| /dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/relay/testing/ |
| H A D | lstm.py | 30 def lstm_cell(num_hidden, batch_size=1, dtype="float32", name=""): argument
122 def get_net(iterations, num_hidden, batch_size=1, dtype="float32"): argument
163 def get_workload(iterations, num_hidden, batch_size=1, dtype="float32"): argument
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| /dports/misc/tvm/incubator-tvm-0.6.1/python/tvm/relay/testing/ |
| H A D | lstm.py | 29 def lstm_cell(num_hidden, batch_size=1, dtype="float32", name=""): argument
116 def get_net(iterations, num_hidden, batch_size=1, dtype="float32"): argument
161 def get_workload(iterations, num_hidden, batch_size=1, dtype="float32"): argument
|
| /dports/misc/py-tvm/incubator-tvm-0.6.1/python/tvm/relay/testing/ |
| H A D | lstm.py | 29 def lstm_cell(num_hidden, batch_size=1, dtype="float32", name=""): argument
116 def get_net(iterations, num_hidden, batch_size=1, dtype="float32"): argument
161 def get_workload(iterations, num_hidden, batch_size=1, dtype="float32"): argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/ctc/ |
| H A D | lstm.py | 34 def _lstm(num_hidden, indata, prev_state, param, seqidx, layeridx): argument
58 def _lstm_unroll_base(num_lstm_layer, seq_len, num_hidden): argument
129 def lstm_unroll(num_lstm_layer, seq_len, num_hidden, num_label, loss_type=None): argument
158 def init_states(batch_size, num_lstm_layer, num_hidden): argument
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| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/ctc/ |
| H A D | lstm.py | 34 def _lstm(num_hidden, indata, prev_state, param, seqidx, layeridx): argument
58 def _lstm_unroll_base(num_lstm_layer, seq_len, num_hidden): argument
129 def lstm_unroll(num_lstm_layer, seq_len, num_hidden, num_label, loss_type=None): argument
158 def init_states(batch_size, num_lstm_layer, num_hidden): argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/rnn/old/ |
| H A D | lstm.py | 34 def lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.): argument
66 num_hidden, num_embed, num_label, dropout=0.): argument
133 num_hidden, num_embed, num_label, dropout=0.): argument
|
| H A D | gru.py | 34 def gru(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.): argument
76 num_hidden, num_embed, num_label, dropout=0.): argument
|
| H A D | rnn.py | 34 def rnn(num_hidden, in_data, prev_state, param, seqidx, layeridx, dropout=0., batch_norm=False): argument
57 num_hidden, num_embed, num_label, dropout=0., batch_norm=False): argument
|
| H A D | rnn_model.py | 34 num_hidden, argument
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/rnn/old/ |
| H A D | lstm.py | 34 def lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.): argument
66 num_hidden, num_embed, num_label, dropout=0.): argument
133 num_hidden, num_embed, num_label, dropout=0.): argument
|
| H A D | gru.py | 34 def gru(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.): argument
76 num_hidden, num_embed, num_label, dropout=0.): argument
|
| H A D | rnn.py | 34 def rnn(num_hidden, in_data, prev_state, param, seqidx, layeridx, dropout=0., batch_norm=False): argument
57 num_hidden, num_embed, num_label, dropout=0., batch_norm=False): argument
|
| H A D | rnn_model.py | 34 num_hidden, argument
|
| /dports/www/chromium-legacy/chromium-88.0.4324.182/chrome/browser/metrics/ |
| H A D | tab_stats_tracker_win.cc | 34 size_t num_hidden = 0; in CalculateAndRecordNativeWindowVisibilities() local
62 size_t num_hidden) { in RecordNativeWindowVisibilities()
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/nce-loss/ |
| H A D | lstm_net.py | 31 def _lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.): argument
57 def get_lstm_net(vocab_size, seq_len, num_lstm_layer, num_hidden): argument
|
| H A D | nce.py | 27 def nce_loss(data, label, label_weight, embed_weight, vocab_size, num_hidden): argument
39 data, label, label_mask, label_weight, embed_weight, vocab_size, num_hidden): argument
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/nce-loss/ |
| H A D | lstm_net.py | 31 def _lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0.): argument
57 def get_lstm_net(vocab_size, seq_len, num_lstm_layer, num_hidden): argument
|
| H A D | nce.py | 27 def nce_loss(data, label, label_weight, embed_weight, vocab_size, num_hidden): argument
39 data, label, label_mask, label_weight, embed_weight, vocab_size, num_hidden): argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/model-parallel/matrix_factorization/ |
| H A D | model.py | 20 def matrix_fact_model_parallel_net(factor_size, num_hidden, max_user, max_item): argument
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/model-parallel/matrix_factorization/ |
| H A D | model.py | 20 def matrix_fact_model_parallel_net(factor_size, num_hidden, max_user, max_item): argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/sparse/matrix_factorization/ |
| H A D | model.py | 20 def matrix_fact_net(factor_size, num_hidden, max_user, max_item, dense): argument
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/sparse/matrix_factorization/ |
| H A D | model.py | 20 def matrix_fact_net(factor_size, num_hidden, max_user, max_item, dense): argument
|
| /dports/science/py-dipy/dipy-1.4.1/dipy/nn/ |
| H A D | model.py | 15 num_hidden=128, act_hidden='relu', argument
148 num_hidden=[128], argument
|
| /dports/misc/mxnet/incubator-mxnet-1.9.0/example/speech_recognition/ |
| H A D | stt_layer_lstm.py | 36 def vanilla_lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, is_batchnorm=False, gamma… argument
65 def lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0., num_hidden_proj=0, is… argument
|
| /dports/misc/py-mxnet/incubator-mxnet-1.9.0/example/speech_recognition/ |
| H A D | stt_layer_lstm.py | 36 def vanilla_lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, is_batchnorm=False, gamma… argument
65 def lstm(num_hidden, indata, prev_state, param, seqidx, layeridx, dropout=0., num_hidden_proj=0, is… argument
|