| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| mean.mod.py | 3 axis = Parameter("axis", "TENSOR_INT32", "{1}", [2]) variable
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_1.mod.py | 3 axis = Parameter("axis", "TENSOR_INT32", "{4}", [1, 0, -3, -3]) variable
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_1_relaxed.mod.py | 19 axis = Parameter("axis", "TENSOR_INT32", "{4}", [1, 0, -3, -3]) variable
23 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_2.mod.py | 3 axis = Parameter("axis", "TENSOR_INT32", "{2}", [0, 2]) variable
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_2_relaxed.mod.py | 19 axis = Parameter("axis", "TENSOR_INT32", "{2}", [0, 2]) variable
23 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_quant8_1.mod.py | 3 axis = Parameter("axis", "TENSOR_INT32", "{4}", [1, 0, -3, -3]) variable
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_quant8_2.mod.py | 3 axis = Parameter("axis", "TENSOR_INT32", "{2}", [0, 2]) variable
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_relaxed.mod.py | 19 axis = Parameter("axis", "TENSOR_INT32", "{1}", [2]) variable
23 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| pack_op.cc | 42 OP_REQUIRES_OK(ctx, ctx->GetAttr("axis", &axis_));
64 int axis = axis_; variable
65 if (axis < 0) axis += expanded_num_dims;
67 OP_REQUIRES(ctx, 0 <= axis && axis < expanded_num_dims,
68 errors::InvalidArgument("axis = ", axis_, " not in [",
75 child_shape.InsertDim(axis, 1);
83 ctx->SetOutput(0, ctx->builder()->ConcatInDim(reshaped_inputs, axis));
|
| unpack_op.cc | 42 OP_REQUIRES_OK(ctx, ctx->GetAttr("axis", &axis_));
49 int axis = axis_; variable
50 if (axis < 0) axis += input_shape.dims();
52 OP_REQUIRES(ctx, 0 <= axis && axis < input_shape.dims(),
53 errors::InvalidArgument("axis = ", axis_, " not in [",
58 ctx, input_shape.dims() > 0 && input_shape.dim_size(axis) == num,
59 errors::InvalidArgument("Input shape axis ", axis, " must equal ", num
[all...] |
| index_ops.cc | 50 const int axis = dim < 0 ? dim + input_dims : dim; local
53 ctx, axis >= 0 && axis < input_dims,
56 const int64 axis_size = input_shape.dim_size(axis);
59 errors::InvalidArgument("Reduction axis ", dim, " is empty in shape ",
71 index_type, axis, &output));
75 index_type, axis, &output));
|
| one_hot_op.cc | 29 OP_REQUIRES_OK(ctx, ctx->GetAttr("axis", &axis_));
44 errors::InvalidArgument("Expected axis to be -1 or between [0, ",
56 const int axis = (axis_ == -1) ? indices_dims : axis_; variable
67 ctx, XlaHelpers::OneHot(ctx->builder(), depth, axis, input_type(0),
|
| /external/tensorflow/tensorflow/contrib/reduce_slice_ops/ops/ |
| reduce_slice_ops.cc | 31 // "axis" must be a scala
41 // if "indices" is a vector of 0 elements, then the axis dimension of
57 int64 axis = _axis->scalar<int64>()(); local
58 TF_RETURN_IF_ERROR(c->ReplaceDim(handle, axis, dim_axis, &handle));
69 .Input("axis: int64")
114 .Input("axis: int64")
171 .Input("axis: int64")
228 .Input("axis: int64")
|
| /external/tensorflow/tensorflow/core/kernels/ |
| unique_op.cc | 47 int64 axis = 0; variable
53 // In case of UniqueV2, the axis is a 1D vector. The purpose is
54 // to allow specifying either "no axis" or "axis". The `[]` means
55 // "no axis", while `[x]` means `axis = x`.
58 errors::InvalidArgument("axis expects a 1D vector."));
62 "axis does not support input tensors larger than 1 elements"));
71 "axis tensor should be int32 or int64, but got ",
74 axis = internal::SubtleMustCopy(axis_tensor.scalar<int32>()())
[all...] |
| /frameworks/ml/nn/runtime/test/generated/models/ |
| mean.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_1.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_1_relaxed.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_2.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_2_relaxed.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_quant8_1.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_quant8_2.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_relaxed.model.cpp | 9 auto axis = model->addOperand(&type1); local
14 model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| /external/eigen/demos/opengl/ |
| trackball.cpp | 24 Vector3f axis = mLastPoint3D.cross(newPoint3D).normalized(); local
30 mpCamera->rotateAroundTarget(Quaternionf(AngleAxisf(angle, axis)));
32 mpCamera->localRotate(Quaternionf(AngleAxisf(-angle, axis)));
|
| /external/tensorflow/tensorflow/contrib/lite/kernels/ |
| mean_test.cc | 48 // Model for the tests case where axis is a const tensor.
53 std::initializer_list<int> axis, bool keep_dims) {
55 axis_ = AddConstInput(TensorType_INT32, axis, axis_shape);
63 // Model for the tests case where axis is a dynamic tensor.
67 const TensorData& axis, bool keep_dims) {
69 axis_ = AddInput(axis);
109 std::initializer_list<int> axis = {1, 0, -3, -3}; local
110 m.SetAxis(axis);
124 std::initializer_list<int> axis = {0, 2}; local
125 m.SetAxis(axis);
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
| convert_expanddims_to_reshape.cc | 51 // Yield until input axis array shape has been resolved.
56 // Yield until the input axis array is constant
59 int axis = axis_array.GetBuffer<ArrayDataType::kInt32>().data[0]; local
61 if (axis < 0) {
62 axis = reshape_dims.size();
64 reshape_dims.insert(reshape_dims.begin() + axis, 1);
66 // The input tensor has shape, and the axis input is constant. We can now
85 // Delete axis array if unused
|
