isinstance(field_info, params.Param)
            and getattr(field_info, "in_", None) is None
        ):
            field_info.in_ = params.ParamTypes.query
        use_annotation_from_field_info = get_annotation_from_field_info(
            use_annotation,
            field_info,
            param_name,
        )
        if not field_info.alias and getattr(field_info, "convert_underscores", None):

  private val noContextTakeover: Boolean,
) : Closeable {
  private val deflatedBytes = Buffer()

  private val deflater =
    Deflater(
      Deflater.DEFAULT_COMPRESSION,
      // nowrap (omits zlib header):
      true,
    )

  private val deflaterSink = DeflaterSink(deflatedBytes, deflater)

  /** Deflates [buffer] in place as described in RFC 7692 section 7.2.1. */
  @Throws(IOException::class)

  }

  @Test fun `deflate golden value`() {
    val deflater = MessageDeflater(false)
    val deflated = deflater.deflate("Hello deflate!".encodeUtf8())
    assertThat(deflated.hex()).isEqualTo("f248cdc9c95748494dcb492c49550400")
  }

  @Test fun `inflate deflate`() {
    val deflater = MessageDeflater(false)
    val inflater = MessageInflater(false)

_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)
setattr(_current_module, "metrics", _metrics)
setattr(_current_module, "optimizers", _optimizers)
setattr(_current_module, "initializers", _initializers)


# Do an eager load for Keras' code so that any function/method that needs to

                                      absl::MakeSpan(in_gradients));
      if (!persistent_) {
        trace.backward_function_deleter(trace.backward_function);
      }
      if (!s.ok()) {
        return s;
      }
    } else {
      if (!persistent_) {
        trace.backward_function_deleter(trace.backward_function);
      }
      for (Gradient* grad : out_gradients) {
        if (grad != nullptr) {

  }
  return valid;
}
}  // namespace

void TFE_CallDLManagedTensorDeleter(void* dlm_ptr) {
  DLManagedTensor* dlMTensor = static_cast<DLManagedTensor*>(dlm_ptr);
  if (dlMTensor->deleter != nullptr) {
    dlMTensor->deleter(dlMTensor);
  }
}

void* TFE_HandleToDLPack(TFE_TensorHandle* h, TF_Status* status) {
  auto tf_dlm_context = GetDlContext(h, status);
  if (!status->status.ok()) {
    return nullptr;

    }

    public void setId(final String id) {
        this.id = id;
    }

    public void setCss(final String css) {
        this.css = css;
    }

    public void setAttr(final String name, final String value) {
        this.attrName = name;
        this.attrValue = value;
    }

    @Override
    public String toString() {

import types
from enum import Enum
from typing import Any, Callable, Dict, Set, Type, TypeVar, Union

from pydantic import BaseModel

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = Dict[Union[Type[BaseModel], Type[Enum]], str]

    }

    public void test_toString() {
        String tag = "tag", id = "id", css = "css", attrName = "attrName", attrValue = "attrValue";
        PrunedTag prunedtag = new PrunedTag(tag);
        prunedtag.setAttr(attrName, attrValue);
        prunedtag.setId(id);
        prunedtag.setCss(css);
        assertEquals("PrunedTag [tag=" + tag + ", id=" + id + ", css=" + css + ", attrName=" + attrName + ", attrValue=" + attrValue + "]",

  import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem

# Lazy-load Keras v1.
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1"))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__