Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Modifying the text_generation.ipynb #1313

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Modifying the text_generation.ipynb #1313

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
28 changes: 15 additions & 13 deletions docs/tutorials/text_generation.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -160,7 +160,9 @@
"\n",
"import numpy as np\n",
"import os\n",
"import time"
"import time",
"!pip install tf-keras",
"import tf_keras as keras"
]
},
{
Expand All @@ -182,7 +184,7 @@
},
"outputs": [],
"source": [
"path_to_file = tf.keras.utils.get_file('shakespeare.txt', 'https://storage.googleapis.com/download.tensorflow.org/data/shakespeare.txt')"
"path_to_file = keras.utils.get_file('shakespeare.txt', 'https://storage.googleapis.com/download.tensorflow.org/data/shakespeare.txt')"
]
},
{
Expand Down Expand Up @@ -288,7 +290,7 @@
},
"outputs": [],
"source": [
"ids_from_chars = tf.keras.layers.StringLookup(\n",
"ids_from_chars = keras.layers.StringLookup(\n",
" vocabulary=list(vocab), mask_token=None)"
]
},
Expand Down Expand Up @@ -339,7 +341,7 @@
},
"outputs": [],
"source": [
"chars_from_ids = tf.keras.layers.StringLookup(\n",
"chars_from_ids = keras.layers.StringLookup(\n",
" vocabulary=ids_from_chars.get_vocabulary(), invert=True, mask_token=None)"
]
},
Expand Down Expand Up @@ -671,14 +673,14 @@
},
"outputs": [],
"source": [
"class MyModel(tf.keras.Model):\n",
"class MyModel(keras.Model):\n",
" def __init__(self, vocab_size, embedding_dim, rnn_units):\n",
" super().__init__(self)\n",
" self.embedding = tf.keras.layers.Embedding(vocab_size, embedding_dim)\n",
" self.gru = tf.keras.layers.GRU(rnn_units,\n",
" self.embedding = keras.layers.Embedding(vocab_size, embedding_dim)\n",
" self.gru = keras.layers.GRU(rnn_units,\n",
" return_sequences=True,\n",
" return_state=True)\n",
" self.dense = tf.keras.layers.Dense(vocab_size)\n",
" self.dense = keras.layers.Dense(vocab_size)\n",
"\n",
" def call(self, inputs, states=None, return_state=False, training=False):\n",
" x = inputs\n",
Expand Down Expand Up @@ -974,7 +976,7 @@
"# Name of the checkpoint files\n",
"checkpoint_prefix = os.path.join(checkpoint_dir, \"ckpt_{epoch}\")\n",
"\n",
"checkpoint_callback = tf.keras.callbacks.ModelCheckpoint(\n",
"checkpoint_callback = keras.callbacks.ModelCheckpoint(\n",
" filepath=checkpoint_prefix,\n",
" save_weights_only=True)"
]
Expand Down Expand Up @@ -1058,7 +1060,7 @@
},
"outputs": [],
"source": [
"class OneStep(tf.keras.Model):\n",
"class OneStep(keras.Model):\n",
" def __init__(self, model, chars_from_ids, ids_from_chars, temperature=1.0):\n",
" super().__init__()\n",
" self.temperature = temperature\n",
Expand Down Expand Up @@ -1306,8 +1308,8 @@
},
"outputs": [],
"source": [
"model.compile(optimizer = tf.keras.optimizers.Adam(),\n",
" loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True))"
"model.compile(optimizer = keras.optimizers.Adam(),\n",
" loss=keras.losses.SparseCategoricalCrossentropy(from_logits=True))"
]
},
{
Expand Down Expand Up @@ -1345,7 +1347,7 @@
"for epoch in range(EPOCHS):\n",
" start = time.time()\n",
"\n",
" mean.reset_states()\n",
" mean.reset_state()\n",
" for (batch_n, (inp, target)) in enumerate(dataset):\n",
" logs = model.train_step([inp, target])\n",
" mean.update_state(logs['loss'])\n",
Expand Down