took out test-only functions from test_util and put them in gradients_util
This commit is contained in:
amturati
parent
0fdb700766
commit
a17c8e3f99
@ -249,13 +249,12 @@ tf_cuda_cc_test(
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)
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cc_library(
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name = "gradients_testutil",
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testonly = True,
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name = "gradients_util",
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srcs = [
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"gradients_testutil.cc",
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"gradients_util.cc",
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],
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hdrs = [
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"gradients_testutil.h",
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"gradients_util.h",
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],
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visibility = [
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"//tensorflow:internal",
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@ -266,22 +265,20 @@ cc_library(
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":tape",
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":abstract_tensor_handle",
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":gradients",
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":c_api",
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":c_api_experimental",
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":c_api_test_util",
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":c_api_unified_internal",
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":gradients_internal",
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"//tensorflow/c/experimental/ops:array_ops",
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"//tensorflow/c/experimental/ops:math_ops",
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"//tensorflow/c/experimental/ops:nn_ops",
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"//tensorflow/c:c_api",
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"//tensorflow/c:c_test_util",
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"//tensorflow/c:tf_status_helper",
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"//tensorflow/cc/profiler",
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"//tensorflow/compiler/mlir/tensorflow/c:mlir_c_api_registration",
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"//tensorflow/core:framework",
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"//tensorflow/core:lib",
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"//tensorflow/core:protos_all_cc",
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"//tensorflow/core:test",
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"//tensorflow/core:test_main",
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"//tensorflow/core/lib/llvm_rtti",
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"@com_google_absl//absl/strings",
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"@com_google_absl//absl/types:span",
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@ -319,7 +316,6 @@ cc_library(
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cc_library(
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name = "gradient_checker",
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testonly = True,
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srcs = [
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"gradient_checker.cc",
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],
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@ -332,13 +328,10 @@ cc_library(
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deps = [
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":abstract_tensor_handle",
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":c_api_experimental",
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":c_api_test_util",
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":c_api_unified_internal",
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":gradients_internal",
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":mnist_gradients_testutil",
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":gradients_testutil",
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":gradients_util",
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"//tensorflow/c:c_api",
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"//tensorflow/c:c_test_util",
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"//tensorflow/c:tf_status_helper",
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"//tensorflow/c/experimental/gradients:math_grad",
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"//tensorflow/c/experimental/gradients:nn_grad",
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@ -349,8 +342,6 @@ cc_library(
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"//tensorflow/compiler/mlir/tensorflow/c:mlir_c_api_registration",
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"//tensorflow/core:lib",
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"//tensorflow/core:protos_all_cc",
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"//tensorflow/core:test",
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"//tensorflow/core:test_main",
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"//tensorflow/core/lib/llvm_rtti",
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"@com_google_absl//absl/strings",
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"@com_google_absl//absl/types:span",
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@ -19,12 +19,10 @@ limitations under the License.
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#include "absl/types/span.h"
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#include "tensorflow/c/eager/abstract_tensor_handle.h"
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#include "tensorflow/c/eager/c_api_experimental.h"
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#include "tensorflow/c/eager/c_api_test_util.h"
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#include "tensorflow/c/eager/c_api_unified_experimental.h"
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#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
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#include "tensorflow/c/eager/gradients.h"
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#include "tensorflow/c/eager/gradients_internal.h"
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#include "tensorflow/c/eager/mnist_gradients_testutil.h"
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#include "tensorflow/c/experimental/gradients/math_grad.h"
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#include "tensorflow/c/experimental/gradients/nn_grad.h"
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#include "tensorflow/c/experimental/ops/array_ops.h"
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@ -32,7 +30,9 @@ limitations under the License.
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#include "tensorflow/c/tf_tensor.h"
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#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
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#include "tensorflow/core/platform/errors.h"
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#include "tensorflow/core/platform/test.h"
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namespace tensorflow {
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namespace gradients {
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using namespace std;
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@ -197,4 +197,7 @@ Status CalcNumericalGrad(AbstractContext* ctx, Model forward,
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}
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return Status::OK();
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}
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}
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} // namespace gradients
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} // namespace tensorflow
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@ -17,13 +17,11 @@ limitations under the License.
