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tf.assert_non_negative

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

Defined in tensorflow/python/ops/check_ops.py.

See the guide: Asserts and boolean checks

Assert the condition x >= 0 holds element-wise.

Example of adding a dependency to an operation:

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

Non-negative means, for every element x[i] of x, we have x[i] >= 0. If x is empty this is trivially satisfied.

Args:

  • x: Numeric Tensor.
  • data: The tensors to print out if the condition is False. Defaults to error message and first few entries of x.
  • summarize: Print this many entries of each tensor.
  • message: A string to prefix to the default message.
  • name: A name for this operation (optional). Defaults to "assert_non_negative".

Returns:

Op raising InvalidArgumentError unless x is all non-negative.

© 2018 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/assert_non_negative