Skip to content
New issue

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

ERROR:root:Unable to execute run on Tensor("fi_Mean_1:0", dtype=float32) #49

Open
abhishektyaagi opened this issue Jun 10, 2021 · 1 comment

Comments

@abhishektyaagi
Copy link

Hi,
While running the logistic_regression.py test case, I am encountering an error.

System Information:
Python=2.7
TensorFlow=1.1.5 (GPU Support)

Command used:
python Tests/logistic_regression.py

Log
WARNING:tensorflow:From Tests/logistic_regression.py:19: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.
WARNING:tensorflow:From /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/contrib/learn/python/learn/datasets/mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Please write your own downloading logic.
WARNING:tensorflow:From /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/contrib/learn/python/learn/datasets/mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
Extracting /tmp/data/train-images-idx3-ubyte.gz
WARNING:tensorflow:From /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/contrib/learn/python/learn/datasets/mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
Extracting /tmp/data/train-labels-idx1-ubyte.gz
WARNING:tensorflow:From /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/contrib/learn/python/learn/datasets/mnist.py:110: dense_to_one_hot (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.one_hot on tensors.
Extracting /tmp/data/t10k-images-idx3-ubyte.gz
Extracting /tmp/data/t10k-labels-idx1-ubyte.gz
WARNING:tensorflow:From /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/contrib/learn/python/learn/datasets/mnist.py:290: init (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.
WARNING:tensorflow:From Tests/logistic_regression.py:28: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

WARNING:tensorflow:From Tests/logistic_regression.py:39: The name tf.log is deprecated. Please use tf.math.log instead.

WARNING:tensorflow:From Tests/logistic_regression.py:41: The name tf.train.GradientDescentOptimizer is deprecated. Please use tf.compat.v1.train.GradientDescentOptimizer instead.

WARNING:tensorflow:From Tests/logistic_regression.py:44: The name tf.global_variables_initializer is deprecated. Please use tf.compat.v1.global_variables_initializer instead.

WARNING:tensorflow:From Tests/logistic_regression.py:47: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

2021-06-09 20:47:16.283375: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2021-06-09 20:47:16.295312: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:5e:00.0
2021-06-09 20:47:16.295797: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 1 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:d8:00.0
2021-06-09 20:47:16.297107: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2021-06-09 20:47:16.299884: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2021-06-09 20:47:16.302552: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2021-06-09 20:47:16.303956: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2021-06-09 20:47:16.306989: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2021-06-09 20:47:16.309497: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2021-06-09 20:47:16.316184: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-06-09 20:47:16.318198: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0, 1
2021-06-09 20:47:16.321113: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA
2021-06-09 20:47:16.334672: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2100000000 Hz
2021-06-09 20:47:16.336866: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x563559e9e1d0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-06-09 20:47:16.336902: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2021-06-09 20:47:16.638280: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:5e:00.0
2021-06-09 20:47:16.638773: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 1 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:d8:00.0
2021-06-09 20:47:16.638838: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2021-06-09 20:47:16.638858: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2021-06-09 20:47:16.638874: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2021-06-09 20:47:16.638891: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2021-06-09 20:47:16.638908: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2021-06-09 20:47:16.638949: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2021-06-09 20:47:16.638966: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-06-09 20:47:16.640706: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0, 1
2021-06-09 20:47:16.640753: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2021-06-09 20:47:16.642010: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-06-09 20:47:16.642032: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 1
2021-06-09 20:47:16.642048: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N N
2021-06-09 20:47:16.642058: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 1: N N
2021-06-09 20:47:16.643804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3050 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:5e:00.0, compute capability: 7.5)
2021-06-09 20:47:16.645540: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 3050 MB memory) -> physical GPU (device: 1, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:d8:00.0, compute capability: 7.5)
2021-06-09 20:47:16.649265: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x56355ad10da0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2021-06-09 20:47:16.649295: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5
2021-06-09 20:47:16.649308: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (1): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5
2021-06-09 20:47:17.779916: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
Epoch: 0001 cost= 1.183628618
Epoch: 0002 cost= 0.665431309
Epoch: 0003 cost= 0.552812954
Epoch: 0004 cost= 0.498707291
Epoch: 0005 cost= 0.465449734
Epoch: 0006 cost= 0.442609885
Epoch: 0007 cost= 0.425485988
Epoch: 0008 cost= 0.412153071
Epoch: 0009 cost= 0.401357169
Epoch: 0010 cost= 0.392367188
Epoch: 0011 cost= 0.384738742
Epoch: 0012 cost= 0.378193522
Epoch: 0013 cost= 0.372418279
Epoch: 0014 cost= 0.367249739
Epoch: 0015 cost= 0.362749526
Epoch: 0016 cost= 0.358563266
Epoch: 0017 cost= 0.354849673
Epoch: 0018 cost= 0.351454730
Epoch: 0019 cost= 0.348317068
Epoch: 0020 cost= 0.345396632
Epoch: 0021 cost= 0.342762511
Epoch: 0022 cost= 0.340233821
Epoch: 0023 cost= 0.337921471
Epoch: 0024 cost= 0.335748342
Epoch: 0025 cost= 0.333688100
Optimization Finished!
Accuracy: 0.9135
/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/TensorFI/fiConfig.py:270: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
params = yaml.load(pStream)
WARNING:tensorflow:From /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/TensorFI/modifyGraph.py:34: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.
Instructions for updating:
tf.py_func is deprecated in TF V2. Instead, there are two
options available in V2.
- tf.py_function takes a python function which manipulates tf eager
tensors instead of numpy arrays. It's easy to convert a tf eager tensor to
an ndarray (just call tensor.numpy()) but having access to eager tensors
means tf.py_functions can use accelerators such as GPUs as well as
being differentiable using a gradient tape.
- tf.numpy_function maintains the semantics of the deprecated tf.py_func
(it is not differentiable, and manipulates numpy arrays). It drops the
stateful argument making all functions stateful.

