experiments/STT
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Updating DeepSpeech for 0.10 API

Browse Source
This commit is contained in:
Alexandre Lissy 2016-08-09 18:57:46 +02:00
parent 78c93711f1
commit 8592093ffc
1 changed files with 16 additions and 17 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
DeepSpeech.ipynb
View File

@ -101,8 +101,7 @@
"outputs": [], "outputs": [],
"source": [ "source": [
"import tensorflow as tf\n", "import tensorflow as tf\n",
"from tensorflow.python.ops.constant_op import constant\n", "from tensorflow.python.framework.constant_op import constant\n",
"from tensorflow.models.rnn import rnn, rnn_cell\n",
"import numpy as np" "import numpy as np"
] ]
}, },
@ -513,19 +512,19 @@
" \n", " \n",
" # Define lstm cells with tensorflow\n", " # Define lstm cells with tensorflow\n",
" # Forward direction cell\n", " # Forward direction cell\n",
" lstm_fw_cell = rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n", " lstm_fw_cell = tf.nn.rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n",
" # Backward direction cell\n", " # Backward direction cell\n",
" lstm_bw_cell = rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n", " lstm_bw_cell = tf.nn.rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n",
" \n", " \n",
" # Split data because rnn cell needs a list of inputs for the BRNN inner loop\n", " # Split data because rnn cell needs a list of inputs for the BRNN inner loop\n",
" layer_3 = tf.split(0, n_steps, layer_3)\n", " layer_3 = tf.split(0, n_steps, layer_3)\n",
" \n", " \n",
" # Get lstm cell output\n", " # Get lstm cell output\n",
" outputs = rnn.bidirectional_rnn(lstm_fw_cell,\n", " outputs = tf.nn.bidirectional_rnn(lstm_fw_cell,\n",
" lstm_bw_cell,\n", " lstm_bw_cell,\n",
" layer_3,\n", " layer_3,\n",
" initial_state_fw=_istate_fw,\n", " initial_state_fw=_istate_fw,\n",
" initial_state_bw=_istate_bw)\n", " initial_state_bw=_istate_bw)\n",
" \n", " \n",
" # Reshape outputs from a list of n_steps tensors each of shape [batch_size, 2*n_cell_dim]\n", " # Reshape outputs from a list of n_steps tensors each of shape [batch_size, 2*n_cell_dim]\n",
" # to a single tensor of shape [n_steps*batch_size, 2*n_cell_dim]\n", " # to a single tensor of shape [n_steps*batch_size, 2*n_cell_dim]\n",
@ -585,9 +584,9 @@
"```python\n", "```python\n",
" # Define lstm cells with tensorflow\n", " # Define lstm cells with tensorflow\n",
" # Forward direction cell\n", " # Forward direction cell\n",
" lstm_fw_cell = rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n", " lstm_fw_cell = tf.nn.rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n",
" # Backward direction cell\n", " # Backward direction cell\n",
" lstm_bw_cell = rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n", " lstm_bw_cell = tf.nn.rnn_cell.BasicLSTMCell(n_cell_dim, forget_bias=1.0)\n",
"```\n", "```\n",
"both of which have inputs of length `n_cell_dim` and bias `1.0` for the forget gate of the LSTM.\n", "both of which have inputs of length `n_cell_dim` and bias `1.0` for the forget gate of the LSTM.\n",
"\n", "\n",
@ -601,11 +600,11 @@
"The next line of `BiRNN`\n", "The next line of `BiRNN`\n",
"```python\n", "```python\n",
" # Get lstm cell output\n", " # Get lstm cell output\n",
" outputs = rnn.bidirectional_rnn(lstm_fw_cell,\n", " outputs = tf.nn.bidirectional_rnn(lstm_fw_cell,\n",
" lstm_bw_cell,\n", " lstm_bw_cell,\n",
" layer_3,\n", " layer_3,\n",
" initial_state_fw=_istate_fw,\n", " initial_state_fw=_istate_fw,\n",
" initial_state_bw=_istate_bw)\n", " initial_state_bw=_istate_bw)\n",
"```\n", "```\n",
"feeds `layer_3` to the LSTM BRNN cell and obtains the LSTM BRNN output.\n", "feeds `layer_3` to the LSTM BRNN cell and obtains the LSTM BRNN output.\n",
"\n", "\n",
@ -1224,7 +1223,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 20, "execution_count": null,
"metadata": { "metadata": {
"collapsed": true "collapsed": true
}, },