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[Feat] Compatible with TensorFlow 2.15 #386

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merged 4 commits into from
Feb 29, 2024
Merged

[Feat] Compatible with TensorFlow 2.15 #386

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6cc1af6
[fix] check wrong array index in kvs_reply from Redis returning. Want…
MoFHeka Feb 28, 2024
5c51481
[fix] json would not printed when a wrong json value type was set.
MoFHeka Feb 28, 2024
ad80160
[fix] some test should not be run when eager mode.
MoFHeka Feb 28, 2024
99f1f56
[feat] Competible with Tensorflow 2.15
MoFHeka Feb 28, 2024
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52 changes: 26 additions & 26 deletions ...low_recommenders_addons/dynamic_embedding/core/kernels/redis_impl/redis_table_op_util.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -273,32 +273,32 @@ Status ParseJsonConfig(const std::string *const redis_config_abs_dir,
} \
}

#define ReadArrayJsonToParams(json_key_name, json_val_type) \
{ \
json_hangar_it = json_hangar.find(#json_key_name); \
if (json_hangar_it != json_hangar.end()) { \
if (json_hangar_it->second->type == json_array) { \
redis_connection_params->json_key_name.clear(); \
for (unsigned i = 0; i < json_hangar_it->second->u.array.length; \
++i) { \
value_depth1 = json_hangar_it->second->u.array.values[i]; \
if (value_depth1->type == json_##json_val_type) { \
redis_connection_params->redis_host_port.push_back( \
value_depth1->u.json_val_type); \
} else { \
LOG(ERROR) << #json_key_name " should be json " #json_val_type \
" array"; \
return ReturnInvalidArgumentStatus( \
" should be json " #json_val_type " array"); \
} \
} \
} else { \
LOG(ERROR) << #json_key_name " should be json " #json_val_type \
" array"; \
return ReturnInvalidArgumentStatus(" should be json " #json_val_type \
" array"); \
} \
} \
#define ReadArrayJsonToParams(json_key_name, json_val_type) \
{ \
json_hangar_it = json_hangar.find(#json_key_name); \
if (json_hangar_it != json_hangar.end()) { \
if (json_hangar_it->second->type == json_array) { \
redis_connection_params->json_key_name.clear(); \
for (unsigned i = 0; i < json_hangar_it->second->u.array.length; \
++i) { \
value_depth1 = json_hangar_it->second->u.array.values[i]; \
if (value_depth1->type == json_##json_val_type) { \
redis_connection_params->redis_host_port.push_back( \
value_depth1->u.json_val_type); \
} else { \
LOG(ERROR) << #json_key_name " should be json " #json_val_type \
" array"; \
return ReturnInvalidArgumentStatus( \
#json_key_name " should be json " #json_val_type " array"); \
} \
} \
} else { \
LOG(ERROR) << #json_key_name " should be json " #json_val_type \
" array"; \
return ReturnInvalidArgumentStatus( \
#json_key_name " should be json " #json_val_type " array"); \
} \
} \
}

#define ReadStringArrayJsonToParams(json_key_name) \
Expand Down
18 changes: 15 additions & 3 deletions tensorflow_recommenders_addons/dynamic_embedding/core/kernels/redis_table_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -599,8 +599,12 @@ class RedisTableOfTensors final : public LookupInterface {
hscan_reply->elements > 1) {
kvs_reply = hscan_reply->element[1];
// fill Tensor keys and values
if (kvs_reply->elements < 2 && cursor == 0) {
// Find nothing in Redis
break;
}
if constexpr (!std::is_same<V, tstring>::value) {
if (kvs_reply->element[0]->len !=
if (kvs_reply->element[1]->len !=
runtime_value_dim_ * sizeof(V)) {
return errors::InvalidArgument(
"Embedding dim in Redis server is not equal to the OP "
Expand Down Expand Up @@ -1035,8 +1039,12 @@ class RedisTableOfTensors final : public LookupInterface {
}
kvs_reply = hscan_reply->element[1];
// fill Tensor keys and values
if (kvs_reply->elements < 2 && cursor == 0) {
// Find nothing in Redis
break;
}
if constexpr (!std::is_same<V, tstring>::value) {
if (kvs_reply->element[0]->len != runtime_value_dim_ * sizeof(V)) {
if (kvs_reply->element[1]->len != runtime_value_dim_ * sizeof(V)) {
return errors::InvalidArgument(
"Embedding dim in Redis server is not equal to the OP runtime "
"dim.");
Expand Down Expand Up @@ -1146,8 +1154,12 @@ class RedisTableOfTensors final : public LookupInterface {
}
kvs_reply = hscan_reply->element[1];
// fill Tensor keys and values
if (kvs_reply->elements < 2 && cursor == 0) {
// Find nothing in Redis
break;
}
if constexpr (!std::is_same<V, tstring>::value) {
if (kvs_reply->element[0]->len != runtime_value_dim_ * sizeof(V)) {
if (kvs_reply->element[1]->len != runtime_value_dim_ * sizeof(V)) {
return errors::InvalidArgument(
"Embedding dim in Redis server is not equal to the OP runtime "
"dim.");
Expand Down
6 changes: 5 additions & 1 deletion tensorflow_recommenders_addons/dynamic_embedding/python/keras/layers/embedding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,11 @@

from tensorflow.python.distribute import distribute_lib
from tensorflow.python.keras.utils import tf_utils
from tensorflow.python.distribute import distribution_strategy_context as distribute_ctx
try: # tf version >= 2.14.0
from tensorflow.python.distribute import distribute_lib as distribute_ctx
assert hasattr(distribute_ctx, 'has_strategy')
except:
from tensorflow.python.distribute import distribution_strategy_context as distribute_ctx
from tensorflow.python.distribute import values_util
from tensorflow.python.framework import ops
from tensorflow.python.eager import tape
Expand Down
6 changes: 5 additions & 1 deletion ...w_recommenders_addons/dynamic_embedding/python/kernel_tests/dynamic_embedding_ops_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,10 @@
from tensorflow.python.ops import script_ops
from tensorflow.python.ops import variables
from tensorflow.python.ops import variable_scope
try: # tf version >= 2.14.0
from tensorflow.python.ops.array_ops_stack import stack
except:
from tensorflow.python.ops.array_ops import stack
from tensorflow.python.platform import test
from tensorflow.python.training import device_setter
from tensorflow.python.training import server_lib
Expand Down Expand Up @@ -309,7 +313,7 @@ def test_max_norm_nontrivial(self):
embedding = de.embedding_lookup(embeddings, ids, max_norm=2.0)
norms = math_ops.sqrt(
math_ops.reduce_sum(embedding_no_norm * embedding_no_norm, axis=1))
normalized = embedding_no_norm / array_ops.stack([norms, norms], axis=1)
normalized = embedding_no_norm / stack([norms, norms], axis=1)
self.assertAllCloseAccordingToType(embedding.eval(),
2 * self.evaluate(normalized))

Expand Down
9 changes: 6 additions & 3 deletions ...ommenders_addons/dynamic_embedding/python/kernel_tests/dynamic_embedding_variable_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,10 @@
from tensorflow.python.training import saver
from tensorflow.python.training import server_lib
from tensorflow.python.training import training
from tensorflow.python.training.tracking import util as track_util
try: # tf version >= 2.14.0
from tensorflow.python.checkpoint.checkpoint import Checkpoint
except:
from tensorflow.python.training.tracking.util import Checkpoint
from tensorflow.python.util import compat
from tensorflow_estimator.python.estimator import estimator
from tensorflow_estimator.python.estimator import estimator_lib
Expand Down Expand Up @@ -1326,13 +1329,13 @@ def _loss_fn():
*sorted(zip(keys1, vals1), key=lambda x: x[0], reverse=False))
slot_keys_and_vals1 = [sv.export() for sv in model1.slot_vars]

ckpt1 = track_util.Checkpoint(model=model1, optimizer=model1.optmz)
ckpt1 = Checkpoint(model=model1, optimizer=model1.optmz)
ckpt_dir = self.get_temp_dir()
model_path = ckpt1.save(ckpt_dir)
del model1

model2 = TestModel()
ckpt2 = track_util.Checkpoint(model=model2, optimizer=model2.optmz)
ckpt2 = Checkpoint(model=model2, optimizer=model2.optmz)
model2.train(features) # Pre-build trace before restore.
ckpt2.restore(model_path)
loss2 = model2(features)
Expand Down
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