Issue 1:
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System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):

yes

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

Ubuntu 14.04

TensorFlow installed from (source or binary):

source

TensorFlow version (use command below):

1.2.0-rc0

Bazel version (if compiling from source):

CUDA/cuDNN version:

8.0

GPU model and memory:

Exact command to reproduce:

cod (mostly from https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/input_fn/boston.py)

from tensorflow.contrib.learn.python.learn.learn_io import pandas_io
import pandas as pd
import tensorflow as tf
import pdb

tf.logging.set_verbosity(tf.logging.INFO)

COLUMNS = ["crim", "zn", "indus", "nox", "rm", "age",
"dis", "tax", "ptratio", "medv"]
FEATURES = ["crim", "zn", "indus", "nox", "rm",
"age", "dis", "tax", "ptratio"]
LABEL = "medv"

training_set = pd.read_csv("boston_train.csv", skipinitialspace=True,
skiprows=1, names=COLUMNS)
# test_set = pd.read_csv("boston_test.csv", skipinitialspace=True,
# skiprows=1, names=COLUMNS)
# prediction_set = pd.read_csv("boston_predict.csv", skipinitialspace=True,
# skiprows=1, names=COLUMNS)

feature_cols = [tf.contrib.layers.real_valued_column(k) for k in FEATURES]

regressor = tf.contrib.learn.DNNRegressor(feature_columns=feature_cols,
hidden_units=[10, 10],
model_dir="/tmp/boston_model")

pd_input_fn = pandas_io.pandas_input_fn(training_set[FEATURES], y=training_set[LABEL],
batch_size=128,target_column='medv')

regressor.fit(input_fn=pd_input_fn, steps=5000)

Describe the problem

Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.

I saw a stakoervlow question here, but I don't think that applies to me.

I have the following confusing warnings. As a result, I am not sure that everything is right.

WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WA

Source code / logs

Full output:

INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_task_type': None, '_task_id': 0, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f5a3710eba8>, '_master': '', '_num_ps_replicas': 0, '_num_worker_replicas': 0, '_environment': 'local', '_is_chief': True, '_evaluation_master': '', '_tf_config': gpu_options {
per_process_gpu_memory_fraction: 1.0
}
, '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_secs': 600, '_session_config': None, '_save_checkpoints_steps': None, '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_model_dir': '/tmp/boston_model'}
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.
WARNING:tensorflow:From /home/jiqiang/anaconda3/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:625: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Restoring parameters from /tmp/boston_model/model.ckpt-16
INFO:tensorflow:Saving checkpoints for 17 into /tmp/boston_model/model.ckpt.
INFO:tensorflow:loss = 115.183, step = 17
INFO:tensorflow:Saving checkpoints for 20 into /tmp/boston_model/model.ckpt.
INFO:tensorflow:Loss for final step: 161.23.

Issue 2:
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Google Colab

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

TensorFlow installed from (source or binary):

TensorFlow version (use command below): 1.9.0

Python version: 3.6

Bazel version (if compiling from source):

GCC/Compiler version (if compiling from source):

CUDA/cuDNN version:

GPU model and memory: Colab GPUs

Exact command to reproduce:

Describe the problem

To make it short, Keras's Tensorboard callback doesn't work in the eager execution mode.

Source code / logs

RuntimeErrorTraceback (most recent call last)

in ()

57 X = np.random.random((20, 10)).astype(np.float32)

58 Y = np.random.random((20, 5)).astype(np.float32)

---> 59 model.fit(x={'input' : X}, y={'clustering' : Y}, batch_size=1, epochs=10, callbacks=[tensorboard])

/usr/local/lib/python2.7/dist-packages/tensorflow/python/keras/engine/training.pyc in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)

1331 initial_epoch=initial_epoch,

1332 steps_per_epoch=steps_per_epoch,

-> 1333 validation_steps=validation_steps)

1334 else:

1335 return training_arrays.fit_loop(

/usr/local/lib/python2.7/dist-packages/tensorflow/python/keras/engine/training_eager.pyc in fit_loop(model, inputs, targets, sample_weights, class_weight, val_inputs, val_targets, val_sample_weights, batch_size, epochs, verbose, callbacks, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)

977 callback_model = model

978

--> 979 callbacks.set_model(callback_model)

980

981 callbacks.set_params({

/usr/local/lib/python2.7/dist-packages/tensorflow/python/keras/callbacks.pyc in set_model(self, model)

68 def set_model(self, model):

69 for callback in self.callbacks:

---> 70 callback.set_model(model)

71

72 def on_epoch_begin(self, epoch, logs=None):

/usr/local/lib/python2.7/dist-packages/tensorflow/python/keras/callbacks.pyc in set_model(self, model)

761 if hasattr(layer, 'output'):

762 tf_summary.histogram('{}_out'.format(layer.name), layer.output)

--> 763 self.merged = tf_summary.merge_all()

764

765 if self.write_graph:

/usr/local/lib/python2.7/dist-packages/tensorflow/python/summary/summary.pyc in merge_all(key, scope)

309 if _context.executing_eagerly():

310 raise RuntimeError(

--> 311 'Merging tf.summary.* ops is not compatible with eager execution. '

312 'Use tf.contrib.summary instead.')

313 summary_ops = _ops.get_collection(key, scope=scope)

RuntimeError: Merging tf.summary.* ops is not compatible with eager execution. Use tf.contrib.summary instead.