| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| cudnn_batchnorm_rewriter.cc | 62 if (ShapeUtil::ElementsIn(batch_norm->operand(0)->shape()) == 0) {
98 if (ShapeUtil::ElementsIn(batch_norm->operand(0)->shape()) == 0) {
167 if (ShapeUtil::ElementsIn(batch_norm->operand(0)->shape()) == 0) {
|
| cusolver_rewriter.cc | 117 Shape call_shape = ShapeUtil::MakeTupleShape(
119 ShapeUtil::MakeShape(operand->shape().element_type(), {workspace_size}),
120 ShapeUtil::MakeShape(S32, {batch_size})});
|
| ir_emitter_unnested.cc | 272 ? ShapeUtil::GetSubshape(hlo->shape(), {0})
274 int64 num_elements = ShapeUtil::ElementsIn(element_shape);
304 ShapeUtil::ForEachSubshape(s, [&](const Shape& sub_shape,
306 if (sub_shape.IsArray() && !IsInt32(ShapeUtil::ElementsIn(sub_shape))) {
510 /*mem_size=*/ShapeUtil::ByteSizeOf(shape), custom_call));
560 /*mem_size=*/ShapeUtil::ByteSizeOf(hlo->operand(1)->shape()), hlo));
690 CHECK(ShapeUtil::Compatible(copy->operand(0)->shape(), copy->shape()));
[all...] |
| cudnn_conv_padding_legalization.cc | 329 ShapeUtil::MakeTupleShape(
330 {new_backward_conv_shape, ShapeUtil::MakeShape(U8, {0})}),
374 CHECK(ShapeUtil::Compatible(slice_shape, backward_conv_shape))
375 << ShapeUtil::HumanString(slice_shape) << " vs "
376 << ShapeUtil::HumanString(backward_conv_shape);
|
| cudnn_conv_runner.cc | 133 VLOG(3) << "input shape: " << ShapeUtil::HumanStringWithLayout(input_shape);
134 VLOG(3) << "filter shape: " << ShapeUtil::HumanStringWithLayout(filter_shape);
135 VLOG(3) << "Output shape: " << ShapeUtil::HumanStringWithLayout(output_shape);
150 << ShapeUtil::HumanString(output_shape);
429 LOG(FATAL) << ShapeUtil::HumanString(*params.output_shape);
|
| hlo_to_ir_bindings.cc | 96 ShapeUtil::ForEachSubshape(
157 ShapeUtil::GetSubshape(hlo.shape(), shape_index), module_);
221 ShapeUtil::GetSubshape(hlo.shape(), shape_index));
|
| /external/tensorflow/tensorflow/compiler/xla/service/ |
| hlo_value.cc | 44 return ShapeUtil::GetSubshape(instruction->shape(), index);
259 DCHECK(ShapeUtil::Compatible(inputs[0]->shape(), inputs[i]->shape()));
284 StrCat("InstructionValueSet(", ShapeUtil::HumanString(shape()), ")\n");
|
| hlo_dataflow_analysis_test.cc | 95 const Shape scalar_shape_ = ShapeUtil::MakeShape(F32, {});
96 const Shape vector_shape_ = ShapeUtil::MakeShape(F32, {42});
97 const Shape tuple_shape_ = ShapeUtil::MakeTupleShape(
98 {ShapeUtil::MakeShape(F32, {}), ShapeUtil::MakeShape(F32, {})});
483 ShapeUtil::MakeTupleShape({scalar_shape_, scalar_shape_});
586 ShapeUtil::MakeTupleShape({scalar_shape_, scalar_shape_});
660 ShapeUtil::MakeTupleShape({scalar_shape_, scalar_shape_});
[all...] |
| hlo_evaluator_test.cc | 391 Shape shape = ShapeUtil::MakeShape(S64, {2, 2});
420 ShapeUtil::MakeShape(F32, dimensions), 0.0, 1.0));
425 Shape shape = ShapeUtil::MakeShape(F32, {8, 7, 11, 9, 5});
486 Shape shape = ShapeUtil::MakeShape(S64, {4, 2});
508 Shape shape = ShapeUtil::MakeShape(S64, {2});
583 Shape shape = ShapeUtil::MakeShape(S32, {5, 2});
608 Shape shape = ShapeUtil::MakeShape(F32, {8, 5, 1, 1});
652 Shape shape = ShapeUtil::MakeShape(F32, {1, 5});
697 Shape shape = ShapeUtil::MakeShape(F32, {0, 9});
734 Shape shape = ShapeUtil::MakeShape(F32, {4, 2})
[all...] |
| batchnorm_expander.cc | 84 Shape shape = ShapeUtil::MakeShape(primitive_type, {});
125 ShapeUtil::MakeShape(U32, {}), operand, i));
