vendor: update all dependencies
* Update all dependencies * Remove all `[[constraint]]` from Gopkg.toml * Add in the minimum number of `[[override]]` to build * Remove go get of github.com/inconshreveable/mousetrap as it is vendored * Update docs with new policy on constraints
This commit is contained in:
Nick Craig-Wood
+33
-19
@@ -118,7 +118,7 @@
|
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"projects": {
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"methods": {
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"getConfig": {
|
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"description": "Get the service account information associated with your project. You need\nthis information in order to grant the service account persmissions for\nthe Google Cloud Storage location where you put your model training code\nfor training the model with Google Cloud Machine Learning.",
|
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"description": "Get the service account information associated with your project. You need\nthis information in order to grant the service account permissions for\nthe Google Cloud Storage location where you put your model training code\nfor training the model with Google Cloud Machine Learning.",
|
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"flatPath": "v1/projects/{projectsId}:getConfig",
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"httpMethod": "GET",
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"id": "ml.projects.getConfig",
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@@ -290,7 +290,7 @@
|
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],
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"parameters": {
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"filter": {
|
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"description": "Optional. Specifies the subset of jobs to retrieve.\nYou can filter on the value of one or more attributes of the job object.\nFor example, retrieve jobs with a job identifier that starts with 'census':\n\u003cp\u003e\u003ccode\u003egcloud ml-engine jobs list --filter='jobId:census*'\u003c/code\u003e\n\u003cp\u003eList all failed jobs with names that start with 'rnn':\n\u003cp\u003e\u003ccode\u003egcloud ml-engine jobs list --filter='jobId:rnn*\nAND state:FAILED'\u003c/code\u003e\n\u003cp\u003eFor more examples, see the guide to\n\u003ca href=\"/ml-engine/docs/monitor-training\"\u003emonitoring jobs\u003c/a\u003e.",
|
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"description": "Optional. Specifies the subset of jobs to retrieve.\nYou can filter on the value of one or more attributes of the job object.\nFor example, retrieve jobs with a job identifier that starts with 'census':\n\u003cp\u003e\u003ccode\u003egcloud ml-engine jobs list --filter='jobId:census*'\u003c/code\u003e\n\u003cp\u003eList all failed jobs with names that start with 'rnn':\n\u003cp\u003e\u003ccode\u003egcloud ml-engine jobs list --filter='jobId:rnn*\nAND state:FAILED'\u003c/code\u003e\n\u003cp\u003eFor more examples, see the guide to\n\u003ca href=\"/ml-engine/docs/tensorflow/monitor-training\"\u003emonitoring jobs\u003c/a\u003e.",
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"location": "query",
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"type": "string"
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},
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@@ -992,7 +992,7 @@
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}
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}
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},
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"revision": "20180315",
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"revision": "20180420",
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"rootUrl": "https://ml.googleapis.com/",
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"schemas": {
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"GoogleApi__HttpBody": {
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@@ -1044,7 +1044,7 @@
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"id": "GoogleCloudMlV1__AutoScaling",
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"properties": {
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"minNodes": {
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"description": "Optional. The minimum number of nodes to allocate for this model. These\nnodes are always up, starting from the time the model is deployed, so the\ncost of operating this model will be at least\n`rate` * `min_nodes` * number of hours since last billing cycle,\nwhere `rate` is the cost per node-hour as documented in\n[pricing](https://cloud.google.com/ml-engine/pricing#prediction_pricing),\neven if no predictions are performed. There is additional cost for each\nprediction performed.\n\nUnlike manual scaling, if the load gets too heavy for the nodes\nthat are up, the service will automatically add nodes to handle the\nincreased load as well as scale back as traffic drops, always maintaining\nat least `min_nodes`. You will be charged for the time in which additional\nnodes are used.\n\nIf not specified, `min_nodes` defaults to 0, in which case, when traffic\nto a model stops (and after a cool-down period), nodes will be shut down\nand no charges will be incurred until traffic to the model resumes.",
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"description": "Optional. The minimum number of nodes to allocate for this model. These\nnodes are always up, starting from the time the model is deployed, so the\ncost of operating this model will be at least\n`rate` * `min_nodes` * number of hours since last billing cycle,\nwhere `rate` is the cost per node-hour as documented in the\n[pricing guide](/ml-engine/docs/pricing),\neven if no predictions are performed. There is additional cost for each\nprediction performed.\n\nUnlike manual scaling, if the load gets too heavy for the nodes\nthat are up, the service will automatically add nodes to handle the\nincreased load as well as scale back as traffic drops, always maintaining\nat least `min_nodes`. You will be charged for the time in which additional\nnodes are used.\n\nIf not specified, `min_nodes` defaults to 0, in which case, when traffic\nto a model stops (and after a cool-down period), nodes will be shut down\nand no charges will be incurred until traffic to the model resumes.",
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"format": "int32",
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"type": "integer"
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}
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@@ -1161,6 +1161,20 @@
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"description": "Represents a set of hyperparameters to optimize.",
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"id": "GoogleCloudMlV1__HyperparameterSpec",
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"properties": {
|
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"algorithm": {
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"description": "Optional. The search algorithm specified for the hyperparameter\ntuning job.\nUses the default CloudML Engine hyperparameter tuning\nalgorithm if unspecified.",
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"enum": [
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"ALGORITHM_UNSPECIFIED",
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"GRID_SEARCH",
|
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"RANDOM_SEARCH"
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],
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"enumDescriptions": [
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"The default algorithm used by hyperparameter tuning service.",
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"Simple grid search within the feasible space. To use grid search,\nall parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.",
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"Simple random search within the feasible space."
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],
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"type": "string"
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},
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"enableTrialEarlyStopping": {
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"description": "Optional. Indicates if the hyperparameter tuning job enables auto trial\nearly stopping.",
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"type": "boolean"
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@@ -1397,7 +1411,7 @@
|
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"type": "boolean"
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},
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"regions": {
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"description": "Optional. The list of regions where the model is going to be deployed.\nCurrently only one region per model is supported.\nDefaults to 'us-central1' if nothing is set.\nSee the \u003ca href=\"/ml-engine/docs/regions\"\u003eavailable regions\u003c/a\u003e for\nML Engine services.\nNote:\n* No matter where a model is deployed, it can always be accessed by\n users from anywhere, both for online and batch prediction.\n* The region for a batch prediction job is set by the region field when\n submitting the batch prediction job and does not take its value from\n this field.",
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"description": "Optional. The list of regions where the model is going to be deployed.\nCurrently only one region per model is supported.\nDefaults to 'us-central1' if nothing is set.\nSee the \u003ca href=\"/ml-engine/docs/tensorflow/regions\"\u003eavailable regions\u003c/a\u003e\nfor ML Engine services.\nNote:\n* No matter where a model is deployed, it can always be accessed by\n users from anywhere, both for online and batch prediction.\n* The region for a batch prediction job is set by the region field when\n submitting the batch prediction job and does not take its value from\n this field.",
|
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"items": {
|
