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| author |  Yash Katariya <yash.katariya10@gmail.com> | 2018-08-11 22:49:07 -0400 |
|---|---|---|
| committer | Yash Katariya <yash.katariya10@gmail.com> | 2018-08-11 22:49:07 -0400 |
| commit | b416db37a20aa1945f928a2c253ae0a8a139c20f (patch) | |
| tree | f1d02c921edfb9dd1b4fa17f9038a7322db06a12 /tensorflow/contrib/eager | |
| parent | d8802756db92bbf032c1d8ee6fbed1aaf873c8fa (diff) | |
Replacing tf.contrib.data.batch_and_drop_remainder by batch(..., drop_remainder=True). Also checkpointing at (epoch + 1) % x while saving the model to consider the last epoch's variables.
Diffstat (limited to 'tensorflow/contrib/eager')
4 files changed, 8 insertions, 7 deletions
diff --git a/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb b/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb index 975105a179..5621d6a358 100644 --- a/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb +++ b/tensorflow/contrib/eager/python/examples/generative_examples/dcgan.ipynb @@ -495,7 +495,7 @@ " random_vector_for_generation)\n", " \n", " # saving (checkpoint) the model every 15 epochs\n", - " if epoch % 15 == 0:\n", + " if (epoch + 1) % 15 == 0:\n", " checkpoint.save(file_prefix = checkpoint_prefix)\n", " \n", " print ('Time taken for epoch {} is {} sec'.format(epoch + 1,\n", diff --git a/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb b/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb index 78a711548d..8c1d6480e7 100644 --- a/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb +++ b/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb @@ -132,6 +132,7 @@ "tf.enable_eager_execution()\n", "\n", "import numpy as np\n", + "import os\n", "import re\n", "import random\n", "import unidecode\n", @@ -313,7 +314,7 @@ "outputs": [], "source": [ "dataset = tf.data.Dataset.from_tensor_slices((input_text, target_text)).shuffle(BUFFER_SIZE)\n", - "dataset = dataset.apply(tf.contrib.data.batch_and_drop_remainder(BATCH_SIZE))" + "dataset = dataset.batch(BATCH_SIZE, drop_remainder=True)" ] }, { @@ -493,7 +494,7 @@ "source": [ "# Training step\n", "\n", - "EPOCHS = 30\n", + "EPOCHS = 20\n", "\n", "for epoch in range(EPOCHS):\n", " start = time.time()\n", @@ -520,7 +521,7 @@ " batch,\n", " loss))\n", " # saving (checkpoint) the model every 5 epochs\n", - " if epoch % 5 == 0:\n", + " if (epoch + 1) % 5 == 0:\n", " checkpoint.save(file_prefix = checkpoint_prefix)\n", "\n", " print ('Epoch {} Loss {:.4f}'.format(epoch+1, loss))\n", diff --git a/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb b/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb index 1d07721e3b..08d8364978 100644 --- a/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb +++ b/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb @@ -319,7 +319,7 @@ "vocab_tar_size = len(targ_lang.word2idx)\n", "\n", "dataset = tf.data.Dataset.from_tensor_slices((input_tensor_train, target_tensor_train)).shuffle(BUFFER_SIZE)\n", - "dataset = dataset.apply(tf.contrib.data.batch_and_drop_remainder(BATCH_SIZE))" + "dataset = dataset.batch(BATCH_SIZE, drop_remainder=True)" ] }, { @@ -619,7 +619,7 @@ " batch,\n", " batch_loss.numpy()))\n", " # saving (checkpoint) the model every 2 epochs\n", - " if epoch % 2 == 0:\n", + " if (epoch + 1) % 2 == 0:\n", " checkpoint.save(file_prefix = checkpoint_prefix)\n", " \n", " print('Epoch {} Loss {:.4f}'.format(epoch + 1,\n", diff --git a/tensorflow/contrib/eager/python/examples/pix2pix/pix2pix_eager.ipynb b/tensorflow/contrib/eager/python/examples/pix2pix/pix2pix_eager.ipynb index acc0f5b653..ee25d25b52 100644 --- a/tensorflow/contrib/eager/python/examples/pix2pix/pix2pix_eager.ipynb +++ b/tensorflow/contrib/eager/python/examples/pix2pix/pix2pix_eager.ipynb @@ -701,7 +701,7 @@ " generate_images(generator, inp, tar)\n", " \n", " # saving (checkpoint) the model every 20 epochs\n", - " if epoch % 20 == 0:\n", + " if (epoch + 1) % 20 == 0:\n", " checkpoint.save(file_prefix = checkpoint_prefix)\n", "\n", " print ('Time taken for epoch {} is {} sec\\n'.format(epoch + 1,\n", |