Estimator Api : Error while training with estimator api












0















I am new to ML. I am not sure how to proceed with data reshape concepts. Earlier, tf.estimator was working fine for me. But when I tried experimenting wth new and large dataset, things started failing.



I am working on the below code.



import numpy as np

import pandas as pd

import tensorflow as tf

import matplotlib.pyplot as plt

from sklearn.model_selection import train_test_split

file='creditcard/creditcard.csv'

dataset=pd.read_csv(file)

dataset['Class']=dataset['Class'].astype('int')

print('Shape of dataset ',dataset.shape)

label=dataset['Class']

data=dataset.drop(['Class'],axis=1)

trainX,testX,trainY,testY=train_test_split(data,label,test_size=.3,random_state=101)

print('Shape of train data : (',trainX.shape,trainY.shape,')')

print('Shape of test data : (',testX.shape,testY.shape,')')

feature_value=[tf.feature_column.numeric_column('x')]

estimator=tf.estimator.LinearRegressor(feature_value)

train_input=tf.estimator.inputs.numpy_input_fn({'x':trainX.values},trainY.values,batch_size=512,shuffle=True)

test_input=tf.estimator.inputs.numpy_input_fn({'x':testX.values},testY.values,batch_size=512,shuffle=True)

estimator.train(input_fn=train_input,steps=1000)


When I am training my model, I am getting below error.



Can someone please help with the below :




  1. How to identify the correct shape.

  2. What correction do I need to make with the shape of data.


Error: 






C:UsersvineetAppDataLocalProgramsPythonPython36python.exe C:/Users/vineet/Desktop/selfML/creditCard.py

Shape of dataset  (284807, 31)

WARNING:tensorflow:Using temporary folder as model directory: C:UsersvineetAppDataLocalTemptmpbyc90zqm

Shape of train data : ( (199364, 30) (199364,) )

Shape of test data : ( (85443, 30) (85443,) )

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_queue_runner.py:62: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

2018-11-24 11:19:24.242005: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py:804: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

Traceback (most recent call last):

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1292, in _do_call

    return fn(*args)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1277, in _run_fn

    options, feed_dict, fetch_list, target_list, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1367, in _call_tf_sessionrun

    run_metadata)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1215, in _train_model_default

    saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1409, in _train_with_estimator_spec

    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 671, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1148, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1239, in run

    raise six.reraise(*original_exc_info)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagessix.py", line 693, in reraise

    raise value

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1224, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1296, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1076, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 887, in run

    run_metadata_ptr)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1110, in _run

    feed_dict_tensor, options, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1286, in _do_run

    run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1308, in _do_call

    raise type(e)(node_def, op, message)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



Caused by op 'linear/linear_model_1/linear_model/x/Reshape', defined at:

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1211, in _train_model_default

    features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1169, in _call_model_fn

    model_fn_results = self._model_fn(features=features, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 492, in _model_fn

    sparse_combiner=sparse_combiner)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 163, in _linear_model_fn

    logits = logit_fn(features=features)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 101, in linear_logit_fn

    cols_to_vars=cols_to_vars)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 464, in linear_model

    retval = linear_model_layer(features)  # pylint: disable=not-callable

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 647, in call

    weighted_sum = layer(builder)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonlayersbase.py", line 364, in __call__

    outputs = super(Layer, self).__call__(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 539, in call

    weight_var=self._weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2030, in _create_weighted_sum

    weight_var=weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2046, in _create_dense_column_weighted_sum

    tensor = array_ops.reshape(tensor, shape=(batch_size, num_elements))

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonopsgen_array_ops.py", line 7546, in reshape

    "Reshape", tensor=tensor, shape=shape, name=name)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkop_def_library.py", line 787, in _apply_op_helper

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonutildeprecation.py", line 488, in new_func

    return func(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 3272, in create_op

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 1768, in __init__

    self._traceback = tf_stack.extract_stack()



InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]





Process finished with exit code 1








tensorflow-estimator







share|improve this question

























  • I got the solution. I was using multiple column in estimator, but I was not making all used cols as feature column.I have made the changes and now code is working fine.

    – Vineet Tripathi
    Nov 25 '18 at 14:25


















0















I am new to ML. I am not sure how to proceed with data reshape concepts. Earlier, tf.estimator was working fine for me. But when I tried experimenting wth new and large dataset, things started failing.



