};
  const uint32 block_count = 256;
  tf_gcs_filesystem::RamFileBlockCache cache(
      block_size, block_count * block_size, 0, fetcher);
  std::vector<char> out;
  out.resize(block_count, 0);
  // The cache has space for `block_count` blocks. The loop with i = 0 should
  // fill the cache, and the loop with i = 1 should be all cache hits. The
  // fetcher checks that it is called once and only once for each offset (to

TensorFlow’s GitHub organization, or any other official TensorFlow web presence allowing for community interactions, as well as at all official TensorFlow events, whether offline or online.

The Code of Conduct also applies within project spaces and in public spaces whenever an individual is representing TensorFlow or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed...

/usr/bin/$VERSION get-pip.py
/usr/bin/$VERSION -m pip install --no-cache-dir --upgrade pip

# Disable the cache dir to save image space, and install packages

//
// Like a TF_Tensor, a TFE_TensorHandle refers to a tensor with a value, shape,
// type etc. Unlike a TF_Tensor, a TFE_TensorHandle may refer to such tensors
// placed in the memory of different devices or remote address spaces.
typedef struct TFE_TensorHandle TFE_TensorHandle;

TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandle(const TF_Tensor* t,
                                                            TF_Status* status);

    int num_dims, void* data, size_t len,
    void (*deallocator)(void* data, size_t len, void* arg),
    void* deallocator_arg, TF_Status* status);

// Retrieves the address space (i.e. job, replia, task) of the local host and
// saves it in the buffer.
TF_CAPI_EXPORT extern void TFE_HostAddressSpace(TFE_Context* ctx,
                                                TF_Buffer* buf);

        "//tensorflow/compiler/mlir/tensorflow:mlir_roundtrip_flags",
        "//tensorflow/compiler/mlir/tensorflow:translate_lib",
        "@local_xla//xla/service:computation_placer",
        "//tensorflow/core",
        "//tensorflow/core/common_runtime/eager:context",
        "//tensorflow/core/common_runtime/eager:tensor_handle",
        "//tensorflow/core/config:flag_defs",

    *   Added int16x8 support for the built-in op `exp`
    *   Added int16x8 support for the built-in op `mirror_pad`
    *   Added int16x8 support for the built-in ops `space_to_batch_nd` and `batch_to_space_nd`
    *   Added 16-bit int type support for built-in op `less`, `greater_than`, `equal`
    *   Added 8-bit and 16-bit support for `floor_div` and `floor_mod`.

authors:
  - family-names: Abadi
    given-names: Martín
  - family-names: Agarwal

  // Update the vector with information from `input_tensors` if provided.
  if (input_tensors != nullptr) {
    // Note that we take the address of the elements in `all_input_tensors`
    // below. Allocate enough space so that no reallocation happens, which will
    // make the pointers invalid.
    all_input_tensors.reserve(num_inputs);
    for (int i = 0; i < num_inputs; ++i) {
      if (input_tensors[i] == nullptr) continue;

using OpTape =
    std::unordered_map<int64_t, OpTapeEntry<BackwardFunction, TapeTensor>>;

// Operations the tape needs to perform on tensors to do backpropagation. Named
// "vspace" because a subset of these are related to a vector space, such as
// adding gradients, getting zeroes, etc. Currently cannot be implemented
// without using tensorflow python code, hence left unspecified here.
//