| /external/tensorflow/tensorflow/lite/micro/kernels/ |
| D | split_v.cc | 30 const TfLiteEvalTensor* input, int axis_value) { in SplitImpl() argument
37 TFLITE_DCHECK_LT(axis_value, split_dimensions); in SplitImpl()
44 tflite::micro::GetEvalOutput(context, node, i)->dims->data[axis_value]; in SplitImpl()
46 TFLITE_DCHECK_EQ(split_size, input_dims->data[axis_value]); in SplitImpl()
48 for (int i = 0; i < axis_value; ++i) { in SplitImpl()
53 for (int i = axis_value + 1; i < split_dimensions; ++i) { in SplitImpl()
64 output_tensor->dims->data[axis_value] * base_inner_size; in SplitImpl()
91 int axis_value = tflite::micro::GetTensorData<int32_t>(axis)[0]; in Eval() local
92 if (axis_value < 0) { in Eval()
93 axis_value += input->dims->size; in Eval()
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| D | split.cc | 29 const TfLiteEvalTensor* input, int axis_value) { in SplitImpl() argument
37 int axis = axis_value < 0 ? axis_value + split_dimensions : axis_value; in SplitImpl()
86 int axis_value = tflite::micro::GetTensorData<int32_t>(axis)[0]; in Eval() local
87 if (axis_value < 0) { in Eval()
88 axis_value += input->dims->size; in Eval()
91 TF_LITE_ENSURE(context, axis_value >= 0); in Eval()
92 TF_LITE_ENSURE(context, axis_value < input->dims->size); in Eval()
96 return SplitImpl<float>(context, node, input, axis_value); in Eval()
99 return SplitImpl<uint8_t>(context, node, input, axis_value); in Eval()
102 return SplitImpl<int8_t>(context, node, input, axis_value); in Eval()
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| D | split_v_test.cc | 334 int32_t axis_value[] = {0}; in TF_LITE_MICRO_TEST() local
387 axis_value, split_size_shape, split, in TF_LITE_MICRO_TEST()
411 int32_t axis_value[] = {0}; in TF_LITE_MICRO_TEST() local
464 axis_value, split_size_shape, split, in TF_LITE_MICRO_TEST()
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | split.cc | 54 int axis_value = GetTensorData<int>(axis)[0]; in ResizeOutputTensors() local
55 if (axis_value < 0) { in ResizeOutputTensors()
56 axis_value += NumDimensions(input); in ResizeOutputTensors()
59 TF_LITE_ENSURE(context, axis_value >= 0); in ResizeOutputTensors()
60 TF_LITE_ENSURE(context, axis_value < NumDimensions(input)); in ResizeOutputTensors()
62 const int input_size = SizeOfDimension(input, axis_value); in ResizeOutputTensors()
69 output_dims->data[axis_value] = slice_size; in ResizeOutputTensors()
118 int axis_value = GetTensorData<int>(op_context.axis)[0]; in Eval() local
119 if (axis_value < 0) { in Eval()
120 axis_value += NumDimensions(op_context.input); in Eval()
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| D | expand_dims.cc | 56 const TfLiteTensor& axis, int* axis_value) { in GetAxisValueFromTensor() argument
60 *axis_value = *GetTensorData<int32_t>(&axis); in GetAxisValueFromTensor()
63 *axis_value = *GetTensorData<int64_t>(&axis); in GetAxisValueFromTensor()
83 int axis_value; in Prepare() local
85 GetAxisValueFromTensor(context, *axis, &axis_value)); in Prepare()
86 return ExpandTensorDim(context, *input, axis_value, output); in Prepare()
101 int axis_value; in Eval() local
103 GetAxisValueFromTensor(context, *axis, &axis_value)); in Eval()
105 ExpandTensorDim(context, *input, axis_value, output)); in Eval()
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| D | arg_min_max_test.cc | 33 ArgBaseOpModel(TensorType input_type, int axis_value, TensorType axis_type, in ArgBaseOpModel() argument
35 : axis_value_(axis_value), in ArgBaseOpModel()
42 AddConstInput(axis_type, {static_cast<int64_t>(axis_value)}, {1}); in ArgBaseOpModel()
44 axis_ = AddConstInput(axis_type, {axis_value}, {1}); in ArgBaseOpModel()
85 int axis_value, TensorType axis_type, bool constant_axis, in ArgMaxOpModel() argument
87 : ArgBaseOpModel(input_type, axis_value, axis_type, constant_axis, in ArgMaxOpModel()
100 int axis_value, TensorType axis_type, bool constant_axis, in ArgMinOpModel() argument
102 : ArgBaseOpModel(input_type, axis_value, axis_type, constant_axis, in ArgMinOpModel()
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| D | split_v.cc | 68 int axis_value = GetTensorData<int>(axis)[0]; in ResizeOutputTensors() local
69 if (axis_value < 0) { in ResizeOutputTensors()
70 axis_value += NumDimensions(input); in ResizeOutputTensors()
99 const int input_size = SizeOfDimension(input, axis_value); in ResizeOutputTensors()
117 output_dims->data[axis_value] = size_splits_vector.at(i); in ResizeOutputTensors()
171 int axis_value = GetTensorData<int>(op_context.axis)[0]; in Eval() local
178 op_params.axis = axis_value; \ in Eval()
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| D | arg_min_max.cc | 40 int axis_value; in ResizeOutput() local