I am working on the below code.



import numpy as np

import pandas as pd

import tensorflow as tf

import matplotlib.pyplot as plt

from sklearn.model_selection import train_test_split

file='creditcard/creditcard.csv'

dataset=pd.read_csv(file)

dataset['Class']=dataset['Class'].astype('int')

print('Shape of dataset ',dataset.shape)

label=dataset['Class']

data=dataset.drop(['Class'],axis=1)

trainX,testX,trainY,testY=train_test_split(data,label,test_size=.3,random_state=101)

print('Shape of train data : (',trainX.shape,trainY.shape,')')

print('Shape of test data : (',testX.shape,testY.shape,')')

feature_value=[tf.feature_column.numeric_column('x')]

estimator=tf.estimator.LinearRegressor(feature_value)

train_input=tf.estimator.inputs.numpy_input_fn({'x':trainX.values},trainY.values,batch_size=512,shuffle=True)

test_input=tf.estimator.inputs.numpy_input_fn({'x':testX.values},testY.values,batch_size=512,shuffle=True)

estimator.train(input_fn=train_input,steps=1000)


When I am training my model, I am getting below error.



Can someone please help with the below :




  1. How to identify the correct shape.

  2. What correction do I need to make with the shape of data.


Error: 






C:UsersvineetAppDataLocalProgramsPythonPython36python.exe C:/Users/vineet/Desktop/selfML/creditCard.py

Shape of dataset  (284807, 31)

WARNING:tensorflow:Using temporary folder as model directory: C:UsersvineetAppDataLocalTemptmpbyc90zqm

Shape of train data : ( (199364, 30) (199364,) )

Shape of test data : ( (85443, 30) (85443,) )

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_queue_runner.py:62: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

2018-11-24 11:19:24.242005: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py:804: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

Traceback (most recent call last):

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1292, in _do_call

    return fn(*args)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1277, in _run_fn

    options, feed_dict, fetch_list, target_list, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1367, in _call_tf_sessionrun

    run_metadata)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1215, in _train_model_default

    saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1409, in _train_with_estimator_spec

    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 671, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1148, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1239, in run

    raise six.reraise(*original_exc_info)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagessix.py", line 693, in reraise

    raise value

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1224, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1296, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1076, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 887, in run

    run_metadata_ptr)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1110, in _run

    feed_dict_tensor, options, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1286, in _do_run

    run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1308, in _do_call

    raise type(e)(node_def, op, message)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



Caused by op 'linear/linear_model_1/linear_model/x/Reshape', defined at:

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1211, in _train_model_default

    features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1169, in _call_model_fn

    model_fn_results = self._model_fn(features=features, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 492, in _model_fn

    sparse_combiner=sparse_combiner)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 163, in _linear_model_fn

    logits = logit_fn(features=features)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 101, in linear_logit_fn

    cols_to_vars=cols_to_vars)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 464, in linear_model

    retval = linear_model_layer(features)  # pylint: disable=not-callable

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 647, in call

    weighted_sum = layer(builder)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonlayersbase.py", line 364, in __call__

    outputs = super(Layer, self).__call__(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 539, in call

    weight_var=self._weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2030, in _create_weighted_sum

    weight_var=weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2046, in _create_dense_column_weighted_sum

    tensor = array_ops.reshape(tensor, shape=(batch_size, num_elements))

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonopsgen_array_ops.py", line 7546, in reshape

    "Reshape", tensor=tensor, shape=shape, name=name)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkop_def_library.py", line 787, in _apply_op_helper

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonutildeprecation.py", line 488, in new_func

    return func(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 3272, in create_op

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 1768, in __init__

    self._traceback = tf_stack.extract_stack()



InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]





Process finished with exit code 1








tensorflow-estimator







share|improve this question

























  • I got the solution. I was using multiple column in estimator, but I was not making all used cols as feature column.I have made the changes and now code is working fine.

    – Vineet Tripathi
    Nov 25 '18 at 14:25
















0












0








0


1






I am new to ML. I am not sure how to proceed with data reshape concepts. Earlier, tf.estimator was working fine for me. But when I tried experimenting wth new and large dataset, things started failing.



I am working on the below code.



import numpy as np

import pandas as pd

import tensorflow as tf

import matplotlib.pyplot as plt

from sklearn.model_selection import train_test_split

file='creditcard/creditcard.csv'

dataset=pd.read_csv(file)

dataset['Class']=dataset['Class'].astype('int')

print('Shape of dataset ',dataset.shape)

label=dataset['Class']

data=dataset.drop(['Class'],axis=1)

trainX,testX,trainY,testY=train_test_split(data,label,test_size=.3,random_state=101)

print('Shape of train data : (',trainX.shape,trainY.shape,')')

print('Shape of test data : (',testX.shape,testY.shape,')')

feature_value=[tf.feature_column.numeric_column('x')]

estimator=tf.estimator.LinearRegressor(feature_value)

train_input=tf.estimator.inputs.numpy_input_fn({'x':trainX.values},trainY.values,batch_size=512,shuffle=True)

test_input=tf.estimator.inputs.numpy_input_fn({'x':testX.values},testY.values,batch_size=512,shuffle=True)

estimator.train(input_fn=train_input,steps=1000)


When I am training my model, I am getting below error.



