Searched refs:outputs (Results 1 - 25 of 887) sorted by relevance

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/external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/
H A Ddrop_im2col_arrays.cc28 if (conv_op->outputs.size() < 2) {
34 CHECK_EQ(conv_op->outputs.size(), 2);
35 model->EraseArray(conv_op->outputs[1]);
36 conv_op->outputs.resize(1);
H A Dunfuse_activation_functions.cc33 if ((op->type == OperatorType::kConv) && (op->outputs.size() == 2)) {
55 CHECK_EQ(op->outputs.size(), 1);
63 ac_op->outputs = op->outputs;
65 AvailableArrayName(*model, op->outputs[0] + "_unfused");
69 op->outputs = {tmp_array_name};
H A Dunroll_batch_matmul.cc64 matmul_op->outputs = batch_op->outputs;
82 std::string(batch_op->outputs[0]) + "_b" + std::to_string(batch);
94 slice_a_op->outputs = {AvailableArrayName(*model, batch_name + "/slice_a")};
95 auto& slice_a_op_output = model->GetOrCreateArray(slice_a_op->outputs[0]);
102 slice_a_op->outputs[0],
105 slice_a_reshape_op->outputs = {
108 model->GetOrCreateArray(slice_a_reshape_op->outputs[0]);
121 slice_b_op->outputs = {AvailableArrayName(*model, batch_name + "/slice_b")};
122 auto& slice_b_op_output = model->GetOrCreateArray(slice_b_op->outputs[
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H A Dresolve_squeeze_attributes.cc34 DCHECK_EQ(squeeze_op->outputs.size(), 1);
37 if (CountOpsWithInput(*model, squeeze_op->outputs[0]) == 1) {
38 const auto* next_op = GetOpWithInput(*model, squeeze_op->outputs[0]);
H A Dreorder_activation_functions.cc49 DCHECK_EQ(exchange_op->outputs[0], ac_op->inputs[0]);
51 const auto& intermediate_array = exchange_op->outputs[0];
52 const auto& ac_op_output = ac_op->outputs[0];
70 if (model->flags.output_arrays(i) == ac_op->outputs[0]) {
74 LogName(*exchange_op), ac_op->outputs[0]);
93 model->GetOrCreateArray(ac_op->outputs[0]).clear_shape();
94 model->GetOrCreateArray(exchange_op->outputs[0]).clear_shape();
H A Didentify_lstm_split_inputs.cc52 if (!model->GetArray(curr_op->outputs[LstmCellOperator::ACTIV_OUTPUT])
66 model->GetArray(curr_op->outputs[LstmCellOperator::ACTIV_OUTPUT])
79 curr_op->outputs[LstmCellOperator::ACTIV_OUTPUT],
80 curr_op->outputs[LstmCellOperator::STATE_OUTPUT]));
141 // Reorder LstmCell's outputs.