127 ShapeUtil::MakeShape(U32, {}), HloOpcode::kMultiply,
132 ShapeUtil::MakeShape(operand->shape().element_type(), {}),
314 if (ShapeUtil::Equal(inst->shape(), operand_shape)) {
418 if (ShapeUtil::Equal(inst->shape(), operand_shape)) {
596 if (ShapeUtil::Equal(inst->shape(), activation_shape)) {
|
| hlo_graph_dumper.cc | 123 if (ShapeUtil::HasPrimitiveType(instr->shape(), OPAQUE) ||
124 ShapeUtil::HasPrimitiveType(instr->shape(), TOKEN)) {
127 return ShapeUtil::ElementsInRecursive(instr->shape()) < 4096;
823 if (ShapeUtil::IsZeroElementArray(shape)) {
824 return StrFormat("{} (%s)", ShapeUtil::HumanString(constant->shape()));
850 ShapeUtil::HumanString(constant->shape()));
[all...] |
| hlo_module.cc | 288 TF_RET_CHECK(ShapeUtil::Compatible(expected_program_shape.parameters(i),
292 << ShapeUtil::HumanStringWithLayout(
294 << ", actual: " << ShapeUtil::HumanStringWithLayout(parameter_shape);
299 ShapeUtil::Compatible(expected_program_shape.result(), result_shape))
302 << ShapeUtil::HumanStringWithLayout(expected_program_shape.result())
303 << ", actual: " << ShapeUtil::HumanStringWithLayout(result_shape);
|
| service.cc | 218 TF_RETURN_IF_ERROR(ShapeUtil::ValidateShapeWithOptionalLayout(client_shape));
219 if (!ShapeUtil::Compatible(client_shape, result_shape)) {
223 ShapeUtil::HumanStringWithLayout(client_shape),
224 ShapeUtil::HumanString(result_shape));
279 if (!ShapeUtil::Compatible(*argument_shapes[i],
284 i, ShapeUtil::HumanString(program_shape.parameters(i)),
285 ShapeUtil::HumanString(*argument_shapes[i]));
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| client_library_test_base.cc | 198 auto layout = ShapeUtil::MakeShapeWithLayout(
205 ShapeUtil::HumanStringWithLayout(layout)));
230 ShapeUtil::HumanStringWithLayout(literal.shape()));
244 ShapeUtil::HumanStringWithLayout(literal_relayout.shape()));
317 if (ShapeUtil::ElementIsFloating(expected.shape()) ||
318 ShapeUtil::ElementIsComplex(expected.shape())) {
331 ShapeUtil::ForEachMutableSubshape(
388 ShapeUtil::ForEachMutableSubshape(
530 auto shape = ShapeUtil::MakeShape(use_bfloat16_ ? BF16 : F32, {});
543 auto shape = ShapeUtil::MakeShape(use_bfloat16_ ? BF16 : F32, {})
[all...] |
| matrix_ops_simple_test.cc | 80 Parameter(&builder, 0, ShapeUtil::MakeShapeWithType<T>({}), "x_value");
197 ShapeUtil::MakeShape(prim_type, {lhs.height(), lhs.width()});
199 ShapeUtil::MakeShape(prim_type, {rhs.height(), rhs.width()});
|
| reduce_test.cc | 85 CHECK(ShapeUtil::Equal(
87 ShapeUtil::MakeShape(F32, {/*z=*/4, /*y=*/2, /*x=*/3})))
95 const Shape input_shape = ShapeUtil::MakeShape(F32, {element_count});
122 const Shape input_shape = ShapeUtil::MakeShape(S32, {element_count});
160 const Shape input_shape = ShapeUtil::MakeShape(U8, {rows, cols});
205 const Shape input_shape = ShapeUtil::MakeShape(F32, {rows, cols});
232 const Shape input_shape = ShapeUtil::MakeShape(F32, {rows, cols});
287 const Shape input_shape = ShapeUtil::MakeShape(
442 const Shape input_shape = ShapeUtil::MakeShape(F32, {rows, cols});
472 const Shape input_shape = ShapeUtil::MakeShape(F32, {rows, cols})
[all...] |
| test_utils.cc | 122 Shape floating_point_shape = ShapeUtil::ChangeElementType(
174 if (no_duplicates && ShapeUtil::ElementsIn(literal->shape()) <
267 ShapeUtil::HumanString(shape));
340 ShapeUtil::HumanString(shape));
460 ShapeUtil::GetDimension(indexed_shape, operand - first_index) -
