To begin, you'll simply need the latest version of TensorFlow installed.
First make sure you've [added the models folder to your Python path](/official/#running-the-models); otherwise you may encounter an error like `ImportError: No module named official.mnist`.
@@ -18,8 +18,9 @@ Please proceed according to which dataset you would like to train/evaluate on:
### Setup
You simply need to have the latest version of TensorFlow installed.
First make sure you've [added the models folder to your Python path](/official/#running-the-models); otherwise you may encounter an error like `ImportError: No module named official.resnet`.
First download and extract the CIFAR-10 data from Alex's website, specifying the location with the `--data_dir` flag. Run the following:
Then download and extract the CIFAR-10 data from Alex's website, specifying the location with the `--data_dir` flag. Run the following:
@@ -15,7 +15,7 @@ The input function for the `Estimator` uses `tf.contrib.data.TextLineDataset`, w
The `Estimator` and `Dataset` APIs are both highly encouraged for fast development and efficient training.
## Running the code
Make sure to run the command to export the `/models` folder to the python path: https://github.com/tensorflow/models/tree/master/official#running-the-models
First make sure you've [added the models folder to your Python path](/official/#running-the-models); otherwise you may encounter an error like `ImportError: No module named official.wide_deep`.
### Setup
The [Census Income Data Set](https://archive.ics.uci.edu/ml/datasets/Census+Income) that this sample uses for training is hosted by the [UC Irvine Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/). We have provided a script that downloads and cleans the necessary files.
