Assert the condition `x`

and `y`

are close element-wise.

tf.compat.v2.debugging.assert_near( x, y, rtol=None, atol=None, message=None, summarize=None, name=None )

This Op checks that `x[i] - y[i] < atol + rtol * tf.abs(y[i])`

holds for every pair of (possibly broadcast) elements of `x`

and `y`

. If both `x`

and `y`

are empty, this is trivially satisfied.

If any elements of `x`

and `y`

are not close, `message`

, as well as the first `summarize`

entries of `x`

and `y`

are printed, and `InvalidArgumentError`

is raised.

The default `atol`

and `rtol`

is `10 * eps`

, where `eps`

is the smallest representable positive number such that `1 + eps != 1`

. This is about `1.2e-6`

in `32bit`

, `2.22e-15`

in `64bit`

, and `0.00977`

in `16bit`

. See `numpy.finfo`

.

Args | |
---|---|

`x` | Float or complex `Tensor` . |

`y` | Float or complex `Tensor` , same dtype as and broadcastable to `x` . |

`rtol` | `Tensor` . Same `dtype` as, and broadcastable to, `x` . The relative tolerance. Default is `10 * eps` . |

`atol` | `Tensor` . Same `dtype` as, and broadcastable to, `x` . The absolute tolerance. Default is `10 * eps` . |

`message` | A string to prefix to the default message. |

`summarize` | Print this many entries of each tensor. |

`name` | A name for this operation (optional). Defaults to "assert_near". |

Returns | |
---|---|

Op that raises `InvalidArgumentError` if `x` and `y` are not close enough. This can be used with `tf.control_dependencies` inside of `tf.function` s to block followup computation until the check has executed. |

Raises | |
---|---|

`InvalidArgumentError` | if the check can be performed immediately and `x != y` is False for any pair of elements in `x` and `y` . The check can be performed immediately during eager execution or if `x` and `y` are statically known. |

returns None

Similar to `numpy.assert_allclose`

, except tolerance depends on data type. This is due to the fact that `TensorFlow`

is often used with `32bit`

, `64bit`

, and even `16bit`

data.

© 2020 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/versions/r1.15/api_docs/python/tf/compat/v2/debugging/assert_near