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#include "absl/types/span.h"
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#include "tensorflow/c/eager/abstract_tensor_handle.h"
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#include "tensorflow/c/eager/c_api_experimental.h"
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#include "tensorflow/c/eager/c_api_test_util.h"
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#include "tensorflow/c/eager/c_api_unified_experimental.h"
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#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
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#include "tensorflow/c/eager/gradients.h"
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#include "tensorflow/c/eager/gradients_internal.h"
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#include "tensorflow/c/eager/gradients_testutil.h"
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#include "tensorflow/c/eager/mnist_gradients_testutil.h"
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#include "tensorflow/c/eager/gradients_util.h"
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#include "tensorflow/c/experimental/gradients/math_grad.h"
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#include "tensorflow/c/experimental/gradients/nn_grad.h"
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#include "tensorflow/c/experimental/ops/array_ops.h"
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@ -31,7 +29,9 @@ limitations under the License.
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#include "tensorflow/c/tf_tensor.h"
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#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
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#include "tensorflow/core/platform/errors.h"
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#include "tensorflow/core/platform/test.h"
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namespace tensorflow {
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namespace gradients {
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using Model = std::function<Status(
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AbstractContext*, absl::Span<AbstractTensorHandle* const>,
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@ -53,3 +53,6 @@ Status CalcNumericalGrad(AbstractContext* ctx, Model forward,
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std::vector<AbstractTensorHandle*> inputs,
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float* dtheta_approx, int input_index,
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bool use_function, bool is_scalar_out = false);
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} // namespace gradients
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} // namespace tensorflow
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@ -10,14 +10,13 @@ See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/c/eager/gradient_checker.h"
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// #include "tensorflow/c/eager/gradients_testutil.h"
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#include "tensorflow/c/eager/gradients_util.h"
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#include <memory>
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#include "absl/types/span.h"
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#include "tensorflow/c/eager/abstract_tensor_handle.h"
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#include "tensorflow/c/eager/c_api_experimental.h"
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#include "tensorflow/c/eager/c_api_test_util.h"
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#include "tensorflow/c/eager/c_api_unified_experimental.h"
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#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
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#include "tensorflow/c/eager/gradients.h"
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@ -109,7 +108,7 @@ TEST_P(GradientCheckerTest, TestGradCheckMul) {
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AbstractTensorHandlePtr x;
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{
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AbstractTensorHandle* x_raw = nullptr;
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Status s = TestScalarTensorHandle(ctx.get(), 2.0f, &x_raw);
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Status s = ScalarTensorHandle(ctx.get(), 2.0f, &x_raw);
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ASSERT_EQ(errors::OK, s.code()) << s.error_message();
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x.reset(x_raw);
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}
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@ -117,7 +116,7 @@ TEST_P(GradientCheckerTest, TestGradCheckMul) {
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AbstractTensorHandlePtr y;
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{
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AbstractTensorHandle* y_raw = nullptr;
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Status s = TestScalarTensorHandle(ctx.get(), 7.0f, &y_raw);
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Status s = ScalarTensorHandle(ctx.get(), 7.0f, &y_raw);
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ASSERT_EQ(errors::OK, s.code()) << s.error_message();
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y.reset(y_raw);
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}
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@ -12,14 +12,13 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/c/eager/gradients_testutil.h"
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#include "tensorflow/c/eager/gradients_util.h"
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#include <memory>
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#include "absl/types/span.h"
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#include "tensorflow/c/eager/abstract_tensor_handle.h"
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#include "tensorflow/c/eager/c_api_experimental.h"
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#include "tensorflow/c/eager/c_api_test_util.h"
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#include "tensorflow/c/eager/c_api_unified_experimental.h"
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#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
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#include "tensorflow/c/eager/gradients.h"
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@ -31,28 +30,66 @@ limitations under the License.
