/third_party/mindspore/tests/st/ops/cpu/ |
D | test_dropout_op.py | 30 self.dropout = P.Dropout() 33 return self.dropout(x) 41 dropout = Net() 42 output, mask = dropout(Tensor(x)) 51 self.dropout = P.Dropout(keep_prob=0.1) 54 return self.dropout(x) 62 dropout = Net1() 63 output, mask = dropout(Tensor(x)) 72 self.dropout = P.Dropout(keep_prob=1.0) 75 return self.dropout(x) [all …]
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D | test_lstm_op.py | 42 dropout=0.0, argument 65 dropout=dropout)) 102 … __init__(self, batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout): argument 109 self.lstm = StackLSTM(input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) 162 dropout = 0.0 166 net = LstmNet(batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) 205 … __init__(self, batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout): argument 213 bidirectional=bidirectional, dropout=dropout) 267 dropout = 0.0 270 dropout) [all …]
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/third_party/mindspore/mindspore/nn/layer/ |
D | lstm.py | 138 dropout=0, argument 151 self.dropout = dropout 157 dropout=float(dropout)) 169 if dropout < 0 or dropout > 1: 172 if dropout == 1: 175 self.dropout_op = nn.Dropout(float(1 - dropout)) 231 pre_layer = self.dropout_op(output) if self.dropout else output 250 pre_layer = self.dropout_op(y) if self.dropout else y 381 dropout=0, argument 392 dropout=float(dropout))
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D | rnns.py | 203 batch_first=False, dropout=0.0, bidirectional=False): argument 208 validator.check_is_float(dropout, "dropout", self.cls_name) 213 if not 0 <= dropout < 1: 217 if dropout > 0 and num_layers == 1: 221 "num_layers={}".format(dropout, num_layers)) 239 self.dropout = dropout 240 self.dropout_op = nn.Dropout(float(1 - dropout)) 311 … pre_layer = self.dropout_op(output) if (self.dropout != 0 and i < self.num_layers - 1) else output 343 … pre_layer = self.dropout_op(output) if (self.dropout != 0 and i < self.num_layers - 1) else output
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/third_party/mindspore/tests/st/export_and_load/ |
D | test_bgcf.py | 35 dropout=0.2): argument 49 self.dropout = nn.Dropout(keep_prob=1 - dropout) 53 neigh_matrix = self.dropout(neigh_matrix) 63 dropout=0.2): argument 75 self.dropout = nn.Dropout(keep_prob=1 - dropout) 79 neigh_matrix = self.dropout(neigh_feature) 111 activation=activation, dropout=neigh_drop_rate[1]) 113 self.gnew_agg_user = AttenConv(self.input_dim, self.layer_dim, dropout=neigh_drop_rate[2]) 115 self.gnew_agg_item = AttenConv(self.input_dim, self.layer_dim, dropout=neigh_drop_rate[2]) 122 activation=activation, dropout=neigh_drop_rate[0]) [all …]
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/third_party/mindspore/tests/st/ops/gpu/ |
D | test_lstm_op.py | 32 …(self, seq_len, batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout): argument 39 self.lstm = P.LSTM(input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) 120 dropout = 0.0 126 …LstmNet(seq_len, batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) 164 …(self, seq_len, batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout): argument 171 self.lstm = P.LSTM(input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) 270 dropout = 0.0 276 …LstmNet(seq_len, batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) 321 …(self, seq_len, batch_size, input_size, hidden_size, num_layers, has_bias, bidirectional, dropout): argument 328 self.lstm = P.LSTM(input_size, hidden_size, num_layers, has_bias, bidirectional, dropout) [all …]
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/third_party/mindspore/mindspore/core/ops/grad/ |
D | lstm_grad.cc | 54 void LSTMGrad::set_dropout(const float dropout) { in set_dropout() argument 55 …CheckAndConvertUtils::CheckInRange<float>(kDropout, dropout, kIncludeBoth, {0.0, 1.0}, this->name(… in set_dropout() 56 (void)AddAttr(kDropout, MakeValue(dropout)); in set_dropout() 80 const float dropout, const bool bidirectional, const float zoneout_cell, in Init() argument 86 this->set_dropout(dropout); in Init()
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D | lstm_grad.h | 36 const float dropout, const bool bidirectional = false, const float zoneout_cell = 0.0f, 46 void set_dropout(const float dropout);
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/third_party/mindspore/tests/ut/python/parallel/ |
D | test_matmul_dropout.py | 77 self.dropout = P.Dropout(keep_prob) 84 out, _ = self.dropout(x) 108 self.dropout = Dropout() 109 self.dropout.dropout_do_mask.shard(strategy2) 110 self.dropout.dropout_gen_mask.shard(strategy2) 115 out = self.dropout(out)
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D | test_batch_parallel_dropout.py | 56 self.dropout = nn.Dropout() 61 out = self.dropout(out)
