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[Library] fixing #696 #939

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merged 2 commits into from
Sep 19, 2018
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[Library] fixing #696 #939

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aa3f4ec
fixing #696
vince62s Sep 3, 2018
38ce8a5
more fix to Library
vince62s Sep 4, 2018
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fixing #696
  • Loading branch information
@vince62s
vince62s committed Sep 3, 2018
commit aa3f4ecc57f458ea02a722ac0822085cbf3a03e1
31 changes: 16 additions & 15 deletions docs/source/Library.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -12,8 +12,9 @@
"import torch.nn as nn\n",
"\n",
"import onmt\n",
"import onmt.io\n",
"import onmt.modules"
"import onmt.inputters\n",
"import onmt.modules\n",
"import onmt.utils"
]
},
{
Expand All @@ -30,8 +31,8 @@
"outputs": [],
"source": [
"vocab = dict(torch.load(\"../../data/data.vocab.pt\"))\n",
"src_padding = vocab[\"src\"].stoi[onmt.io.PAD_WORD]\n",
"tgt_padding = vocab[\"tgt\"].stoi[onmt.io.PAD_WORD]"
"src_padding = vocab[\"src\"].stoi[onmt.inputters.PAD_WORD]\n",
"tgt_padding = vocab[\"tgt\"].stoi[onmt.inputters.PAD_WORD]"
]
},
{
Expand All @@ -53,22 +54,22 @@
"encoder_embeddings = onmt.modules.Embeddings(emb_size, len(vocab[\"src\"]),\n",
" word_padding_idx=src_padding)\n",
"\n",
"encoder = onmt.modules.RNNEncoder(hidden_size=rnn_size, num_layers=1, \n",
"encoder = onmt.encoders.RNNEncoder(hidden_size=rnn_size, num_layers=1, \n",
" rnn_type=\"LSTM\", bidirectional=True,\n",
" embeddings=encoder_embeddings)\n",
"\n",
"decoder_embeddings = onmt.modules.Embeddings(emb_size, len(vocab[\"tgt\"]),\n",
" word_padding_idx=tgt_padding)\n",
"decoder = onmt.modules.InputFeedRNNDecoder(hidden_size=rnn_size, num_layers=1, \n",
"decoder = onmt.decoders.decoder.InputFeedRNNDecoder(hidden_size=rnn_size, num_layers=1, \n",
" bidirectional_encoder=True,\n",
" rnn_type=\"LSTM\", embeddings=decoder_embeddings)\n",
"model = onmt.modules.NMTModel(encoder, decoder)\n",
"model = onmt.models.model.NMTModel(encoder, decoder)\n",
"\n",
"# Specify the tgt word generator and loss computation module\n",
"model.generator = nn.Sequential( \n",
" nn.Linear(rnn_size, len(vocab[\"tgt\"])), \n",
" nn.LogSoftmax())\n",
"loss = onmt.Loss.NMTLossCompute(model.generator, vocab[\"tgt\"]) "
"loss = onmt.utils.loss.NMTLossCompute(model.generator, vocab[\"tgt\"]) "
]
},
{
Expand All @@ -84,8 +85,8 @@
"metadata": {},
"outputs": [],
"source": [
"optim = onmt.Optim(method=\"sgd\", lr=1, max_grad_norm=2)\n",
"optim.set_parameters(model.parameters())"
"optim = onmt.utils.optimizers.Optimizer(method=\"sgd\", lr=1, max_grad_norm=2)\n",
"optim.set_parameters(model.named_parameters())"
]
},
{
Expand All @@ -102,8 +103,8 @@
"outputs": [],
"source": [
"# Load some data\n",
"data = torch.load(\"../../data/data.train.pt\")\n",
"valid_data = torch.load(\"../../data/data.valid.pt\")\n",
"data = torch.load(\"../../data/data.train.1.pt\")\n",
"valid_data = torch.load(\"../../data/data.valid.1.pt\")\n",
"data.load_fields(vocab)\n",
"valid_data.load_fields(vocab)\n",
"data.examples = data.examples[:100] "
Expand All @@ -122,11 +123,11 @@
"metadata": {},
"outputs": [],
"source": [
"train_iter = onmt.io.OrderedIterator( \n",
"train_iter = onmt.inputters.OrderedIterator( \n",
" dataset=data, batch_size=10, \n",
" device=-1, \n",
" repeat=False)\n",
"valid_iter = onmt.io.OrderedIterator( \n",
"valid_iter = onmt.inputters.OrderedIterator( \n",
" dataset=valid_data, batch_size=10, \n",
" device=-1,\n",
" train=False) "
Expand Down Expand Up @@ -176,7 +177,7 @@
}
],
"source": [
"trainer = onmt.Trainer(model, train_iter, valid_iter, loss, loss, optim)\n",
"trainer = onmt.Trainer(model, loss, loss, optim)\n",
"\n",
"def report_func(*args):\n",
" stats = args[-1]\n",
Expand Down