AttributeError: module 'tensorflow.core.framework.types_pb2 this error giving when i was executing code please help me
We need a little bit of context here. What is your use case?
Deep Learning tuning and optimization . yesterday it was working ny tensorflow tool but today not ruuning tensorflow library. i am doing this code “Deep Learning tuning and optimization”
What is your TF version? Can you share an minimal example?
tf version 2.5
import tensorflow as tf
run this code via jupyter
show error
AttributeError Traceback (most recent call last)
in
----> 1 import tensorflow as tf
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow_init_.py in
39 import sys as _sys
40
—> 41 from tensorflow.python.tools import module_util as _module_util
42 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
43
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python_init_.py in
44
45 # Bring in subpackages.
—> 46 from tensorflow.python import data
47 from tensorflow.python import distribute
48 from tensorflow.python import keras
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\data_init_.py in
23
24 # pylint: disable=unused-import
—> 25 from tensorflow.python.data import experimental
26 from tensorflow.python.data.ops.dataset_ops import AUTOTUNE
27 from tensorflow.python.data.ops.dataset_ops import Dataset
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\data\experimental_init_.py in
97
98 # pylint: disable=unused-import
—> 99 from tensorflow.python.data.experimental import service
100 from tensorflow.python.data.experimental.ops.batching import dense_to_ragged_batch
101 from tensorflow.python.data.experimental.ops.batching import dense_to_sparse_batch
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\data\experimental\service_init_.py in
138 from future import print_function
139
→ 140 from tensorflow.python.data.experimental.ops.data_service_ops import distribute
141 from tensorflow.python.data.experimental.ops.data_service_ops import from_dataset_id
142 from tensorflow.python.data.experimental.ops.data_service_ops import register_dataset
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\data\experimental\ops\data_service_ops.py in
23
24 from tensorflow.python import tf2
—> 25 from tensorflow.python.data.experimental.ops import compression_ops
26 from tensorflow.python.data.experimental.ops.distribute_options import AutoShardPolicy
27 from tensorflow.python.data.experimental.ops.distribute_options import ExternalStatePolicy
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\data\experimental\ops\compression_ops.py in
18 from future import print_function
19
—> 20 from tensorflow.python.data.util import structure
21 from tensorflow.python.ops import gen_experimental_dataset_ops as ged_ops
22
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\data\util\structure.py in
24 import wrapt
25
—> 26 from tensorflow.python.data.util import nest
27 from tensorflow.python.framework import composite_tensor
28 from tensorflow.python.framework import ops
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\data\util\nest.py in
38 import six as _six
39
—> 40 from tensorflow.python.framework import sparse_tensor as _sparse_tensor
41 from tensorflow.python.util import _pywrap_utils
42 from tensorflow.python.util import nest
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\framework\sparse_tensor.py in
26 from tensorflow.python import tf2
27 from tensorflow.python.framework import composite_tensor
—> 28 from tensorflow.python.framework import constant_op
29 from tensorflow.python.framework import dtypes
30 from tensorflow.python.framework import ops
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\framework\constant_op.py in
27 from tensorflow.core.framework import types_pb2
28 from tensorflow.python.eager import context
—> 29 from tensorflow.python.eager import execute
30 from tensorflow.python.framework import dtypes
31 from tensorflow.python.framework import op_callbacks
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\eager\execute.py in
26 from tensorflow.python.eager import core
27 from tensorflow.python.framework import dtypes
—> 28 from tensorflow.python.framework import ops
29 from tensorflow.python.framework import tensor_shape
30 from tensorflow.python.util import compat
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\framework\ops.py in
52 from tensorflow.python.framework import c_api_util
53 from tensorflow.python.framework import composite_tensor
—> 54 from tensorflow.python.framework import cpp_shape_inference_pb2
55 from tensorflow.python.framework import device as pydev
56 from tensorflow.python.framework import dtypes
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\python\framework\cpp_shape_inference_pb2.py in
188 _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE.fields_by_name[‘shape’].message_type = tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2._TENSORSHAPEPROTO
189 _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE.fields_by_name[‘dtype’].enum_type = tensorflow_dot_core_dot_framework_dot_types__pb2._DATATYPE
→ 190 _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE.fields_by_name[‘specialized_type’].enum_type = tensorflow_dot_core_dot_framework_dot_types__pb2._SPECIALIZEDTYPE
191 _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE.containing_type = _CPPSHAPEINFERENCERESULT
192 _CPPSHAPEINFERENCERESULT_HANDLEDATA.fields_by_name[‘shape_and_type’].message_type = _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE
AttributeError: module ‘tensorflow.core.framework.types_pb2’ has no attribute ‘_SPECIALIZEDTYPE’
Are you using a conda env?
