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math floordiv function gives incorrect result #56130

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mattbarrett98 opened this issue May 17, 2022 · 5 comments
Closed

math floordiv function gives incorrect result #56130

mattbarrett98 opened this issue May 17, 2022 · 5 comments
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@chunduriv
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comp:ops OPs related issues stat:awaiting response Status - Awaiting response from author TF 2.8 type:bug Bug

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@mattbarrett98
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mattbarrett98 commented May 17, 2022 •
edited by google-ml-butler bot
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Issue Type

Bug

Source

source

Tensorflow Version

2.8

Custom Code

No

OS Platform and Distribution

No response

Mobile device

No response

Python version

No response

Bazel version

No response

GCC/Compiler version

No response

CUDA/cuDNN version

No response

GPU model and memory

No response

Current Behaviour?

The code 

import tensorflow as tf
x = tf.constant([1e-37], dtype=tf.float32)
y = tf.constant([-2.0], dtype=tf.float32)
tf.math.floordiv(x, y)

works as expected, giving
<tf.Tensor: shape=(1,), dtype=float32, numpy=array([-1.], dtype=float32)>.

However

import tensorflow as tf
x = tf.constant([1e-38], dtype=tf.float32)
y = tf.constant([-2.0], dtype=tf.float32)
tf.math.floordiv(x, y)

gives
<tf.Tensor: shape=(1,), dtype=float32, numpy=array([-0.], dtype=float32)>.

Any idea why when x gets small enough it starts to output -0. rather than -1.. 1e-38 is still in range for float32 I believe so I think it should still work?



### Standalone code to reproduce the issue

```shell
https://colab.research.google.com/drive/1J583b0h11hee3UItK6l4VyaJ_hG7J4AT#scrollTo=c4-4DQ72QPZy

Relevant log output

No response
@google-ml-butler google-ml-butler bot added the type:bug Bug label May 17, 2022
@mohantym mohantym assigned sushreebarsa and unassigned mohantym May 17, 2022
@sushreebarsa sushreebarsa added TF 2.8 comp:ops OPs related issues labels May 17, 2022
@sushreebarsa
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@chunduriv I was able to replicate the issue on colab , please find the gist here for your reference.
Thank you!

@chunduriv
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@mattbarrett98,

This is an intended behavior and the same can also be seen in all cases mentioned below

Using TF without dtype

import tensorflow as tf
x = tf.constant([1e-38])
y = tf.constant([-2.0])
print(tf.math.floordiv(x, y))

Output:

tf.Tensor([-0.], shape=(1,), dtype=float32)

Using math module

import tensorflow as tf
from math import floor
x2 = tf.constant([1e-38], dtype=tf.float32)
y2 = tf.constant([-2.0], dtype=tf.float32)
print(floor(x2/y2))

Output:

0

Using Python

x3 = tf.constant([1e-38], dtype=tf.float32)
y3 = tf.constant([-2.0], dtype=tf.float32)
print(x3//y3)

tf.Tensor([-0.], shape=(1,), dtype=float32)

Thank you.

@chunduriv chunduriv added the stat:awaiting response Status - Awaiting response from author label Jun 16, 2022
@mattbarrett98
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I see, thanks for your help!

@google-ml-butler google-ml-butler bot removed the stat:awaiting response Status - Awaiting response from author label Jun 16, 2022
@chunduriv
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@mattbarrett98,

Please feel free to close the issue if it is resolved? Thank you.

@chunduriv chunduriv added the stat:awaiting response Status - Awaiting response from author label Jun 16, 2022
@google-ml-butler
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@chunduriv @mattbarrett98 @sushreebarsa @mohantym