| /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
| read_fake_quant_min_max.cc | 56 CHECK_EQ(fakequant_op->inputs.size(), 3);
60 if (!IsConstantParameterArray(*model, fakequant_op->inputs[1])) {
66 const auto& min_array = model->GetArray(fakequant_op->inputs[1]);
67 const auto& max_array = model->GetArray(fakequant_op->inputs[2]);
82 if (CountOpsWithInput(*model, fakequant_op->inputs[i]) == 1) {
83 model->EraseArray(fakequant_op->inputs[i]);
86 fakequant_op->inputs.resize(1);
94 CHECK_EQ(1, fakequant_op->inputs.size());
99 changed |= ApplyMinMaxToArray(this, model, minmax, fakequant_op->inputs[0]);
|
| resolve_tensorflow_tile.cc | 32 CHECK_EQ(binary_op->inputs.size(), 2);
33 CHECK_EQ(tile_op->inputs.size(), 2);
34 const string tile_multiplier_array = tile_op->inputs[1];
36 binary_op->inputs[operand_index] = tile_op->inputs[0];
60 if (binary_op->inputs.size() != 2) {
71 GetOpWithOutput(*model, binary_op->inputs[0]),
72 GetOpWithOutput(*model, binary_op->inputs[1]),
87 if (CountOpsWithInput(*model, binary_op->inputs[i]) == 1) {
|
| remove_tensorflow_assert.cc | 36 auto it = op->inputs.begin();
37 while (it != op->inputs.end()) {
39 op->inputs.erase(it);
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| resolve_mean_attributes.cc | 36 if (op->inputs.size() != 2) return false;
37 if (!IsConstantParameterArray(*model, op->inputs[1])) return false;
39 const auto& indices_array = model->GetArray(op->inputs[1]);
|
| drop_fake_quant.cc | 45 // Drop min/max inputs
46 for (int i = 1; i < fakequant_op->inputs.size(); i++) {
47 if (CountOpsWithInput(*model, fakequant_op->inputs[i]) == 1) {
48 model->EraseArray(fakequant_op->inputs[i]);
51 fakequant_op->inputs.resize(1);
|
| resolve_tensorflow_merge.cc | 37 // non-selected inputs, so that at some point there will be only 1 input left.
38 if (merge_op->inputs.size() > 1) {
45 CHECK_EQ(merge_op->inputs.size(), 1);
49 for (auto& input : other_op->inputs) {
51 input = merge_op->inputs[0];
|
| reorder_activation_functions.cc | 39 auto exchange_it = FindOpWithOutput(*model, ac_op->inputs[0]);
49 DCHECK_EQ(exchange_op->outputs[0], ac_op->inputs[0]);
50 const auto& exchange_op_input = exchange_op->inputs[0];
79 // Rewire by changing inputs, including all consumers.
82 for (int i = 0; i < consumer->inputs.size(); ++i) {
83 if (consumer->inputs[i] == ac_op_output) {
84 consumer->inputs[i] = intermediate_array;
89 ac_op->inputs[0] = exchange_op_input;
90 exchange_op->inputs[0] = ac_op_output;
|
| resolve_tensorflow_switch.cc | 34 CHECK_EQ(switch_op->inputs.size(), 2);
36 const string& predicate_name = switch_op->inputs[1];
74 for (auto& input : other_op->inputs) {
76 input = switch_op->inputs[0];
90 auto input_it = other_op->inputs.begin();
91 while (input_it != other_op->inputs.end()) {
96 input_it = other_op->inputs.erase(input_it);
111 for (const auto& input : switch_op->inputs) {
|
| /external/tensorflow/tensorflow/cc/framework/ |
| while_gradients_test.cc | 42 const std::vector<Output>* inputs = nullptr) {
43 if (inputs == nullptr) inputs = &inputs_;
44 TF_ASSERT_OK(ops::BuildWhileLoop(scope_, *inputs, cond, body, "test_loop",
95 [](const Scope& s, const std::vector<Output>& inputs, Output* output) {
96 *output = ops::Less(s, inputs[0], 10);
99 [](const Scope& s, const std::vector<Output>& inputs,
104 outputs->push_back(ops::AddN(s, {inputs[0], 1}));
117 [](const Scope& s, const std::vector<Output>& inputs, Output* output) {
118 *output = ops::Less(s, inputs[0], 10)
[all...] |
| gradients.h | 29 /// 'grad_outputs') the symbolic partial derivatives of 'L' w.r.t 'inputs'.
