| __init__(self, encoder_output_dim, encoder_outputs, encoder_lengths, decoder_cell, decoder_state_dim, attention_type, weighted_encoder_outputs, attention_memory_optimization, kwargs) (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| __init__(self, name=None, forward_only=False, initializer=None) (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| apply(self, model, input_t, seq_lengths, states, timestep) (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| apply_over_sequence(self, model, inputs, seq_lengths=None, initial_states=None, outputs_with_grads=None) (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| apply_override(self, model, input_t, seq_lengths, timestep, extra_inputs=None) | caffe2.python.rnn_cell.RNNCell | |
| attention_memory_optimization (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| attention_type (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| build_initial_coverage(self, model) | caffe2.python.rnn_cell.AttentionCell | |
| coverage_weights (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| decoder_cell (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| decoder_state_dim (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| encoder_lengths (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| encoder_output_dim (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| encoder_outputs (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| encoder_outputs_transposed (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| forward_only (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| get_attention_weights(self) (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| get_output_dim(self) (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| get_output_state_index(self) (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| get_state_names(self) (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| get_state_names_override(self) | caffe2.python.rnn_cell.RNNCell | |
| hidden_t_intermediate (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| initializer(self) (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| initializer(self, value) (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| name (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| prepare_input(self, model, input_blob) (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |
| recompute_blobs (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| scope(self, name) (defined in caffe2.python.rnn_cell.RNNCell) | caffe2.python.rnn_cell.RNNCell | |
| weighted_encoder_outputs (defined in caffe2.python.rnn_cell.AttentionCell) | caffe2.python.rnn_cell.AttentionCell | |