Can someone please help with the below :




  1. How to identify the correct shape.

  2. What correction do I need to make with the shape of data.


Error: 






C:UsersvineetAppDataLocalProgramsPythonPython36python.exe C:/Users/vineet/Desktop/selfML/creditCard.py

Shape of dataset  (284807, 31)

WARNING:tensorflow:Using temporary folder as model directory: C:UsersvineetAppDataLocalTemptmpbyc90zqm

Shape of train data : ( (199364, 30) (199364,) )

Shape of test data : ( (85443, 30) (85443,) )

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_queue_runner.py:62: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

2018-11-24 11:19:24.242005: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py:804: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

Traceback (most recent call last):

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1292, in _do_call

    return fn(*args)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1277, in _run_fn

    options, feed_dict, fetch_list, target_list, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1367, in _call_tf_sessionrun

    run_metadata)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1215, in _train_model_default

    saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1409, in _train_with_estimator_spec

    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 671, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1148, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1239, in run

    raise six.reraise(*original_exc_info)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagessix.py", line 693, in reraise

    raise value

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1224, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1296, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1076, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 887, in run

    run_metadata_ptr)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1110, in _run

    feed_dict_tensor, options, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1286, in _do_run

    run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1308, in _do_call

    raise type(e)(node_def, op, message)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



Caused by op 'linear/linear_model_1/linear_model/x/Reshape', defined at:

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1211, in _train_model_default

    features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1169, in _call_model_fn

    model_fn_results = self._model_fn(features=features, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 492, in _model_fn

    sparse_combiner=sparse_combiner)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 163, in _linear_model_fn

    logits = logit_fn(features=features)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 101, in linear_logit_fn

    cols_to_vars=cols_to_vars)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 464, in linear_model

    retval = linear_model_layer(features)  # pylint: disable=not-callable

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 647, in call

    weighted_sum = layer(builder)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonlayersbase.py", line 364, in __call__

    outputs = super(Layer, self).__call__(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 539, in call

    weight_var=self._weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2030, in _create_weighted_sum

    weight_var=weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2046, in _create_dense_column_weighted_sum

    tensor = array_ops.reshape(tensor, shape=(batch_size, num_elements))

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonopsgen_array_ops.py", line 7546, in reshape

    "Reshape", tensor=tensor, shape=shape, name=name)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkop_def_library.py", line 787, in _apply_op_helper

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonutildeprecation.py", line 488, in new_func

    return func(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 3272, in create_op

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 1768, in __init__

    self._traceback = tf_stack.extract_stack()



InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]





Process finished with exit code 1








tensorflow-estimator







share|improve this question
















I am new to ML. I am not sure how to proceed with data reshape concepts. Earlier, tf.estimator was working fine for me. But when I tried experimenting wth new and large dataset, things started failing.



I am working on the below code.



import numpy as np

import pandas as pd

import tensorflow as tf

import matplotlib.pyplot as plt

from sklearn.model_selection import train_test_split

file='creditcard/creditcard.csv'

dataset=pd.read_csv(file)

dataset['Class']=dataset['Class'].astype('int')

print('Shape of dataset ',dataset.shape)

label=dataset['Class']

data=dataset.drop(['Class'],axis=1)

trainX,testX,trainY,testY=train_test_split(data,label,test_size=.3,random_state=101)

print('Shape of train data : (',trainX.shape,trainY.shape,')')

print('Shape of test data : (',testX.shape,testY.shape,')')

feature_value=[tf.feature_column.numeric_column('x')]

estimator=tf.estimator.LinearRegressor(feature_value)

train_input=tf.estimator.inputs.numpy_input_fn({'x':trainX.values},trainY.values,batch_size=512,shuffle=True)

test_input=tf.estimator.inputs.numpy_input_fn({'x':testX.values},testY.values,batch_size=512,shuffle=True)

estimator.train(input_fn=train_input,steps=1000)


When I am training my model, I am getting below error.