32 const std::vector<Output>& inputs,
40 const std::vector<Output>& inputs,
|
| /external/tensorflow/tensorflow/cc/ops/ |
| while_loop.h | 25 // Function that takes cond graph inputs and returns cond graph boolean output.
27 typedef std::function<Status(const Scope&, const std::vector<Output>& inputs,
31 // Function that takes body graph inputs and returns body graph outputs.
33 typedef std::function<Status(const Scope&, const std::vector<Output>& inputs,
41 // * inputs: the initial values of the loop variables. Must be non-empty.
43 // current loop variables as inputs and returns a scalar boolean Output
46 // loop variables as inputs and returns the updated loop variables.
65 Status BuildWhileLoop(const Scope& scope, const std::vector<Output>& inputs,
|
| /external/deqp/modules/gles3/functional/ |
| es3fShaderPackingFunctionTests.cpp | 151 m_spec.inputs.push_back(Symbol("in0", glu::VarType(glu::TYPE_FLOAT_VEC2, precision)));
160 std::vector<tcu::Vec2> inputs; local
167 inputs.push_back(tcu::Vec2(0.0f, 0.0f));
168 inputs.push_back(tcu::Vec2(-1.0f, 1.0f));
169 inputs.push_back(tcu::Vec2(0.5f, -0.5f));
170 inputs.push_back(tcu::Vec2(-1.5f, 1.5f));
171 inputs.push_back(tcu::Vec2(0.25f, -0.75f));
178 inputs.push_back(tcu::Vec2(x, y));
186 inputs.push_back(tcu::Vec2(x, y));
189 outputs.resize(inputs.size())
264 std::vector<deUint32> inputs; local
351 std::vector<tcu::Vec2> inputs; local
455 std::vector<deUint32> inputs; local
542 std::vector<tcu::Vec2> inputs; local
648 std::vector<deUint32> inputs; local
[all...] |
| /external/deqp/external/vulkancts/modules/vulkan/shaderexecutor/ |
| vktShaderPackingFunctionTests.cpp | 166 std::vector<tcu::Vec2> inputs; local
173 inputs.push_back(tcu::Vec2(0.0f, 0.0f));
174 inputs.push_back(tcu::Vec2(-1.0f, 1.0f));
175 inputs.push_back(tcu::Vec2(0.5f, -0.5f));
176 inputs.push_back(tcu::Vec2(-1.5f, 1.5f));
177 inputs.push_back(tcu::Vec2(0.25f, -0.75f));
184 inputs.push_back(tcu::Vec2(x, y));
192 inputs.push_back(tcu::Vec2(x, y));
195 outputs.resize(inputs.size());
197 m_testCtx.getLog() << TestLog::Message << "Executing shader for " << inputs.size() << " input values" << tcu::TestLog::EndMessage
288 std::vector<deUint32> inputs; local
389 std::vector<tcu::Vec2> inputs; local
511 std::vector<deUint32> inputs; local
614 std::vector<tcu::Vec2> inputs; local
735 std::vector<deUint32> inputs; local
860 std::vector<tcu::Vec4> inputs; local
992 std::vector<deUint32> inputs; local
1103 std::vector<tcu::Vec4> inputs; local
1235 std::vector<deUint32> inputs; local
[all...] |
| /external/deqp/modules/gles31/functional/ |
| es31fShaderPackingFunctionTests.cpp | 155 m_spec.inputs.push_back(Symbol("in0", glu::VarType(glu::TYPE_FLOAT_VEC2, precision)));
164 std::vector<tcu::Vec2> inputs; local
171 inputs.push_back(tcu::Vec2(0.0f, 0.0f));
172 inputs.push_back(tcu::Vec2(-1.0f, 1.0f));
173 inputs.push_back(tcu::Vec2(0.5f, -0.5f));
174 inputs.push_back(tcu::Vec2(-1.5f, 1.5f));
175 inputs.push_back(tcu::Vec2(0.25f, -0.75f));
182 inputs.push_back(tcu::Vec2(x, y));
190 inputs.push_back(tcu::Vec2(x, y));
193 outputs.resize(inputs.size())
268 std::vector<deUint32> inputs; local
355 std::vector<tcu::Vec2> inputs; local
459 std::vector<deUint32> inputs; local
546 std::vector<tcu::Vec2> inputs; local
652 std::vector<deUint32> inputs; local
762 std::vector<tcu::Vec4> inputs; local
876 std::vector<deUint32> inputs; local
971 std::vector<tcu::Vec4> inputs; local
1085 std::vector<deUint32> inputs; local
