| /frameworks/opt/gamesdk/third_party/protobuf-3.0.0/src/google/protobuf/io/ |
| D | zero_copy_stream_impl.cc | 298 : input_(input) { in CopyingIstreamInputStream()
305 input_->read(reinterpret_cast<char*>(buffer), size); in Read()
306 int result = input_->gcount(); in Read()
307 if (result == 0 && input_->fail() && !input_->eof()) { in Read()
417 : input_(input), limit_(limit) { in LimitingInputStream()
418 prior_bytes_read_ = input_->ByteCount(); in LimitingInputStream()
423 if (limit_ < 0) input_->BackUp(-limit_); in ~LimitingInputStream()
428 if (!input_->Next(data, size)) return false; in Next()
440 input_->BackUp(count - limit_); in BackUp()
443 input_->BackUp(count); in BackUp()
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| D | zero_copy_stream_impl.h | 242 istream* input_;
345 ZeroCopyInputStream* input_;
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| D | coded_stream.cc | 76 if (input_ != NULL) { in ~CodedInputStream()
96 input_->BackUp(backup_bytes); in BackUpInputToCurrentPosition()
242 input_->Skip(bytes_until_limit); in Skip()
248 return input_->Skip(count); in Skip()
618 if (NextNonEmpty(input_, &void_buffer, &buffer_size)) { in Refresh()
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| D | coded_stream.h | 525 ZeroCopyInputStream* input_; variable
1315 input_(input), in CodedInputStream()
1336 input_(NULL), in CodedInputStream()
1355 return input_ == NULL; in IsFlat()
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| D | tokenizer.h | 262 ZeroCopyInputStream* input_; variable
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| /frameworks/ml/nn/common/operations/ |
| D | Multinomial.cpp | 49 input_ = GetInput(operation, operands, kInputTensor); in Multinomial()
79 switch (input_->type) { in Eval()
81 std::vector<float> inputDataFloat32(getNumberOfElements(input_->shape())); in Eval()
82 convertFloat16ToFloat32(GetBuffer<_Float16>(input_), &inputDataFloat32); in Eval()
87 EvalFloat32(GetBuffer<float>(input_)); in Eval()
91 LOG(ERROR) << "Unsupported data type: " << static_cast<int>(input_->type); in Eval()
99 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32()
100 const int class_size = SizeOfDimension(input_, 1); in EvalFloat32()
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| D | BidirectionalSequenceLSTM.cpp | 50 input_ = GetInput(operation, operands, kInputTensor); in BidirectionalSequenceLSTM()
141 if (input_->type == OperandType::TENSOR_FLOAT32) { in BidirectionalSequenceLSTM()
165 NN_CHECK(NumDimensions(input_) == 3); in Prepare()
166 const uint32_t max_time = SizeOfDimension(input_, params_.time_major ? 0 : 1); in Prepare()
167 const uint32_t n_batch = SizeOfDimension(input_, params_.time_major ? 1 : 0); in Prepare()
168 const uint32_t n_input = SizeOfDimension(input_, 2); in Prepare()
180 input_, fw_input_to_input_weights_, fw_input_to_forget_weights_, in Prepare()
208 NN_CHECK_EQ(aux_input_->shape().dimensions[0], input_->shape().dimensions[0]); in Prepare()
209 NN_CHECK_EQ(aux_input_->shape().dimensions[1], input_->shape().dimensions[1]); in Prepare()
220 const Shape& inputShape = input_->shape(); in Prepare()
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| D | SVDF.cpp | 31 input_ = GetInput(operation, operands, kInputTensor); in SVDF()
98 switch (input_->type) { in Eval()
100 std::vector<float> inputDataFloat32(getNumberOfElements(input_->shape())); in Eval()
101 convertFloat16ToFloat32(reinterpret_cast<_Float16*>(input_->buffer), &inputDataFloat32); in Eval()
131 EvalFloat32(reinterpret_cast<float*>(input_->buffer), in Eval()
141 LOG(ERROR) << "Unsupported data type: " << static_cast<int>(input_->type); in Eval()
154 const int batch_size = SizeOfDimension(input_, 0); in EvalFloat32()
155 const int input_size = SizeOfDimension(input_, 1); in EvalFloat32()
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| D | MultinomialTest.cpp | 69 input_.push_back(srng.RandDouble()); in Invoke()
71 ASSERT_EQ(execution.setInput(Multinomial::kInputTensor, input_.data(), in Invoke()
72 sizeof(float) * input_.size()), in Invoke()
91 const std::vector<float>& GetInput() const { return input_; } in GetInput()
101 std::vector<float> input_; member in android::nn::wrapper::MultinomialOpModel
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| D | RNN.cpp | 31 input_ = GetInput(operation, operands, kInputTensor); in RNN()
86 switch (input_->type) { in Eval()
88 RNNStep<_Float16>(reinterpret_cast<_Float16*>(input_->buffer), input_->shape(), in Eval()
100 RNNStep<float>(reinterpret_cast<float*>(input_->buffer), input_->shape(), in Eval()
112 LOG(ERROR) << "Unsupported data type: " << static_cast<int>(input_->type); in Eval()
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| D | LSTM.cpp | 50 input_ = GetInput(operation, operands, kInputTensor); in LSTMCell()
83 if (input_->type == OperandType::TENSOR_FLOAT32) { in LSTMCell()
124 const RunTimeOperandInfo* input_, const RunTimeOperandInfo* input_to_input_weights, in CheckInputTensorDimensions() argument
304 NN_CHECK(NumDimensions(input_) > 1); in Prepare()