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#include "tensorflow/c/tf_tensor.h"
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#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
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#include "tensorflow/core/platform/errors.h"
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#include "tensorflow/core/platform/test.h"
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namespace tensorflow {
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namespace gradients {
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using namespace std;
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// ================== TensorHandle generating functions =================
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TFE_TensorHandle* ScalarTensorHandleHelper(TFE_Context* ctx, float value) {
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float data[] = {value};
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TF_Status* status = TF_NewStatus();
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TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_FLOAT, nullptr, 0, status);
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memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));
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TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);
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CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
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TF_DeleteTensor(t);
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TF_DeleteStatus(status);
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return th;
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}
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TFE_TensorHandle* TensorHandleWithDimsFloatHelper(TFE_Context* ctx, float data[],
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int64_t dims[], int num_dims) {
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TF_Status* status = TF_NewStatus();
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TF_Tensor* t =
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TFE_AllocateHostTensor(ctx, TF_FLOAT, &dims[0], num_dims, status);
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memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));
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TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);
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CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
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TF_DeleteTensor(t);
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TF_DeleteStatus(status);
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return th;
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}
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TFE_TensorHandle* TensorHandleWithDimsIntHelper(TFE_Context* ctx, int data[],
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int64_t dims[], int num_dims) {
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TF_Status* status = TF_NewStatus();
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TF_Tensor* t =
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TFE_AllocateHostTensor(ctx, TF_INT32, &dims[0], num_dims, status);
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memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));
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TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);
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CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
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TF_DeleteTensor(t);
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TF_DeleteStatus(status);
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return th;
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}
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// Get a scalar TensorHandle with given value
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Status TestScalarTensorHandle(AbstractContext* ctx, float value,
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Status ScalarTensorHandle(AbstractContext* ctx, float value,
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AbstractTensorHandle** tensor) {
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std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
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TF_NewStatus(), TF_DeleteStatus);
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TFE_Context* eager_ctx =
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TF_ExecutionContextGetTFEContext(wrap(ctx), status.get());
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TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
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TFE_TensorHandle* input_eager = TestScalarTensorHandle(eager_ctx, value);
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TFE_TensorHandle* input_eager = ScalarTensorHandleHelper(eager_ctx, value);
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*tensor =
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unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get()));
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return StatusFromTF_Status(status.get());
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}
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// Get a TensorHandle with given float values and dimensions
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Status TestTensorHandleWithDimsFloat(AbstractContext* ctx, float data[],
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Status TensorHandleWithDimsFloat(AbstractContext* ctx, float data[],
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int64_t dims[], int num_dims,
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AbstractTensorHandle** tensor) {
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std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
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@ -61,14 +98,14 @@ Status TestTensorHandleWithDimsFloat(AbstractContext* ctx, float data[],
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TF_ExecutionContextGetTFEContext(wrap(ctx), status.get());
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TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
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TFE_TensorHandle* input_eager =
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TestTensorHandleWithDimsFloat(eager_ctx, data, dims, num_dims);
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TensorHandleWithDimsFloatHelper(eager_ctx, data, dims, num_dims);
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*tensor =
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unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get()));
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return StatusFromTF_Status(status.get());
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}
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// Get a TensorHandle with given int values and dimensions
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Status TestTensorHandleWithDimsInt(AbstractContext* ctx, int data[],
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Status TensorHandleWithDimsInt(AbstractContext* ctx, int data[],
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int64_t dims[], int num_dims,
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AbstractTensorHandle** tensor) {
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std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
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@ -77,7 +114,7 @@ Status TestTensorHandleWithDimsInt(AbstractContext* ctx, int data[],
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TF_ExecutionContextGetTFEContext(wrap(ctx), status.get());
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TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
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TFE_TensorHandle* input_eager =
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TestTensorHandleWithDimsInt(eager_ctx, data, dims, num_dims);
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TensorHandleWithDimsIntHelper(eager_ctx, data, dims, num_dims);
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*tensor =
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unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get()));
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return StatusFromTF_Status(status.get());
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@ -98,7 +135,7 @@ AbstractTensorHandlePtr GetTensorHandleUtilFloat(AbstractContext* ctx,
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int num_dims) {
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AbstractTensorHandlePtr A;
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AbstractTensorHandle* a_raw = nullptr;
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Status s = TestTensorHandleWithDimsFloat(ctx, vals, dims, num_dims, &a_raw);
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Status s = TensorHandleWithDimsFloat(ctx, vals, dims, num_dims, &a_raw);
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if (s.ok()) {
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A.reset(a_raw);
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}
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@ -109,7 +146,7 @@ AbstractTensorHandlePtr GetTensorHandleUtilInt(AbstractContext* ctx, int vals[],
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int64_t dims[], int num_dims) {
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AbstractTensorHandlePtr A;
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AbstractTensorHandle* a_raw = nullptr;
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Status s = TestTensorHandleWithDimsInt(ctx, vals, dims, num_dims, &a_raw);
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Status s = TensorHandleWithDimsInt(ctx, vals, dims, num_dims, &a_raw);
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if (s.ok()) {
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A.reset(a_raw);
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}
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@ -120,7 +157,7 @@ AbstractTensorHandlePtr GetScalarTensorHandleUtil(AbstractContext* ctx,
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float val) {
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AbstractTensorHandlePtr y;
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AbstractTensorHandle* y_raw = nullptr;
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Status s = TestScalarTensorHandle(ctx, val, &y_raw);
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Status s = ScalarTensorHandle(ctx, val, &y_raw);
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if (s.ok()) {
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y.reset(y_raw);
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}
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@ -268,4 +305,7 @@ Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx) {
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TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
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TFE_DeleteContextOptions(opts);
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return Status::OK();
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}
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}
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} // namespace gradients
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} // namespace tensorflow
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@ -18,7 +18,6 @@ limitations under the License.
