def llama()

in dags/pytorch_xla/nightly.py [0:0]

• 40 lines of code
• 1 McCabe index (conditional complexity)

def llama():
  llama_inference_v4_8 = task.run_queued_resource_test(
      test_config.JSonnetTpuVmTest.from_pytorch(
          "pt-nightly-llama2-infer-func-v4-8-1vm"
      ),
      US_CENTRAL2_B,
  )
  llama_train_v4_8 = task.run_queued_resource_test(
      test_config.JSonnetTpuVmTest.from_pytorch(
          "pt-nightly-llama2-train-spmd-func-v4-8-1vm"
      ),
      US_CENTRAL2_B,
  )
  llama_3_train_trillium = task.run_queued_resource_test(
      test_config.JSonnetTpuVmTest.from_pytorch(
          "pt-nightly-llama3-train-func-v6e-4-1vm",
          network=V5_NETWORKS,
          subnetwork=V6E_SUBNETWORKS,
      ),
      US_CENTRAL2_B_TPU_PROD_ENV,
  )
  llama_3_train_v5p_2_slices = task.run_queued_resource_test(
      test_config.JSonnetTpuVmTest.from_pytorch(
          "pt-nightly-llama3-train-2-slice-func-v5p-8-1vm",
          reserved=True,
          network=V5_NETWORKS,
          subnetwork=V5P_SUBNETWORKS,
          num_slices=2,
      ),
      US_EAST5_A_TPU_PROD_ENV_AUTOMATED,
  )
  llama_3_train_v5p_8 = task.run_queued_resource_test(
      test_config.JSonnetTpuVmTest.from_pytorch(
          "pt-nightly-llama3-train-func-v5p-8-1vm",
          reserved=True,
          network=V5_NETWORKS,
          subnetwork=V5P_SUBNETWORKS,
      ),
      US_EAST5_A_TPU_PROD_ENV_AUTOMATED,
  )