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:

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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

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github.com/tensorflow/tensorflow

RELEASE.md

    *   Added support for `tflite_convert` command line tool in 2.0.
    *   Post-training quantization tool supports quantizing weights shared by
        multiple operations. The models made with versions of this tool will use
        INT8 types for weights and will only be executable interpreters from
        this version onwards.
    *   Post-training quantization tool supports fp16 weights and GPU delegate

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github.com/tensorflow/tensorflow

tensorflow/c/c_test_util.cc

}

static void FloatDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<float*>(data);
}

TF_Tensor* BoolTensor(bool v) {
  const int num_bytes = sizeof(bool);
  bool* values = new bool[1];
  values[0] = v;
  return TF_NewTensor(TF_BOOL, nullptr, 0, values, num_bytes, &BoolDeallocator,
                      nullptr);
}

TF_Tensor* Int8Tensor(const int64_t* dims, int num_dims, const char* values) {

C++

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github.com/tensorflow/tensorflow

tensorflow/c/eager/c_api_remote_function_test.cc

#include "tensorflow/core/platform/test.h"

namespace {

void TestRemoteExecuteSilentCopiesFunc(bool async, bool remote,
                                       bool heavy_load_on_streaming_rpc,
                                       bool remote_func_outputs = false,
                                       bool has_packed_input = false) {
  return TestRemoteExecuteSilentCopies(async, remote, /*func=*/true,

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github.com/tensorflow/tensorflow

tensorflow/c/eager/custom_device_test.cc

  TFE_Context* context = TFE_NewContext(opts, status.get());
  TFE_DeleteContextOptions(opts);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  bool arrived = false;
  bool executed = false;
  const char* name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  RegisterLoggingDevice(context, name, /*strict_scope_placement=*/true,

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github.com/tensorflow/tensorflow

tensorflow/c/experimental/gradients/array_grad_test.cc

  outputs[0] = temp_outputs[1];
  temp_outputs[0]->Unref();
  return absl::OkStatus();
}

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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github.com/tensorflow/tensorflow

tensorflow/c/eager/c_api_experimental.h

typedef struct TFE_MonitoringBoolGaugeCell TFE_MonitoringBoolGaugeCell;
TF_CAPI_EXPORT extern void TFE_MonitoringBoolGaugeCellSet(
    TFE_MonitoringBoolGaugeCell* cell, bool value);
TF_CAPI_EXPORT extern bool TFE_MonitoringBoolGaugeCellValue(
    TFE_MonitoringBoolGaugeCell* cell);

// APIs for Bool Gauge without label.
typedef struct TFE_MonitoringBoolGauge0 TFE_MonitoringBoolGauge0;
TF_CAPI_EXPORT extern TFE_MonitoringBoolGauge0* TFE_MonitoringNewBoolGauge0(

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