142 lstm_cell_op->outputs.resize(LstmCellOperator::NUM_OUTPUTS);
143 lstm_cell_op->outputs[kScratchBufferTensor] =
144 curr_op->outputs[LstmCellOperator::CONCAT_TEMP];
145 lstm_cell_op->outputs[kOutputStateTensor] =
146 curr_op->outputs[LstmCellOperato
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/external/tensorflow/tensorflow/cc/client/
H A Dclient_session_test.cc38 std::vector<Tensor> outputs; local
40 TF_EXPECT_OK(session.Run({c}, &outputs));
41 test::ExpectTensorEqual<int>(outputs[0], test::AsTensor<int>({1, 1}, {1, 2}));
50 std::vector<Tensor> outputs; local
52 TF_EXPECT_OK(session.Run({{a, 1}, {b, 41}}, {c}, &outputs));
53 test::ExpectTensorEqual<int>(outputs[0], test::AsTensor<int>({42}, {}));
61 std::vector<Tensor> outputs; local
63 TF_EXPECT_OK(session.Run({{a, {1, 1}}}, {c}, &outputs));
64 test::ExpectTensorEqual<int>(outputs[0], test::AsTensor<int>({3, 3}, {2}));
67 outputs
93 std::vector<Tensor> outputs; local
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/external/tensorflow/tensorflow/contrib/rnn/python/ops/
H A Dfused_rnn_cell.py104 outputs, state = rnn.dynamic_rnn(
113 # Convert outputs back to list
114 outputs = array_ops.unstack(outputs)
118 outputs, state = rnn.static_rnn(
126 # Convert outputs back to tensor
127 outputs = array_ops.stack(outputs)
129 return outputs, state
176 outputs, stat
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/external/libvpx/libvpx/test/
H A Dsvc_test.cc137 struct vpx_fixed_buf *const outputs,
153 outputs[*frame_received].buf = malloc(frame_size + 16);
154 ASSERT_TRUE(outputs[*frame_received].buf != NULL);
155 memcpy(outputs[*frame_received].buf, cx_pkt->data.frame.buf,
157 outputs[*frame_received].sz = frame_size;
165 struct vpx_fixed_buf *const outputs) {
169 ASSERT_TRUE(outputs != NULL);
191 StoreFrames(n, outputs, &frame_received);
199 StoreFrames(n, outputs, &frame_received);
450 vpx_fixed_buf outputs[ local
136 StoreFrames(const size_t max_frame_received, struct vpx_fixed_buf *const outputs, size_t *const frame_received) argument
163 Pass2EncodeNFrames(std::string *const stats_buf, const int n, const int layers, struct vpx_fixed_buf *const outputs) argument
464 vpx_fixed_buf outputs[10]; local
479 vpx_fixed_buf outputs[20]; local
494 vpx_fixed_buf outputs[10]; local
510 vpx_fixed_buf outputs[10]; local
536 vpx_fixed_buf outputs[20]; local
552 vpx_fixed_buf outputs[20]; local
585 vpx_fixed_buf outputs[10]; local
602 vpx_fixed_buf outputs[10]; local
622 vpx_fixed_buf outputs[10]; local
642 vpx_fixed_buf outputs[10]; local
666 vpx_fixed_buf outputs[10]; local
687 vpx_fixed_buf outputs[10]; local
705 vpx_fixed_buf outputs[10]; local
731 vpx_fixed_buf outputs[10]; local
757 vpx_fixed_buf outputs[10]; local
782 vpx_fixed_buf outputs[10]; local
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/external/mesa3d/src/gallium/drivers/r300/
H A Dr300_vs.c109 struct r300_shader_semantics* outputs = &vs->outputs; local
112 boolean any_bcolor_used = outputs->bcolor[0] != ATTR_UNUSED ||
113 outputs->bcolor[1] != ATTR_UNUSED;
120 if (outputs->pos != ATTR_UNUSED) {
121 c->code->outputs[outputs->pos] = reg++;
127 if (outputs->psize != ATTR_UNUSED) {
128 c->code->outputs[outputs
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/external/tensorflow/tensorflow/contrib/specs/python/
H A Dspecs_test.py44 outputs = specs.create_net(spec, inputs)
45 self.assertEqual(outputs.get_shape().as_list(), [1, 18, 19, 64])
47 result = outputs.eval()
59 outputs = specs.create_net(spec, inputs)
60 self.assertEqual(outputs.get_shape().as_list(), [17, 55])
62 result = outputs.eval()
69 outputs = specs.create_net(spec, inputs)
70 self.assertEqual(outputs.get_shape().as_list(), [17, 10])
72 result = outputs.eval()
83 outputs
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H A Dsummaries_test.py41 outputs = specs.create_net(spec, inputs)
43 result = outputs.eval()
54 outputs = specs.create_net(spec, inputs)
56 result = outputs.eval()
66 outputs = specs.create_net(spec, inputs)
68 result = outputs.eval()
76 outputs = specs.create_net(spec, inputs)
78 result = outputs.eval()
/external/tensorflow/tensorflow/cc/tools/
H A Dfreeze_saved_model.h28 // `inputs` and `outputs` consist of the union of all inputs and outputs in the
31 // `outputs`. All variables in the supplied SavedModelBundle are converted to
39 std::unordered_set<string>* outputs);
/external/toybox/toys/posix/
H A Dtee.c1 /* tee.c - cat to multiple outputs.