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"type": "string"
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},
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@@ -1588,7 +1602,7 @@
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"type": "string"
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},
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"modelName": {
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"description": "Use this field if you want to use the default version for the specified\nmodel. The string must use the following format:\n\n`\"projects/\u003cvar\u003e[YOUR_PROJECT]\u003c/var\u003e/models/\u003cvar\u003e[YOUR_MODEL]\u003c/var\u003e\"`",
|
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"description": "Use this field if you want to use the default version for the specified\nmodel. The string must use the following format:\n\n`\"projects/YOUR_PROJECT/models/YOUR_MODEL\"`",
|
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"type": "string"
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},
|
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"outputPath": {
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@@ -1596,7 +1610,7 @@
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"type": "string"
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},
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"region": {
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"description": "Required. The Google Compute Engine region to run the prediction job in.\nSee the \u003ca href=\"/ml-engine/docs/regions\"\u003eavailable regions\u003c/a\u003e for\nML Engine services.",
|
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"description": "Required. The Google Compute Engine region to run the prediction job in.\nSee the \u003ca href=\"/ml-engine/docs/tensorflow/regions\"\u003eavailable regions\u003c/a\u003e\nfor ML Engine services.",
|
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"type": "string"
|
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},
|
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"runtimeVersion": {
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@@ -1612,7 +1626,7 @@
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"type": "string"
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},
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"versionName": {
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"description": "Use this field if you want to specify a version of the model to use. The\nstring is formatted the same way as `model_version`, with the addition\nof the version information:\n\n`\"projects/\u003cvar\u003e[YOUR_PROJECT]\u003c/var\u003e/models/\u003cvar\u003eYOUR_MODEL/versions/\u003cvar\u003e[YOUR_VERSION]\u003c/var\u003e\"`",
|
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"description": "Use this field if you want to specify a version of the model to use. The\nstring is formatted the same way as `model_version`, with the addition\nof the version information:\n\n`\"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION\"`",
|
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"type": "string"
|
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}
|
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},
|
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@@ -1651,7 +1665,7 @@
|
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"type": "object"
|
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},
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"GoogleCloudMlV1__TrainingInput": {
|
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"description": "Represents input parameters for a training job. When using the\ngcloud command to submit your training job, you can specify\nthe input parameters as command-line arguments and/or in a YAML configuration\nfile referenced from the --config command-line argument. For\ndetails, see the guide to\n\u003ca href=\"/ml-engine/docs/training-jobs\"\u003esubmitting a training job\u003c/a\u003e.",
|
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"description": "Represents input parameters for a training job. When using the\ngcloud command to submit your training job, you can specify\nthe input parameters as command-line arguments and/or in a YAML configuration\nfile referenced from the --config command-line argument. For\ndetails, see the guide to\n\u003ca href=\"/ml-engine/docs/tensorflow/training-jobs\"\u003esubmitting a training\njob\u003c/a\u003e.",
|
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"id": "GoogleCloudMlV1__TrainingInput",
|
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"properties": {
|
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"args": {
|
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@@ -1670,7 +1684,7 @@
|
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"type": "string"
|
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},
|
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"masterType": {
|
