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Typo on #263 & #361 #4

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25 changes: 9 additions & 16 deletions DeepPATH_code/01_training/2Classes/inception/slim/README.md
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Expand Up @@ -9,8 +9,7 @@ keeping a model's architecture transparent and its hyperparameters explicit.
## Teaser

As a demonstration of the simplicity of using TF-Slim, compare the simplicity of
the code necessary for defining the entire [VGG]
(http://www.robots.ox.ac.uk/~vgg/research/very_deep/) network using TF-Slim to
the code necessary for defining the entire [VGG](http://www.robots.ox.ac.uk/~vgg/research/very_deep/) network using TF-Slim to
the lengthy and verbose nature of defining just the first three layers (out of
16) using native tensorflow:

Expand Down Expand Up @@ -244,12 +243,9 @@ number. More concretely, the scopes in the example above would be 'conv3_1',

### Scopes

In addition to the types of scope mechanisms in TensorFlow ([name_scope]
(https://www.tensorflow.org/api_docs/python/framework.html#name_scope),
[variable_scope]
(https://www.tensorflow.org/api_docs/python/state_ops.html#variable_scope),
TF-Slim adds a new scoping mechanism called "argument scope" or [arg_scope]
(scopes.py). This new scope allows a user to specify one or more operations and
In addition to the types of scope mechanisms in TensorFlow ([name_scope](https://www.tensorflow.org/api_docs/python/framework.html#name_scope),
[variable_scope](https://www.tensorflow.org/api_docs/python/state_ops.html#variable_scope),
TF-Slim adds a new scoping mechanism called "argument scope" or [arg_scope](./scopes.py). This new scope allows a user to specify one or more operations and
a set of arguments which will be passed to each of the operations defined in the
`arg_scope`. This functionality is best illustrated by example. Consider the
following code snippet:
Expand All @@ -264,7 +260,7 @@ It should be clear that these three Convolution layers share many of the same
hyperparameters. Two have the same padding, all three have the same weight_decay
and standard deviation of its weights. Not only do the duplicated values make
the code more difficult to read, it also adds the addition burder to the writer
of needing to doublecheck that all of the values are identical in each step. One
of needing to double-check that all of the values are identical in each step. One
solution would be to specify default values using variables:

```python
Expand Down Expand Up @@ -362,7 +358,7 @@ classes. For regression problems, this is often the sum-of-squares differences
between the predicted and true values.

Certain models, such as multi-task learning models, require the use of multiple
loss functions simultaneously. In other words, the loss function ultimatey being
loss functions simultaneously. In other words, the loss function ultimately being
minimized is the sum of various other loss functions. For example, consider a
model that predicts both the type of scene in an image as well as the depth from
the camera of each pixel. This model's loss function would be the sum of the
Expand Down Expand Up @@ -494,12 +490,9 @@ with tf.Session() as sess:
...
```

See [Restoring Variables]
(https://www.tensorflow.org/versions/r0.7/how_tos/variables/index.html#restoring-variables)
and [Choosing which Variables to Save and Restore]
(https://www.tensorflow.org/versions/r0.7/how_tos/variables/index.html#choosing-which-variables-to-save-and-restore)
sections of the [Variables]
(https://www.tensorflow.org/versions/r0.7/how_tos/variables/index.html) page for
See [Restoring Variables](https://www.tensorflow.org/versions/r0.7/how_tos/variables/index.html#restoring-variables)
and [Choosing which Variables to Save and Restore](https://www.tensorflow.org/versions/r0.7/how_tos/variables/index.html#choosing-which-variables-to-save-and-restore)
sections of the [Variables](https://www.tensorflow.org/versions/r0.7/how_tos/variables/index.html) page for
more details.

### Using slim.variables to Track which Variables need to be Restored
Expand Down