EXPECT_TRUE(differencer.Compare(node_in, node_out));
}

TEST(CAPI, TestTensorNonScalarBytesAllocateDelete) {
  const int batch_size = 4;
  const int num_dims = 2;
  int64_t* dims = new int64_t[num_dims];
  int64_t num_elements = 1;
  dims[0] = batch_size;
  dims[1] = 1;
  for (int64_t i = 0; i < num_dims; ++i) {
    num_elements *= dims[i];
  }

¨CSumAlgo ¨PartNums‘ ©PartETagsÀ©PartSizes‘Ñ$CªPartASizes‘Ñ$C¤SizeÑ$C¥MTimeÓ É ¸Åñ€§MetaSys ¼x-minio-internal-inline-dataÄ true§MetaUsr‚¬content-type°application/json¤etagÙ d6566afb36d109141150¡v Î W G ¤nullÅ ,”³ §<“ a j ž¤ðŒ•{ ìë¡ 8±õe"… ™ k{"key":"batch_size","value":"1"},{"key":"queue_size","value":"100000"},{"key":"queue_dir","value":""}]},"notify_amqp":{"_":[{"key":"enable","value":"off"},{"key":"url","value":""},{"key":"exchange","value":""},{"key":"exchange_type","value":""},{"key":"routing_ke...

# Release 2.7.0

## Breaking Changes

*   `tf.keras`:

    *   The methods `Model.fit()`, `Model.predict()`, and `Model.evaluate()`
        will no longer uprank input data of shape `(batch_size,)` to become
        `(batch_size, 1)`. This enables `Model` subclasses to process scalar
        data in their `train_step()`/`test_step()`/`predict_step()` methods. \
        Note that this change may break certain subclassed models. You can