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tensorflow/c/experimental/gradients/nn_grad_test.cc

  return ops::BiasAdd(ctx, inputs[0], inputs[1], &outputs[0], "NHWC",
                      "BiasAdd");
}

class CppGradients
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    status_ = StatusFromTF_Status(status.get());

C++

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github.com/tensorflow/tensorflow

ci/official/utilities/generate_index_html.sh

cat > "$1" <<EOF
<html>
<head>
<title>$(basename "$KOKORO_JOB_NAME")</title>
</head>
<body>
<h1>TensorFlow Job Logs and Links</h1>
<h2>Job Details</h2>
<ul>
<li>Job name: $KOKORO_JOB_NAME</li>
<li>Job pool: $KOKORO_JOB_POOL</li>
<li>Job ID: $KOKORO_BUILD_ID</li>
<li>Current HEAD Piper Changelist, if any: cl/${KOKORO_PIPER_CHANGELIST:-not available}</li>
<li>Pull Request Number, if any: ${KOKORO_GITHUB_PULL_REQUEST_NUMBER_tensorflow:- none}</li>

Shell Script

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github.com/tensorflow/tensorflow

tensorflow/c/eager/unified_api_testutil.h

//   outputs = model(inputs)
Status RunModel(Model model, AbstractContext* ctx,
                absl::Span<AbstractTensorHandle* const> inputs,
                absl::Span<AbstractTensorHandle*> outputs, bool use_function);

Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx);

// Return a tensor handle with given type, values and dimensions.
template <class T, TF_DataType datatype>

C

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github.com/tensorflow/tensorflow

tensorflow/c/c_api_test.cc

  // Serialize to GraphDef.
  GraphDef graph_def;
  ASSERT_TRUE(GetGraphDef(graph, &graph_def));

  // Validate GraphDef is what we expect.
  bool found_placeholder = false;
  bool found_scalar_const = false;
  bool found_add = false;
  for (const auto& n : graph_def.node()) {
    if (IsPlaceholder(n)) {
      EXPECT_FALSE(found_placeholder);
      found_placeholder = true;

C++

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github.com/tensorflow/tensorflow

tensorflow/c/eager/c_api_test.cc

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TFE_DeleteExecutor(executor);
  TFE_DeleteContext(ctx);
}

void ExecuteAdd(bool async, bool forward_input, bool tfrt) {
#ifdef PLATFORM_WINDOWS
  // On windows, we flakily get a failure due to pointer instability.
  // Disable the 4 tests using this helper until we fix the issue.
  return;
#else

C++

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github.com/tensorflow/tensorflow

tensorflow/c/eager/c_api_experimental_test.cc

#include "tensorflow/core/protobuf/cluster.pb.h"
#include "tensorflow/core/protobuf/config.pb.h"

using tensorflow::string;

namespace tensorflow {
namespace {

static bool HasSubstr(absl::string_view base, absl::string_view substr) {
  bool ok = absl::StrContains(base, substr);
  EXPECT_TRUE(ok) << base << ", expected substring " << substr;
  return ok;
}

TEST(CAPI, MonitoringCounter0) {

C++

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github.com/tensorflow/tensorflow

tensorflow/c/checkpoint_reader.h

// other languages.
//
// The class currently only interacts with single-slice (i.e., non-partitioned)
// variables.
class CheckpointReader {
 public:
  CheckpointReader(const string& filename, TF_Status* status);

  bool HasTensor(const string& name) const;
  const string DebugString() const;

  // Returns a map from variable names to their shapes.  Slices of a partitioned
  // tensor are combined into a single entry.

C

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github.com/tensorflow/tensorflow

ci/official/wheel_test/README.md

and a requirements_lock file. The requirements_lock file is generated by the
[requirements_updater](https://github.com/tensorflow/tensorflow/tree/master/ci/official/requirements_updater)
tool using the path to this wheel file.

### Hermetic Python

For details about hermetic Python and setting its toolchain version, see

Plain Text

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github.com/tensorflow/tensorflow

tensorflow/c/checkpoint_reader.cc

        new TensorSliceReader::VarToShapeMap(reader_->GetVariableToShapeMap()));
    var_to_data_type_map_.reset(new TensorSliceReader::VarToDataTypeMap(
        reader_->GetVariableToDataTypeMap()));
  }
}

bool CheckpointReader::HasTensor(const string& name) const {
  if (reader_ != nullptr) {
    return reader_->HasTensor(name, nullptr, nullptr);
  }
  return v2_reader_->Contains(name);
}

C++

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github.com/tensorflow/tensorflow

tensorflow/c/experimental/filesystem/modular_filesystem.cc

  ops_->path_exists(filesystem_.get(), translated_name.c_str(),
                    plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

bool ModularFileSystem::FilesExist(const std::vector<std::string>& files,
                                   TransactionToken* token,
                                   std::vector<Status>* status) {
  if (ops_->paths_exist == nullptr)

C++

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