TF_TensorDefaultAlignment(), num_bytes));
  int64_t dims[] = {2, 3};
  bool deallocator_called = false;
  TF_Tensor* t = TF_NewTensor(TF_FLOAT, dims, 2, values, num_bytes,
                              &Deallocator, &deallocator_called);
  EXPECT_FALSE(deallocator_called);
  EXPECT_EQ(TF_FLOAT, TF_TensorType(t));
  EXPECT_EQ(2, TF_NumDims(t));
  EXPECT_EQ(dims[0], TF_Dim(t, 0));

// A create function. This will never actually get called in this test, it's
// just nice to know that it compiles.
void* create(TF_OpKernelConstruction* ctx) {
  TF_DataType type;
  TF_Status* s = TF_NewStatus();
  TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s);
  TF_DeleteStatus(s);
  return NULL;
}

// A compute function. This will never actually get called in this test, it's
// just nice to know that it compiles.

  for (int i = 0; i < noutputs; ++i) {
    output_names[i] = c_output_names[i];
  }
  std::vector<string> target_oper_names(ntargets);
  for (int i = 0; i < ntargets; ++i) {
    target_oper_names[i] = c_target_oper_names[i];
  }
  TF_Run_Helper(s->session, nullptr, run_options, input_pairs, output_names,
                c_outputs, target_oper_names, run_metadata, status);
}

void TF_PRunSetup(TF_DeprecatedSession* s,

*   <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

*   Add `is_cpu_target_available`, which indicates whether or not TensorFlow was
    built with support for a given CPU target. This can be useful for skipping
    target-specific tests if a target is not supported.

*   `tf.data`
    * Support `data.experimental.distribued_save`. `distribued_save` uses
      tf.data service

  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a
  // CPU tensor to GPU).
  // Setting a larger thread pool does not help with the Swift caller, as we use
  // a different TFE context for each thread of execution (for running graph

certifi==2024.2.2 \
    --hash=sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f \
    --hash=sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1
    # via requests
charset-normalizer==3.3.2 \
    --hash=sha256:06435b539f889b1f6f4ac1758871aae42dc3a8c0e24ac9e60c2384973ad73027 \
    --hash=sha256:06a81e93cd441c56a9b65d8e1d043daeb97a3d0856d177d5c90ba85acb3db087 \

certifi==2024.2.2 \
    --hash=sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f \
    --hash=sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1
    # via requests
charset-normalizer==3.3.2 \
    --hash=sha256:06435b539f889b1f6f4ac1758871aae42dc3a8c0e24ac9e60c2384973ad73027 \
    --hash=sha256:06a81e93cd441c56a9b65d8e1d043daeb97a3d0856d177d5c90ba85acb3db087 \