| /external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
| parallel_loop_emitter.cc | 41 const int64 num_dims = shape_.dimensions_size(); local
42 std::vector<llvm::Value*> array_multi_index(num_dims);
47 const int bounds_index = num_dims - 1 - i;
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| conv_canonicalization.cc | 46 const int64 num_dims = num_spatial_dims + 2; local
59 std::vector<int64> new_input_dim_order(num_dims);
60 std::vector<int64> new_input_dims(num_dims);
68 new_input_dim_order[num_dims - 1] = input_feature_dim;
69 new_input_dims[num_dims - 1] =
80 std::vector<int64> new_kernel_dim_order(num_dims);
81 std::vector<int64> new_kernel_dims(num_dims);
87 new_kernel_dim_order[num_dims - 2] = kernel_input_feature_dim;
88 new_kernel_dims[num_dims - 2] =
90 new_kernel_dim_order[num_dims - 1] = kernel_output_feature_dim
[all...] |
| /external/tensorflow/tensorflow/lite/delegates/flex/ |
| util.cc | 40 int num_dims = src.dims(); local
41 TfLiteIntArray* shape = TfLiteIntArrayCreate(num_dims);
42 for (int j = 0; j < num_dims; ++j) {
|
| buffer_map.cc | 149 int num_dims = tensor->dims->size; local
150 for (int i = 0; i < num_dims; ++i) {
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| reshape_op.cc | 43 const int64 num_dims = sizes_shape.num_elements(); variable
54 for (int d = 0; d < num_dims; ++d) {
|
| sparse_to_dense_op.cc | 39 const int64 num_dims = variable
45 OP_REQUIRES(context, output_shape.dims() == num_dims,
48 output_shape.num_elements(), " should be: ", num_dims));
77 /*indices_are_vectors=*/num_dims > 1,
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| diag_op.cc | 129 int num_dims = dims.size(); variable
130 const int out_dims = num_dims / 2;
132 OP_REQUIRES(ctx, 2 <= num_dims,
135 OP_REQUIRES(ctx, num_dims % 2 == 0,
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| extract_image_patches_op.cc | 38 const int num_dims = ksizes_.size(); variable
41 ctx, num_dims >= 3,
43 const int num_spatial_dims = num_dims - 2;
45 OP_REQUIRES(ctx, strides_.size() == num_dims,
48 num_dims, " dimensions"));
49 OP_REQUIRES(ctx, dilations_.size() == num_dims,
52 num_dims, " dimensions"));
54 int batch_dim = GetTensorBatchDimIndex(num_dims, data_format);
55 int feature_dim = GetTensorFeatureDimIndex(num_dims, data_format);
71 int input_dim = GetTensorSpatialDimIndex(num_dims, data_format, i)
[all...] |
| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/ |
| scatter_add_ndim_op.cc | 69 const int32 num_dims = variable
75 for (int32 i = 0; i < input_tensor.shape().dims() - num_dims; ++i) {
76 num_data_per_index *= input_tensor.shape().dim_size(num_dims + i);
86 for (int32 j = 0; j < num_dims; j++) {
95 for (int32 j = 0; j < num_dims; j++) {
|
| /external/tensorflow/tensorflow/core/kernels/ |
| reshape_op.h | 98 const int64 num_dims = sizes.NumElements(); local
100 for (int d = 0; d < num_dims; ++d) {
|
| conv_grad_ops.cc | 105 const int num_dims = num_spatial_dims + 2; local
106 if (input_shape.dims() != num_dims) {
107 return errors::InvalidArgument(label, ": input must be ", num_dims,
110 if (filter_shape.dims() != num_dims) {
111 return errors::InvalidArgument(label, ": filter must be ", num_dims,
114 if (out_backprop_shape.dims() != num_dims) {
115 return errors::InvalidArgument(label, ": out_backprop must be ", num_dims,
118 int batch_dim = GetTensorBatchDimIndex(num_dims, data_format);
128 int feature_dim = GetTensorFeatureDimIndex(num_dims, data_format);
133 << filter_shape.dim_size(num_dims - 2)
[all...] |