26 void *outputs;
41 temp->next = TT.outputs;
43 TT.outputs = temp;
64 fdl = TT.outputs;
/external/tensorflow/tensorflow/contrib/lite/java/src/main/java/org/tensorflow/lite/
H A DInterpreter.java38 * <p>If a model takes multiple inputs or outputs:
50 * <p>Orders of inputs and outputs are determined when converting TensorFlow model to TensorFlowLite
91 Map<Integer, Object> outputs = new HashMap<>();
92 outputs.put(0, output);
93 runForMultipleInputsOutputs(inputs, outputs);
97 * Runs model inference if the model takes multiple inputs, or returns multiple outputs.
104 * @param outputs a map mapping output indices to multidimensional arrays of output data. It only
105 * needs to keep entries for the outputs to be used.
108 @NotNull Object[] inputs, @NotNull Map<Integer, Object> outputs) {
113 if (outputs
107 runForMultipleInputsOutputs( @otNull Object[] inputs, @NotNull Map<Integer, Object> outputs) argument
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/external/tensorflow/tensorflow/cc/framework/
H A Dtestutil.cc34 std::vector<Tensor> outputs; local
35 GetTensors(scope, {std::move(tensor)}, &outputs);
36 *out = outputs[0];
48 std::vector<Tensor> outputs; local
49 GetTensors(scope, assign_vars, {std::move(tensor)}, &outputs);
50 *out = outputs[0];
/external/tensorflow/tensorflow/contrib/tpu/python/tpu/
H A Dtraining_loop.py120 outputs = body(*(inputs + dequeue_ops))
123 if not isinstance(outputs, (list, tuple)):
124 outputs = (outputs,)
126 outputs = [
128 for o in outputs
132 output_operations = [o for o in outputs if isinstance(o, ops.Operation)]
133 output_tensors = [o for o in outputs
136 if outputs != output_tensors + output_operations:
206 outputs
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/external/tensorflow/tensorflow/core/kernels/
H A Dshape_op_test.cc86 std::vector<Tensor> outputs; local
93 Status s = session.Run({{input, variant_tensor}}, {shape_output}, &outputs);
104 Status s = session.Run({{input, variant_tensor}}, {shape_output}, &outputs);
117 &outputs));
118 EXPECT_EQ(outputs[0].dims(), 1); // shape
119 EXPECT_EQ(vec_dim_value, outputs[0].vec<int32>()(0));
120 EXPECT_EQ(outputs[1].dims(), 0); // rank
121 EXPECT_EQ(1, outputs[1].scalar<int32>()());
122 EXPECT_EQ(outputs[2].dims(), 0); // size
123 EXPECT_EQ(vec_dim_value, outputs[
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/external/tensorflow/tensorflow/cc/ops/
H A Dwhile_loop.cc35 std::vector<OutputTensor> ToOutputTensors(const std::vector<Output>& outputs) { argument
36 std::vector<OutputTensor> result(outputs.size());
37 for (int i = 0; i < outputs.size(); ++i) {
38 result[i] = ToOutputTensor(outputs[i]);
44 std::vector<Node*> ToNodes(const std::vector<Output>& outputs) { argument
45 std::vector<Node*> result(outputs.size());
46 for (int i = 0; i < outputs.size(); ++i) {
47 result[i] = outputs[i].node();
119 // Create the body subgraph defined by `body`. `outputs` must be non-null and
123 std::vector<Output>* outputs) {
121 CreateBody(const Scope& scope, const BodyGraphBuilderFn& body, const std::vector<Output>& inputs, std::vector<Output>* outputs) argument
172 BuildWhileLoop(const Scope& scope, const std::vector<Output>& inputs, const CondGraphBuilderFn& cond, const BodyGraphBuilderFn& body, const string& frame_name, OutputList* outputs, bool create_while_ctx, Output* cond_output) argument