Can someone please help with the below :




  1. How to identify the correct shape.

  2. What correction do I need to make with the shape of data.


Error: 






C:UsersvineetAppDataLocalProgramsPythonPython36python.exe C:/Users/vineet/Desktop/selfML/creditCard.py

Shape of dataset  (284807, 31)

WARNING:tensorflow:Using temporary folder as model directory: C:UsersvineetAppDataLocalTemptmpbyc90zqm

Shape of train data : ( (199364, 30) (199364,) )

Shape of test data : ( (85443, 30) (85443,) )

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_queue_runner.py:62: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

2018-11-24 11:19:24.242005: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py:804: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

Traceback (most recent call last):

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1292, in _do_call

    return fn(*args)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1277, in _run_fn

    options, feed_dict, fetch_list, target_list, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1367, in _call_tf_sessionrun

    run_metadata)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1215, in _train_model_default

    saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1409, in _train_with_estimator_spec

    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 671, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1148, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1239, in run

    raise six.reraise(*original_exc_info)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagessix.py", line 693, in reraise

    raise value

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1224, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1296, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1076, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 887, in run

    run_metadata_ptr)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1110, in _run

    feed_dict_tensor, options, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1286, in _do_run

    run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1308, in _do_call

    raise type(e)(node_def, op, message)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



Caused by op 'linear/linear_model_1/linear_model/x/Reshape', defined at:

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1211, in _train_model_default

    features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1169, in _call_model_fn

    model_fn_results = self._model_fn(features=features, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 492, in _model_fn

    sparse_combiner=sparse_combiner)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 163, in _linear_model_fn

    logits = logit_fn(features=features)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 101, in linear_logit_fn

    cols_to_vars=cols_to_vars)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 464, in linear_model

    retval = linear_model_layer(features)  # pylint: disable=not-callable

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 647, in call

    weighted_sum = layer(builder)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonlayersbase.py", line 364, in __call__

    outputs = super(Layer, self).__call__(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 539, in call

    weight_var=self._weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2030, in _create_weighted_sum

    weight_var=weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2046, in _create_dense_column_weighted_sum

    tensor = array_ops.reshape(tensor, shape=(batch_size, num_elements))

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonopsgen_array_ops.py", line 7546, in reshape

    "Reshape", tensor=tensor, shape=shape, name=name)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkop_def_library.py", line 787, in _apply_op_helper

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonutildeprecation.py", line 488, in new_func

    return func(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 3272, in create_op

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 1768, in __init__

    self._traceback = tf_stack.extract_stack()



InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]





Process finished with exit code 1








C:UsersvineetAppDataLocalProgramsPythonPython36python.exe C:/Users/vineet/Desktop/selfML/creditCard.py

Shape of dataset  (284807, 31)

WARNING:tensorflow:Using temporary folder as model directory: C:UsersvineetAppDataLocalTemptmpbyc90zqm

Shape of train data : ( (199364, 30) (199364,) )

Shape of test data : ( (85443, 30) (85443,) )

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_queue_runner.py:62: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

2018-11-24 11:19:24.242005: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py:804: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

Traceback (most recent call last):

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1292, in _do_call

    return fn(*args)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1277, in _run_fn

    options, feed_dict, fetch_list, target_list, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1367, in _call_tf_sessionrun

    run_metadata)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1215, in _train_model_default

    saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1409, in _train_with_estimator_spec

    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 671, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1148, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1239, in run

    raise six.reraise(*original_exc_info)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagessix.py", line 693, in reraise

    raise value

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1224, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1296, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1076, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 887, in run

    run_metadata_ptr)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1110, in _run

    feed_dict_tensor, options, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1286, in _do_run

    run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1308, in _do_call

    raise type(e)(node_def, op, message)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



Caused by op 'linear/linear_model_1/linear_model/x/Reshape', defined at:

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1211, in _train_model_default

    features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1169, in _call_model_fn

    model_fn_results = self._model_fn(features=features, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 492, in _model_fn

    sparse_combiner=sparse_combiner)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 163, in _linear_model_fn

    logits = logit_fn(features=features)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 101, in linear_logit_fn

    cols_to_vars=cols_to_vars)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 464, in linear_model

    retval = linear_model_layer(features)  # pylint: disable=not-callable

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 647, in call

    weighted_sum = layer(builder)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonlayersbase.py", line 364, in __call__

    outputs = super(Layer, self).__call__(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 539, in call

    weight_var=self._weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2030, in _create_weighted_sum

    weight_var=weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2046, in _create_dense_column_weighted_sum

    tensor = array_ops.reshape(tensor, shape=(batch_size, num_elements))

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonopsgen_array_ops.py", line 7546, in reshape

    "Reshape", tensor=tensor, shape=shape, name=name)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkop_def_library.py", line 787, in _apply_op_helper

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonutildeprecation.py", line 488, in new_func

    return func(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 3272, in create_op

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 1768, in __init__

    self._traceback = tf_stack.extract_stack()



InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]





Process finished with exit code 1





C:UsersvineetAppDataLocalProgramsPythonPython36python.exe C:/Users/vineet/Desktop/selfML/creditCard.py

Shape of dataset  (284807, 31)

WARNING:tensorflow:Using temporary folder as model directory: C:UsersvineetAppDataLocalTemptmpbyc90zqm

Shape of train data : ( (199364, 30) (199364,) )

Shape of test data : ( (85443, 30) (85443,) )

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_queue_runner.py:62: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorinputsqueuesfeeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

2018-11-24 11:19:24.242005: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

WARNING:tensorflow:From C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py:804: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.