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"description": "Optional. Specifies the type of virtual machine to use for your training\njob's master worker.\n\nThe following types are supported:\n\n\u003cdl\u003e\n \u003cdt\u003estandard\u003c/dt\u003e\n \u003cdd\u003e\n A basic machine configuration suitable for training simple models with\n small to moderate datasets.\n \u003c/dd\u003e\n \u003cdt\u003elarge_model\u003c/dt\u003e\n \u003cdd\u003e\n A machine with a lot of memory, specially suited for parameter servers\n when your model is large (having many hidden layers or layers with very\n large numbers of nodes).\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_s\u003c/dt\u003e\n \u003cdd\u003e\n A machine suitable for the master and workers of the cluster when your\n model requires more computation than the standard machine can handle\n satisfactorily.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_m\u003c/dt\u003e\n \u003cdd\u003e\n A machine with roughly twice the number of cores and roughly double the\n memory of \u003ccode suppresswarning=\"true\"\u003ecomplex_model_s\u003c/code\u003e.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_l\u003c/dt\u003e\n \u003cdd\u003e\n A machine with roughly twice the number of cores and roughly double the\n memory of \u003ccode suppresswarning=\"true\"\u003ecomplex_model_m\u003c/code\u003e.\n \u003c/dd\u003e\n \u003cdt\u003estandard_gpu\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to \u003ccode suppresswarning=\"true\"\u003estandard\u003c/code\u003e that\n also includes a single NVIDIA Tesla K80 GPU. See more about\n \u003ca href=\"/ml-engine/docs/how-tos/using-gpus\"\u003e\n using GPUs for training your model\u003c/a\u003e.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_m_gpu\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to\n \u003ccode suppresswarning=\"true\"\u003ecomplex_model_m\u003c/code\u003e that also includes\n four NVIDIA Tesla K80 GPUs.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_l_gpu\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to\n \u003ccode suppresswarning=\"true\"\u003ecomplex_model_l\u003c/code\u003e that also includes\n eight NVIDIA Tesla K80 GPUs.\n \u003c/dd\u003e\n \u003cdt\u003estandard_p100\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to \u003ccode suppresswarning=\"true\"\u003estandard\u003c/code\u003e that\n also includes a single NVIDIA Tesla P100 GPU. The availability of these\n GPUs is in the Beta launch stage.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_m_p100\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to\n \u003ccode suppresswarning=\"true\"\u003ecomplex_model_m\u003c/code\u003e that also includes\n four NVIDIA Tesla P100 GPUs. The availability of these GPUs is in\n the Beta launch stage.\n \u003c/dd\u003e\n\u003c/dl\u003e\n\nYou must set this value when `scaleTier` is set to `CUSTOM`.",
|
||||
"description": "Optional. Specifies the type of virtual machine to use for your training\njob's master worker.\n\nThe following types are supported:\n\n\u003cdl\u003e\n \u003cdt\u003estandard\u003c/dt\u003e\n \u003cdd\u003e\n A basic machine configuration suitable for training simple models with\n small to moderate datasets.\n \u003c/dd\u003e\n \u003cdt\u003elarge_model\u003c/dt\u003e\n \u003cdd\u003e\n A machine with a lot of memory, specially suited for parameter servers\n when your model is large (having many hidden layers or layers with very\n large numbers of nodes).\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_s\u003c/dt\u003e\n \u003cdd\u003e\n A machine suitable for the master and workers of the cluster when your\n model requires more computation than the standard machine can handle\n satisfactorily.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_m\u003c/dt\u003e\n \u003cdd\u003e\n A machine with roughly twice the number of cores and roughly double the\n memory of \u003ccode suppresswarning=\"true\"\u003ecomplex_model_s\u003c/code\u003e.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_l\u003c/dt\u003e\n \u003cdd\u003e\n A machine with roughly twice the number of cores and roughly double the\n memory of \u003ccode suppresswarning=\"true\"\u003ecomplex_model_m\u003c/code\u003e.\n \u003c/dd\u003e\n \u003cdt\u003estandard_gpu\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to \u003ccode suppresswarning=\"true\"\u003estandard\u003c/code\u003e that\n also includes a single NVIDIA Tesla K80 GPU. See more about\n \u003ca href=\"/ml-engine/docs/tensorflow/using-gpus\"\u003eusing GPUs to\n train your model\u003c/a\u003e.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_m_gpu\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to\n \u003ccode suppresswarning=\"true\"\u003ecomplex_model_m\u003c/code\u003e that also includes\n four NVIDIA Tesla K80 GPUs.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_l_gpu\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to\n \u003ccode suppresswarning=\"true\"\u003ecomplex_model_l\u003c/code\u003e that also includes\n eight NVIDIA Tesla K80 GPUs.\n \u003c/dd\u003e\n \u003cdt\u003estandard_p100\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to \u003ccode suppresswarning=\"true\"\u003estandard\u003c/code\u003e that\n also includes a single NVIDIA Tesla P100 GPU. The availability of these\n GPUs is in the Beta launch stage.