/third_party/mindspore/mindspore/parallel/nn/ |
D | loss.py | 94 def construct(self, logits, label, input_mask): argument 95 self._check_input(logits, label, input_mask) 118 input_mask = P.Reshape()(input_mask, (-1,)) 119 numerator = self.sum2(self.mul2(loss_reduce, input_mask)) 122 self.sum2(input_mask), 127 def _check_input(self, logits, label, input_mask): argument 131 _check_is_tensor('input_mask', input_mask, self.cls_name) 134 _check_input_dtype(F.dtype(input_mask), "input_mask", [mstype.float32], self.cls_name) 137 _check_input_shape(F.shape(input_mask), "input_mask", self.cls_name, 1)
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D | layers.py | 585 input_mask = self.slice1(attention_mask, (0, self.seq_length - 1, 0), 587 input_mask = self.reshape(input_mask, (-1, self.seq_length)) 588 input_shape = P.Shape()(input_mask) # bs, seq_length 593 local_mask_left = self.reshape(input_mask, local_shape_left) 594 local_mask_right = self.reshape(input_mask, local_shape_right)
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D | transformer.py | 447 def construct(self, input_mask): argument 448 _check_input_shape(F.shape(input_mask), "input_mask", self.cls_name, 2) 449 …_check_input_dtype(F.dtype(input_mask), "input_mask", [mstype.float32, mstype.float16], self.cls_n… 450 … _check_input_shape_value(F.shape(input_mask), 1, "input_mask", self.cls_name, self.seq_length) 451 input_mask = P.Cast()(self.not_equal(input_mask, 0), mstype.float16) 452 input_shape = P.Shape()(input_mask) 456 mask_left = self.reshape(input_mask, shape_left) 457 mask_right = self.reshape(input_mask, shape_right) 1239 def construct(self, x, input_mask, init_reset=True, batch_valid_length=None): argument 1240 self._check_input(x, input_mask, init_reset, batch_valid_length) [all …]
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/third_party/mindspore/mindspore/_extends/graph_kernel/expanders/ |
D | gkdropout.py | 25 input_x, input_mask = self.inputs 31 if input_mask.dtype != input_x.dtype: 32 input_mask = graph_builder.emit('Cast', [input_mask], attrs={'dst_type': input_x.dtype}) 33 mask = graph_builder.emit('LessEqual', [input_mask, keep_prob]) # output is bool type
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D | dropout_grad.py | 25 input_dy, input_mask = self.inputs 29 result = graph_builder.emit('Mul', [result, input_mask])
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/third_party/mindspore/tests/mindspore_test_framework/apps/ |
D | test_bert_parts.py | 86 input_ids, input_mask, token_type_id, \ variable 93 'desc_inputs': [input_ids, input_mask, token_type_id, 99 'desc_inputs': [input_ids, input_mask, token_type_id, 105 'desc_inputs': [input_ids, input_mask, token_type_id, 110 'desc_inputs': [input_ids, input_mask, token_type_id, 116 'desc_inputs': [input_ids, input_mask, token_type_id, masked_lm_positions], 120 'desc_inputs': [input_ids, input_mask, token_type_id, masked_lm_positions], 125 'desc_inputs': [input_ids, input_mask, token_type_id, masked_lm_positions], 206 'desc_inputs': [input_ids, input_mask, token_type_id, masked_lm_positions],
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/third_party/mindspore/tests/st/networks/models/bert/src/ |
D | cluener_evaluation.py | 41 input_ids, input_mask, token_type_id = feature 43 input_mask = Tensor(np.array(input_mask), mstype.int32) 46 … backpointers, best_tag_id = model.predict(input_ids, input_mask, token_type_id, Tensor(1)) 53 logits = model.predict(input_ids, input_mask, token_type_id, Tensor(1))
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D | sample_process.py | 41 input_mask = [1] * len(input_ids) 44 input_mask.append(0) 49 assert len(input_mask) == max_seq_len 52 feature = (input_ids, input_mask, segment_ids)
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D | bert_for_pre_training.py | 165 def construct(self, input_ids, input_mask, token_type_id, argument 168 self.bert(input_ids, token_type_id, input_mask) 244 input_mask, argument 251 self.bert(input_ids, input_mask, token_type_id, masked_lm_positions) 294 input_mask, argument 304 input_mask, 311 input_mask, 383 input_mask, argument 393 input_mask, 409 input_mask,
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D | bert_model.py | 811 self.input_mask = None 814 self.input_mask = initializer( 824 def construct(self, input_mask): argument 826 input_mask = self.input_mask 828 input_mask = self.cast(self.reshape(input_mask, self.shape), mstype.float32) 829 attention_mask = self.batch_matmul(self.broadcast_ones, input_mask) 915 def construct(self, input_ids, token_type_ids, input_mask): argument 925 attention_mask = self._create_attention_mask_from_input_mask(input_mask)
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/third_party/mindspore/tests/st/fl/albert/src/ |
D | dataset.py | 28 def __init__(self, input_ids, input_mask, segment_ids, label_id, seq_length=None): argument 30 self.input_mask = input_mask 57 input_mask = [1] * len(input_ids) 62 input_mask += padding 66 assert len(input_mask) == max_seq_length 71 input_mask=input_mask, 134 np.array(feature.input_mask),
