rocm_jax/jax/experimental/gda_serialization/serialization_test.py

224 lines
7.7 KiB
Python

# Copyright 2021 The JAX Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for serialization and deserialization of GDA."""
import pathlib
from absl.testing import absltest
import jax
from jax._src import test_util as jtu
from jax._src import util
from jax._src import config as jax_config
from jax.config import config
from jax._src import array
from jax._src.sharding import NamedSharding, GSPMDSharding
from jax.sharding import PartitionSpec as P
from jax.experimental.gda_serialization import serialization
import numpy as np
import tensorstore as ts
config.parse_flags_with_absl()
class CheckpointTest(jtu.JaxTestCase):
@jax_config.jax_array(True)
def test_checkpointing_jax_array(self):
global_mesh = jtu.create_global_mesh((4, 2), ('x', 'y'))
inp_shape = (8, 2)
pspec = P('x', 'y')
num = util.prod(inp_shape)
# First Array
global_input_data1 = np.arange(num).reshape(inp_shape)
a1 = array.make_array_from_callback(
inp_shape, NamedSharding(global_mesh, pspec),
lambda idx: global_input_data1[idx])
ckpt_dir1 = pathlib.Path(self.create_tempdir('first').full_path)
# Second Array
global_input_data2 = np.arange(num, num + num).reshape(inp_shape)
a2 = array.make_array_from_callback(
inp_shape, NamedSharding(global_mesh, pspec),
lambda idx: global_input_data2[idx])
ckpt_dir2 = pathlib.Path(self.create_tempdir('second').full_path)
# Third Array
def cb3(_):
return np.array([])
global_mesh1d = jtu.create_global_mesh((8,), ('x',))
a3 = array.make_array_from_callback(
(0,), NamedSharding(global_mesh1d, P(None)), cb3)
ckpt_dir3 = pathlib.Path(self.create_tempdir('third').full_path)
ckpt_paths = [str(ckpt_dir1), str(ckpt_dir2), str(ckpt_dir3)]
tspecs = jax.tree_util.tree_map(serialization.get_tensorstore_spec, ckpt_paths)
serialization.run_serialization([a1, a2, a3], tspecs)
m1, m2, m3 = serialization.run_deserialization(
[NamedSharding(global_mesh, pspec),
NamedSharding(global_mesh, P('x')),
NamedSharding(global_mesh1d, P(None))],
tspecs)
self.assertIsInstance(m1, array.ArrayImpl)
self.assertArraysEqual(np.asarray(m1.addressable_shards[0].data),
np.array([[0], [2]]))
self.assertArraysEqual(np.asarray(m1.addressable_shards[1].data),
np.array([[1], [3]]))
self.assertEqual(m1.addressable_shards[0].data.shape, (2, 1))
self.assertEqual(m1.dtype, np.int32)
self.assertIsInstance(m2, array.ArrayImpl)
self.assertArraysEqual(np.asarray(m2.addressable_shards[0].data),
np.array([[16, 17], [18, 19]]))
self.assertArraysEqual(np.asarray(m2.addressable_shards[1].data),
np.array([[16, 17], [18, 19]]))
self.assertEqual(m2.addressable_shards[0].data.shape, (2, 2))
self.assertEqual(m2.dtype, np.int32)
self.assertIsInstance(m3, array.ArrayImpl)
for i, s in enumerate(m3.addressable_shards):
self.assertEqual(s.index, (slice(None),))
self.assertEqual(s.replica_id, i)
self.assertArraysEqual(np.asarray(s.data), np.array([]))
self.assertEqual(m3.dtype, np.float32)
@jax_config.jax_array(True)
def test_checkpointing_with_bigger_shape_jax_array(self):
global_mesh = jtu.create_global_mesh((2, 2), ('x', 'y'))
global_input_shape = (8, 2)
num = util.prod(global_input_shape)