\n \u003c/dd\u003e\n \u003cdt\u003ecomplex_model_m_p100\u003c/dt\u003e\n \u003cdd\u003e\n A machine equivalent to\n \u003ccode suppresswarning=\"true\"\u003ecomplex_model_m\u003c/code\u003e that also includes\n four NVIDIA Tesla P100 GPUs. The availability of these GPUs is in\n the Beta launch stage.\n \u003c/dd\u003e\n \u003cdt\u003estandard_tpu\u003c/dt\u003e\n \u003cdd\u003e\n A TPU VM including one Cloud TPU. The availability of Cloud TPU is in\n \u003ci\u003eBeta\u003c/i\u003e launch stage. See more about\n \u003ca href=\"/ml-engine/docs/tensorflow/using-tpus\"\u003eusing TPUs to train\n your model\u003c/a\u003e.\n \u003c/dd\u003e\n\u003c/dl\u003e\n\nYou must set this value when `scaleTier` is set to `CUSTOM`.",
|
||||
"type": "string"
|
||||
},
|
||||
"packageUris": {
|
||||
@@ -1698,11 +1712,11 @@
|
||||
"type": "string"
|
||||
},
|
||||
"region": {
|
||||
"description": "Required. The Google Compute Engine region to run the training job in.\nSee the \u003ca href=\"/ml-engine/docs/regions\"\u003eavailable regions\u003c/a\u003e for\nML Engine services.",
|
||||
"description": "Required. The Google Compute Engine region to run the training job in.\nSee the \u003ca href=\"/ml-engine/docs/tensorflow/regions\"\u003eavailable regions\u003c/a\u003e\nfor ML Engine services.",
|
||||
"type": "string"
|
||||
},
|
||||
"runtimeVersion": {
|
||||
"description": "Optional. The Google Cloud ML runtime version to use for training. If not\nset, Google Cloud ML will choose the latest stable version.",
|
||||
"description": "Optional. The Google Cloud ML runtime version to use for training. If not\nset, Google Cloud ML will choose a stable version, which is defined in the\ndocumentation of runtime version list.",
|
||||
"type": "string"
|
||||
},
|
||||
"scaleTier": {
|
||||
@@ -1719,8 +1733,8 @@
|
||||
"A single worker instance. This tier is suitable for learning how to use\nCloud ML, and for experimenting with new models using small datasets.",
|
||||
"Many workers and a few parameter servers.",
|
||||
"A large number of workers with many parameter servers.",
|
||||
"A single worker instance [with a\nGPU](/ml-engine/docs/how-tos/using-gpus).",
|
||||
"A single worker instance with a [Cloud TPU](/tpu)",
|
||||
"A single worker instance [with a\nGPU](/ml-engine/docs/tensorflow/using-gpus).",
|
||||
"A single worker instance with a\n[Cloud TPU](/ml-engine/docs/tensorflow/using-tpus).\nThe availability of Cloud TPU is in \u003ci\u003eBeta\u003c/i\u003e launch stage.",
|
||||
"The CUSTOM tier is not a set tier, but rather enables you to use your\nown cluster specification. When you use this tier, set values to\nconfigure your processing cluster according to these guidelines:\n\n* You _must_ set `TrainingInput.masterType` to specify the type\n of machine to use for your master node. This is the only required\n setting.\n\n* You _may_ set `TrainingInput.workerCount` to specify the number of\n workers to use. If you specify one or more workers, you _must_ also\n set `TrainingInput.workerType` to specify the type of machine to use\n for your worker nodes.\n\n* You _may_ set `TrainingInput.parameterServerCount` to specify the\n number of parameter servers to use. If you specify one or more\n parameter servers, you _must_ also set\n `TrainingInput.parameterServerType` to specify the type of machine to\n use for your parameter servers.\n\nNote that all of your workers must use the same machine type, which can\nbe different from your parameter server type and master type. Your\nparameter servers must likewise use the same machine type, which can be\ndifferent from your worker type and master type."
|
||||
],
|
||||
"type": "string"
|
||||
@@ -1779,7 +1793,7 @@
|
||||
"type": "string"
|
||||
},
|
||||
"deploymentUri": {
|
||||
"description": "Required. The Google Cloud Storage location of the trained model used to\ncreate the version. See the\n[overview of model\ndeployment](/ml-engine/docs/concepts/deployment-overview) for more\ninformation.\n\nWhen passing Version to\n[projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)\nthe model service uses the specified location as the source of the model.\nOnce deployed, the model version is hosted by the prediction service, so\nthis location is useful only as a historical record.\nThe total number of model files can't exceed 1000.",
|
||||
"description": "Required. The Google Cloud Storage location of the trained model used to\ncreate the version. See the\n[guide to model\ndeployment](/ml-engine/docs/tensorflow/deploying-models) for more\ninformation.\n\nWhen passing Version to\n[projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)\nthe model service uses the specified location as the source of the model.\nOnce deployed, the model version is hosted by the prediction service, so\nthis location is useful only as a historical record.\nThe total number of model files can't exceed 1000.",
|
||||
"type": "string"
|
||||
},
|
||||
"description": {
|
||||
@@ -1791,7 +1805,7 @@
|
||||
"type": "string"
|
||||
},
|
||||
"framework": {
|
||||