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D | cell_wrapper.py | 170 def construct(self, input_ids, input_mask, token_type_id, label_ids): argument 171 logits = self.cls_network(input_ids, input_mask, token_type_id) 184 def construct(self, input_ids, input_mask, token_type_id, label_ids): argument 185 prediction_scores = self.mlm_network(input_ids, input_mask, token_type_id) 255 def construct(self, input_ids, input_mask, token_type_id, label_ids): argument 259 loss = self.network(input_ids, input_mask, token_type_id, label_ids) 261 input_mask, 288 def construct(self, input_ids, input_mask, token_type_id, label_ids): argument 290 loss = self.network(input_ids, input_mask, token_type_id, label_ids) 292 input_mask,
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D | model.py | 709 def construct(self, input_mask): argument 710 attention_mask = self.cast(self.reshape(input_mask, self.shape), mstype.float32) 749 def construct(self, input_ids, token_type_ids, input_mask): argument 758 attention_mask = self._create_attention_mask_from_input_mask(input_mask) 828 def construct(self, input_ids, input_mask, token_type_id): argument 830 _, pooled_output = self.albert(input_ids, token_type_id, input_mask) 861 def construct(self, input_ids, input_mask, token_type_id): argument 863 sequence_output, pooled_output = self.albert(input_ids, token_type_id, input_mask) 887 def construct(self, input_ids, input_mask, token_type_id): argument 889 sequence_output, _ = self.albert(input_ids, token_type_id, input_mask)
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/third_party/mindspore/mindspore/lite/examples/export_models/models/ |
D | tinybert_train_export.py | 160 input_mask = M.Tensor(np.zeros((32, 128), np.int32)) variable 175 export(net, input_ids, token_type_id, input_mask, label, 177 y = net(input_ids, token_type_id, input_mask, label) 179 out = net.network.bert(input_ids, token_type_id, input_mask) 185 save_t(input_mask, path + 'tinybert_input4.bin')
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/third_party/libinput/include/linux/linux/ |
D | input.h | 116 struct input_mask { struct 208 #define EVIOCGMASK _IOR('E', 0x92, struct input_mask) /* Get event-masks */ 231 #define EVIOCSMASK _IOW('E', 0x93, struct input_mask) /* Set event-masks */
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/third_party/libevdev/include/linux/linux/ |
D | input.h | 121 struct input_mask { struct 213 #define EVIOCGMASK _IOR('E', 0x92, struct input_mask) /* Get event-masks */ 236 #define EVIOCSMASK _IOW('E', 0x93, struct input_mask) /* Set event-masks */
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/third_party/libinput/include/linux/freebsd/ |
D | input.h | 117 struct input_mask { struct 209 #define EVIOCGMASK _IOW('E', 0x92, struct input_mask) /* Get event-masks */ 232 #define EVIOCSMASK _IOW('E', 0x93, struct input_mask) /* Set event-masks */
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/third_party/mindspore/mindspore/lite/test/config/ |
D | models_tflite.cfg | 190 albert_lite_base_squadv1_1.tflite;3:input_ids,input_mask,segment_ids 191 mobilebert_1_default_1.tflite;3:input_ids,input_mask,segment_ids 194 hdc_tb_cn_neg.tflite;3:input_ids,input_mask,segment_ids 0.5 199 lite-model_albert_lite_base_squadv1_metadata_1.tflite;3:input_ids,input_mask,segment_ids 200 lite-model_mobilebert_1_metadata_1.tflite;3:input_ids,input_mask,segment_ids
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D | models_tf.cfg | 99 hiai_nlu_model.pb;3:input_ids,input_mask,segment_ids;1,16:1,16:1,16 104 hiai_nlu_model_v2.pb;7:input_ids,input_mask,segment_ids,prev_intent,filling_slots,followup_intents,… 106 hiai_nlu_model_single.pb;3:input_ids,input_mask,segment_ids;1,32:1,32:1,32
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/third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/ |
D | pooling_grad_gpu_kernel.h | 88 auto input_mask = AnfAlgo::GetInputDeviceShape(kernel_node, 1); in InitShape() local 97 …is_null_input_ = CHECK_NULL_INPUT(input_shape) || CHECK_NULL_INPUT(input_mask) || CHECK_NULL_INPUT… in InitShape() 104 CheckTensorSize({input_shape, input_mask, dout_shape, output_shape}); in InitShape() 112 SetDimA(input_mask, dimAy, nbDims, data_format); in InitShape() 113 SetStrideA(input_mask, strideAiny, nbDims, data_format); in InitShape()
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/third_party/mesa3d/src/gallium/drivers/llvmpipe/ |
D | lp_linear.c | 95 unsigned input_mask = variant->linear_input_mask; in lp_fs_linear_run() local 140 while (input_mask) { in lp_fs_linear_run() 141 int i = u_bit_scan(&input_mask); in lp_fs_linear_run()
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/third_party/mindspore/tests/ut/python/mindrecord/ |
D | utils.py | 207 input_mask = np.reshape(np.array(mask), [1, -1]) 214 "input_mask": input_mask,
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/third_party/mindspore/tests/ut/python/nn/ |
D | test_transformer.py | 234 input_mask = Tensor(np.ones(1).astype(np.float32)) 236 _cell_graph_executor.compile(model, logits, labels, input_mask)
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/third_party/mindspore/tests/ut/python/parallel/ |
D | test_parallel_transformer.py | 118 input_mask = Tensor(np.ones((2 * seq,)), mstype.float32) 124 memory_mask, label, input_mask) 556 input_mask = Tensor(np.ones((2 * 64,)), mstype.float32) 557 dataset = Dataset(embed_ids, labels, input_mask)
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/third_party/mindspore/tests/ut/python/dataset/ |
D | test_minddataset_padded.py | 650 input_mask = np.reshape(np.array(mask), [1, -1]) 657 "input_mask": input_mask,
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