Instructions for updating:

To construct input pipelines, use the `tf.data` module.

Traceback (most recent call last):

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1292, in _do_call

    return fn(*args)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1277, in _run_fn

    options, feed_dict, fetch_list, target_list, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1367, in _call_tf_sessionrun

    run_metadata)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1215, in _train_model_default

    saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1409, in _train_with_estimator_spec

    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 671, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1148, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1239, in run

    raise six.reraise(*original_exc_info)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagessix.py", line 693, in reraise

    raise value

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1224, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1296, in run

    run_metadata=run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythontrainingmonitored_session.py", line 1076, in run

    return self._sess.run(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 887, in run

    run_metadata_ptr)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1110, in _run

    feed_dict_tensor, options, run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1286, in _do_run

    run_metadata)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonclientsession.py", line 1308, in _do_call

    raise type(e)(node_def, op, message)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]



Caused by op 'linear/linear_model_1/linear_model/x/Reshape', defined at:

  File "C:/Users/vineet/Desktop/selfML/creditCard.py", line 19, in <module>

    estimator.train(input_fn=train_input,steps=1000)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 356, in train

    loss = self._train_model(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1181, in _train_model

    return self._train_model_default(input_fn, hooks, saving_listeners)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1211, in _train_model_default

    features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorestimator.py", line 1169, in _call_model_fn

    model_fn_results = self._model_fn(features=features, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 492, in _model_fn

    sparse_combiner=sparse_combiner)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 163, in _linear_model_fn

    logits = logit_fn(features=features)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonestimatorcannedlinear.py", line 101, in linear_logit_fn

    cols_to_vars=cols_to_vars)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 464, in linear_model

    retval = linear_model_layer(features)  # pylint: disable=not-callable

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 647, in call

    weighted_sum = layer(builder)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonlayersbase.py", line 364, in __call__

    outputs = super(Layer, self).__call__(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonkerasenginebase_layer.py", line 769, in __call__

    outputs = self.call(inputs, *args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 539, in call

    weight_var=self._weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2030, in _create_weighted_sum

    weight_var=weight_var)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonfeature_columnfeature_column.py", line 2046, in _create_dense_column_weighted_sum

    tensor = array_ops.reshape(tensor, shape=(batch_size, num_elements))

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonopsgen_array_ops.py", line 7546, in reshape

    "Reshape", tensor=tensor, shape=shape, name=name)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkop_def_library.py", line 787, in _apply_op_helper

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonutildeprecation.py", line 488, in new_func

    return func(*args, **kwargs)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 3272, in create_op

    op_def=op_def)

  File "C:UsersvineetAppDataLocalProgramsPythonPython36libsite-packagestensorflowpythonframeworkops.py", line 1768, in __init__

    self._traceback = tf_stack.extract_stack()



InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 15360 values, but the requested shape has 512

	 [[{{node linear/linear_model_1/linear_model/x/Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](linear/linear_model_1/linear_model/x/ToFloat, linear/linear_model_1/linear_model/x/Reshape/shape)]]





Process finished with exit code 1





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edited Nov 24 '18 at 6:22







Vineet Tripathi

















asked Nov 24 '18 at 6:10









Vineet TripathiVineet Tripathi

163




163













  • I got the solution. I was using multiple column in estimator, but I was not making all used cols as feature column.I have made the changes and now code is working fine.

    – Vineet Tripathi
    Nov 25 '18 at 14:25





















  • I got the solution. I was using multiple column in estimator, but I was not making all used cols as feature column.I have made the changes and now code is working fine.

    – Vineet Tripathi
    Nov 25 '18 at 14:25



















I got the solution. I was using multiple column in estimator, but I was not making all used cols as feature column.I have made the changes and now code is working fine.

– Vineet Tripathi
Nov 25 '18 at 14:25







I got the solution. I was using multiple column in estimator, but I was not making all used cols as feature column.I have made the changes and now code is working fine.

– Vineet Tripathi
Nov 25 '18 at 14:25














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