Im new with petastorm and Im facing some issues.
I need to iterate over a dataset getting three equals batches to transform 2 of them to extract some info.
The dataset consist on users ratings movies (like the Movie-Lens dataset). I need to get three batches with the same ratings(rows) to extract each user(in ratings the user could appear repeated) and extract each movie rated. I write this code.

Creating fake dataset and spark converter:

ratings_l = [
    {'uid_dec': 0, 'mid_dec': 6, 'eval': 2.18},
    {'uid_dec': 0, 'mid_dec': 7, 'eval': 3.83},
    {'uid_dec': 0, 'mid_dec': 8, 'eval': 3.94},
    {'uid_dec': 0, 'mid_dec': 9, 'eval': 4.31},
    {'uid_dec': 0, 'mid_dec': 10, 'eval': 4.48},
    {'uid_dec': 0, 'mid_dec': 11, 'eval': 3.74},
    {'uid_dec': 1, 'mid_dec': 6, 'eval': 3.21},
    {'uid_dec': 1, 'mid_dec': 7, 'eval': 2.05},
    {'uid_dec': 1, 'mid_dec': 8, 'eval': 2.24},
    {'uid_dec': 1, 'mid_dec': 9, 'eval': 2.08},
    {'uid_dec': 1, 'mid_dec': 10, 'eval': 4.94},
    {'uid_dec': 1, 'mid_dec': 11, 'eval': 4.22},
    {'uid_dec': 2, 'mid_dec': 6, 'eval': 3.52},
    {'uid_dec': 2, 'mid_dec': 7, 'eval': 2.67},
    {'uid_dec': 2, 'mid_dec': 8, 'eval': 2.69},
    {'uid_dec': 2, 'mid_dec': 9, 'eval': 2.75},
    {'uid_dec': 2, 'mid_dec': 10, 'eval': 4.93},
    {'uid_dec': 2, 'mid_dec': 11, 'eval': 2.9},
    {'uid_dec': 3, 'mid_dec': 6, 'eval': 2.0},
    {'uid_dec': 3, 'mid_dec': 7, 'eval': 2.9},
    {'uid_dec': 3, 'mid_dec': 8, 'eval': 4.74},
    {'uid_dec': 3, 'mid_dec': 9, 'eval': 2.5},
    {'uid_dec': 3, 'mid_dec': 10, 'eval': 2.18},
    {'uid_dec': 3, 'mid_dec': 11, 'eval': 4.93},
    {'uid_dec': 4, 'mid_dec': 6, 'eval': 4.46},
    {'uid_dec': 4, 'mid_dec': 7, 'eval': 2.23},
    {'uid_dec': 4, 'mid_dec': 8, 'eval': 4.42},
    {'uid_dec': 4, 'mid_dec': 9, 'eval': 4.67},
    {'uid_dec': 4, 'mid_dec': 10, 'eval': 2.65},
    {'uid_dec': 4, 'mid_dec': 11, 'eval': 2.11},
    {'uid_dec': 5, 'mid_dec': 6, 'eval': 2.31},
    {'uid_dec': 5, 'mid_dec': 7, 'eval': 2.69},
    {'uid_dec': 5, 'mid_dec': 8, 'eval': 2.41},
    {'uid_dec': 5, 'mid_dec': 9, 'eval': 4.62},
    {'uid_dec': 5, 'mid_dec': 10, 'eval': 3.96},
    {'uid_dec': 5, 'mid_dec': 11, 'eval': 2.23}
]

train_ds = spark.createDataFrame(ratings_l)

conv_train = make_spark_converter(train_ds)

Get three batches from the same converter(hoping they are the same):

epochs = 4
batch_size = 6
with conv_train.make_tf_dataset(batch_size=batch_size, num_epochs=epochs, seed=1) as train, 
     conv_train.make_tf_dataset(batch_size=batch_size, num_epochs=epochs, seed=1) as train1, 
     conv_train.make_tf_dataset(batch_size=batch_size, num_epochs=epochs, seed=1) as train2:
     epoch_eval = True
     for i, (b, b1, b2) in enumerate(zip(train, train1, train2)):
        if i%(36//batch_size) == 0:
            print('==========Epoch==========: {0}'.format(i//(36//batch_size)))
        print('==========Batch: {}'.format(i%(36//batch_size)))
        print(b[0].numpy())
        print(b1[0].numpy())
        print(b2[0].numpy())

This is the output:

==========Epoch==========: 0
==========Batch: 0
[2.   2.9  4.74 2.5  2.18 4.93]
[2.18 3.83 3.94 4.31 4.48 3.74]
[2.   2.9  4.74 2.5  2.18 4.93]
==========Batch: 1
[4.46 2.23 4.42 4.67 2.65 2.11]
[3.21 2.05 2.24 2.08 4.94 4.22]
[4.46 2.23 4.42 4.67 2.65 2.11]
==========Batch: 2
[2.31 2.69 2.41 4.62 3.96 2.23]
[3.52 2.67 2.69 2.75 4.93 2.9 ]
[2.31 2.69 2.41 4.62 3.96 2.23]
==========Batch: 3
[2.18 3.83 3.94 4.31 4.48 3.74]
[2.18 3.83 3.94 4.31 4.48 3.74]
[2.18 3.83 3.94 4.31 4.48 3.74]
==========Batch: 4
[3.21 2.05 2.24 2.08 4.94 4.22]
[3.21 2.05 2.24 2.08 4.94 4.22]
[3.21 2.05 2.24 2.08 4.94 4.22]
==========Batch: 5
[3.52 2.67 2.69 2.75 4.93 2.9 ]
[3.52 2.67 2.69 2.75 4.93 2.9 ]
[3.52 2.67 2.69 2.75 4.93 2.9 ]
==========Epoch==========: 1
==========Batch: 0
[2.18 3.83 3.94 4.31 4.48 3.74]
[2.   2.9  4.74 2.5  2.18 4.93]
[2.18 3.83 3.94 4.31 4.48 3.74]
==========Batch: 1
[3.21 2.05 2.24 2.08 4.94 4.22]
[4.46 2.23 4.42 4.67 2.65 2.11]
[3.21 2.05 2.24 2.08 4.94 4.22]
==========Batch: 2
[3.52 2.67 2.69 2.75 4.93 2.9 ]
[2.31 2.69 2.41 4.62 3.96 2.23]
[3.52 2.67 2.69 2.75 4.93 2.9 ]
==========Batch: 3
[2.   2.9  4.74 2.5  2.18 4.93]
[2.   2.9  4.74 2.5  2.18 4.93]
[2.   2.9  4.74 2.5  2.18 4.93]
==========Batch: 4
[4.46 2.23 4.42 4.67 2.65 2.11]
[4.46 2.23 4.42 4.67 2.65 2.11]
[4.46 2.23 4.42 4.67 2.65 2.11]
==========Batch: 5
[2.31 2.69 2.41 4.62 3.96 2.23]
[2.31 2.69 2.41 4.62 3.96 2.23]
[2.31 2.69 2.41 4.62 3.96 2.23]

The question is: Why Im getting three differents batches insted of three batches with the same values.