python jupyter not using conda two days earlier working afterthat giving error
Can you test in a fresh virtualenv
?
how can i test please guide me
Check
thank you very much my tensorflow is working but i m getting another error.
AttributeError Traceback (most recent call last)
in
2 tf.compat.v1.ConfigProto
3 tf.executing_eagerly()
----> 4 he_init = tf.contrib.layers.variance_scaling_initializer()
5 hidden1 = tf.layers.dense(X,n_hidden1,activation=tf.nn.relu,kernel_initializer=he_init,name=“hidden1”)
AttributeError: module ‘tensorflow.compat.v1’ has no attribute ‘contrib’
tf.contrib was removed.
You can use:
from tensorflow.examples.tutorials.mnist import input_data
#from tensorflow.keras.datasets.mnist import input_data
mnist = input_data.read_data_sets(“/tmp/data/”) this code giving error
in tensorflow 2.5
ModuleNotFoundError Traceback (most recent call last)
in
----> 1 from tensorflow.examples.tutorials.mnist import input_data
2 #from tensorflow.keras.datasets.mnist import input_data
3 mnist = input_data.read_data_sets(“/tmp/data/”)
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\examples\tutorials\mnist_init_.py in
19 from future import print_function
20
—> 21 from tensorflow.examples.tutorials.mnist import input_data
22 from tensorflow.examples.tutorials.mnist import mnist
c:\users\eshant\appdata\local\programs\python\python38\lib\site-packages\tensorflow\examples\tutorials\mnist\input_data.py in
27 from six.moves import xrange # pylint: disable=redefined-builtin
28 import tensorflow as tf
—> 29 from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
from tensorflow.examples.tutorials.mnist import input_data
I don’t think we have this in TF 2.5.
for each observation in the training set, as test sample
initialize a dataframe to save all the test run results
df_loocv = pd.DataFrame()
for index, row in df_iris.iterrows():
# save the current in the processed df_loocv
df_loocv = df_loocv.append(df_iris.iloc[index: index+1])
# drop the current row chosen as test sample
# save it in temp df
df_iris_trim = df_iris.drop(index)
test_sepal_length = float(df_iris.loc[index, ['sepal_length']])
test_sepal_width = float(df_iris.loc[index, ['sepal_width']])
test_petal_length = float(df_iris.loc[index, ['petal_length']])
test_petal_width = float(df_iris.loc[index, ['petal_width']])
# for each row in the dataframe, calculate the distance
for index1, row1 in df_iris_trim.iterrows():
eucDist = sqrt(((test_sepal_length - float(row1['sepal_length'])) ** 2 +
(test_sepal_width - float(row1['sepal_width'])) ** 2 +
(test_petal_length - float(row1['petal_length'])) ** 2 +
(test_petal_width - float(row1['petal_width'])) ** 2))
df_iris_trim.loc[index1, 'distance'] = eucDist
# sort on distance, ascending.
df_iris_trim.sort_values('distance', ascending=True, inplace=True)
# select the first K rows, into a new df
K = int(K1)
df_iris_trim_K = df_iris_trim.iloc[0:K, :]
# The resulting object will be in descending order so that the first element
# is the most frequently-occurring element. Excludes NA values by default.
df_iris_trim_K_grouped = df_iris_trim_K['class'].value_counts()
# get the first index of the resulting pandas series above (value_counts)
pred_class = df_iris_trim_K_grouped.index[0]
# save the predicated class in the test data frame
df_loocv.loc[index, 'pred_class'] = pred_class
I AM GETTING ERROR THINS ONE FOR SEPAL_LENGTH, SEPAL_WIDTH
KeyError: “None of [Index([‘sepal_length’], dtype=‘object’)] are in the [index]”