43 axis_value = static_cast<int>(*GetTensorData<int64_t>(axis)); in ResizeOutput()
45 axis_value = *GetTensorData<int>(axis); in ResizeOutput()
47 if (axis_value < 0) { in ResizeOutput()
48 axis_value += NumDimensions(input); in ResizeOutput()
55 if (i != axis_value) { in ResizeOutput()
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| /external/tensorflow/tensorflow/lite/testing/op_tests/ |
| D | expand_dims.py | 55 axis_value = tf.constant(
58 axis_value = tf.compat.v1.placeholder(
60 inputs.append(axis_value)
62 out = tf.expand_dims(input_value, axis=axis_value)
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| /external/tensorflow/tensorflow/lite/delegates/hexagon/builders/ |
| D | arg_min_max_builder.cc | 48 int axis_value = axis.data.i32[0]; in PopulateSubGraph() local
49 if (axis_value < 0) { in PopulateSubGraph()
50 axis_value += input_tensor.dims->size; in PopulateSubGraph()
53 kScalarShape, reinterpret_cast<char*>(&axis_value), sizeof(int)); in PopulateSubGraph()
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| D | split_builder.cc | 46 int axis_value = axis.data.i32[0] + (4 - input_tensor.dims->size); in PopulateSubGraph() local
47 if (axis_value < 0) { in PopulateSubGraph()
48 axis_value += input_tensor.dims->size; in PopulateSubGraph()
51 kScalarShape, reinterpret_cast<char*>(&axis_value), sizeof(int)); in PopulateSubGraph()
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| /external/harfbuzz_ng/src/ |
| D | hb-ot-stat-table.hh | 268 const AxisValue &axis_value = (this + get_axis_value_offsets ()[axis_value_index]); in get_axis_value_name_id() local
269 return axis_value.get_value_name_id (); in get_axis_value_name_id()
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| /external/tensorflow/tensorflow/lite/delegates/nnapi/ |
| D | nnapi_delegate_device_selection_test.cc | 245 int axis_value, TensorType output_type, const NnApi* nnapi, in ArgMaxOpModel() argument
248 Init(input_shape, input_type, axis_value, output_type); in ArgMaxOpModel()
252 int axis_value, TensorType output_type, const NnApi* nnapi, in ArgMaxOpModel() argument
255 Init(input_shape, input_type, axis_value, output_type); in ArgMaxOpModel()
266 int axis_value, TensorType output_type) { in Init() argument
269 axis_ = AddConstInput(TensorType_INT32, {axis_value}, {1}); in Init()
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| /external/tensorflow/tensorflow/compiler/mlir/lite/ir/ |
| D | tfl_ops.cc | 1179 int32_t axis_value = op.axis(); in Verify() local
1180 if (axis_value < 0) axis_value += input_type.getRank() + 1; in Verify()
1181 if (axis_value < 0 || axis_value >= input_type.getRank() + 1) in Verify()
1792 int64_t axis_value = op.axis().getInt(); in inferReturnTypes() local
1793 if (axis_value < 0) { in inferReturnTypes()
1794 axis_value += rank; in inferReturnTypes()
1796 if (axis_value < 0 || axis_value >= rank) { in inferReturnTypes()
1802 if (!ShapedType::isDynamic(input_type.getDimSize(axis_value)) && in inferReturnTypes()
1803 input_type.getDimSize(axis_value) != num_value) { in inferReturnTypes()
1808 output_shape.erase(output_shape.begin() + axis_value); in inferReturnTypes()
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| /external/tensorflow/tensorflow/core/ops/ |
| D | array_ops.cc | 1006 std::vector<int64> axis_value; in __anondb9326b21402() local
1008 axis_value = AsInt64<int32>(axis_tensor, axis_tensor->NumElements()); in __anondb9326b21402()
1010 axis_value = AsInt64<int64>(axis_tensor, axis_tensor->NumElements()); in __anondb9326b21402()
1013 for (int i = 0; i < axis_value.size(); i++) { in __anondb9326b21402()
1015 axis_value[i] < 0 ? rank + axis_value[i] : axis_value[i]; in __anondb9326b21402()
1017 return errors::InvalidArgument("'axis'[", i, "] = ", axis_value[i], in __anondb9326b21402()
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| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/transforms/ |
| D | lower_tf.cc | 747 auto axis_value = rewriter.create<ConstOp>( in matchAndRewrite() local
766 rewriter.create<ExpandDimsOp>(loc, inferred_ty, input, axis_value)); in matchAndRewrite()
770 axis_value); in matchAndRewrite()
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| /external/tensorflow/tensorflow/python/ops/ |
| D | array_ops.py | 1839 axis_value = tensor_util.constant_value(axis)
1840 if axis_value is not None:
1841 axis = axis_value
1855 if axis_value is not None:
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| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | pfor.py | 2350 axis_value = tensor_util.constant_value(axis)
2351 if axis_value is not None:
2352 axis = axis_value
|