global_input_data1 = np.arange(num, dtype=np.int32).reshape(global_input_shape)
def cb1(index):
return global_input_data1[index]
arr = array.make_array_from_callback(
global_input_shape, NamedSharding(global_mesh, P('x', 'y')), cb1)
ckpt_dir1 = pathlib.Path(self.create_tempdir('first').full_path)
ckpt_paths = [str(ckpt_dir1)]
tspecs = jax.tree_util.tree_map(serialization.get_tensorstore_spec, ckpt_paths)
serialization.run_serialization([arr], tspecs)
ds = NamedSharding(jtu.create_global_mesh((4, 2), ('x', 'y')), P('x', 'y'))
m1, = serialization.run_deserialization([ds], tspecs, [(12, 2)],
[np.float32])
expected_data = {
0: np.array([[0], [2], [4]], dtype=np.float32),
1: np.array([[1], [3], [5]], dtype=np.float32),
2: np.array([[6], [8], [10]], dtype=np.float32),
3: np.array([[7], [9], [11]], dtype=np.float32),
4: np.array([[12], [14], [0]], dtype=np.float32),
5: np.array([[13], [15], [0]], dtype=np.float32),
6: np.array([[0], [0], [0]], dtype=np.float32),
7: np.array([[0], [0], [0]], dtype=np.float32),
}
for l in m1.addressable_shards:
self.assertArraysEqual(np.asarray(l.data), expected_data[l.device.id])
new_ds = GSPMDSharding.get_replicated(list(global_mesh.devices.flat))
m2, = serialization.run_deserialization([new_ds], tspecs, [(8, 2)], [np.float32])
for l in m2.addressable_shards:
self.assertArraysEqual(l.data, global_input_data1.astype('float32'))
@jax_config.jax_array(True)
def test_checkpointing_scalar_jax_array(self):
global_mesh = jtu.create_global_mesh((2,), ('x'))
global_input_shape = ()
data = np.array(4)
s = NamedSharding(global_mesh, P(None))
array1 = array.make_array_from_callback(
global_input_shape, s, lambda idx: data[idx])
ckpt_dir1 = pathlib.Path(self.create_tempdir('first').full_path)
ckpt_paths = [str(ckpt_dir1)]
tspecs = jax.tree_util.tree_map(serialization.get_tensorstore_spec, ckpt_paths)
serialization.run_serialization([array1], tspecs)
ds = NamedSharding(jtu.create_global_mesh((2,), ('x')), P(None))
m1, = serialization.run_deserialization(
[ds],
tspecs,
[()],
[np.float32]
)
for l in m1.addressable_shards:
self.assertArraysEqual(np.asarray(l.data), data.astype(np.float32))
@jax_config.jax_array(True)
def test_deserialize_tensorstore_array_jax_array(self):
global_mesh = jtu.create_global_mesh((2,), ('x'))
data = np.arange(1024)
tspec = ts.array(data).spec()
m1, = serialization.run_deserialization(
[NamedSharding(global_mesh, P(None))],
[tspec]
)
for l in m1.addressable_shards:
self.assertArraysEqual(np.asarray(l.data), data)
def test_spec_has_metadata(self):
spec = {
'a': {
'b': 1,
'c': 2,
},
'd': 3,
'e': {
'a': 2,
'metadata': 3
},
'f': 4
}
self.assertTrue(serialization._spec_has_metadata(spec))
self.assertTrue(
serialization._spec_has_metadata({
'driver': 'zarr',
'kvstore': 'gfile',
'metadata': {
'chunks': 4,
'shape': (32, 64)
},
'one_more': 'thing'
}))
def test_spec_has_no_metadata(self):
spec = {
'a': {
'b': 1,
'c': 2,
},
'd': 3,
'e': {
'a': 2,
},
'f': 4
}
self.assertFalse(serialization._spec_has_metadata(spec))
def test_empty_spec_has_no_metadata(self):
spec = {}
self.assertFalse(serialization._spec_has_metadata(spec))
if __name__ == '__main__':
absltest.main(testLoader=jtu.JaxTestLoader())