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| math_grad_test.py | 102 inputs = constant_op.constant([1.0], dtype=dtypes.float32)
103 outputs = math_ops.reduce_min(array_ops.concat([inputs, inputs], 0))
105 error = gradient_checker.compute_gradient_error(inputs, [1], outputs, [])
109 inputs = constant_op.constant([1.0], dtype=dtypes.float32)
110 outputs = math_ops.reduce_max(array_ops.concat([inputs, inputs], 0))
112 error = gradient_checker.compute_gradient_error(inputs, [1], outputs, [])
119 inputs = constant_op.constant([1.0, 2.0, 3.0, 4.0], dtype=dtypes.float32)
120 outputs = math_ops.maximum(inputs, 3.0
[all...] |
| nn_grad.py | 48 array_ops.shape(op.inputs[1]),
49 op.inputs[2],
57 op.inputs[1],
70 array_ops.shape(op.inputs[0]),
72 op.inputs[2],
79 op.inputs[0],
94 array_ops.shape(op.inputs[0]),
95 op.inputs[1],
101 op.inputs[0],
102 array_ops.shape(op.inputs[1])
[all...] |
| image_grad.py | 38 image = op.inputs[0]
66 grad, op.inputs[0], align_corners=op.get_attr("align_corners"))
84 if op.inputs[0].dtype in allowed_types:
87 grad, op.inputs[0], align_corners=op.get_attr("align_corners"))
107 image = op.inputs[0]
114 if op.inputs[0].dtype in allowed_types:
117 op.inputs[1],
118 op.inputs[2],
125 grad1 = gen_image_ops.crop_and_resize_grad_boxes(grad, op.inputs[0],
126 op.inputs[1], op.inputs[2]
[all...] |
| /external/pdfium/core/fpdfapi/page/ |
| cpdf_expintfunc.h | 19 bool v_Call(float* inputs, float* results) const override;
|
| cpdf_psfunc.h | 22 bool v_Call(float* inputs, float* results) const override;
|
| /external/skia/include/effects/ |
| SkComposeImageFilter.h | 23 explicit SkComposeImageFilter(sk_sp<SkImageFilter> inputs[2]) : INHERITED(inputs, 2, nullptr) {
24 SkASSERT(inputs[0].get());
25 SkASSERT(inputs[1].get());
|
| /external/skqp/include/effects/ |
| SkComposeImageFilter.h | 23 explicit SkComposeImageFilter(sk_sp<SkImageFilter> inputs[2]) : INHERITED(inputs, 2, nullptr) {
24 SkASSERT(inputs[0].get());
25 SkASSERT(inputs[1].get());
|
| /external/tensorflow/tensorflow/cc/tools/ |
| freeze_saved_model.h | 28 // `inputs` and `outputs` consist of the union of all inputs and outputs in the
38 std::unordered_set<string>* inputs,
|
| /external/tensorflow/tensorflow/core/common_runtime/ |
| function_testlib.h | 31 gtl::ArraySlice<Input> inputs);
|
| /external/tensorflow/tensorflow/contrib/specs/python/ |
| summaries_test.py | 39 inputs = constant_op.constant(_rand(*inputs_shape))
41 outputs = specs.create_net(spec, inputs)
52 inputs = constant_op.constant(_rand(1, 18, 19, 5))
54 outputs = specs.create_net(spec, inputs)
59 summaries.tf_spec_structure(spec, inputs),
64 inputs = constant_op.constant(_rand(1, 18, 19, 5))
66 outputs = specs.create_net(spec, inputs)
70 summaries.tf_spec_print(spec, inputs)
74 inputs = constant_op.constant(_rand(1, 18, 19, 5))
76 outputs = specs.create_net(spec, inputs)
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| merge.py | 17 """Layers that can merge several inputs into one.
42 def _merge_function(self, inputs):
87 raise ValueError('A merge layer should be called ' 'on a list of inputs.')
90 'on a list of at least 2 inputs. '
91 'Got ' + str(len(input_shape)) + ' inputs.')
109 # If the inputs have different ranks, we have to reshape them
116 def call(self, inputs):
117 if not isinstance(inputs, list):
118 raise ValueError('A merge layer should be called ' 'on a list of inputs.')
121 input_ndims = list(map(K.ndim, inputs))
[all...] |