305 const uint32_t n_batch = SizeOfDimension(input_, 0); in Prepare()
306 const uint32_t n_input = SizeOfDimension(input_, 1); in Prepare()
318 input_, input_to_input_weights_, input_to_forget_weights_, input_to_cell_weights_, in Prepare()
330 const Shape& inputShape = input_->shape(); in Prepare()
953 switch (input_->type) { in Eval()
955 LSTMEvalFloat32(params_, GetBuffer<const float>(input_), input_->shape(), in Eval()
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| D | LSHProjection.cpp | 30 input_ = GetInput(operation, operands, kInputTensor); in LSHProjection()
158 DenseLshProjection<T>(hash_, input_, weight_, out_buf); in Eval()
162 SparseLshProjection<T>(type_, hash_, input_, weight_, out_buf); in Eval()
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| D | QuantizedLSTM.cpp | 218 input_ = GetInput(operation, operands, kInputTensor); in QuantizedLSTMCell()
377 SizeOfDimension(input_, 1) + SizeOfDimension(prevOutput_, 1)}; in eval()
387 concatTempShape.dimensions = {SizeOfDimension(input_, 0), getSizeOfDimension(weightsShape, 1)}; in eval()
390 activationTempShape.dimensions = {SizeOfDimension(input_, 0), in eval()
410 GetBuffer<const uint8_t>(input_), convertShapeToDims(input_->shape()), in eval()
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| D | Multinomial.h | 51 RunTimeOperandInfo* input_; variable
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| D | QuantizedLSTMTest.cpp | 76 initializeInputData(inputOperandTypeParams[QuantizedLSTMCell::kInputTensor], &input_); in QuantizedLSTMOpModel()
96 ASSERT_EQ(setInputTensor(&execution, QuantizedLSTMCell::kInputTensor, input_), in invoke()
156 void setInput(const std::vector<uint8_t>& input) { input_ = input; } in setInput()
202 std::vector<uint8_t> input_; member in android::nn::wrapper::QuantizedLSTMOpModel
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| D | SVDF.h | 63 const RunTimeOperandInfo* input_; variable
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| D | LSHProjection.h | 58 const RunTimeOperandInfo* input_; variable
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| D | LSTM.h | 185 const RunTimeOperandInfo* input_, const RunTimeOperandInfo* input_to_input_weights,
207 const RunTimeOperandInfo* input_; variable
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| D | QuantizedLSTM.h | 52 const RunTimeOperandInfo* input_;
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| D | RNN.h | 65 const RunTimeOperandInfo* input_; variable
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| /frameworks/opt/gamesdk/third_party/protobuf-3.0.0/src/google/protobuf/compiler/ |
| D | parser.cc | 124 : input_(NULL), in Parser()
138 return input_->current().text == text; in LookingAt()
142 return input_->current().type == token_type; in LookingAtType()
151 input_->Next(); in TryConsume()
178 *output = input_->current().text; in ConsumeIdentifier()
179 input_->Next(); in ConsumeIdentifier()
190 if (!io::Tokenizer::ParseInteger(input_->current().text, in ConsumeInteger()
196 input_->Next(); in ConsumeInteger()
221 if (!io::Tokenizer::ParseInteger(input_->current().text, max_value, in ConsumeInteger64()
227 input_->Next(); in ConsumeInteger64()
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| D | parser_unittest.cc | 111 input_.reset(new io::Tokenizer(raw_input_.get(), &error_collector_)); in SetupParser()
124 parser_->Parse(input_.get(), &actual); in ExpectParsesTo()
125 EXPECT_EQ(io::Tokenizer::TYPE_END, input_->current().type); in ExpectParsesTo()
145 EXPECT_EQ(io::Tokenizer::TYPE_END, input_->current().type); in ExpectHasErrors()
153 parser_->Parse(input_.get(), &file); in ExpectHasEarlyExitErrors()
167 parser_->Parse(input_.get(), &file); in ExpectHasValidationErrors()
168 EXPECT_EQ(io::Tokenizer::TYPE_END, input_->current().type); in ExpectHasValidationErrors()
182 google::protobuf::scoped_ptr<io::Tokenizer> input_; member in google::protobuf::compiler::__anon458863de0111::ParserTest
195 EXPECT_TRUE(parser_->Parse(input_.get(), NULL)); in TEST_F()
205 EXPECT_TRUE(parser_->Parse(input_.get(), NULL)); in TEST_F()
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| /frameworks/ml/nn/runtime/test/specs/V1_2/ |
| D | quantized_lstm.mod.py | 25 input_ = Input("input", ("TENSOR_QUANT8_ASYMM", (n_batch, n_input), 1 / 128, 128)) variable
53 input_,
71 input_: [166, 179, 50, 150],
104 input_ = Input("input", variable
179 model = model.Operation("QUANTIZED_16BIT_LSTM", input_, input_to_input_weights,
189 input_: [166, 179],
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| /frameworks/opt/gamesdk/third_party/protobuf-3.0.0/src/google/protobuf/stubs/ |
| D | bytestream.cc | 147 return input_.size(); in Available()
151 return input_; in Peek()
155 GOOGLE_DCHECK_LE(n, input_.size()); in Skip()
156 input_.remove_prefix(n); in Skip()
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| D | bytestream.h | 297 explicit ArrayByteSource(StringPiece s) : input_(s) {} in ArrayByteSource()
304 StringPiece input_;
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