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| author |  Shanqing Cai <cais@google.com> | 2017-02-20 04:07:32 +0000 |
|---|---|---|
| committer |  GitHub <noreply@github.com> | 2017-02-20 04:07:32 +0000 |
| commit | 195b3063e48e089cceeeb165e50eef90122f3344 (patch) | |
| tree | 4881dcc5c4d1a0a1085691fa682930adf16ebb68 | |
| parent | bbe05bf0e87c6030012a66a9fd0e3de977269215 (diff) | |
| parent | 68ebdc9a2029ae82f7d665f131823f9f580b658b (diff) | |
Merge pull request #7673 from aldanor/bugfix/example-mnist-layer-import
Make learn/mnist.py work again
| -rw-r--r-- | tensorflow/examples/learn/mnist.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/examples/learn/mnist.py b/tensorflow/examples/learn/mnist.py index 6e5fe7891b..15cf4b91dd 100644 --- a/tensorflow/examples/learn/mnist.py +++ b/tensorflow/examples/learn/mnist.py @@ -46,13 +46,13 @@ def conv_model(feature, target, mode): # First conv layer will compute 32 features for each 5x5 patch with tf.variable_scope('conv_layer1'): - h_conv1 = layers.convolution( + h_conv1 = layers.convolution2d( feature, 32, kernel_size=[5, 5], activation_fn=tf.nn.relu) h_pool1 = max_pool_2x2(h_conv1) # Second conv layer will compute 64 features for each 5x5 patch. with tf.variable_scope('conv_layer2'): - h_conv2 = layers.convolution( + h_conv2 = layers.convolution2d( h_pool1, 64, kernel_size=[5, 5], activation_fn=tf.nn.relu) h_pool2 = max_pool_2x2(h_conv2) # reshape tensor into a batch of vectors |