Merge pull request rasbt#43 from rasbt/ch16-figs

Ch16 figs
shalevy1 · Nov 4, 2019 · 9e2550b · 9e2550b
2 parents 397df59 + 3b4798e
commit 9e2550b
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diff --git a/ch16/ch16_part1.ipynb b/ch16/ch16_part1.ipynb
diff --git a/ch16/ch16_part1.py b/ch16/ch16_part1.py
@@ -31,22 +31,57 @@
 
 
 
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 # # Introducing sequential data
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 # ## Modeling sequential data⁠—order matters
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 # ## Representing sequences
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 # ## The different categories of sequence modeling
 
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 # # RNNs for modeling sequences
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 # ## Understanding the RNN looping mechanism
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 # ## Computing activations in an RNN
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 # ## Hidden-recurrence vs. output-recurrence
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 # ## The challenges of learning long-range interactions
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 # ## Long Short-Term Memory cells 
 
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 # # Implementing RNNs for sequence modeling in TensorFlow
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 # ## Project one: predicting the sentiment of IMDb movie reviews
@@ -261,7 +306,7 @@ def encode_map_fn(text, label):
     32, padded_shapes=([-1],[]))
 
 
-# #### Embedding layers for sentence encoding
+# ### Embedding layers for sentence encoding
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 #  * `input_dim`: number of words, i.e. maximum integer index + 1.
@@ -281,6 +326,10 @@ def encode_map_fn(text, label):
 
 
 
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 model = tf.keras.Sequential()
 
 model.add(Embedding(input_dim=100,

diff --git a/ch16/ch16_part2.ipynb b/ch16/ch16_part2.ipynb
diff --git a/ch16/ch16_part2.py b/ch16/ch16_part2.py
@@ -21,8 +21,17 @@
 
 
 
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 # ## Project two: character-level language modeling in TensorFlow
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 # ### Preprocessing the dataset
 
 
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 chars_sorted = sorted(char_set)
 char2int = {ch:i for i,ch in enumerate(chars_sorted)}
 char_array = np.array(chars_sorted)
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 ds_text_encoded = tf.data.Dataset.from_tensor_slices(text_encoded)
 
 for ex in ds_text_encoded.take(5):
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 ## define the function for splitting x & y
 def split_input_target(chunk):
     input_seq = chunk[:-1]
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 # ## A basic version of self-attention
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 # ### Parameterizing the self-attention mechanism with query, key, and value weights
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 # ## Multi-head attention and the Transformer block
 
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 # 
 # ...
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