return Expression of total loss

return Expression of total loss

return Expression of total loss

return Expression of total loss

<summary> <para>Initialize dynet with the current dynetparams object.</para> <remarks>This is one way, you can't uninitialize dynet</remarks> </summar

return Expression for total loss

<summary> <para>VanillaLSTM allows to create an "standard" LSTM, ie with decoupled input and forget gate and no peepholes connections</para> <para>For

Adds a subcollection.

Computes argmax

* \brief signature for automatic batching * \detail This will be equal only for nodes that can be combined. Returns * 0 for unbatchable

Returns the size of a batch. The returned value is equal to the product of all dimensions with in a batch. # Examples ``` # use dynet::Dim; let dim

Applies block dropout

Computes circular convolution.

Computes circular correlation.

Computes columnwise addition.

Looks up constant parameters.

Contracts a rank 3 tensor and two rank 1 tensor into a rank 1 tensor

Applies dropout to entire elements of a minibatch

Applies dropout along a specific dimension

* \brief Batched encoding * \details Encodes a batch of sentences of the same size (don't forget to pad them) * * \param isents Whole d

Convolution operation

perform the forward/backward passes in one or multiple calls TODO: This is a lot of code for something simple. Can it be shortened?

* \brief Computes the negative log probability on a batch * * \param sents Full training set * \param id Start index of the batch * \param

Returns the output of any hidden layer.

Check if the indent exists

Returns the state of any hidden layer.

Initializes one paticular column of the values in the parameter.

Returns update status of the parameter.

Convolution operation

Performs layer normalization

wget -O - http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz | gunzip > train-images-idx3-ubyte wget -O - http://yann.lecun.com/exdb