pool - Code Search

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>

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github.com/tensorflow/tensorflow

ci/official/README.md

    -   Uses `pycpp.sh`, `code_check_changed_files.sh`

These "env" files match up with an environment matrix that roughly covers:

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs

## How to Test Your Changes to TensorFlow

You may check how your changes will affect TensorFlow by:

Plain Text

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github.com/tensorflow/tensorflow

ci/official/containers/linux_arm64/builder.devtoolset/build_devtoolset.sh

# the `VERSION` parameter
  # Download binary libstdc++ 4.8 shared library release
wget --retry-connrefused --waitretry=1 --read-timeout=20 --timeout=15 --tries=5 "http://old-releases.ubuntu.com/ubuntu/pool/main/g/gcc-4.8/libstdc++6_4.8.1-10ubuntu8_arm64.deb" && \
    unar "libstdc++6_4.8.1-10ubuntu8_arm64.deb" && \

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github.com/tensorflow/tensorflow

tensorflow/c/eager/parallel_device/parallel_device_lib.h

  // A sequence of thread wrappers, one per device, for executing operations in
  // parallel.
  //
  // Conceptually this is a thread pool with one thread per device. It requires
  // less synchronization than a thread pool would for this task, since Execute
  // acquires each thread in order (and so only one Execute will schedule
  // blocking collective operations at a time), and avoids some dynamic

C

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github.com/tensorflow/tensorflow

tensorflow/c/eager/c_api_remote_test_util.h

// is not ready when we start running an op or a function.
void TestRemoteExecuteSilentCopies(bool async, bool remote, bool func,
                                   bool heavy_load_on_streaming_rpc,
                                   bool remote_func_outputs = false,
                                   bool has_packed_input = false);

C

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github.com/tensorflow/tensorflow

tensorflow/c/eager/custom_device_testutil.h

#include "tensorflow/c/tf_status.h"

void RegisterLoggingDevice(TFE_Context* context, const char* name,
                           bool strict_scope_placement, bool* arrived_flag,
                           bool* executed_flag, TF_Status* status);
void AllocateLoggingDevice(const char* name, bool* arrived_flag,
                           bool* executed_flag, TFE_CustomDevice** device,
                           void** device_info);

C

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github.com/tensorflow/tensorflow

tensorflow/c/eager/abstract_op_attrs.h

  virtual void GetNameAttrList(
      tensorflow::NameAttrList* name_and_attrs) const = 0;

  virtual bool GetInt(absl::string_view, int64_t* result) const = 0;
  virtual bool GetFloat(absl::string_view attr_name, float* result) const = 0;
  virtual bool GetBool(absl::string_view attr_name, bool* result) const = 0;
  virtual bool GetType(absl::string_view attr_name, DataType* result) const = 0;
  virtual Status GetTypeList(

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github.com/tensorflow/tensorflow

tensorflow/c/c_api_macros.h

#else
#define TF_CAPI_EXPORT __attribute__((visibility("default")))
#endif  // TF_CAPI_WEAK
#endif  // _WIN32
#endif  // SWIG

// TF_Bool is the C API typedef for unsigned char, while TF_BOOL is
// the datatype for boolean tensors.
#ifndef TF_Bool
#define TF_Bool unsigned char
#endif  // TF_Bool

// Macro used to calculate struct size for maintaining ABI stability across
// different struct implementations.
#ifndef TF_OFFSET_OF_END

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github.com/tensorflow/tensorflow

tensorflow/c/experimental/gradients/tape/tape_operation.cc

                                      int num_values) {
  std::unique_ptr<bool[]> b(new bool[num_values]);
  for (int i = 0; i < num_values; ++i) {
    b[i] = values[i];
  }
  forward_op_.attrs.Set(attr_name,
                        gtl::ArraySlice<const bool>(b.get(), num_values));
  return parent_op_->SetAttrBoolList(attr_name, values, num_values);
}

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github.com/tensorflow/tensorflow

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());

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