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# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.serialization import Model
class TensorFlowSettings(Model):
"""Specifies the settings for TensorFlow job.
All required parameters must be populated in order to send to Azure.
:param python_script_file_path: Required. The path and file name of the
python script to execute the job.
:type python_script_file_path: str
:param python_interpreter_path: The path to python interpreter.
:type python_interpreter_path: str
:param master_command_line_args: Specifies the command line arguments for
the master task.
:type master_command_line_args: str
:param worker_command_line_args: Specifies the command line arguments for
the worker task. This property is optional for single machine training.
:type worker_command_line_args: str
:param parameter_server_command_line_args: Specifies the command line
arguments for the parameter server task. This property is optional for
single machine training.
:type parameter_server_command_line_args: str
:param worker_count: The number of worker tasks. If specified, the value
must be less than or equal to (nodeCount * numberOfGPUs per VM). If not
specified, the default value is equal to nodeCount. This property can be
specified only for distributed TensorFlow training
:type worker_count: int
:param parameter_server_count: The number of parmeter server tasks. If
specified, the value must be less than or equal to nodeCount. If not
specified, the default value is equal to 1 for distributed TensorFlow
training (This property is not applicable for single machine training).
This property can be specified only for distributed TensorFlow training.
:type parameter_server_count: int
"""
_validation = {
'python_script_file_path': {'required': True},
}
_attribute_map = {
'python_script_file_path': {'key': 'pythonScriptFilePath', 'type': 'str'},
'python_interpreter_path': {'key': 'pythonInterpreterPath', 'type': 'str'},
'master_command_line_args': {'key': 'masterCommandLineArgs', 'type': 'str'},
'worker_command_line_args': {'key': 'workerCommandLineArgs', 'type': 'str'},
'parameter_server_command_line_args': {'key': 'parameterServerCommandLineArgs', 'type': 'str'},
'worker_count': {'key': 'workerCount', 'type': 'int'},
'parameter_server_count': {'key': 'parameterServerCount', 'type': 'int'},
}
def __init__(self, **kwargs):
super(TensorFlowSettings, self).__init__(**kwargs)
self.python_script_file_path = kwargs.get('python_script_file_path', None)
self.python_interpreter_path = kwargs.get('python_interpreter_path', None)
self.master_command_line_args = kwargs.get('master_command_line_args', None)
self.worker_command_line_args = kwargs.get('worker_command_line_args', None)
self.parameter_server_command_line_args = kwargs.get('parameter_server_command_line_args', None)
self.worker_count = kwargs.get('worker_count', None)
self.parameter_server_count = kwargs.get('parameter_server_count', None)
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