN.

is_non_decreasing(...): Returns True if x is non-decreasing.

is_numeric_tensor(...) is_strictly_increasing(...): Returns True if x is strictly increasing.