We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient
Bug
Yes
source
tf 2.16.1
Ubuntu 20.04
No response
3.11
Check Failed in tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient when the input of inputs is scalar, which causes the program to crash.
# FakeQuantWithMinMaxVarsPerChannelGradientOp import tensorflow as tf num_bits = 8 narrow_range = False gradients = tf.constant(0, shape=[], dtype=tf.float32) inputs = tf.constant(0, shape=[], dtype=tf.float32) min = tf.constant(124, shape=[3,1], dtype=tf.float32) max = tf.constant(124, shape=[3,1], dtype=tf.float32) tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient(gradients=gradients, inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)
2024-05-01 03:10:46.669162: F tensorflow/core/framework/tensor_shape.cc:356] Check failed: d >= 0 (0 vs. -1) Aborted (core dumped)
The text was updated successfully, but these errors were encountered:
Hi @LongZE666 ,
Thanks for reporting. I have reproduced the reported behaviour and attached gist here.
The check fail observed when the inputs arg shape is empty.
inputs
shape
Attaching also snapshot of same below.
Sorry, something went wrong.
SuryanarayanaY
No branches or pull requests
Issue type
Bug
Have you reproduced the bug with TensorFlow Nightly?
Yes
Source
source
TensorFlow version
tf 2.16.1
Custom code
Yes
OS platform and distribution
Ubuntu 20.04
Mobile device
No response
Python version
3.11
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
Check Failed in
tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient
when the input of inputs is scalar, which causes the program to crash.Standalone code to reproduce the issue
# FakeQuantWithMinMaxVarsPerChannelGradientOp import tensorflow as tf num_bits = 8 narrow_range = False gradients = tf.constant(0, shape=[], dtype=tf.float32) inputs = tf.constant(0, shape=[], dtype=tf.float32) min = tf.constant(124, shape=[3,1], dtype=tf.float32) max = tf.constant(124, shape=[3,1], dtype=tf.float32) tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient(gradients=gradients, inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)
Relevant log output
2024-05-01 03:10:46.669162: F tensorflow/core/framework/tensor_shape.cc:356] Check failed: d >= 0 (0 vs. -1) Aborted (core dumped)
The text was updated successfully, but these errors were encountered: