diff options
Diffstat (limited to 'tensorflow/models/image')
| -rw-r--r-- | tensorflow/models/image/alexnet/alexnet_benchmark.py | 2 | ||||
| -rw-r--r-- | tensorflow/models/image/cifar10/cifar10.py | 10 | ||||
| -rw-r--r-- | tensorflow/models/image/cifar10/cifar10_multi_gpu_train.py | 2 |
3 files changed, 7 insertions, 7 deletions
diff --git a/tensorflow/models/image/alexnet/alexnet_benchmark.py b/tensorflow/models/image/alexnet/alexnet_benchmark.py index d70f213708..0baedcc9e9 100644 --- a/tensorflow/models/image/alexnet/alexnet_benchmark.py +++ b/tensorflow/models/image/alexnet/alexnet_benchmark.py @@ -164,7 +164,7 @@ def time_tensorflow_run(session, target, info_string): Args: session: the TensorFlow session to run the computation under. - target: the targe Tensor that is passed to the session's run() function. + target: the target Tensor that is passed to the session's run() function. info_string: a string summarizing this run, to be printed with the stats. Returns: diff --git a/tensorflow/models/image/cifar10/cifar10.py b/tensorflow/models/image/cifar10/cifar10.py index 32234db496..ef89becf52 100644 --- a/tensorflow/models/image/cifar10/cifar10.py +++ b/tensorflow/models/image/cifar10/cifar10.py @@ -230,7 +230,7 @@ def inference(images): weights = _variable_with_weight_decay('weights', shape=[dim, 384], stddev=0.04, wd=0.004) biases = _variable_on_cpu('biases', [384], tf.constant_initializer(0.1)) - local3 = tf.nn.relu_layer(reshape, weights, biases, name=scope.name) + local3 = tf.nn.relu(tf.matmul(reshape, weights) + biases, name=scope.name) _activation_summary(local3) # local4 @@ -238,7 +238,7 @@ def inference(images): weights = _variable_with_weight_decay('weights', shape=[384, 192], stddev=0.04, wd=0.004) biases = _variable_on_cpu('biases', [192], tf.constant_initializer(0.1)) - local4 = tf.nn.relu_layer(local3, weights, biases, name=scope.name) + local4 = tf.nn.relu(tf.matmul(local3, weights) + biases, name=scope.name) _activation_summary(local4) # softmax, i.e. softmax(WX + b) @@ -247,7 +247,7 @@ def inference(images): stddev=1/192.0, wd=0.0) biases = _variable_on_cpu('biases', [NUM_CLASSES], tf.constant_initializer(0.0)) - softmax_linear = tf.nn.xw_plus_b(local4, weights, biases, name=scope.name) + softmax_linear = tf.add(tf.matmul(local4, weights), biases, name=scope.name) _activation_summary(softmax_linear) return softmax_linear @@ -301,7 +301,7 @@ def _add_loss_summaries(total_loss): losses = tf.get_collection('losses') loss_averages_op = loss_averages.apply(losses + [total_loss]) - # Attach a scalar summmary to all individual losses and the total loss; do the + # Attach a scalar summary to all individual losses and the total loss; do the # same for the averaged version of the losses. for l in losses + [total_loss]: # Name each loss as '(raw)' and name the moving average version of the loss @@ -384,5 +384,5 @@ def maybe_download_and_extract(): reporthook=_progress) print() statinfo = os.stat(filepath) - print('Succesfully downloaded', filename, statinfo.st_size, 'bytes.') + print('Successfully downloaded', filename, statinfo.st_size, 'bytes.') tarfile.open(filepath, 'r:gz').extractall(dest_directory) diff --git a/tensorflow/models/image/cifar10/cifar10_multi_gpu_train.py b/tensorflow/models/image/cifar10/cifar10_multi_gpu_train.py index 9ba4730b31..f594b86627 100644 --- a/tensorflow/models/image/cifar10/cifar10_multi_gpu_train.py +++ b/tensorflow/models/image/cifar10/cifar10_multi_gpu_train.py @@ -95,7 +95,7 @@ def tower_loss(scope): loss_averages = tf.train.ExponentialMovingAverage(0.9, name='avg') loss_averages_op = loss_averages.apply(losses + [total_loss]) - # Attach a scalar summmary to all individual losses and the total loss; do the + # Attach a scalar summary to all individual losses and the total loss; do the # same for the averaged version of the losses. for l in losses + [total_loss]: # Remove 'tower_[0-9]/' from the name in case this is a multi-GPU training |