Issue 1:
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): Linux Ubuntu 16.04

Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:

TensorFlow installed from (source or binary): binary

TensorFlow version (use command below): r1.13

Python version: 3.6

Bazel version (if compiling from source):

GCC/Compiler version (if compiling from source):

CUDA/cuDNN version:

GPU model and memory:

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

I have created .tflite with single ADD op. It has two inputs and one output.

When reading this .tflite with interpreter(e.g. tensorflow.lite.python)

import sys

import numpy as np

from tensorflow.lite.python import interpreter as interpreter_wrapper

interpreter = interpreter_wrapper.Interpreter(model_path=sys.argv[1])
interpreter.allocate_tensors()

input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

print(input_details)
print(output_details)

[{'name': 'input0', 'index': 0, 'shape': array([2, 5], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0)}, {'name': 'input1', 'index': 1, 'shape': array([2, 5], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0)}]
[{'name': 'output0', 'index': 2, 'shape': array([2, 5], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0)}, {'name': 'output0', 'index': 2, 'shape': array([2, 5], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0)}]

Code using C++ interpreter also reports duplicated outputs(2 2), even though outout of ADD(builtin code 0) shows one output.

Interpreter has 3 tensors and 1 nodes
Inputs: 0 1
Outputs: 2 2

Tensor 0 input0 kTfLiteFloat32 kTfLiteArenaRw 40 bytes ( 0.0 MB) 2 5
Tensor 1 input1 kTfLiteFloat32 kTfLiteArenaRw 40 bytes ( 0.0 MB) 2 5
Tensor 2 output0 kTfLiteFloat32 kTfLiteArenaRw 40 bytes ( 0.0 MB) 2 5

Node 0 Operator Builtin Code 0
Inputs: 0 1
Outputs: 2

Describe the expected behavior

get_output_details() returns unique list of outputs.

Code to reproduce the issue

Use attached .tflite file to reproduce the issue.

add.tflite.zip

Issue 2:
Installed nightly build using

pip3 install tensorflow-1.1.0rc0-cp35-cp35m-win_amd64.whl

on Windows 7 Professional x64. Simple run gives warning that the libs were not compiled to use SSE, SSE2, SSE3, SSE4.1, SSE4.2 and AVX instructions even though available.

c:\python

Python 3.5.2 (v3.5.2:4def2a2901a5, Jun 25 2016, 22:18:55) [MSC v.1900 64 bit (AMD64)] on win32

Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as tf

print( tf.version)

1.1.0-rc0

hello = tf.constant('Hello, TensorFlow!')

sess = tf.Session()

2017-03-30 15:20:06.126686: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_

tions, but these are available on your machine and could speed up CPU computations.

<

print(sess.run(hello))

b'Hello, TensorFlow!'