| sparse_slice_grad_op.cc | 72 const int num_dims = input_indices->dim_size(1); variable
73 OP_REQUIRES(ctx, num_dims == input_start->NumElements(),
75 "Expected input_start to be a vector of length ", num_dims,
96 for (int d = 0; d < num_dims; ++d) {
|
| sparse_to_dense_op.cc | 60 const int64 num_dims = indices.dims() > 1 ? indices.dim_size(1) : 1; variable
68 OP_REQUIRES(c, output_shape.NumElements() == num_dims,
71 output_shape.NumElements(), " should be: ", num_dims));
96 TensorShape ix_shape({num_elems, num_dims});
|
| attention_ops.cc | 69 const int32 num_dims = input_shape.dims(); variable
71 context, num_dims == 4,
|
| diag_op.cc | 49 const int num_dims = diagonal.dims(); variable
51 context, 0 != num_dims,
54 for (int i = 0; i < num_dims; ++i) {
57 for (int i = 0; i < num_dims; ++i) {
79 const int num_dims = tensor.dims(); variable
80 const int out_dims = num_dims / 2;
81 OP_REQUIRES(context, 0 == num_dims % 2,
|
| nth_element_op.cc | 52 const int num_dims = input_in.dims(); variable
53 OP_REQUIRES(context, num_dims >= 1,
58 context, input_in.dim_size(num_dims - 1) > n,
63 n = input_in.dim_size(num_dims - 1) - n - 1;
68 for (int i = 0; i < num_dims - 1; ++i) {
|
| roll_op.cc | 40 const int num_dims, const gtl::ArraySlice<int>& dim_size,
43 auto work = [input, output, num_dims, &dim_size, &threshold, &dim_range](
46 gtl::InlinedVector<int, 4> indices(num_dims);
49 for (int i = 0; i < num_dims; i++) {
66 for (int j = num_dims - 1; j >= 0; j--) {
103 const int num_dims, const gtl::ArraySlice<int>& dim_size,
108 auto work = [input, output, num_dims, &dim_size, &threshold, &dim_range, isd](
132 gtl::InlinedVector<int, 4> indicies(num_dims);
136 for (int i = 0; i < num_dims; i++) {
154 for (int i = num_dims - 1; i > isd; i--) indicies[i] = 0
252 const int num_dims = input.dims(); variable
[all...] |
| sparse_add_grad_op.cc | 67 const int num_dims = a_indices->dim_size(1); variable
90 idx, k, num_dims)) { \
|
| mkl_reshape_op.cc | 226 const int64 num_dims = sizes.NumElements(); local
228 for (int d = 0; d < num_dims; ++d) {
|
| parameterized_truncated_normal_op.cc | 342 const int32 num_dims = shape_tensor.dim_size(0); variable
343 for (int32 i = 1; i < num_dims; i++) {
|
| sparse_add_op.cc | 102 const int num_dims = a_shape->dim_size(0); variable
110 num_dims)) {
149 ctx->allocate_output(0, TensorShape({sum_nnz, num_dims}),
|
| /external/tensorflow/tensorflow/java/src/main/native/ |
| operation_jni.cc | 106 jsize num_dims = TF_GraphGetTensorNumDims(graph, output, status); local
111 if (num_dims < 0) return nullptr;
120 std::unique_ptr<int64_t[]> cdims(new int64_t[num_dims]);
121 TF_GraphGetTensorShape(graph, output, cdims.get(), static_cast<int>(num_dims),
129 jlongArray ret = env->NewLongArray(num_dims);
131 for (int i = 0; i < num_dims; ++i) {
|
| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| svd_test.cc | 87 int num_dims = u_shape.rank(); local
88 std::vector<int64> broadcast_dims(num_dims - 1);
90 broadcast_dims[num_dims - 2] = num_dims - 1;
|
| /external/deqp-deps/SPIRV-Tools/source/opt/ |
| fold_spec_constant_op_and_composite_pass.cpp | 351 uint32_t num_dims = result_type->AsVector()->element_count(); local
353 context()->get_instruction_folder().FoldVectors(spec_opcode, num_dims,
|
| /external/swiftshader/third_party/SPIRV-Tools/source/opt/ |
| fold_spec_constant_op_and_composite_pass.cpp | 351 uint32_t num_dims = result_type->AsVector()->element_count(); local
353 context()->get_instruction_folder().FoldVectors(spec_opcode, num_dims,
|