"description": "The ML framework used to train this version of the model. If not specified,\ndefaults to `TENSORFLOW`",
|
||||
"description": "Optional. The machine learning framework Cloud ML Engine uses to train\nthis version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,\nand `XGBOOST`. If you do not specify a framework, Cloud ML Engine uses\nTensorFlow. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set\nthe runtime version of the model to 1.4 or greater.",
|
||||
"enum": [
|
||||
"FRAMEWORK_UNSPECIFIED",
|
||||
"TENSORFLOW",
|
||||
@@ -1859,7 +1873,7 @@
|
||||
"id": "GoogleIamV1__AuditConfig",
|
||||
"properties": {
|
||||
"auditLogConfigs": {
|
||||
"description": "The configuration for logging of each type of permission.\nNext ID: 4",
|
||||
"description": "The configuration for logging of each type of permission.",
|
||||
"items": {
|
||||
"$ref": "GoogleIamV1__AuditLogConfig"
|
||||
},
|
||||
@@ -1907,7 +1921,7 @@
|
||||
"id": "GoogleIamV1__Binding",
|
||||
"properties": {
|
||||
"members": {
|
||||
"description": "Specifies the identities requesting access for a Cloud Platform resource.\n`members` can have the following values:\n\n* `allUsers`: A special identifier that represents anyone who is\n on the internet; with or without a Google account.\n\n* `allAuthenticatedUsers`: A special identifier that represents anyone\n who is authenticated with a Google account or a service account.\n\n* `user:{emailid}`: An email address that represents a specific Google\n account. For example, `alice@gmail.com` or `joe@example.com`.\n\n\n* `serviceAccount:{emailid}`: An email address that represents a service\n account. For example, `my-other-app@appspot.gserviceaccount.com`.\n\n* `group:{emailid}`: An email address that represents a Google group.\n For example, `admins@example.com`.\n\n\n* `domain:{domain}`: A Google Apps domain name that represents all the\n users of that domain. For example, `google.com` or `example.com`.\n\n",
|
||||
"description": "Specifies the identities requesting access for a Cloud Platform resource.\n`members` can have the following values:\n\n* `allUsers`: A special identifier that represents anyone who is\n on the internet; with or without a Google account.\n\n* `allAuthenticatedUsers`: A special identifier that represents anyone\n who is authenticated with a Google account or a service account.\n\n* `user:{emailid}`: An email address that represents a specific Google\n account. For example, `alice@gmail.com` .\n\n\n* `serviceAccount:{emailid}`: An email address that represents a service\n account. For example, `my-other-app@appspot.gserviceaccount.com`.\n\n* `group:{emailid}`: An email address that represents a Google group.\n For example, `admins@example.com`.\n\n\n* `domain:{domain}`: A Google Apps domain name that represents all the\n users of that domain. For example, `google.com` or `example.com`.\n\n",
|
||||
"items": {
|
||||
"type": "string"
|
||||
},
|
||||
@@ -1921,7 +1935,7 @@
|
||||
"type": "object"
|
||||
},
|
||||
"GoogleIamV1__Policy": {
|
||||
"description": "Defines an Identity and Access Management (IAM) policy. It is used to\nspecify access control policies for Cloud Platform resources.\n\n\nA `Policy` consists of a list of `bindings`. A `Binding` binds a list of\n`members` to a `role`, where the members can be user accounts, Google groups,\nGoogle domains, and service accounts. A `role` is a named list of permissions\ndefined by IAM.\n\n**Example**\n\n {\n \"bindings\": [\n {\n \"role\": \"roles/owner\",\n \"members\": [\n \"user:mike@example.com\",\n \"group:admins@example.com\",\n \"domain:google.com\",\n \"serviceAccount:my-other-app@appspot.gserviceaccount.com\",\n ]\n },\n {\n \"role\": \"roles/viewer\",\n \"members\": [\"user:sean@example.com\"]\n }\n ]\n }\n\nFor a description of IAM and its features, see the\n[IAM developer's guide](https://cloud.google.com/iam/docs).",
|
||||
"description": "Defines an Identity and Access Management (IAM) policy. It is used to\nspecify access control policies for Cloud Platform resources.\n\n\nA `Policy` consists of a list of `bindings`. A `binding` binds a list of\n`members` to a `role`, where the members can be user accounts, Google groups,\nGoogle domains, and service accounts. A `role` is a named list of permissions\ndefined by IAM.\n\n**JSON Example**\n\n {\n \"bindings\": [\n {\n \"role\": \"roles/owner\",\n \"members\": [\n \"user:mike@example.com\",\n \"group:admins@example.com\",\n \"domain:google.com\",\n \"serviceAccount:my-other-app@appspot.gserviceaccount.com\"\n ]\n },\n {\n \"role\": \"roles/viewer\",\n \"members\": [\"user:sean@example.com\"]\n }\n ]\n }\n\n**YAML Example**\n\n bindings:\n - members:\n - user:mike@example.com\n - group:admins@example.com\n - domain:google.com\n - serviceAccount:my-other-app@appspot.gserviceaccount.com\n role: roles/owner\n - members:\n - user:sean@example.com\n role: roles/viewer\n\n\nFor a description of IAM and its features, see the\n[IAM developer's guide](https://cloud.google.com/iam/docs).",
|
||||
"id": "GoogleIamV1__Policy",
|
||||
"properties": {
|
||||
"auditConfigs": {
|
||||
|
||||
Reference in New Issue
Block a user