onnx
tutorials/tutorials/assets/tf-train-mnist.py not working
getting the following error when running this script
⟩ python tf-train-mnist.py
WARNING:tensorflow:From tf-train-mnist.py:125: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.
WARNING:tensorflow:From /usr/local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Please write your own downloading logic.
WARNING:tensorflow:From /usr/local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:252: wrapped_fn (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Please use urllib or similar directly.
Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.
WARNING:tensorflow:From /usr/local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz
Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.
WARNING:tensorflow:From /usr/local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz
Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.
Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz
Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.
Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz
WARNING:tensorflow:From /usr/local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:290: __init__ (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.
Saving graph to: /var/folders/xg/lb58443132sb9khl0f8k7m700000gn/T/tmpaitUPD
2018-06-27 11:53:51.868247: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-06-27 11:53:52.129638: E tensorflow/core/common_runtime/executor.cc:660] Executor failed to create kernel. Invalid argument: Default MaxPoolingOp only supports NHWC on device type CPU
[[Node: pool1/MaxPool = MaxPool[T=DT_FLOAT, data_format="NCHW", ksize=[1, 1, 2, 2], padding="SAME", strides=[1, 1, 2, 2], _device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/Relu)]]
Traceback (most recent call last):
File "tf-train-mnist.py", line 183, in <module>
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "tf-train-mnist.py", line 167, in main
x: batch[0], y_: batch[1]})
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 710, in eval
return _eval_using_default_session(self, feed_dict, self.graph, session)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 5180, in _eval_using_default_session
return session.run(tensors, feed_dict)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 900, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1135, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1316, in _do_run
run_metadata)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1335, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Default MaxPoolingOp only supports NHWC on device type CPU
[[Node: pool1/MaxPool = MaxPool[T=DT_FLOAT, data_format="NCHW", ksize=[1, 1, 2, 2], padding="SAME", strides=[1, 1, 2, 2], _device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/Relu)]]
Caused by op u'pool1/MaxPool', defined at:
File "tf-train-mnist.py", line 183, in <module>
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "tf-train-mnist.py", line 131, in main
y_conv = deepnn(x)
File "tf-train-mnist.py", line 69, in deepnn
h_pool1 = max_pool_2x2(h_conv1)
File "tf-train-mnist.py", line 108, in max_pool_2x2
strides=[1, 1, 2, 2], padding='SAME', data_format="NCHW")
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/nn_ops.py", line 2142, in max_pool
name=name)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 4604, in max_pool
data_format=data_format, name=name)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3392, in create_op
op_def=op_def)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1718, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InvalidArgumentError (see above for traceback): Default MaxPoolingOp only supports NHWC on device type CPU
[[Node: pool1/MaxPool = MaxPool[T=DT_FLOAT, data_format="NCHW", ksize=[1, 1, 2, 2], padding="SAME", strides=[1, 1, 2, 2], _device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/Relu)]]
python test1.py --device=cpu --data_format=NHWC WARNING:tensorflow:From test1.py:122: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use alternatives such as official/mnist/dataset.py from tensorflow/models. WARNING:tensorflow:From /Users/liusichao/anaconda3/envs/py3.6/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version. Instructions for updating: Please write your own downloading logic. WARNING:tensorflow:From /Users/liusichao/anaconda3/envs/py3.6/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use tf.data to implement this functionality. Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz WARNING:tensorflow:From /Users/liusichao/anaconda3/envs/py3.6/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use tf.data to implement this functionality. Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz WARNING:tensorflow:From /Users/liusichao/anaconda3/envs/py3.6/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:290: DataSet.init (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. Instructions for updating: Please use alternatives such as official/mnist/dataset.py from tensorflow/models. Saving graph to: /var/folders/5x/prh0yx817bz_gky7k98hnvnc0000gn/T/tmpsbp0zfjd 2018-07-10 14:17:05.739052: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2018-07-10 14:17:05.988595: E tensorflow/core/common_runtime/executor.cc:660] Executor failed to create kernel. Invalid argument: Default MaxPoolingOp only supports NHWC on device type CPU [[Node: pool1/MaxPool = MaxPoolT=DT_FLOAT, data_format="NCHW", ksize=[1, 1, 2, 2], padding="SAME", strides=[1, 1, 2, 2], _device="/job:localhost/replica:0/task:0/device:CPU:0"]] Traceback (most recent call last): File "/Users/liusichao/anaconda3/envs/py3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1322, in _do_call return fn(*args) File "/Users/liusichao/anaconda3/envs/py3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1307, in _run_fn options, feed_dict, fetch_list, target_list, run_metadata) File "/Users/liusichao/anaconda3/envs/py3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1409, in _call_tf_sessionrun run_metadata) tensorflow.python.framework.errors_impl.InvalidArgumentError: Default MaxPoolingOp only supports NHWC on device type CPU [[Node: pool1/MaxPool = MaxPoolT=DT_FLOAT, data_format="NCHW", ksize=[1, 1, 2, 2], padding="SAME", strides=[1, 1, 2, 2], _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "test1.py", line 180, in
Caused by op 'pool1/MaxPool', defined at:
File "test1.py", line 180, in
InvalidArgumentError (see above for traceback): Default MaxPoolingOp only supports NHWC on device type CPU [[Node: pool1/MaxPool = MaxPoolT=DT_FLOAT, data_format="NCHW", ksize=[1, 1, 2, 2], padding="SAME", strides=[1, 1, 2, 2], _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
I have deal with this problem. data_format="NCHW". This data format is for GPU training. So you need to train it in GPU machine
Not sure when you mentioned that this data format is for GPU training. does it work on CPU?
I have made the changes in the .py file to run it Like: Previous W_conv1 = weight_variable([5, 5, 1, 32]) b_conv1 = bias_variable([32]) h_conv1 = tf.nn.relu(add(conv2d(x_image, W_conv1), b_conv1))
Changed by this New #W_conv1 = weight_variable([5, 5, 1, 32]) #b_conv1 = bias_variable([32]) h_conv1 = tf.layers.conv2d(x_image, 32, 5, activation=tf.nn.relu)
