Batch prediction Input - google-cloud-platform

Question

I have a tensorflow model deployed on Vertex AI of Google Cloud. The model definition is:
item_model = tf.keras.Sequential([
tf.keras.layers.StringLookup(
vocabulary=item_vocab, mask_token=None),
tf.keras.layers.Embedding(len(item_vocab) + 1, embedding_dim)
])
user_model = tf.keras.Sequential([
tf.keras.layers.StringLookup(
vocabulary=user_vocab, mask_token=None),
# We add an additional embedding to account for unknown tokens.
tf.keras.layers.Embedding(len(user_vocab) + 1, embedding_dim)
])
class NCF_model(tf.keras.Model):
def __init__(self,user_model, item_model):
super(NCF_model, self).__init__()
# define all layers in init
self.user_model = user_model
self.item_model = item_model
self.concat_layer = tf.keras.layers.Concatenate()
self.feed_forward_1 = tf.keras.layers.Dense(32,activation= 'relu')
self.feed_forward_2 = tf.keras.layers.Dense(64,activation= 'relu')
self.final = tf.keras.layers.Dense(1,activation= 'sigmoid')
def call(self, inputs ,training=False):
user_id , item_id = inputs[:,0], inputs[:,1]
x = self.user_model(user_id)
y = self.item_model(item_id)
x = self.concat_layer([x,y])
x = self.feed_forward_1(x)
x = self.feed_forward_2(x)
x = self.final(x)
return x
The model has two string inputs and it outputs a probability value.
When I use the following input in the batch prediction file, I get an empty prediction file.
Sample of csv input file:
userid,itemid
yuu,190767
yuu,364
yuu,154828
yuu,72998
yuu,130618
yuu,183979
yuu,588
When I use a jsonl file with the following input.
{"input":["yuu", "190767"]}
I get the following error.
('Post request fails. Cannot get predictions. Error: Exceeded retries: Non-OK result 400 ({\n "error": "Failed to process element: 0 key: input of \'instances\' list. Error: INVALID_ARGUMENT: JSON object: does not have named input: input"\n}) from server, retry=3.', 1)
What seems to be going wrong with these inputs?

Answer 1

After a bit of experimenting, I found out what was wrong with the batch prediction input. In the csv file, the item column was being interpreted as an integer whereas the model has a string as an input. I'm not sure why there was no output at all in that case and I couldn't find the logs for the batch prediction.
The correct format for jsonlines was:
["user1", "item1"]
["user2", "item2"]
["user3", "item3"]
The one I used assumed the input was a named layer, 'input'. In all of this, I found the documentation of google cloud to be lacking.