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DAGContexta Global settings for Ray DAG.
You can configure parameters in the DAGContext by setting the environment
variables, `RAY_CGRAPH_` (e.g., `RAY_CGRAPH_buffer_size_bytes`) or Python.
Examples:
>>> from ray.dag import DAGContext
>>> DAGContext.get_current().buffer_size_bytes
1000000
>>> DAGContext.get_current().buffer_size_bytes = 500
>>> DAGContext.get_current().buffer_size_bytes
500
Args:
submit_timeout: The maximum time in seconds to wait for execute()
calls.
get_timeout: The maximum time in seconds to wait when retrieving
a result from the DAG during `ray.get`. This should be set to a
value higher than the expected time to execute the entire DAG.
teardown_timeout: The maximum time in seconds to wait for the DAG to
cleanly shut down.
read_iteration_timeout: The timeout in seconds for each read iteration
that reads one of the input channels. If the timeout is reached, the
read operation will be interrupted and will try to read the next
input channel. It must be less than or equal to `get_timeout`.
buffer_size_bytes: The initial buffer size in bytes for messages
that can be passed between tasks in the DAG. The buffers will
be automatically resized if larger messages are written to the
channel.
max_inflight_executions: The maximum number of in-flight executions that
can be submitted via `execute` or `execute_async` before consuming
the output using `ray.get()`. If the caller submits more executions,
`RayCgraphCapacityExceeded` is raised.
overlap_gpu_communication: (experimental) Whether to overlap GPU
communication with computation during DAG execution. If True, the
communication and computation can be overlapped, which can improve
the performance of the DAG execution.
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