ValueError: The first layer in a Sequential model must get an input_shape argument. #4104
Description
When running the officials/mnist/mnist.py there is an error message:
Traceback (most recent call last):
File "mnist.py", line 261, in
main(argv=sys.argv)
File "mnist.py", line 225, in main
mnist_classifier.train(input_fn=train_input_fn, hooks=train_hooks)
File "/Users/yangsong/tensorflow/lib/python3.5/site-packages/tensorflow/python/estimator/estimator.py", line 355, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/Users/yangsong/tensorflow/lib/python3.5/site-packages/tensorflow/python/estimator/estimator.py", line 824, in _train_model
features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)
File "/Users/yangsong/tensorflow/lib/python3.5/site-packages/tensorflow/python/estimator/estimator.py", line 805, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "mnist.py", line 89, in model_fn
model = create_model(params['data_format'])
File "mnist.py", line 83, in create_model
l.Dense(10)
File "/Users/yangsong/tensorflow/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/sequential.py", line 120, in init
self.add(layer)
File "/Users/yangsong/tensorflow/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/sequential.py", line 163, in add
raise ValueError('The first layer in a '
ValueError: The first layer in a Sequential model must get an input_shape argument.
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System information
- What is the top-level directory of the model you are using:
- 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):
- TensorFlow installed from (source or binary):
- TensorFlow version (use command below):
- Bazel version (if compiling from source):
- CUDA/cuDNN version:
- GPU model and memory:
- Exact command to reproduce:
You can collect some of this information using our environment capture script:
https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh
You can obtain the TensorFlow version with
python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
Describe the problem
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Source code / logs
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