/dports/misc/py-gluonnlp/gluon-nlp-0.10.0/scripts/natural_language_inference/ |
H A D | decomposable_attention.py | 34 def __init__(self, vocab_size, word_embed_size, hidden_size, argument 82 def __init__(self, inp_size, hidden_size, dropout=0., **kwargs): argument 119 def __init__(self, inp_size, hidden_size, num_class, dropout=0., **kwargs): argument
|
H A D | esim.py | 49 def __init__(self, vocab_size, num_classes, word_embed_size, hidden_size, dense_size, argument
|
/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/tests/python/frontend/pytorch/ |
H A D | test_lstm.py | 37 def __init__(self, input_size, hidden_size): argument 176 def lstm(input_size, hidden_size): argument 180 def stacked_lstm(input_size, hidden_size, num_layers): argument 189 def bidir_lstm(input_size, hidden_size): argument 193 def stacked_bidir_lstm(input_size, hidden_size, num_layers): argument
|
/dports/misc/py-gluonnlp/gluon-nlp-0.10.0/scripts/machine_translation/ |
H A D | gnmt.py | 71 def __init__(self, cell_type='lstm', num_layers=2, num_bi_layers=1, hidden_size=128, argument 165 num_layers=2, hidden_size=128, argument 460 num_bi_layers=1, hidden_size=128, dropout=0.0, use_residual=False, argument
|
H A D | hyperparameters.py | 27 hidden_size = 2048 variable
|
/dports/misc/py-onnx/onnx-1.10.2/onnx/defs/rnn/ |
H A D | old.cc | 208 hidden_size; in RNNShapeInference1() local 723 hidden_size; in RNNShapeInference2() local
|
H A D | defs.cc | 11 hidden_size; in RNNShapeInference() local
|
/dports/misc/py-gluonnlp/gluon-nlp-0.10.0/src/gluonnlp/model/ |
H A D | transformer.py | 90 def __init__(self, *, units=512, hidden_size=2048, dropout=0.0, use_residual=True, argument 199 def __init__(self, *, attention_cell='multi_head', units=128, hidden_size=512, num_heads=4, argument 314 def __init__(self, *, attention_cell='multi_head', num_layers=2, units=512, hidden_size=2048, argument 491 hidden_size=512, num_heads=4, scaled=True, argument 584 def __init__(self, attention_cell='multi_head', num_layers=2, units=128, hidden_size=2048, argument 881 units=512, hidden_size=2048, dropout=0.0, use_residual=True, argument
|
H A D | utils.py | 162 def _get_rnn_cell(mode, num_layers, input_size, hidden_size, argument 245 def _get_rnn_layer(mode, num_layers, input_size, hidden_size, dropout, weight_dropout): argument
|
H A D | bilm_encoder.py | 61 def __init__(self, mode, num_layers, input_size, hidden_size, dropout=0.0, argument
|
H A D | language_model.py | 65 def __init__(self, mode, vocab_size, embed_size, hidden_size, num_layers, argument 132 def __init__(self, mode, vocab_size, embed_size, hidden_size, argument 498 def __init__(self, vocab_size, embed_size, hidden_size, num_layers, argument
|
H A D | lstmpcellwithclip.py | 80 def __init__(self, hidden_size, projection_size, argument
|
/dports/misc/py-gluonnlp/gluon-nlp-0.10.0/tests/unittest/ |
H A D | test_sequence_sampler.py | 175 def __init__(self, vocab_size, hidden_size, prefix=None, params=None): argument 193 def __init__(self, vocab_size, hidden_size, prefix=None, params=None, use_tuple=False): argument 228 def __init__(self, vocab_size, hidden_size, prefix=None, params=None): argument
|
/dports/misc/mxnet/incubator-mxnet-1.9.0/python/mxnet/gluon/rnn/ |
H A D | rnn_layer.py | 35 def __init__(self, hidden_size, num_layers, layout, argument 387 def __init__(self, hidden_size, num_layers=1, activation='relu', argument 507 def __init__(self, hidden_size, num_layers=1, layout='TNC', argument 620 def __init__(self, hidden_size, num_layers=1, layout='TNC', argument
|
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/python/mxnet/gluon/rnn/ |
H A D | rnn_layer.py | 35 def __init__(self, hidden_size, num_layers, layout, argument 387 def __init__(self, hidden_size, num_layers=1, activation='relu', argument 507 def __init__(self, hidden_size, num_layers=1, layout='TNC', argument 620 def __init__(self, hidden_size, num_layers=1, layout='TNC', argument
|
/dports/math/py-theano/Theano-1.0.5/theano/gpuarray/c_code/ |
H A D | dnn_rnn_desc.c | 3 int dnn_rnn_desc(int hidden_size, int num_layers, in dnn_rnn_desc()
|
/dports/misc/py-gluonnlp/gluon-nlp-0.10.0/src/gluonnlp/model/train/ |
H A D | language_model.py | 60 def __init__(self, mode, vocab_size, embed_size=400, hidden_size=1150, num_layers=3, argument 236 def __init__(self, mode, vocab_size, embed_size, hidden_size, argument 419 def __init__(self, vocab_size, embed_size, hidden_size, num_layers, argument
|
/dports/misc/glow/glow-f24d960e3cc80db95ac0bc17b1900dbf60ca044a/thirdparty/onnx/onnx/defs/rnn/ |
H A D | defs.cc | 9 hidden_size; in RNNShapeInference() local
|
H A D | old.cc | 204 hidden_size; in RNNShapeInference1() local
|
/dports/misc/py-mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
H A D | test_gluon_rnn.py | 651 def check_rnn_consistency(fused_layer, stack_layer, loss, input_size, hidden_size, bidirectional=Fa… argument 717 def check_rnn_unidir_layer_gradients(mode, input_size, hidden_size, num_layers, loss): argument 731 def check_rnn_bidir_layer_gradients(mode, input_size, hidden_size, num_layers, loss): argument
|
/dports/misc/mxnet/incubator-mxnet-1.9.0/tests/python/unittest/ |
H A D | test_gluon_rnn.py | 651 def check_rnn_consistency(fused_layer, stack_layer, loss, input_size, hidden_size, bidirectional=Fa… argument 717 def check_rnn_unidir_layer_gradients(mode, input_size, hidden_size, num_layers, loss): argument 731 def check_rnn_bidir_layer_gradients(mode, input_size, hidden_size, num_layers, loss): argument
|
/dports/misc/py-gluonnlp/gluon-nlp-0.10.0/docs/examples/machine_translation/ |
H A D | hyperparameters.py | 29 hidden_size = 2048 variable
|
/dports/misc/glow/glow-f24d960e3cc80db95ac0bc17b1900dbf60ca044a/utils/scripts/ |
H A D | gen_onnx_rnn_model.py | 37 def gen_rnn_onnx_test_model(model_path, seq_length, batch_size, hidden_size, input_size, direction,… argument
|
H A D | gen_onnx_gru_model.py | 37 def gen_gru_onnx_test_model(model_path, seq_length, batch_size, hidden_size, input_size, direction,… argument
|
/dports/misc/py-gluonnlp/gluon-nlp-0.10.0/scripts/language_model/transformer/ |
H A D | transformer.py | 107 hidden_size=512, num_heads=4, activation='relu', scaled=True, dropout=0.0, argument 173 units=128, hidden_size=2048, num_heads=4, scaled=True, dropout=0.0, argument 531 def __init__(self, vocab_size, num_layers=2, units=128, hidden_size=2048, num_heads=4, argument
|