Skip to content

Fix nightly tf failure #1316

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Nov 14, 2023
Merged

Fix nightly tf failure #1316

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 2 additions & 4 deletions keras_nlp/models/bart/bart_seq_2_seq_lm_preprocessor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -266,10 +266,8 @@ def generate_postprocess(
x["decoder_token_ids"],
x["decoder_padding_mask"],
)
if not isinstance(decoder_token_ids, tf.Tensor):
decoder_token_ids = ops.convert_to_numpy(decoder_token_ids)
if not isinstance(decoder_padding_mask, tf.Tensor):
decoder_padding_mask = ops.convert_to_numpy(decoder_padding_mask)
decoder_token_ids = ops.convert_to_numpy(decoder_token_ids)
decoder_padding_mask = ops.convert_to_numpy(decoder_padding_mask)
# Strip any special tokens during detokenization, i.e., the start and
# end markers. In the future, we could make this configurable.
decoder_padding_mask = (
Expand Down
5 changes: 2 additions & 3 deletions keras_nlp/models/bart/bart_seq_2_seq_lm_preprocessor_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@

import pytest

from keras_nlp.backend import ops
from keras_nlp.models.bart.bart_seq_2_seq_lm_preprocessor import (
BartSeq2SeqLMPreprocessor,
)
Expand Down Expand Up @@ -82,8 +81,8 @@ def test_generate_preprocess(self):
def test_generate_postprocess(self):
preprocessor = BartSeq2SeqLMPreprocessor(**self.init_kwargs)
input_data = {
"decoder_token_ids": ops.array([0, 4, 5, 6, 2], dtype="int32"),
"decoder_padding_mask": ops.array([1, 1, 1, 1, 1], dtype="bool"),
"decoder_token_ids": [0, 4, 5, 6, 2],
"decoder_padding_mask": [1, 1, 1, 1, 1],
}
output = preprocessor.generate_postprocess(input_data)
self.assertAllEqual(output, " airplane at")
Expand Down
6 changes: 2 additions & 4 deletions keras_nlp/models/gpt2/gpt2_causal_lm_preprocessor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -163,10 +163,8 @@ def generate_postprocess(
back to a string.
"""
token_ids, padding_mask = x["token_ids"], x["padding_mask"]
if not isinstance(token_ids, tf.Tensor):
token_ids = ops.convert_to_numpy(token_ids)
if not isinstance(padding_mask, tf.Tensor):
padding_mask = ops.convert_to_numpy(padding_mask)
token_ids = ops.convert_to_numpy(token_ids)
padding_mask = ops.convert_to_numpy(padding_mask)
# Strip any special tokens during detokenization (e.g. the start and
# end markers). In the future we could make this configurable.
padding_mask = padding_mask & (token_ids != self.tokenizer.end_token_id)
Expand Down
5 changes: 2 additions & 3 deletions keras_nlp/models/gpt2/gpt2_causal_lm_preprocessor_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
# limitations under the License.

import pytest
import tensorflow as tf

from keras_nlp.models.gpt2.gpt2_causal_lm_preprocessor import (
GPT2CausalLMPreprocessor,
Expand Down Expand Up @@ -78,8 +77,8 @@ def test_generate_preprocess(self):

def test_generate_postprocess(self):
input_data = {
"token_ids": tf.constant([6, 1, 3, 4, 2, 5, 0, 0]),
"padding_mask": tf.cast([1, 1, 1, 1, 1, 1, 0, 0], dtype="bool"),
"token_ids": [6, 1, 3, 4, 2, 5, 0, 0],
"padding_mask": [1, 1, 1, 1, 1, 1, 0, 0],
}
preprocessor = GPT2CausalLMPreprocessor(**self.init_kwargs)
x = preprocessor.generate_postprocess(input_data)
Expand Down
6 changes: 2 additions & 4 deletions keras_nlp/models/opt/opt_causal_lm_preprocessor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -164,10 +164,8 @@ def generate_postprocess(
back to a string.
"""
token_ids, padding_mask = x["token_ids"], x["padding_mask"]
if not isinstance(token_ids, tf.Tensor):
token_ids = ops.convert_to_numpy(token_ids)
if not isinstance(padding_mask, tf.Tensor):
padding_mask = ops.convert_to_numpy(padding_mask)
token_ids = ops.convert_to_numpy(token_ids)
padding_mask = ops.convert_to_numpy(padding_mask)
# Strip any special tokens during detokenization (e.g. the start and
# end markers). In the future we could make this configurable.
padding_mask = padding_mask & (token_ids != self.tokenizer.end_token_id)
Expand Down
5 changes: 2 additions & 3 deletions keras_nlp/models/opt/opt_causal_lm_preprocessor_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
# limitations under the License.

import pytest
import tensorflow as tf

from keras_nlp.models.opt.opt_causal_lm_preprocessor import (
OPTCausalLMPreprocessor,
Expand Down Expand Up @@ -77,8 +76,8 @@ def test_generate_preprocess(self):

def test_generate_postprocess(self):
input_data = {
"token_ids": tf.constant([1, 2, 4, 5, 3, 6, 0, 0]),
"padding_mask": tf.cast([1, 1, 1, 1, 1, 1, 0, 0], dtype="bool"),
"token_ids": [1, 2, 4, 5, 3, 6, 0, 0],
"padding_mask": [1, 1, 1, 1, 1, 1, 0, 0],
}
preprocessor = OPTCausalLMPreprocessor(**self.init_kwargs)
x = preprocessor.generate_postprocess(input_data)
Expand Down
2 changes: 1 addition & 1 deletion keras_nlp/tokenizers/byte_pair_tokenizer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -561,7 +561,7 @@ def process_unseen_tokens():

def detokenize(self, inputs):
inputs, unbatched, _ = convert_to_ragged_batch(inputs)

inputs = tf.cast(inputs, self.dtype)
unicode_text = tf.strings.reduce_join(
self.id_to_token_map.lookup(inputs), axis=-1
)
Expand Down