Issue 1:
Please make sure that this is a feature request. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:feature_template

System information

TensorFlow version (you are using):1.12.0

Are you willing to contribute it (Yes/No):Yes

Describe the feature and the current behavior/state.

Deformable Convolutional Network(https://arxiv.org/pdf/1703.06211.pdf,https://arxiv.org/pdf/1703.06211.pdf) has achieved good results in the du detection task.But the current version of Tensorflow (1.12)does not seem to implement deformable convolution operations.The efficiency of some third-party implementations of deformable convolution operations is lower than that of the mxnet version(https://github.com/msracver/Deformable-ConvNets).I hope that Tensorflow can add native deformable convolution operations in future versions.

Thanks.

Will this change the current api? How?

Yes,Add a new API

Who will benefit with this feature?

Anyone who wants to use Tensorflow for object detection

Any Other info.

N/A

Issue 2:
Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): CentOS 7

Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: No

TensorFlow installed from (source or binary): source with tag v1.13.2

TensorFlow version (use command below): b'v1.13.2-0-g04256c89d8' 1.13.2

Python version:3.6.5

Bazel version (if compiling from source): 0.20.0

GCC/Compiler version (if compiling from source): 4.9.2

CUDA/cuDNN version: N/A

GPU model and memory: N/A

You can collect some of this information using our environment capture

script

You can also obtain the TensorFlow version with: 1. TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)" 2. TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the current behavior

The following error happened when I was convert my model to tf.lite. It's quite similar to #24525 .

Traceback (most recent call last):
File "tfconvert.py", line 18, in <module>
tflite_quantized_model = converter.convert()
File "/home/user/.local/lib/python3.6/site-packages/tensorflow/lite/python/lite.py", line 455, in convert
**converter_kwargs)
File "/home/user/.local/lib/python3.6/site-packages/tensorflow/lite/python/convert.py", line 442, in toco_convert_impl
input_data.SerializeToString())
File "/home/user/.local/lib/python3.6/site-packages/tensorflow/lite/python/convert.py", line 205, in toco_convert_protos
"TOCO failed. See console for info.\n%s\n%s\n" % (stdout, stderr))
tensorflow.lite.python.convert.ConverterError: TOCO failed. See console for info.
2019-10-10 10:12:14.730948: F tensorflow/core/framework/function.cc:1626] Check failed: GetOpGradFactory()->insert({op, func}).second Duplicated gradient for MapAccumulate

Code to reproduce the issue

converter = tf.lite.TFLiteConverter.from_saved_model(
model_path, input_arrays=input_arrays, output_arrays=output_arrays, input_shapes=input_shapes)
converter.post_training_quantize=True
converter.target_ops = [
# tf.lite.OpsSet.TFLITE_BUILTINS,
tf.lite.OpsSet.SELECT_TF_OPS
]
tflite_quantized_model = converter.convert()
open("quantized_model.tflite", "wb").write(tflite_quantized_model)

Any help will be appreciated! Thanks in advance.