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D | test_auto_parallel_matmul_drop.py | 56 self.dropout = nn.Dropout() 61 out = self.dropout(out)
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/third_party/mindspore/tests/st/ops/ascend/ |
D | test_gru_op.py | 40 …__init__(self, input_size, hidden_size, num_layers, has_bias, batch_first, bidirectional, dropout): argument 43 batch_first=batch_first, bidirectional=bidirectional, dropout=dropout) 112 bidirectional=bidirectional, dropout=0.0) 122 batch_first=False, bidirectional=bidirectional, dropout=0.0) 153 bidirectional=bidirectional, dropout=0.0) 168 batch_first=False, bidirectional=bidirectional, dropout=0.0)
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D | test_lstm_op.py | 41 … def __init__(self, input_s, hidden_s, num_layers, has_bias, batch_first, bidirectional, dropout): argument 44 batch_first=batch_first, bidirectional=bidirectional, dropout=dropout) 112 bidirectional=bidirectional, dropout=0.0) 120 bidirectional=bidirectional, dropout=0.0) 152 bidirectional=bidirectional, dropout=0.0) 166 bidirectional=bidirectional, dropout=0.0)
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D | test_rnn_op.py | 40 …__init__(self, input_size, hidden_size, num_layers, has_bias, batch_first, bidirectional, dropout): argument 43 batch_first=batch_first, bidirectional=bidirectional, dropout=dropout) 112 bidirectional=bidirectional, dropout=0.0) 122 batch_first=False, bidirectional=bidirectional, dropout=0.0) 153 batch_first=False, bidirectional=bidirectional, dropout=0.0) 168 batch_first=False, bidirectional=bidirectional, dropout=0.0)
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp16_grad/ |
D | dropout_fp16_grad.cc | 82 auto dropout = reinterpret_cast<DropoutGradCPUKernelFp16 *>(cdata); in RunDropoutFp16Grad() local 83 CHECK_NULL_RETURN(dropout); in RunDropoutFp16Grad() 84 auto error_code = dropout->DoExecute(task_id); in RunDropoutFp16Grad()
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/third_party/mindspore/mindspore/lite/examples/export_models/models/ |
D | mini_alexnet.py | 49 self.dropout = nn.Dropout(dropout_ratio) 64 x = self.dropout(x) 67 x = self.dropout(x)
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp32_grad/ |
D | dropout_grad.cc | 82 auto dropout = reinterpret_cast<DropoutGradCPUKernel *>(cdata); in RunDropoutGrad() local 83 CHECK_NULL_RETURN(dropout); in RunDropoutGrad() 84 auto error_code = dropout->Execute(task_id); in RunDropoutGrad()
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D | dropout.cc | 92 auto dropout = reinterpret_cast<DropoutCPUKernel *>(cdata); in RunDropout() local 93 auto error_code = dropout->Execute(task_id); in RunDropout()
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/third_party/mindspore/tests/ut/python/pynative_mode/nn/ |
D | test_dropout.py | 35 self.dropout = nn.Dropout(0.5) 38 return self.dropout(x)
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/third_party/mindspore/mindspore/core/ops/ |
D | lstm.cc | 126 void LSTM::set_dropout(const float dropout) { in set_dropout() argument 127 …CheckAndConvertUtils::CheckInRange<float>(kDropout, dropout, kIncludeBoth, {0.0, 1.0}, this->name(… in set_dropout() 128 (void)AddAttr(kDropout, MakeValue(dropout)); in set_dropout() 152 …const float dropout, const bool bidirectional, const float zoneout_cell, const float zoneout_hidde… in Init() argument 157 this->set_dropout(dropout); in Init()
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D | lstm.h | 45 const float dropout, const bool bidirectional = false, const float zoneout_cell = 0.0f, 72 void set_dropout(const float dropout);
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/third_party/mindspore/tests/st/ops/graph_kernel/ |
D | test_dropout.py | 40 dropout = Net(keep_prob) 42 output, mask = dropout(tx)
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D | test_layernorm_stitch.py | 34 self.dropout = nn.Dropout(1 - 0.1) 41 output = self.dropout(output)
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D | test_softmax_stitch.py | 34 self.dropout = nn.Dropout(1 - 0.1) 48 attention_probs = self.dropout(attention_probs)
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/third_party/mindspore/tests/st/fl/albert/src/ |
D | model.py | 192 self.dropout = nn.Dropout(1 - config.hidden_dropout_prob) 221 output = self.dropout(output) 237 self.dropout = nn.Dropout(1 - config.hidden_dropout_prob) 251 output = self.dropout(output) 425 self.dropout = nn.Dropout(1 - config.attention_probs_dropout_prob) 491 attention_probs = self.dropout(attention_probs) 826 self.dropout = nn.Dropout(1 - config.classifier_dropout_prob) 833 pooled_output = self.dropout(pooled_output) 856 self.dropout = nn.Dropout(1 - config.classifier_dropout_prob) 865 pooled_output = self.dropout(pooled_output)
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