461 ShapeUtil::GetDimension(slice_shape,
|
| /external/tensorflow/tensorflow/compiler/tf2xla/ |
| xla_compiler_test.cc | 326 xla::ShapeUtil::MakeShapeWithLayout(xla::S32, {2, 3}, {0, 1});
329 xla::ShapeUtil::MakeTupleShape({transposed, transposed}));
368 xla::ShapeUtil::MakeShapeWithLayout(xla::S32, {2, 3}, {1, 0});
371 xla::ShapeUtil::MakeTupleShape({transposed, transposed}));
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/tools/ |
| replay_computation.cc | 126 LOG(ERROR) << " " << ShapeUtil::HumanString(Shape(infeed.shape())) << " "
167 << ShapeUtil::HumanString(*xfeed_shape);
257 << ShapeUtil::HumanStringWithLayout(*outfeed_shape);
401 ShapeUtil::HumanString(result.shape()).c_str(),
409 ShapeUtil::HumanString(Shape(snapshot.result().shape())).c_str(),
|
| /external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
| dot_op_emitter.cc | 241 int64 size_bytes = m * n * ShapeUtil::ByteSizeOfPrimitiveType(primitive_type);
380 if (ShapeUtil::IsScalar(lhs_shape) || ShapeUtil::IsScalar(rhs_shape)) {
382 TF_RET_CHECK(ShapeUtil::IsScalar(lhs_shape) &&
383 ShapeUtil::IsScalar(rhs_shape));
495 if (ShapeUtil::ElementIsComplex(lhs_shape)) {
556 if (ShapeUtil::ElementIsComplex(lhs_array_.GetShape())) {
773 if (ShapeUtil::IsZeroElementArray(dot_info.lhs_shape) ||
774 ShapeUtil::IsZeroElementArray(dot_info.rhs_shape)) {
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/ |
| shape_tree.h | 100 ShapeTree() : ShapeTree(ShapeUtil::MakeNil()) {}
118 // given index (see ShapeUtil::GetSubshape for how indexes are defined).
244 // index : the index of the element in the shape. See ShapeUtil::GetSubshape
311 // ShapeUtil::GetSubshape).
399 int64 count = ShapeUtil::TupleElementCount(shape);
411 const int64 size = ShapeUtil::TupleElementCount(shape);
447 const int64 size = ShapeUtil::TupleElementCount(shape);
646 CHECK(ShapeUtil::Compatible(
647 ShapeUtil::GetSubshape(shape(), target_base_index),
648 ShapeUtil::GetSubshape(other.shape(), source_base_index)))
[all...] |
| literal_util.h | 315 Literal literal(ShapeUtil::MakeShape(
324 ShapeUtil::MakeShape(primitive_util::NativeToPrimitiveType<NativeT>(),
334 Literal literal(ShapeUtil::MakeShapeWithLayout(
420 Literal literal(ShapeUtil::MakeShapeWithSparseLayout(
438 Literal literal(ShapeUtil::MakeShapeWithLayout(
554 Literal literal(ShapeUtil::MakeShapeWithDescendingLayout(
|
| shape_util.h | 47 // ShapeUtil::GetSubshape and other interfaces. Shapes are recursive data
171 class ShapeUtil {
261 return ShapeUtil::SameElementType(a, b);
393 return ShapeUtil::MakeShape(primitive_util::NativeToPrimitiveType<T>(),
598 // ShapeUtil::ReshapeIsBitcast(input_shape, output_shape_with_layout) returns
637 // Simple ergonomic wrapper around ShapeUtil::ForEachIndexWithStatus.
648 return ShapeUtil::ForEachIndexWithStatus(
728 if (ShapeUtil::IsZeroElementArray(shape)) {
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/client/ |
| local_client.cc | 75 ShapeUtil::HumanStringWithLayout(
77 ShapeUtil::HumanStringWithLayout(arguments[i]->on_host_shape()));
332 ::xla::ShapeUtil::HumanString(shape))));
|
| /external/tensorflow/tensorflow/compiler/xla/service/cpu/tests/ |
| cpu_fusion_test.cc | 153 auto cshape = ShapeUtil::MakeShape(F32, {6});
158 Shape r0f32 = ShapeUtil::MakeShape(F32, {});
172 ShapeUtil::MakeShape(F32, {6, 1}), concatenate)),
|