WARNING:tensorflow:From /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/TensorFI/modifyGraph.py:34: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.
Instructions for updating:
tf.py_func is deprecated in TF V2. Instead, there are two
options available in V2.
- tf.py_function takes a python function which manipulates tf eager
tensors instead of numpy arrays. It's easy to convert a tf eager tensor to
an ndarray (just call tensor.numpy()) but having access to eager tensors
means tf.py_functions can use accelerators such as GPUs as well as
being differentiable using a gradient tape.
- tf.numpy_function maintains the semantics of the deprecated tf.py_func
(it is not differentiable, and manipulates numpy arrays). It drops the
stateful argument making all functions stateful.

Accuracy (with no injections): 0.9135
WARNING:tensorflow:From Tests/logistic_regression.py:85: The name tf.summary.FileWriter is deprecated. Please use tf.compat.v1.summary.FileWriter instead.

WARNING:tensorflow:From Tests/logistic_regression.py:85: The name tf.summary.FileWriter is deprecated. Please use tf.compat.v1.summary.FileWriter instead.

2021-06-09 20:49:13.454866: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:5e:00.0
2021-06-09 20:49:13.456646: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 1 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:d8:00.0
2021-06-09 20:49:13.456835: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2021-06-09 20:49:13.456945: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2021-06-09 20:49:13.457038: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2021-06-09 20:49:13.457137: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2021-06-09 20:49:13.457219: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2021-06-09 20:49:13.457327: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2021-06-09 20:49:13.457408: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-06-09 20:49:13.462890: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0, 1
2021-06-09 20:49:13.463164: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-06-09 20:49:13.463219: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 1
2021-06-09 20:49:13.463259: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N N
2021-06-09 20:49:13.463295: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 1: N N
2021-06-09 20:49:13.467357: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3050 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:5e:00.0, compute capability: 7.5)
2021-06-09 20:49:13.468799: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 3050 MB memory) -> physical GPU (device: 1, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:d8:00.0, compute capability: 7.5)
2021-06-09 20:49:13.482558: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:5e:00.0
2021-06-09 20:49:13.483020: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 1 with properties:
name: NVIDIA GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:d8:00.0
2021-06-09 20:49:13.483080: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2021-06-09 20:49:13.483100: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2021-06-09 20:49:13.483123: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2021-06-09 20:49:13.483138: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2021-06-09 20:49:13.483155: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2021-06-09 20:49:13.483172: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2021-06-09 20:49:13.483189: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2021-06-09 20:49:13.484656: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0, 1
2021-06-09 20:49:13.484699: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-06-09 20:49:13.484712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 1
2021-06-09 20:49:13.484724: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N N
2021-06-09 20:49:13.484734: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 1: N N
2021-06-09 20:49:13.485860: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3050 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:5e:00.0, compute capability: 7.5)
2021-06-09 20:49:13.486318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 3050 MB memory) -> physical GPU (device: 1, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:d8:00.0, compute capability: 7.5)
ERROR:root:Encountered exception pyfunc_6 returns 2 values, but expects to see 1 values.
[[node fi_add (defined at /u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Original stack trace for u'fi_add':
File "Tests/logistic_regression.py", line 78, in
fi = ti.TensorFI(sess, name = "logistReg", logLevel = 30, disableInjections = True)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/TensorFI/tensorFI.py", line 189, in init
self.fiMap = mg.modifyNodes(graph, fiPrefix)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/TensorFI/modifyGraph.py", line 98, in modifyNodes
newOp = createFIFunc(op.type, inputs, outputTypeList, name)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/TensorFI/modifyGraph.py", line 34, in createFIFunc
res = tf.py_func(fiFunc, inputs, outputTypes, name = name)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/util/deprecation.py", line 324, in new_func
return func(*args, **kwargs)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/ops/script_ops.py", line 513, in py_func
return py_func_common(func, inp, Tout, stateful, name=name)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/ops/script_ops.py", line 495, in py_func_common
func=func, inp=inp, Tout=Tout, stateful=stateful, eager=False, name=name)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/ops/script_ops.py", line 318, in _internal_py_func
input=inp, token=token, Tout=Tout, name=name)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/ops/gen_script_ops.py", line 170, in py_func
"PyFunc", input=input, token=token, Tout=Tout, name=name)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
op_def=op_def)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
attrs, op_def, compute_device)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
op_def=op_def)
File "/u/atyagi2/anaconda3/envs/tf1.15/lib/python2.7/site-packages/tensorflow_core/python/framework/ops.py", line 1748, in init
self._traceback = tf_stack.extract_stack()

ERROR:root:Unable to execute run on Tensor("fi_Mean_1:0", dtype=float32)
Accuracy (with injections): None

Is it possible to elaborate on what the issue might be as this is the only test which is not passing

@nniranjhana
Copy link
Contributor

nniranjhana commented Jun 13, 2021

Hi @abhishek-t-naive I believe this is a documented bug with injectFaultMean (fi_Mean), see #22 and #42. We will soon have someone look into this, meanwhile feel free to dig deeper and send a fix PR yourself ;)

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants