TensorFlowDistribution Class
TensorFlow distribution configuration.
- Inheritance
-
azure.ai.ml.entities._job.distribution.DistributionConfigurationTensorFlowDistribution
Constructor
TensorFlowDistribution(*, parameter_server_count: int | None = 0, worker_count: int | None = None, **kwargs: Any)
Keyword-Only Parameters
Name | Description |
---|---|
parameter_server_count
|
The number of parameter server tasks. Defaults to 0. |
worker_count
|
The number of workers. Defaults to the instance count. |
Examples
Configuring a CommandComponent with a TensorFlowDistribution.
from azure.ai.ml import TensorFlowDistribution
from azure.ai.ml.entities import CommandComponent
component = CommandComponent(
name="microsoftsamples_tf",
description="This is the TF command component",
inputs={
"component_in_number": {"description": "A number", "type": "number", "default": 10.99},
"component_in_path": {"description": "A path", "type": "uri_folder"},
},
outputs={"component_out_path": {"type": "uri_folder"}},
command="echo Hello World & echo ${{inputs.component_in_number}} & echo ${{inputs.component_in_path}} "
"& echo ${{outputs.component_out_path}}",
environment="AzureML-sklearn-1.0-ubuntu20.04-py38-cpu:33",
distribution=TensorFlowDistribution(
parameter_server_count=1,
worker_count=2,
),
instance_count=2,
)
Variables
Name | Description |
---|---|
parameter_server_count
|
Number of parameter server tasks. |
worker_count
|
Number of workers. If not specified, will default to the instance count. |
type
|
Specifies the type of distribution. Set automatically to "tensorflow" for this class. |
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Azure SDK for Python