STT-tensorflow/tensorflow/c/kernels/bitcast_op_test.cc
Derek Murray 06e20a2fe2 Remove unused tensor-reference-recording feature from the executor.
This change also removes the `Device::RequiresRecordingAccessedTensors()` and `Device::ConsumeListOfAccessedTensors()` methods.

Some device objects (historically, GPUs with experimental multi-stream support) required the ability to record which tensors were used during kernel execution. This support has bit-rotted since it was introduced, and causes runtime overhead for most devices that do not use the feature.

PiperOrigin-RevId: 300443774
Change-Id: Ia44ff65dee57f4d9f971f0079f79edd2fde2a1dc
2020-03-11 17:40:42 -07:00

160 lines
5.5 KiB
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/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/attr_value_util.h"
#include "tensorflow/core/framework/fake_input.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/platform/test.h"
namespace tensorflow {
namespace {
class DummyDevice : public DeviceBase {
public:
explicit DummyDevice(Env* env) : DeviceBase(env) {}
Allocator* GetAllocator(AllocatorAttributes /*attr*/) override {
return cpu_allocator();
}
};
void TestBitcastOp(Tensor* input_tensor, DataType out_type,
TensorShape expected_shape, error::Code expected_code) {
Status status;
NodeDef def;
def.set_op("Bitcast");
def.set_device(DEVICE_CPU);
AttrValue typeAttr;
SetAttrValue(input_tensor->dtype(), &typeAttr);
AttrValue outTypeAttr;
SetAttrValue(out_type, &outTypeAttr);
(*def.mutable_attr())["T"] = typeAttr;
(*def.mutable_attr())["type"] = outTypeAttr;
def.add_input(
strings::StrCat("input1: ", DataTypeString(input_tensor->dtype())));
std::unique_ptr<OpKernel> kernel =
CreateOpKernel(DeviceType(DEVICE_CPU), nullptr, nullptr, def, 1, &status);
ASSERT_TRUE(status.ok()) << status.ToString();
OpKernelContext::Params params;
DummyDevice dummy_device(nullptr);
params.device = &dummy_device;
params.op_kernel = kernel.get();
gtl::InlinedVector<TensorValue, 4> inputs;
inputs.emplace_back(input_tensor);
params.inputs = &inputs;
OpKernelContext ctx(&params);
kernel->Compute(&ctx);
ASSERT_EQ(expected_code, ctx.status().code());
if (expected_code == error::OK) {
ASSERT_EQ(expected_shape, ctx.mutable_output(0)->shape())
<< ctx.mutable_output(0)->shape().DebugString();
}
}
TEST(BitcastOpTest, TestUpcast) {
Tensor int8_input(DT_UINT8, {8});
for (int i = 0; i < 8; i++) {
int8_input.vec<uint8>()(i) = static_cast<uint8>(1);
}
TestBitcastOp(&int8_input, DT_UINT64, TensorShape(), error::OK);
}
TEST(BitcastOpTest, TestDowncast) {
Tensor int64_input(static_cast<uint64>(1));
TestBitcastOp(&int64_input, DT_UINT8, TensorShape({8}), error::OK);
}
TEST(BitcastOpTest, TestCastToSameSize) {
Tensor int32_input(DT_UINT32, {4, 6});
TestBitcastOp(&int32_input, DT_UINT8, TensorShape({4, 6, 4}), error::OK);
}
TEST(BitcastOpTest, TestImpossibleCast) {
Tensor int8_input(DT_UINT8, {1});
TestBitcastOp(&int8_input, DT_UINT32, TensorShape(), error::INVALID_ARGUMENT);
}
PartialTensorShape S(std::initializer_list<int64> dims) {
return PartialTensorShape(dims);
}
TEST(BitcastOpTest, TestShapeInference_LargerShape) {
const OpRegistrationData* reg;
TF_CHECK_OK(OpRegistry::Global()->LookUp("Bitcast", &reg));
OpDef op_def = reg->op_def;
NodeDef def;
TF_CHECK_OK(NodeDefBuilder("dummy", &op_def)
.Attr("type", DT_INT8)
.Attr("T", DT_INT64)
.Input(FakeInput(DT_INT64))
.Finalize(&def));
shape_inference::InferenceContext c(0, def, op_def, {S({3, 4})}, {}, {}, {});
std::vector<shape_inference::ShapeHandle> input_shapes;
TF_CHECK_OK(c.input("input", &input_shapes));
ASSERT_EQ("[3,4]", c.DebugString(input_shapes[0]));
TF_CHECK_OK(reg->shape_inference_fn(&c));
ASSERT_EQ("[3,4,8]", c.DebugString(c.output(0)));
}
TEST(BitcastOpTest, TestShapeInference_SmallerShape) {
const OpRegistrationData* reg;
TF_CHECK_OK(OpRegistry::Global()->LookUp("Bitcast", &reg));
OpDef op_def = reg->op_def;
NodeDef def;
TF_CHECK_OK(NodeDefBuilder("dummy", &op_def)
.Attr("type", DT_INT64)
.Attr("T", DT_INT8)
.Input(FakeInput(DT_INT8))
.Finalize(&def));
shape_inference::InferenceContext c(0, def, op_def, {S({3, 4, 8})}, {}, {},
{});
std::vector<shape_inference::ShapeHandle> input_shapes;
TF_CHECK_OK(c.input("input", &input_shapes));
ASSERT_EQ("[3,4,8]", c.DebugString(input_shapes[0]));
TF_CHECK_OK(reg->shape_inference_fn(&c));
ASSERT_EQ("[3,4]", c.DebugString(c.output(0)));
}
TEST(BitcastOpTest, TestShapeInference_SameShape) {
const OpRegistrationData* reg;
TF_CHECK_OK(OpRegistry::Global()->LookUp("Bitcast", &reg));
OpDef op_def = reg->op_def;
NodeDef def;
TF_CHECK_OK(NodeDefBuilder("dummy", &op_def)
.Attr("type", DT_INT32)
.Attr("T", DT_FLOAT)
.Input(FakeInput(DT_FLOAT))
.Finalize(&def));
shape_inference::InferenceContext c(0, def, op_def, {S({3, 4})}, {}, {}, {});
std::vector<shape_inference::ShapeHandle> input_shapes;
TF_CHECK_OK(c.input("input", &input_shapes));
ASSERT_EQ("[3,4]", c.DebugString(input_shapes[0]));
TF_CHECK_OK(reg->shape_inference_fn(&c));
ASSERT_EQ("[3,4]", c.DebugString(c.output(0)));
}
} // namespace
} // namespace tensorflow