add_comment_mutation = """
mutation Q($discussion_id: ID!, $body: String!) {
  addDiscussionComment(input: {discussionId: $discussion_id, body: $body}) {
    comment {
      id
      url
      body
    }
  }
}
"""

update_comment_mutation = """
mutation Q($comment_id: ID!, $body: String!) {
  updateDiscussionComment(input: {commentId: $comment_id, body: $body}) {
    comment {
      id
      url
      body
    }

// Test for authentication
func testBucketLifecycleHandlersWrongCredentials(obj ObjectLayer, instanceType, bucketName string, apiRouter http.Handler,
	credentials auth.Credentials, t *testing.T,
) {
	// test cases with sample input and expected output.
	testCases := []struct {
		method     string
		bucketName string
		accessKey  string
		secretKey  string
		// Sent body
		body []byte
		// Expected response
		expectedRespStatus int

// `shape_inference::InferenceContext` constructor. Note the following:
//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the
//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.

                                    <div class="form-inline col-sm-9">
                                        <la:errors property="sortOrder"/>
                                        <input type="number" name="sortOrder" id="sortOrder"
                                               value="${f:h(sortOrder)}" class="form-control"
                                               min="0" max="100000">

      call: RealCall,
      e: IOException?,
    )

    fun noNewExchanges()

    fun cancel()
  }

  companion object {
    /**
     * The timeout to use while discarding a stream of input data. Since this is used for connection
     * reuse, this timeout should be significantly less than the time it takes to establish a new
     * connection.
     */
    const val DISCARD_STREAM_TIMEOUT_MILLIS = 100
  }

                "detail": [
                    {
                        "type": "missing",
                        "loc": ["cookie", "session_id"],
                        "msg": "Field required",
                        "input": {},
                    }
                ]
            }
        )
        | IsDict(
            # TODO: remove when deprecating Pydantic v1
            {
                "detail": [
                    {

        IsDict(
            {
                "type": "value_error",
                "loc": ("response", "name"),
                "msg": "Value error, name must end in A",
                "input": "modelX",
                "ctx": {"error": HasRepr("ValueError('name must end in A')")},
            }
        )
        | IsDict(
            # TODO remove when deprecating Pydantic v1
            {

import org.gradle.api.DefaultTask
import org.gradle.api.file.DirectoryProperty
import org.gradle.api.logging.Logger
import org.gradle.api.provider.Property
import org.gradle.api.provider.Provider
import org.gradle.api.tasks.Input
import org.gradle.api.tasks.Optional
import org.gradle.api.tasks.OutputDirectory
import org.gradle.api.tasks.TaskAction
// Using star import to workaround https://youtrack.jetbrains.com/issue/KTIJ-24390

    requests with the actual input and output keys used by the trainer code, or
    conversely, update the trainer code to name the input and output Tensors
    'inputs' and 'outputs', respectively. Signatures using the 'classify' and
    'regress' methods are not affected by this change; they will continue to
    standardize their input and output keys as before.
*   Add in-memory caching to the Dataset API.

                {
                    "type": "string_pattern_mismatch",
                    "loc": ["query", "q"],
                    "msg": "String should match pattern '^fixedquery$'",
                    "input": "nonregexquery",
                    "ctx": {"pattern": "^fixedquery$"},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {