GetMasterImageUri().AddToParser(parser)
GetParameterServerMachineTypeConfig().AddToParser(parser)
GetParameterServerAccelerator().AddToParser(parser)
GetParameterServerImageUri().AddToParser(parser)
GetWorkerMachineConfig().AddToParser(parser)
GetWorkerAccelerator().AddToParser(parser)
GetWorkerImageUri().AddToParser(parser)
GetUseChiefInTfConfig().AddToParser(parser)
if support_tpu_tf_version:
GetTpuTfVersion().AddToParser(parser)
# Custom Container Flags
_ACCELERATOR_TYPE_MAPPER = arg_utils.ChoiceEnumMapper(
'generic-accelerator',
jobs.GetMessagesModule(
).GoogleCloudMlV1AcceleratorConfig.TypeValueValuesEnum,
help_str='Available types of accelerators.',
include_filter=lambda x: x != 'ACCELERATOR_TYPE_UNSPECIFIED',
required=False)
_OP_ACCELERATOR_TYPE_MAPPER = arg_utils.ChoiceEnumMapper(
'generic-accelerator',
jobs.GetMessagesModule(
).GoogleCloudMlV1AcceleratorConfig.TypeValueValuesEnum,
help_str='Available types of accelerators.',
include_filter=lambda x: x.startswith('NVIDIA'),
required=False)
_OP_AUTOSCALING_METRIC_NAME_MAPPER = arg_utils.ChoiceEnumMapper(
'autoscaling-metric-name',
versions_api.GetMessagesModule(
_LOGS_URL = ('https://console.cloud.google.com/logs?'
'resource=ml.googleapis.com%2Fjob_id%2F{job_id}'
'&project={project}')
JOB_FORMAT = 'yaml(jobId,state,startTime.date(tz=LOCAL),endTime.date(tz=LOCAL))'
# Check every 10 seconds if the job is complete (if we didn't fetch any logs the
# last time)
_CONTINUE_INTERVAL = 10
_TEXT_FILE_URL = ('https://www.tensorflow.org/guide/datasets'
'#consuming_text_data')
_TF_RECORD_URL = ('https://www.tensorflow.org/guide/datasets'
'#consuming_tfrecord_data')
_PREDICTION_DATA_FORMAT_MAPPER = arg_utils.ChoiceEnumMapper(
'--data-format',
jobs.GetMessagesModule(
).GoogleCloudMlV1PredictionInput.DataFormatValueValuesEnum,
custom_mappings={
'TEXT': ('text', ('Text files; see {}'.format(_TEXT_FILE_URL))),
'TF_RECORD':
('tf-record', 'TFRecord files; see {}'.format(_TF_RECORD_URL)),
'TF_RECORD_GZIP': ('tf-record-gzip', 'GZIP-compressed TFRecord files.')
},
help_str='Data format of the input files.',
required=True)
_ACCELERATOR_MAP = arg_utils.ChoiceEnumMapper(
'--accelerator-type',
jobs.GetMessagesModule(
).GoogleCloudMlV1AcceleratorConfig.TypeValueValuesEnum,
custom_mappings={
'NVIDIA_TESLA_K80': ('nvidia-tesla-k80', 'NVIDIA Tesla K80 GPU'),
_LOGS_URL = ('https://console.cloud.google.com/logs?'
'resource=ml.googleapis.com%2Fjob_id%2F{job_id}'
'&project={project}')
JOB_FORMAT = 'yaml(jobId,state,startTime.date(tz=LOCAL),endTime.date(tz=LOCAL))'
# Check every 10 seconds if the job is complete (if we didn't fetch any logs the
# last time)
_CONTINUE_INTERVAL = 10
_TF_RECORD_URL = ('https://www.tensorflow.org/versions/r0.12/how_tos/'
'reading_data/index.html#file-formats')
_PREDICTION_DATA_FORMAT_MAPPER = arg_utils.ChoiceEnumMapper(
'--data-format',
jobs.GetMessagesModule(
).GoogleCloudMlV1PredictionInput.DataFormatValueValuesEnum,
custom_mappings={
'TEXT': ('text', ('Text files with instances separated '
'by the new-line character.')),
'TF_RECORD': ('tf-record',
'TFRecord files; see {}'.format(_TF_RECORD_URL)),
'TF_RECORD_GZIP': ('tf-record-gzip',
'GZIP-compressed TFRecord files.')
},
help_str='Data format of the input files.',
required=True)
def DataFormatFlagMap():
"""Return the ChoiceEnumMapper for the --data-format flag."""
return _PREDICTION_DATA_FORMAT_MAPPER