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/external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/
H A Dcandidate_graph_runner.cc72 std::vector<Tensor>* outputs) {
77 TF_CHECK_OK(session_->Run(inputs, output_tensor_names, op_name, outputs))
98 std::vector<Tensor> outputs; local
99 RunOp(kNoOp, TensorNameValueList(), {kSplitScoreName}, &outputs);
100 return outputs[0].unaligned_flat<float>()(0);
104 std::vector<Tensor> outputs; local
105 RunOp(kNoOp, TensorNameValueList(), {kGetSplitName}, &outputs);
106 ParseProtoUnlimited(node, outputs[0].unaligned_flat<string>()(0));
116 std::vector<Tensor> outputs; local
117 RunOp(kNoOp, TensorNameValueList(), {kGetLeftStatsName}, &outputs);
69 RunOp(const string& name, const TensorNameValueList& inputs, const std::vector<string>& output_tensor_names, std::vector<Tensor>* outputs) argument
126 std::vector<Tensor> outputs; local
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/external/deqp/modules/gles3/scripts/
H A Dgen-large-constant-arrays.py59 def __init__(self, name, array, inputs, outputs):
63 self.outputs = outputs
69 "VALUES": genValues(self.inputs, self.outputs),
104 outputs = [array[index] for index in indexes] variable
105 outType = outputs[0].typeString()
111 [("%s out0" % outType, outputs)])
/external/tensorflow/tensorflow/contrib/batching/python/ops/
H A Dbatch_ops.py37 op.outputs[-2],
38 op.outputs[-1],
122 outputs = f(*batched_tensors)
123 if isinstance(outputs, ops.Tensor):
124 outputs_list = [outputs]
126 outputs_list = outputs
133 if isinstance(outputs, ops.Tensor):
/external/tensorflow/tensorflow/core/common_runtime/
H A Dgraph_runner_test.cc50 std::vector<Tensor> outputs; local
51 Status s = graph_runner.Run(root.graph(), nullptr, {}, {c.name()}, &outputs);
53 ExpectEqual(42.0f, outputs[0].scalar<float>()());
71 // Create and destroy the GraphRunner, and ensure that the outputs are
73 std::vector<Tensor> outputs; local
77 graph_runner.Run(root.graph(), nullptr, inputs, {"add:0"}, &outputs);
80 ExpectEqual(3.0f, outputs[0].scalar<float>()());
88 std::vector<Tensor> outputs; local
90 &outputs);
92 ExpectEqual(42.0f, outputs[
110 std::vector<Tensor> outputs; local
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/external/tensorflow/tensorflow/python/keras/_impl/keras/utils/
H A Dtraining_utils.py170 for i in range(len(model.outputs)):
194 outputs = model(inputs)
195 if not isinstance(outputs, list):
196 outputs = [outputs]
198 # Save the outputs for merging back together later.
199 for o in range(len(outputs)):
200 all_outputs[o].append(outputs[o])
202 # Merge outputs on CPU.
205 for name, outputs i
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/external/tensorflow/tensorflow/python/saved_model/
H A Dsignature_def_utils_impl.py33 def build_signature_def(inputs=None, outputs=None, method_name=None):
39 outputs: Outputs of the SignatureDef defined as a proto map of string to
50 if outputs is not None:
51 for item in outputs:
52 signature_def.outputs[item].CopyFrom(outputs[item])
154 def predict_signature_def(inputs, outputs):
155 """Creates prediction signature from given inputs and outputs.
163 outputs: dict of string to `Tensor`.
169 ValueError: If inputs or outputs i
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