lib/exercises-in-programming-style
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Minor clean up

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This commit is contained in:
Crista Lopes
2020-01-01 15:45:18 -08:00
parent df289f0d2c
commit e0d99d546c
2 changed files with 10 additions and 9 deletions
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4
37-dense-shallow-monolithic/tf-37.py
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@@ -31,8 +31,8 @@ def decode_one_hot(y):
def normalization_layer_set_weights(n_layer): def normalization_layer_set_weights(n_layer):
wb = [] wb = []
w = np.zeros((LINE_SIZE*INPUT_VOCAB_SIZE, LINE_SIZE*INPUT_VOCAB_SIZE), dtype=np.float32) w = np.zeros((LINE_SIZE*INPUT_VOCAB_SIZE, LINE_SIZE*INPUT_VOCAB_SIZE))
b = np.zeros((LINE_SIZE*INPUT_VOCAB_SIZE), dtype=np.float32) b = np.zeros((LINE_SIZE*INPUT_VOCAB_SIZE))
for r in range(0, LINE_SIZE*INPUT_VOCAB_SIZE, INPUT_VOCAB_SIZE): for r in range(0, LINE_SIZE*INPUT_VOCAB_SIZE, INPUT_VOCAB_SIZE):
# Let lower case letters go through # Let lower case letters go through
for c in string.ascii_lowercase: for c in string.ascii_lowercase:

15
38-sliding-window/tf-38.py
View File

@@ -11,7 +11,7 @@ INPUT_VOCAB_SIZE = len(characters)
WINDOW_SIZE = 3 WINDOW_SIZE = 3
def encode_one_hot(line): def encode_one_hot(line):
line = " " + line line = " " + line + " "
x = np.zeros((len(line), INPUT_VOCAB_SIZE)) x = np.zeros((len(line), INPUT_VOCAB_SIZE))
for i, c in enumerate(line): for i, c in enumerate(line):
index = char_indices[c] if c in characters else char_indices[' '] index = char_indices[c] if c in characters else char_indices[' ']
@@ -35,8 +35,8 @@ def prepare_for_window(x):
def normalization_layer_set_weights(n_layer): def normalization_layer_set_weights(n_layer):
wb = [] wb = []
w = np.zeros((WINDOW_SIZE*INPUT_VOCAB_SIZE, INPUT_VOCAB_SIZE), dtype=np.float32) w = np.zeros((WINDOW_SIZE*INPUT_VOCAB_SIZE, INPUT_VOCAB_SIZE))
b = np.zeros((INPUT_VOCAB_SIZE), dtype=np.float32) b = np.zeros((INPUT_VOCAB_SIZE))
# Let lower case letters go through # Let lower case letters go through
for c in string.ascii_lowercase: for c in string.ascii_lowercase:
i = char_indices[c] i = char_indices[c]
@@ -48,11 +48,12 @@ def normalization_layer_set_weights(n_layer):
w[INPUT_VOCAB_SIZE+i, il] = 1 w[INPUT_VOCAB_SIZE+i, il] = 1
# Map all non-letters to space # Map all non-letters to space
sp_idx = char_indices[' '] sp_idx = char_indices[' ']
for c in [c for c in list(string.printable) if c not in list(string.ascii_letters)]: non_letters = [c for c in list(characters) if c not in list(string.ascii_letters)]
for c in non_letters:
i = char_indices[c] i = char_indices[c]
w[INPUT_VOCAB_SIZE+i, sp_idx] = 1 w[INPUT_VOCAB_SIZE+i, sp_idx] = 1
# Map single letters to space # Map single letters to space
for c in [c for c in list(string.printable) if c not in list(string.ascii_letters)]: for c in non_letters:
i = char_indices[c] i = char_indices[c]
w[i, sp_idx] = 0.75 w[i, sp_idx] = 0.75
w[INPUT_VOCAB_SIZE*2+i, sp_idx] = 0.75 w[INPUT_VOCAB_SIZE*2+i, sp_idx] = 0.75
@@ -66,8 +67,8 @@ def build_model():
# Normalize characters using a dense layer # Normalize characters using a dense layer
model = Sequential() model = Sequential()
dense_layer = Dense(INPUT_VOCAB_SIZE, dense_layer = Dense(INPUT_VOCAB_SIZE,
input_shape=(WINDOW_SIZE*INPUT_VOCAB_SIZE,), input_shape=(WINDOW_SIZE*INPUT_VOCAB_SIZE,),
activation='softmax') activation='softmax')
model.add(dense_layer) model.add(dense_layer)
return model return model