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#include "absl/types/span.h"
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#include "tensorflow/c/eager/abstract_tensor_handle.h"
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#include "tensorflow/c/eager/c_api_experimental.h"
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#include "tensorflow/c/eager/c_api_test_util.h"
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#include "tensorflow/c/eager/c_api_unified_experimental.h"
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#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
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#include "tensorflow/c/eager/gradients.h"
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@ -30,24 +29,37 @@ limitations under the License.
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#include "tensorflow/c/tf_tensor.h"
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#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
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#include "tensorflow/core/platform/errors.h"
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#include "tensorflow/core/platform/test.h"
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#include "tensorflow/c/eager/c_api.h"
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#include "tensorflow/core/platform/types.h"
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using namespace std;
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using namespace tensorflow;
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using namespace tensorflow::gradients;
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using namespace tensorflow::gradients::internal;
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// Get a scalar TensorHandle with given value.
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Status TestScalarTensorHandle(AbstractContext* ctx, float value,
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// using namespace std;
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// using namespace tensorflow;
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// using namespace tensorflow::gradients;
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// using namespace tensorflow::gradients::internal;
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namespace tensorflow {
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namespace gradients {
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TFE_TensorHandle* ScalarTensorHandleHelper(TFE_Context* ctx, float value);
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TFE_TensorHandle* TensorHandleWithDimsFloatHelper(TFE_Context* ctx, float data[],
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int64_t dims[], int num_dims);
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TFE_TensorHandle* TensorHandleWithDimsIntHelper(TFE_Context* ctx, int data[],
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int64_t dims[], int num_dims);
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// Get a scalar TensorHandle with given value
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Status ScalarTensorHandle(AbstractContext* ctx, float value,
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AbstractTensorHandle** tensor);
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// Get a TensorHandle with given float values and dimensions.
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Status TestTensorHandleWithDimsFloat(AbstractContext* ctx, float data[],
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// Get a TensorHandle with given float values and dimensions
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Status TensorHandleWithDimsFloat(AbstractContext* ctx, float data[],
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int64_t dims[], int num_dims,
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AbstractTensorHandle** tensor);
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// Get a TensorHandle with given int values and dimensions.
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Status TestTensorHandleWithDimsInt(AbstractContext* ctx, int data[],
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// Get a TensorHandle with given int values and dimensions
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Status TensorHandleWithDimsInt(AbstractContext* ctx, int data[],
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int64_t dims[], int num_dims,
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AbstractTensorHandle** tensor);
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@ -68,8 +80,8 @@ AbstractTensorHandlePtr GetScalarTensorHandleUtil(AbstractContext* ctx,
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float val);
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// Performs gradient update for each weight using given learning rate.
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Status UpdateWeights(AbstractContext* ctx, vector<AbstractTensorHandle*>& grads,
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vector<AbstractTensorHandle*>& weights,
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Status UpdateWeights(AbstractContext* ctx, std::vector<AbstractTensorHandle*>& grads,
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std::vector<AbstractTensorHandle*>& weights,
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AbstractTensorHandle* learning_rate);
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// Helper function for RunModel to build the function for graph mode.
|
||||
@ -78,7 +90,7 @@ AbstractContext* BuildFunction(const char* fn_name);
|
||||
// Helper function for RunModel to add params for graph mode.
|
||||
Status CreateParamsForInputs(AbstractContext* ctx,
|
||||
absl::Span<AbstractTensorHandle* const> inputs,
|
||||
vector<AbstractTensorHandle*>* params);
|
||||
std::vector<AbstractTensorHandle*>* params);
|
||||
|
||||
using Model = std::function<Status(
|
||||
AbstractContext*, absl::Span<AbstractTensorHandle* const>,
|
||||
@ -91,4 +103,7 @@ Status RunModel(Model model, AbstractContext* ctx,
|
||||
absl::Span<AbstractTensorHandle*> outputs, bool use_function,
|
||||
const GradientRegistry& registry);
|
||||
|
||||
Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx);
|
||||
Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx);
|
||||
|
||||
} // namespace gradients
|
||||
} // namespace tensorflow
|
||||
Loading…
Reference in New Issue
Block a user